Welcome to the first session on investment philosophies. The central theme will be to establish an investment philosophy that works effectively. Initial observations in investing reveal two facts:
There are relatively few great investors.
Successful investors, like Peter Lynch (a growth investor) and Warren Buffett (a value investor), encompass a spectrum of philosophies.
The aim is to argue that success can be achieved through various investment philosophies if:
The philosophy fundamentally works.
The philosophy aligns with individual investor characteristics.
The best investment philosophy for you is not the one that works for someone else but rather one that suits your unique approach as an investor.
An investment philosophy is a framework for understanding how markets operate and identifying their inefficiencies. It differs from a strategy; an example of a strategy would be investing in low P/E stocks, which is specific and narrow.
Having a defined investment philosophy helps avoid:
Being influenced by opportunistic sales pitches.
The temptation to chase last year’s successful strategies, resulting in increased transaction costs and potential losses.
Adopting strategies that do not align with personal risk tolerance.
The investment process consists of several stages, beginning with understanding the investor followed by:
Risk Preferences: Are you risk-averse? How much risk can you accept?
Time Horizon: Are you investing short-term or long-term?
Tax Status: What is your tax rate, and how does it influence your investment strategy?
The steps in managing a portfolio include:
Determine how much capital goes into different broad asset classes:
Stocks: Domestic or foreign
Bonds: Corporate, Treasury, or high yield
Real Assets: Real estate, gold, etc.
Deciding which specific assets or securities to invest in, based on:
Chart analysis
Growth potential
Value considerations
Engaging in the actual purchasing of selected assets, which may involve considerations of:
Transaction costs versus the urgency of investment.
Different trading strategies and their implications.
After execution, it’s essential to evaluate portfolio performance:
Measure risk and returns.
Compare against relevant benchmarks.
Reflect on whether the effort resulted in satisfactory returns.
Investment philosophies can be categorized based on their focus:
Market Timing: Focus on asset allocation and predicting market movements.
Asset Selection: Concentrate on identifying the best securities regardless of market conditions.
Activist vs. Passive Investing: Activist investing involves influencing the management of companies, whereas passive investing relies on diversified investments like index funds.
Term Philosophy: Short-term, medium-term, or long-term strategies.
To create a robust investment philosophy, understand:
Risk: Develop a comprehension of risk and its impact on returns.
Financial Statements: Acquire the ability to analyze balance sheets, income statements, and cash flow statements.
Trading Process: Understand the costs associated with trading and why strategies may fail in practice.
Develop a viewpoint on market efficiencies and inefficiencies:
If you perceive markets as generally efficient, a buy-and-hold strategy (e.g., index funds) might be suitable.
If you believe in market inefficiencies, identify specific areas where errors occur and choose an investment philosophy that exploits these.
Evaluate your risk aversion which can be quantified through various models or assessed qualitatively. Recognize this affects potential returns.
Investment strategies should align with your control over cash needs:
Patience and cash needs directly influence your time horizon.
Understand how taxation affects returns:
Different parts of the portfolio are subject to different tax rates.
Maximizing after-tax returns is critical for investment success.
To be a successful investor, establish a personal investment philosophy that embodies:
Your understanding of market functioning.
The type of risks you are willing to take.
Your investment horizon and tax situation.
In subsequent sessions, we will explore various investment philosophies and determine which may be the best fit for you.
In bond investments, understanding the basis for risk is crucial. This session focuses on the measurement of risk in bonds, specifically analyzing two main types of risks: interest rate risk and default risk.
A conventional bond is characterized by:
A known coupon rate set at issuance.
A known maturity date.
For example, consider a 10-year bond with a 5% coupon rate.
The cash flows from a conventional bond are:
Annual coupon payments: $ = C = 40 1000
Face value at maturity: $1000$.
There are two primary risks associated with bond investments:
Interest rate risk arises from changes in the market interest rates after the bond has been issued.
The present value of future cash flows, such as coupons and face value, is influenced by market interest rates.
If market interest rates rise above the bond’s coupon rate, the present value of the bond diminishes.
Conversely, if interest rates fall, the present value increases.
The present value (PV) of bond cash flows can be calculated using the formula:
$$PV = \sum_{t=1}^{n} \frac{C}{(1+r)^t} + \frac{FV}{(1+r)^n}$$
where:
C = annual coupon payment
FV = face value
r = market interest rate
n = number of periods until maturity
For a 10-year bond with a 4% coupon:
If r = 4%: Bond trades at par, PV = 1000.
If r = 2%: PV = 1180.97.
If r = 5%: PV = 923.08.
Duration is a measure of the bond’s sensitivity to interest rate changes.
Higher coupon payments lead to a lower duration, making the bond less sensitive to interest rate changes.
Longer bonds generally have higher durations.
The Macaulay duration can be computed as:
$$\text{Duration} = \frac{\sum_{t=1}^{n} \frac{t \cdot C}{(1+r)^t} + \frac{n \cdot FV}{(1+r)^n}}{PV}$$
Where t is the time of cash flow.
Default risk refers to the risk that the bond issuer may fail to make promised payments.
Cash Flows: A company with stable cash flows has a lower default risk.
Debt Obligations: A company with significant existing commitments creates higher default risk.
Credit ratings are used to assess the default risk.
Agencies like S&P and Moody’s rate companies from AAA (lowest risk) to D (in default).
Ratings help investors assess the risk premium over the risk-free rate.
The interest rate required for a bond reflects the risk-free rate plus a default spread:
Total Rate = Risk-Free Rate + Default Spread
If the risk-free rate is 1.5% and the default spread on a company rated BBB is 1.84%, the total rate would be:
Total Rate = 1.5% + 1.84% = 3.34%
Investing in bonds involves understanding interest rate risk and default risk for successful evaluation and decision-making. The concepts of duration and credit ratings play critical roles in measuring these risks effectively.
Investing in stocks involves various kinds of risks. Understanding these risks is essential for making informed investment decisions. The concept of risk is best understood through its components—a combination of danger and opportunity.
Risk can be defined using the Chinese symbol for crisis which comprises two parts: danger and opportunity. Formally, we can express risk as:
Risk = Danger + Opportunity
This definition serves as a reminder that higher potential returns entail greater risks.
There are several dimensions on which the risk of investing in stocks can be defined:
This refers to the risk associated with fluctuations in stock prices over time. Prices can change due to various reasons—both good and bad:
Implicitly, investors may feel this risk by monitoring the stock’s market value continually.
Explicitly, when selling stocks, investors face the risk of price fluctuations.
Long-term investors may prioritize cash flows (dividends) over price movements, making the risk related to uncertain cash flows a significant concern.
Total risk refers to any deviation from expected outcomes, which could be either better or worse than expected. However, downside risk focuses specifically on outcomes that are worse than expected.
Risk can be measured in two contexts:
Standalone Risk: The risk of the stock in isolation.
Add-On Risk: The additional risk the stock contributes to a diversified portfolio.
Risk models can be categorized into two groups: theory-based models and alternative models.
Theory-based models, like the Capital Asset Pricing Model (CAPM), define risk typically in terms of variance.
The variance of actual returns around expected returns is a common measure of risk. Formally, if Ri is the actual return and E[Ri] is the expected return, we have:
$$\text{Variance} = \frac{1}{n} \sum_{i=1}^{n} (R_i - E[R_i])^2$$
In CAPM, the risk of an investment is encapsulated in one number, beta. The formula for expected return based on beta is:
E[R] = rf + β(E[Rm] − rf)
Where:
E[R] = expected return of the investment,
rf = risk-free rate,
β = measure of systemic risk,
E[Rm] = expected return of the market.
Beta is often estimated using linear regression of stock returns against market returns. The slope of the regression line is the beta coefficient:
$$\text{Beta} = \frac{\text{Cov}(R_i, R_m)}{\text{Var}(R_m)}$$
If CAPM and traditional models are not satisfactory, there are several alternative approaches:
Accounting-based models that use financial ratios (like debt ratios or earnings ratios).
Proxy models, such as size and value premium, which consider attributes like market cap or price-to-book ratio as stand-ins for risk.
Expected returns backed out from cash flows or dividend models.
Margin of safety, which determines the discount from intrinsic value necessary before purchasing a stock.
Regardless of the approach taken, it is crucial to consider risk in stock investments. It can be quantified in various ways—whether through theoretical models, accounting ratios, or qualitative assessments. The key takeaway is that understanding and measuring risk is fundamental for sound investment decision-making.
In this session, we focus on extracting valuable investment data from accounting statements. Despite a general skepticism towards accountants, their reports are crucial for investors. Key financial statements include:
Balance Sheet
Income Statement
Statement of Cash Flows
When evaluating a company, consider these fundamental questions:
What investments have already been made, and what is their current value?
What is the growth potential of the company, and how valuable is that growth?
How much debt does the company have, and what is the equity stake?
Broadly, the focus can be summarized as:
How profitable are you? What do you own? What do you owe?
The Balance Sheet summarizes a company’s financial position at a specific point in time, including:
Assets: Resources owned by the company
Fixed Assets (land, buildings, equipment)
Current Assets (inventory, accounts receivable, cash)
Financial Investments (equity in other companies)
Intangible Assets (goodwill, etc.)
Liabilities: Obligations the company owes
Current Liabilities (accounts payable, short-term debt)
Long-term Liabilities (bank debt, corporate bonds)
Equity: Shareholders’ stake in the company
The balance sheet must balance according to the equation:
Assets = Liabilities + Equity
The Income Statement summarizes a company’s performance over a period, detailing revenues and expenses:
Revenues
Operating Expenses
Operating Income:
Operating Income = Revenues − Operating Expenses
Financial Expenses (Interest)
Taxes
Net Income:
Net Income = Operating Income − Financial Expenses − Taxes
The Statement of Cash Flows provides insights into cash movements during a period, categorized into:
Cash Flows from Operations
Cash Flows from Investing
Cash Flows from Financing
Accountants often rely on historical cost, which does not reflect current market value:
Book Value ≠ Market Value
Accountants prefer to understate assets and overstate liabilities, leading to conservative accounting practices.
A financial balance sheet reconsiders:
Only two assets:
Investments made
Expected future investments
Liabilities as a sum of debt and equity.
To assess profitability using net income, consider:
$$\text{Return on Equity (ROE)} = \frac{\text{Net Income}}{\text{Equity}}$$
$$\text{Return on Capital (ROC)} = \frac{\text{Operating Income}}{\text{Invested Capital}}$$
Leverage analysis can be conducted by comparing debt to equity or total capital.
R&D is often treated as an operating expense, but it should be capitalized. Similarly, lease commitments should be treated as debt obligations and included in the balance sheet.
Understanding and analyzing accounting statements require practical engagement. Investors should regularly review financial statements to glean insights and enhance their valuation skills.
Investors often observe discrepancies between hypothetical portfolio returns and actual returns achieved. Many potential investment strategies yield attractive returns on paper, but when implemented, the actual returns are often lower. This discrepancy is primarily due to trading costs.
Trading costs encompass more than just brokerage fees; they can significantly affect overall portfolio performance. The main components of trading costs are:
Brokerage Costs: Historically, these costs were substantial. However, with the rise of online trading platforms, brokerage fees have dropped significantly.
Bid-Ask Spread: The difference between the price you can buy (ask price) and sell (bid price) a stock. If an investor attempts to sell immediately after buying, they incur a loss that depends on the spread magnitude.
Price Impact: Larger trades lead to a market price impact where buying increases the stock price and selling decreases it. Smaller investors may experience negligible price impact, but large investors trading millions of shares will encounter marked effects.
Opportunity Costs of Waiting: Delaying trades can lead to lost opportunities, either due to price movements or missed trading chances.
Active money managers typically underperform index funds by about 1.5% annually, a substantial figure attributed largely to trading costs. Strategies that seem beneficial may lack practical application due to these costs.
A notable case involved Value Line, known for its investment recommendations. While their recommendations indicated high potential returns, the actual managed fund underperformed due to high trading costs:
Paper Return: Red Line in visual aids shows hypothetical returns from following recommendations.
Actual Returns: Blue Line illustrates lower returns after accounting for trading costs.
This discrepancy underscores the significance of transaction costs in assessing investment performance.
The bid-ask spread is influenced by:
Liquidity: More liquid stocks, such as large companies (e.g., ), feature narrower spreads, while less liquid stocks experience wider spreads.
Market Activity: Institutional trading may influence spread variations as liquidity and investor behavior change.
Stock Risk: Riskier stocks generally present wider spreads due to price volatility.
Share Price: Lower-priced stocks tend to incur higher spreads as a fraction of their price.
Transparency and Corporate Governance: Stocks with lower transparency and poor governance structures report higher spreads due to increased perceived risk by traders.
Price impact pertains to how large trades affect market prices, leading to diminished returns:
Large investors must account for potential price declines when selling significant volumes of shares.
The market’s liquidity can reduce the speed of price adjustment, particularly for smaller-cap stocks.
Delaying trades affects potential gains:
If relevant information is fleeting, timely execution is crucial.
Market conditions may change rapidly, impacting the investor’s ability to capitalize on previously assessed opportunities.
The relationship between trading costs and taxes is notable:
Higher trading frequency in mutual funds leads to increased tax liabilities and a pronounced drag on overall investment returns.
Funds with lower turnover ratios incur substantially lower tax costs upon liquidation of assets.
When evaluating investment strategies:
Trading real estate incurs high brokerage costs (5-6%).
Trading costs can be exorbitant (15-30% for fine art).
Keep in mind that actual versus expected returns can vary significantly due to trading costs, which encompass much more than just brokerage fees. The bid-ask spread, price impact, and opportunity costs of waiting can play critical roles in shaping the profitability of investment strategies. Additionally, taxes exacerbate these costs, making it essential for investors to analyze turnover and trading activity when assessing mutual funds or individual investment strategies.
Market efficiency is a fundamental concept in finance that significantly impacts investment strategies and money management. Understanding it involves exploring the definitions, implications, and dynamics of efficient and inefficient markets.
An efficient market is one in which the market prices reflect all available information, making it impossible to consistently achieve higher returns without taking on more risk.
True Value vs. Market Price: The market price is an unbiased estimate of the investment’s true value, denoted as V. Thus,
P ≈ E[V]
where P is the market price and E[V] is the expected value.
Random Pricing Errors: In efficient markets, mispricings are random, meaning that one cannot predict whether a stock is underpriced or overpriced.
Eugene Fama defined three forms of market efficiency based on how information is reflected in stock prices:
Weak Form Efficiency: Current prices reflect all past price information. Therefore, technical analysis (charts) will not provide an advantage.
Semi-Strong Form Efficiency: Prices reflect all publicly available information, including financial statements and news. Fundamental analysis cannot yield superior returns.
Strong Form Efficiency: Prices reflect all information, both public and private (insider information). No one can consistently achieve higher returns.
These forms can drive different investment philosophies based on beliefs about market efficiency.
In an efficient market:
No group of investors can consistently beat the market with a common investment strategy over the long term.
Active investment strategies incur costs that often negate potential excess returns.
A strategy based on diversification or index investing is typically more effective than active stock picking.
Investors earn returns equivalent to the market index less transaction costs. In terms of expected returns based on risk:
E[Ri] = Rf + βi(E[Rm] − Rf)
where:
E[Ri]: Expected return on investment i.
Rf: Risk-free rate.
βi: Beta of the investment.
E[Rm]: Expected return of the market.
Liquidity and Trading Costs: Greater trading costs and lower liquidity increase the likelihood of inefficiencies.
Investor Behavior: Investors must actively seek to exploit inefficiencies for the market to adjust and become efficient.
Access to Information: The cost of obtaining and processing information should be low for efficiency to prevail.
Recent developments in behavioral finance challenge traditional efficient market hypotheses. Key psychological factors affecting investor behavior include:
Anchoring: Investors tend to anchor their decisions based on initial information.
Loss Aversion: Investors prefer to avoid losses more than they seek equivalent gains.
Overconfidence: Investors often believe they can predict market outcomes better than they actually can.
Herd Behavior: Investors may follow trends, often leading to irrational market movements.
Mental Accounting: Investors treat money differently based on subjective categorization rather than economic rationality.
While many markets are efficient for most investors at most times, pockets of inefficiency exist due to factors such as behavioral biases and transaction costs. The challenge for investors is to identify and exploit these inefficiencies while maintaining an understanding of the overall market dynamics.
9 Eugene F. Fama, Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance, 1970.
Richard H. Thaler, Advances in Behavioral Finance, 1993.
In our previous session, we discussed market efficiency and the importance of understanding whether markets are efficient when building an investment philosophy. This session will delve into specifics regarding how to identify market inefficiencies and evaluate whether an investment strategy is capable of surpassing market performance.
To test any investment strategy, we need to evaluate its success in generating returns after accounting for risk. A crucial element of this testing involves having a sound risk model, as a faulty risk model may lead to incorrect assessments of a strategy’s efficacy. Hence, every test of market efficiency inherently involves two components: the test of market efficiency itself and the validity of the risk model used.
When assessing whether an investment strategy can beat the market, it is vital to control for risk. The strategy must outperform a relevant benchmark, such as the S&P 500, but simply beating this index isn’t sufficient if the strategy entails more risk. Conversely, if the strategy is lower in risk, beating the index should not be the sole measure of success.
There are various methods to adjust for risk:
1. Sharpe Ratio: Measures the excess return per unit of risk.
$$\text{Sharpe Ratio} = \frac{E[R_p] - R_f}{\sigma_p}$$
where E[Rp] is the expected portfolio return, Rf is the risk-free rate, and σp is the standard deviation of portfolio returns.
2. Information Ratio: Assesses the return of the strategy relative to a benchmark, adjusted by tracking error.
$$\text{Information Ratio} = \frac{R_p - R_{benchmark}}{\sigma_{tracking}}$$
3. Jensen’s Alpha: Evaluates performance of the portfolio against expected return based on the CAPM.
α = Rp − [Rf + β(Rm − Rf)]
where β is the sensitivity of the portfolio’s returns to market returns.
4. Treynor Measure:
$$\text{Treynor} = \frac{R_p - R_f}{\beta}$$
5. Multi-factor Models: Include multiple factors to explain expected returns, extending the CAPM to capture different risk dimensions.
6. Proxy and Composite Models: Aimed at mitigating biases within standard CAPM methodologies.
To evaluate whether a strategy is valid, various methods can be employed:
An event study assesses the impact of specific events on stock returns. The process involves:
Identifying the event (e.g., earnings announcements, stock splits).
Collecting stock returns around the event, typically a window of 30 days before and 30 days after the announcement.
Adjusting the returns for overall market performance.
Computing excess returns to gauge performance against a benchmark.
As an example, one could analyze stocks after options are first listed and determine if these stocks yield positive excess returns in the subsequent days.
In a portfolio study, stocks are grouped based on common characteristics (e.g., trading volume). The steps include:
Classifying stocks according to the chosen criteria.
Computing the returns for each group over a predetermined period.
Assessing statistical significance of the differences in returns across portfolios.
For instance, one might explore whether low P/E ratio stocks consistently outperform higher P/E counterparts.
To analyze multiple variables (e.g., P/E ratio, growth rate), regression analysis can be utilized. The process involves:
Identifying independent variables that are believed to influence returns.
Running the regression to determine the relationships and significance of these variables.
Predicting values based on the model to identify potentially undervalued or overvalued stocks.
Several common errors can undermine the evaluation of investment strategies:
Anecdotal Evidence: Relying on personal stories without statistical backing.
Look-Ahead Bias: Testing strategies on the same data from which the strategy was derived. It is essential to have a holdout period to avoid skewing results.
Sampling Biases: Ensuring that the sample truly represents the universe of stocks being analyzed.
Ignoring Market Performance: Evaluating strategies solely based on nominal returns without adjustments for market conditions or risk.
Correlation vs. Causation: Distinguishing between mere correlations and actual causal relationships.
Data Mining: Overfitting strategies to historical data can lead to non-robust conclusions.
Survivorship Bias: Only considering stocks that remain in the market may lead to optimism bias.
In your quest to evaluate investment strategies, apply rigorous testing and statistical analysis. Always maintain skepticism, and subject any promising strategy to analytical scrutiny before integrating it into your investment arsenal.
This will lead to a more disciplined and informed approach to investing, thereby increasing the likelihood of achieving superior returns.
The question of whether future prices can be predicted by analyzing past prices is a contentious topic in the field of finance. While most academics and value investors may argue that it is impossible, numerous past and present investors rely on charts to make predictions about future price movements.
The Random Walk Hypothesis asserts that stock price changes are random, with a 50% chance of moving higher and a 50% chance of moving lower at any given moment. This hypothesis suggests that past prices provide no information about future prices.
The random walk hypothesis is built on three fundamental assumptions:
Information Block: All public information about a company is available and accessible to investors.
Investor Block: Investors are rational and create unbiased expectations based on available information.
Market Block: Market prices reflect these unbiased expectations, providing an accurate estimate of a stock’s value.
If these assumptions hold, the introduction of new information results naturally in a balanced probability distribution, supporting the conclusion that subsequent price changes are random.
Challenges to the random walk hypothesis arise from behavioral economists who argue that:
Investors are not always rational and may form biased expectations.
Price changes can influence other investors’ perceptions, leading to herd behavior.
Investors use various methodologies to analyze price movements, including correlation studies that measure the strength of relationships between past and future returns. Studies can be categorized based on the time frames of interest:
For very short time frames (minutes to hours):
Evidence generally shows low or no serial correlation.
Any observed correlations are likely a result of market microstructure issues such as bid-ask spreads.
For daily or weekly returns:
Some studies provide evidence of negative serial correlation, indicating a reversal of previous trends.
For example, stocks that performed well last week may be more likely to perform poorly this week.
For longer time frames (months to years):
There is evidence of positive momentum, where stocks that have performed well over an extended period tend to continue performing well.
A prominent study by Jagadish and Titman shows that stocks in the top performance decile yielded higher returns than those in the bottom decile over six-month periods.
Research shows significant negative correlation for stocks over five years, indicating that poorly performing stocks may rebound in subsequent years.
Momentum investing refers to strategies that leverage the persistence of price trends. Investors might capitalize on upward price movement seen in a stock’s previous weeks or months. However, momentum investing carries risks:
Momentum can create bubbles, pushing prices away from fundamental values.
Investors must be adept at identifying shifts in market momentum to succeed.
Despite the prevailing belief in the random walk hypothesis, evidence supports the existence of price patterns. The key takeaways include:
Short-term trends show little to no predictability due to random fluctuations.
Moderate-term strategies may capitalize on negative serial correlation.
Long-term strategies benefit from positive momentum.
Investors should approach momentum investing with caution due to inherent risks and potential for sudden reversals.
In closing, while charts and technical indicators can complement fundamental analysis, they should be utilized judiciously. The core objective should focus on making informed investment choices to maximize returns.
In the last session, we explored price patterns over time, analyzing the relationship between past and current prices. This session will shift focus to temporal patterns—specifically, calendar-time patterns in stock prices.
Temporal patterns are trends that can be observed consistently over specific calendar periods. In this context, we will discuss two notable calendar effects:
The January effect refers to the observation that stock returns in January tend to be lower than those in other months of the year. Evidence suggests that this phenomenon is not limited to the U.S. market but can be observed globally.
$$R_j = \frac{P_j - P_{j-1}}{P_{j-1}}$$
where Rj is the return in January, Pj is the price at the end of January, and Pj − 1 is the price at the end of December.
A historical analysis of stock returns from 1927 to 2011 indicates that January consistently demonstrates the worst returns, while September and October are also noted as poor months, likely influenced by historical market crashes during those periods.
Small-cap stocks have historically demonstrated higher returns than large-cap stocks. A significant portion of these excess returns occurs in January, indicating a possible correlation between the small-cap effect and the January effect.
Several hypotheses attempt to explain the January effect:
Tax-Loss Selling: Investors may sell losing stocks in December for tax reasons, leading to an overselling effect that is corrected in January.
Institutional Behavior: Institutions may engage in window dressing—selling poor-performing stocks at year-end and purchasing well-performing ones once the new year begins.
Behavioral Finance: Investors may feel a psychological boost from a "clean slate" in the new year, encouraging buying activity.
If attempting to capitalize on the January effect, one might consider buying stocks at the end of December, as this could increase potential returns due to the January bounce-back dynamic.
The weekend effect is a market anomaly where returns on Mondays are significantly lower compared to other weekdays, with evidence suggesting that negative returns predominantly occur at the market’s opening on Monday.
$$R_d = \frac{P_d - P_{d-1}}{P_{d-1}}$$
where Rd is the return on a particular day, Pd is the price at the opening of the day, and Pd − 1 is the closing price from the previous trading day.
Analysis of returns from 1927 to 2001 reinforces that Mondays yield worse performance across various global markets. The degree of negative returns on Mondays tends to be more pronounced for smaller stocks.
The possible explanations for the weekend effect include:
Information Release: Companies may withhold bad news until after the market’s close on Friday, causing a negative reaction throughout Monday.
Market Microstructure: Changes in trading activity, such as derivatives trading, may influence stock prices before market openings.
Historical analysis indicates fluctuations in the magnitude of the weekend effect across decades. For example, the Monday effect was pronounced in the 1980s but diminished in the following decades, with Fridays becoming less favorable in more recent years.
The analysis of temporal patterns in stock prices reveals notable calendar effects, specifically:
January returns are generally worse than in other months, with a notable connection to small-cap performance.
Monday returns are consistently lower due to various potential influences, though the impact has varied over time.
These effects, while interesting, represent relatively minor numbers in portfolio performance. Investors should exercise caution when attempting to leverage these patterns in trading strategies, as the impacts are nuanced and context-dependent.
Skeptical perspective on technical indicators, price patterns, and charts.
Acknowledgment that many traders effectively use technical analysis to predict future stock prices.
Aim to categorize various technical indicators and understand their underlying assumptions.
Four key assumptions underpin technical analysis:
Supply and Demand: Prices of securities are determined by the forces of supply and demand.
Irrational Behavior: Market behavior is influenced by both rational and irrational factors.
Market Trends: Technical analysts believe that stock prices move in identifiable trends, which can persist over time, contrary to the random walk theory.
Predicting Shifts: Success in trading is about anticipating shifts in supply and demand, which technical indicators can help identify.
Technical indicators can be classified into several categories based on their behavioral assumptions and goals:
These are based on the assumption that markets overreact to news (both positive and negative).
Common indicators include:
Odd Lot Trading:
Examines buying activity in odd lots (less than 100 shares).
Assumes that individual investors tend to overreact to news.
Strategy: Sell when there’s heightened odd lot buying.
Mutual Fund Cash Position:
Looks at cash reserves held by equity mutual funds.
High cash positions indicate bearish sentiment among fund managers.
Strategy: Buy stocks when mutual funds hold high cash positions.
Investment Advisor Sentiment:
Tracks the percentage of bullish versus bearish investment advisors.
High bullish sentiment suggests over-enthusiasm.
Strategy: Sell when advisors are overly bullish and buy when overly bearish.
Designed to detect potential shifts in market conditions before they manifest.
Notable indicators include:
Normalized P/E Ratios:
Compares the current P/E ratio to historical averages.
Overvalued stocks (high P/E) may signal a sell.
Undervalued stocks (low P/E) may suggest a buy.
Market Breadth:
Compares the number of advancing stocks to declining ones.
Strong upward movement with few advancing stocks may be a warning sign.
Support and Resistance Lines:
Indicates price levels where stocks have difficulty moving above (resistance) or below (support).
A breach of these levels can indicate a shift in market sentiment.
Moving Averages:
Examines the trend of a stock’s price over a specific period.
Price crossing above/below the moving average can be indicative of future price direction.
Focus on the persistence of price trends.
Classic indicators include:
Relative Strength Index (RSI):
$$\text{RSI} = \frac{\text{Current Price}}{\text{Price Six Months Ago}}$$
Stocks with high relative strength may continue to perform well, while those with low strength may underperform.
Trend Lines:
A positive upward trend indicates continued momentum.
Utilizes the actions of more knowledgeable investors as indicators for market direction.
Examples include:
Specialist Short Sales:
Tracks stocks that specialists on the exchange sell short.
Indicates potential downtrends when specialists are bearish.
Insider Trading:
Monitoring buying/selling activities of company insiders.
Assumes insiders possess superior information compared to the general market.
Based on theories and models that propose markets are influenced by complex patterns or cycles.
Examples include:
Elliott Wave Theory: Suggests price movements can be predicted based on historical wave patterns.
Dow Theory: Focuses on overall market trends and phases, primarily viewed statistically rather than fundamentally.
When applying technical analysis, consider the following suggestions:
Understand Behavioral Basis: Clarify assumptions about market behavior that underpin the use of a strategy.
Verification of Effectiveness: Rigorously test indicators before relying on them.
Timely Trading: Rapid execution is often necessary, as technical indicators may require quick decisions.
Balancing Costs: Consider trading costs that can erode profits due to frequent trading.
Discipline in Holding Periods: Maintain a consistent time horizon to avoid premature selling or holding.
Technical indicators can provide insights into market trends and shifts in supply and demand. While some may work based on behavioral assumptions, it is critical to understand the underlying principles behind each indicator before incorporating them into a trading strategy.
Value investing is an investment strategy that involves selecting stocks that appear to be trading for less than their intrinsic or book value. This lecture introduces the screening approaches employed by value investors, explaining the rationale behind various screens and assessing their effectiveness based on empirical evidence.
Screener: A passive approach that involves sifting through stocks to identify undervalued assets using various metrics.
Contrarian Investor: An approach that invests against prevailing market trends, based on the belief that the market overreacts to news.
Activist Investor: Involves taking an active role in a company’s management to unlock value.
The following four groups of screens are frequently utilized by value investors:
The price-to-book (P/B) ratio is calculated as:
$$\text{P/B Ratio} = \frac{\text{Price per Share}}{\text{Book Value per Share}}$$
A low P/B ratio may indicate that a stock is undervalued relative to its assets. Investors often consider stocks with a P/B less than 1 to be good candidates for investment, as they imply potential liquidation value that exceeds purchase price.
Studies have shown that portfolios constructed with low P/B ratios historically provide higher raw returns compared to higher P/B stocks.
Risk Considerations: Low P/B stocks may be riskier, possibly due to higher debt levels or distressed market conditions.
Quality of Returns: A low return on equity can indicate poor management or unproductive use of capital.
The price-to-earnings (P/E) ratio is defined as:
$$\text{P/E Ratio} = \frac{\text{Price per Share}}{\text{Earnings per Share}}$$
A low P/E ratio suggests that investors are paying less for each dollar of earnings, indicating a bargain.
Long-term data indicates that stocks with low P/E ratios tend to outperform those with high P/E ratios.
Earnings Quality: Fluctuating or unsustainable earnings can misguide investors. Look for stable earnings trends.
Growth Outlook: Low P/E stocks may also have low growth; avoid stocks without growth potential.
Revenue multiples, such as price-to-sales (P/S) ratios, allow investors to assess value based on sales rather than earnings or book value, particularly applicable for growth startups.
$$\text{P/S Ratio} = \frac{\text{Market Value of Equity}}{\text{Revenue}}$$
The effectiveness of revenue multiples is less extensively validated compared to P/E and P/B ratios, with mixed results across studies.
Leverage Considerations: High debt levels can obscure true financial health.
Margin Analysis: Low revenue multiples may correlate with companies that have poor margins.
Investors interested in dividends may seek stocks with high dividend yields:
$$\text{Dividend Yield} = \frac{\text{Annual Dividend per Share}}{\text{Price per Share}}$$
The evidence supporting high dividend yield stocks outperforming the market is mixed; many high-yield stocks may signal distress.
Sustainability of Dividends: Companies may cut dividends if they can no longer afford them, so assess free cash flow.
Growth Assessment: High-yielding stocks may face declining revenues or profitability.
Value investors often employ various protective measures to ensure they do not invest in seemingly cheap stocks that are fundamentally flawed:
Accounting Checks: Using normalized earnings or tangible book value to avoid overstated financials.
Economic Moat: Invest in companies that can maintain profits above the cost of equity over time, assessed by analyzing competitive advantages.
Margin of Safety: Acquire stocks at a price significantly below intrinsic value to enhance the likelihood of a favorable outcome.
A structured approach to screening for value investing can follow these four steps:
Select a Valuation Multiple: Begin with a criterion, e.g., P/E < 10.
Filter for Risk: Assess companies with stable earnings over time.
Growth Requirement: Target companies with revenue or earnings growth above a certain threshold (e.g., greater than 10%).
Quality of Growth: Look for high-quality growth by requiring returns on equity to exceed a certain level (e.g., > 20%).
By following this structured screening approach, investors can enhance the likelihood of selecting value stocks that are genuinely undervalued and have solid fundamentals.
Screening for undervalued stocks requires a balanced understanding of various financial metrics and an awareness of intrinsic value. This approach can lead to superior long-term investment outcomes when combined with sound judgment regarding risk and quality.
Contrarian value investing is a strategy rooted in the belief that markets often overreact to news, leading to mispriced stocks. The goal is to identify good companies that face temporary setbacks, purchasing them at a discount due to the market’s overreaction.
Contrarian investing relies on the fundamental premise that:
Markets overreact to both good and bad news.
This overreaction can create opportunities for investors.
The essence of contrarian investing is to find high-quality companies whose stock prices have been unjustly depressed by bad news. An example of this is Warren Buffett’s investment in American Express after the salad oil scandal in the 1960s.
Research by De Bondt and Thaler examined stock performance based on prior performance.
Established two portfolios:
Winners Portfolio: 35 stocks that performed best over the past year.
Losers Portfolio: 35 stocks that performed worst over the past year.
Over the subsequent five years:
$$\begin{aligned}
\text{Winners Portfolio:} & \quad \text{loses } 11\% \\
\text{Losers Portfolio:} & \quad \text{gains } 28\%
\end{aligned}$$
The differential is approximately 39% (28% + 11%).
While the strategy seems straightforward, several challenges must be considered:
Transaction Costs: Lower stock prices may result in higher relative transaction costs, impacting returns.
Timing Effects: Investments in loser stocks perform better if initiated in December due to tax-loss selling tendencies.
Holding Period: Investor behavior over different time frames affects performance significantly.
Investors should recognize the difference between a company being a good company versus a good investment:
Good companies are often overvalued due to high expectations.
Poorly performing companies may offer more room for surprise recovery, thus presenting better investment opportunities.
To successfully engage in contrarian investing, one needs:
Self-Confidence: Ability to remain steadfast while others are selling.
Communication: Keep clients informed about the rationale for contrarian strategy.
Patience: Must endure short-term fluctuations and hold positions long enough to realize gains.
Tolerance for Volatility: Be prepared for significant price swings in their portfolios.
Awareness of Transaction Costs: Monitor effects of trading shares with lower prices.
Contrarian value investing is supported by substantial empirical evidence, yet it requires a strong psychological disposition to counteract the prevailing market sentiment. Success hinges not only on finding undervalued stocks but also on the investor’s ability to remain resolute and patient amidst market noise.
In the study of value investing, we have explored three primary strategies:
Passive Screening
Contrarian Value Investing
Activist Value Investing
In passive screening, investors look for stocks with:
Low Price-to-Earnings (P/E) ratios
Low Price-to-Book (P/B) ratios
High Dividend Yields
The goal is to buy these stocks in the hope that their prices will increase as they are driven towards their intrinsic value.
This approach is based on empirical evidence that undervalued stocks tend to earn higher returns and that markets become more rational and efficient over time.
Contrarian value investing involves purchasing stocks that have recently lost value. This strategy operates under the assumption that those stocks will recover over time.
Activist value investing empowers investors to effect change rather than simply waiting for the market to recognize value. It typically requires a significant capital investment, making it less accessible to average investors.
There are three main groupings of activist investors:
Lone Wolves: Individual investors recognizable for their activism, such as Bill Ackman and Nelson Peltz.
Institutional Investors: Smaller mutual funds that focus on activist strategies, such as CalPERS.
Hedge Funds and Private Equity: They often collaborate with existing management but can create friction due to their influence and objectives.
Unlike passive investors who wait for price adjustments, activist investors take proactive measures to catalyze change.
The value of a company can be determined by four key variables:
Cash Flow from Existing Assets, CF
Growth Rate, g
Cost of Capital, r
Time until the company matures
The valuation formula can be expressed as:
$$\text{Value} = CF \cdot \frac{1 - (1 + g)^{-t}}{r - g}$$
Status Quo Value: Value when run as-is.
Optimal Value: Value when management is improved.
The current market price reflects a weighted average (WA) between these two values:
Market Price = WA(Status Quo Value, Optimal Value)
As an activist investor, several actions can be taken:
Improve operational efficiency.
Adjust investment strategies (over or under-investing).
Enhance competitive advantages.
Optimize the capital structure.
Identify the optimal debt-to-equity ratio to minimize the cost of capital:
$$WACC = \frac{E}{V} r_e + \frac{D}{V} r_d (1-T)$$
where:
WACC = Weighted Average Cost of Capital
E = Market value of equity
D = Market value of debt
V = E + D = Total market value of the firm
re = Cost of equity
rd = Cost of debt
T = Tax rate
The goal is to minimize WACC through an appropriate mix of debt and equity.
Corporate finance theory suggests that dividends themselves don’t affect the company’s value, as investors can create their own cash flows. However, shareholder perception is critical:
Companies with excess cash and negative investor perception should return cash to shareholders.
Effective corporate governance is paramount for activist investors. The aim is to create a plan that distinguishes between current management’s strategy and the potential for improved governance:
Calculate status quo value with existing policies.
Calculate optimal value with proposed changes.
The market value is determined by these calculations and reflects the probability of management change as a result of activism.
Activist investors not only seek out undervalued companies but also initiate the necessary changes to enhance company value. This requires:
Sufficient capital
In-depth understanding of the targeted companies
Strategic persistence
With these tools, an activist investor can act as a catalyst for change, moving prices towards their true value.
Value investing is investing in undervalued stocks based on fundamental analyses. This approach contrasts with growth investing, which focuses on companies that exhibit signs of above-average growth.
Passive Screening: Following Benjamin Graham’s principles, investors screen for low Price-to-Earnings (P/E) and Price-to-Book (P/B) ratios, as well as strong fundamentals.
$$\text{P/E Ratio} = \frac{\text{Market Price per Share}}{\text{Earnings per Share}}$$
$$\text{P/B Ratio} = \frac{\text{Market Price per Share}}{\text{Book Value per Share}}$$
Contrarian Investing: Investing in companies facing setbacks, assuming that market prices will correct overreactions.
Activist Investors: Investors who acquire shares to influence a company’s strategy in order to increase its stock price.
The efficacy of active value investing compared to index funds presents mixed results.
Active value funds often underperform their corresponding value index funds.
Excess Return = Active Fund Return − Index Fund Return
Evidence indicates that the payoff from researching cheap value stocks is greater in growth investing than in value investing.
Studies found that the average individual investor underperformed compared to indices, though top quartile performers exceeded market returns by about 6%.
Despite the theoretical backing for value investing, various factors hinder its consistent success.
Rigidity: Strict adherence to rules can undermine flexibility in investment strategies.
Righteousness: An overly self-assured mentality can lead to disregard for differing market opinions and insights.
Ritualism: Relying on established rituals and benchmarks that may not correlate with successful investing outcomes.
1. Discounted Cash Flow (DCF): Avoid dismissing DCF as mere academia; it provides intrinsic value insight.
$$V = \sum \frac{CF_t}{(1 + r)^t}$$
where V is intrinsic value, CFt is expected cash flow at time t, and r is the discount rate.
2. Betas and Risk Measurement:
Beta indicates relative risk; it should not be wholly disregarded.
Distinguish between standalone risk and risk addition to a portfolio.
3. Margin of Safety:
Margin must be calculated post-value assessment. It should vary depending on the security’s stability and market conditions.
4. Management Quality:
Good management does not guarantee lower risk; high expectations increase the likelihood of poor performance against expectations.
5. Moats (Competitive Advantages):
Not every company with a moat is an automatic buy; investments must be evaluated against market expectations of that moat’s value.
6. Intrinsic Value Stability:
Intrinsic value fluctuates due to various factors, such as macroeconomic changes and company performance metrics. It is essential to update valuations regularly.
The alluring theory of value investing does not always translate to superior returns in practice. Potential value investors should proceed with caution, armed with a comprehensive understanding of techniques, ample research, and readiness to adapt strategies to changing market dynamics.
Growth investing is an investment philosophy aimed at outperforming the market through investments in companies expected to grow at an above-average rate.
Unlike value investing, which is well-supported by empirical evidence and historical performance, growth investing does not have the same pedigree.
Despite this, there exists a loyal following among growth investors who believe in its efficacy.
A common but oversimplified definition of a growth investor is someone who buys low price-to-earnings (P/E) stocks or invests in sectors like technology.
A more refined definition considers a growth investor as someone who invests based on a company’s growth assets, which are future investments expected to generate growth.
Growth investors believe they can better assess the value of these growth assets than the market, focusing more on growth assets than on existing (in-place) assets.
The discussion on growth investing will focus on four phases:
Small Cap Investing: Primarily focuses on small capitalized companies, many of which are growth companies.
Initial Public Offerings (IPOs): Investing in companies shortly after they go public, with the anticipation of capturing their growth potential.
Screening for Cheap Growth Companies: Identifying growth companies that are undervalued by the market.
Activist Growth Investing: Investing in young growth companies before they become widely recognized.
Small cap investing is a widely-used strategy, often aligned with growth investing.
Empirical evidence suggests that small cap companies generally yield higher returns than larger counterparts, per unit of risk.
Returns on small cap versus large cap stocks can be illustrated through various measures of market capitalization.
The small cap premium can be defined as the excess return that investing in small cap stocks provides over investing in large cap stocks. This can be represented as:
Small Cap Premium = E(Rsmall) − E(Rlarge)
where E(R) denotes the expected return from investments.
Historical returns are typically analyzed by breaking stocks into deciles based on market capitalization.
The smallest decile typically shows the highest premium relative to the larger market averages.
The small cap premium fluctuates significantly over time.
Notably, many researchers contend that the premium could dissipate or fluctuate depending on market conditions.
Such variations necessitate a review of historical returns sub-divided into periods (e.g., pre- and post-1970s).
High transaction costs associated with small cap investing necessitate higher expected returns.
Risks may not be fully captured in conventional risk metrics like beta, due to:
Information Risk: Small companies attract less analyst attention, leading to asymmetrical information.
Liquidity Risk: Smaller companies may face larger price impacts from trades due to lower trading volume.
Diversification: A broader range of investments (e.g., owning 50+ smaller stocks) is advocated to mitigate risks.
Due Diligence: Investors must undertake independent research and not rely on market consensus, which may be flawed due to a lack of information.
Long-term Horizon: A longer investment timeframe reduces exposure to short-term volatility and operational risks.
In this session, we established the groundwork for understanding growth investing with an emphasis on small cap strategies. There exists a documented small cap premium over large cap stocks; however, investors must be cautious of associated transaction costs and risks not reflected in conventional metrics. A disciplined approach, characterized by extensive research and a long-term outlook, is essential for success in small cap investing.
This document discusses a strategy for growth investing focusing on investing in companies at the moment they go public, referred to as Initial Public Offerings (IPOs). The goal is to exploit perceived mispricing during this phase.
The IPO process is crucial to understand for effective investing. It typically follows these steps:
A private company approaches an investment banker to discuss going public.
The investment banker organizes a syndicate of other banks, particularly for large offerings.
The syndicate evaluates the company and prepares a prospectus, which is filed with the Securities and Exchange Commission (SEC).
The banker prices the offering based on market demand and supply, often setting the price lower than market value to ensure successful sales.
Investment banks usually provide an underwriting guarantee, which implies they will buy shares at a guaranteed price before the IPO. However, the actual price is determined shortly before the offering, making the perceived risk smaller than it might appear.
There is a distinction between valuation and pricing:
Valuation: Determining a company’s intrinsic value based on its fundamentals.
Pricing: Setting a price that reflects current market demand and supply.
The banker primarily engages in pricing rather than intrinsic valuation.
On average, IPOs are underpriced. For instance: - If the offering price is $9.00, it may open at $9.50 to $9.80, indicating a typical underpricing of 16%.
Statistical findings reveal that: - The average underpricing rate is approximately 15.8% across a sample of 13,300 IPOs. - On average, about 15% of IPOs are overpriced.
Offerings where the price has been revised upwards before the IPO tend to see a significant increase compared to those downgraded.
Market dynamics, such as hot vs. cold market cycles, can influence the degree of underpricing.
Given that IPOs tend to be underpriced, investors might consider the following:
Investors face a selection bias: not receiving the full number of shares requested due to higher competition for underpriced IPOs. Consequently, portfolios may skew towards overpriced offerings.
The IPO market operates in cycles:
Hot Cycles: Characterized by numerous IPOs with high underpricing.
Cold Cycles: Few IPOs and potential overpricing.
Understanding these trends helps investors time their investments more effectively.
Investing in IPOs for the long term may not yield favorable results. Post-IPO stock performance often underperforms compared to the broader market. Therefore, the timing of sale is critical.
Investing in IPOs can be beneficial due to the average underpricing but comes with challenges such as selection bias, market cycles, and timing. To enhance investment success, potential strategies include:
Conducting valuation analysis to identify undervalued IPOs.
Attempting to become a favored client of investment banks to enhance share allocation during IPOs.
Timing exits to maximize gains post-offering.
Thank you for considering these insights on IPO investing.
Value investing focuses on screening for stocks that are undervalued based on fundamental metrics. In contrast, the goal of growth investing is to identify companies where growth prospects are underestimated or underpriced.
When screening for growth companies, the aim is to find opportunities where investors can get a dollar of growth for less than a dollar cost. This involves using similar frameworks as value investing but focusing on growth attributes.
The first primary strategy for identifying growth companies is the PEG ratio, defined as:
$$\text{PEG} = \frac{P/E}{g}$$
where P/E is the price-to-earnings ratio and g is the expected growth rate of earnings. A PEG ratio less than 1.0 indicates a potentially undervalued stock.
The second common approach is to look for companies with a history of high earnings growth. However, evidence indicates that historical growth is not a reliable predictor of future performance due to low correlation. Companies that have shown high growth in the past may not necessarily sustain this growth.
Correlations Over Time: Historical growth rates lack strong correlations across time periods. For example, businesses with high growth in the preceding three to five years might not be the same entities that perform well in subsequent years.
Subjectivity: Historical growth rates depend on the chosen timeframe. This selectivity can easily manipulate growth metrics.
Research shows that revenue growth tends to be more stable and sustainable than earnings growth. As such, when constructing an investment strategy, prioritizing revenue growth data is advisable.
While it may seem counterintuitive, investing in high P/E stocks can yield positive returns during specific economic conditions, such as when the yield curve is flat or inverted.
The GARP strategy combines expected growth rates with the P/E ratio:
A P/E ratio lower than the expected growth rate suggests a good investment opportunity.
Conversely, if the P/E ratio exceeds the expected growth rate, the stock may be overvalued.
To refine the GARP approach, one can look at the inverse with the PEG ratio calculated as:
$$\text{PEG} = \frac{P/E}{g}$$
A lower PEG ratio indicates better value concerning growth. Empirical studies have indicated that lower PEG ratios outperform higher ones.
The challenge with low PEG ratio searches is they can lead to high-risk investments. This is because riskier companies often exhibit lower PEG ratios, potentially skewing results towards risk-laden stocks.
Identifying growth companies that provide a good entry point is more complex than for value stocks. A deep understanding of growth fundamentals, a long-term investment horizon, and the ability to manage macroeconomic factors can significantly enhance the chances of successful growth investing.
Investors interested in pursuing growth investing should employ a robust analysis of sustainable growth and be prepared for longer time horizons before realizing returns.
In this session, we explore the fourth and final method of growth investing, known as activist growth investing. Unlike traditional growth investors, activist growth investors participate actively in the company’s governance and management to enhance its growth prospects.
Activist Value Investing involves investing in mature or declining companies, seeking to turn them around after their peak performance.
Activist Growth Investing targets young startups before they gain market recognition, with the goal of profiting as the company grows and potentially goes public or is sold.
Venture capital (VC) investing began in the 1950s with firms like American Research and Development. The goal is to provide capital to startups with high growth potential.
Traditional Venture Capital: Focuses on early-stage companies.
Private Equity (PE): Involves pooling capital from wealthy individuals to invest in promising private firms, often competing with VCs.
Leveraged Buyout (LBO) Funds: Typically target mature companies but may also invest in public firms with growth potential.
Initial Idea: Entrepreneurs begin with personal funding and ideas for a business.
Seeking Investors: After exhausting personal funds, they approach venture capitalists (VCs) for investment.
Negotiation: An agreement is reached regarding the amount of investment versus the percentage of equity in the company.
Pre-Money Valuation: The value of a company prior to investment.
Post-Money Valuation: The company’s value after the investment has been added:
Post-Money Valuation = Pre-Money Valuation + Investment
Venture capitalists have three primary exit strategies to realize their investment returns:
Initial Public Offering (IPO): Taking the company public, often the most lucrative option.
Sale to a Public Company: Selling the private company to a publicly traded firm.
Cash Flow Utilization: If other options fail, relying on operational cash flows to recoup investments.
Statistical data shows the failure rates of startups over time:
| Year | Percentage of Firms Surviving |
|---|---|
| 1 | 81% |
| 2 | 65% |
| 3 | 50% |
| 4 | 40% |
| 5 | 30% |
Discount Rate Adjustment: Given the high risk of failure, VCs typically increase the discount rates used in their models, often to 40-60%.
1. Projected earnings after n years (e.g. n = 3):
Future Earnings = Earnings × Multiple
For example, if a company has projected earnings of $10M with a multiplier of 20:
Valuation = 20 × 10, 000, 000 = 200, 000, 000
2. Present Value Calculation:
$$\text{Present Value} = \frac{\text{Future Value}}{(1 + r)^n}$$
where r is the desired rate of return and n is the number of years into the future.
Company Selection: The most crucial skill is identifying promising entrepreneurs and innovative ideas.
Diversification: Spread investments across various sectors and geographies.
Management Support: Provide guidance to founders who may lack managerial experience.
Protect Investments: Ensure adequate protection and terms in future funding rounds.
Exit Strategy: Develop a strategic exit plan to maximize returns.
Activist growth investing involves investing in young companies and actively influencing their success. While potential returns are substantial, historical performance indicates that actual gains may fall short of expectations. Successful investors must focus on thorough due diligence, strategic management support, and prudent risk management.
Growth investing focuses on purchasing stocks of companies expected to grow at an above-average rate compared to their industry or the overall market. This document summarizes various approaches and considerations for growth investing as discussed in the course.
The course outlined four distinct strategies:
Investing in small-cap stocks is a common growth investing strategy. While these stocks can also be part of a value investing approach, their potential for higher growth often attracts growth investors.
Investing in IPOs at the time of offering represents another growth investing strategy. This involves acquiring shares of newly public companies that are expected to expand rapidly after their market debut.
Utilizing screens to identify growth stocks that are reasonably priced is essential. Common screening metrics include:
Earnings Growth Screens
PEG Ratio Screens
Price/Earnings Relative to Growth Screens
This strategy involves proactively investing in young growth companies at the beginning of their growth phase, betting on their success to generate returns.
It is essential to understand that while growth investing can be lucrative, it often underperforms compared to value investing over long periods. Historical data shows that:
$$\text{Return} \propto \frac{1}{\text{PE Ratio}}$$
where stocks with lower PE ratios tend to have higher returns. Nevertheless, growth stocks can outperform in certain scenarios, especially:
During periods of low earnings growth in the market.
When identified through market timing as a growth investor.
Studies suggest that active growth investors tend to outperform passive growth index funds. Specifically, findings from Bert Malkiel in 1995 indicated that while actively managed value funds often underperform their index, active growth funds can outperform their index counterparts.
The apparent contradiction where value stocks outperform growth stocks but active growth investing shows promise can be explained through:
Company Fundamentals: Growth investors often target smaller, less-followed companies, increasing the potential for mispricing.
Valuation Complexity: Mature companies (often favored by value investors) are easier to value than young, high-growth companies.
Sector Knowledge: Growth investors equipped with specialized knowledge of new sectors can find undervalued opportunities that others overlook.
Potential pitfalls include:
Scaling Challenges: As successful growth investors scale up their funds, it may become difficult to maintain the same level of opportunity in smaller companies.
Excess Returns: Growth must be coupled with excess returns to truly add value. Investors need to evaluate how much a company invests to achieve growth and the returns generated.
Momentum Risk: Growth stocks often operate within a momentum framework, where prices can detach from intrinsic value, affecting the investment returns.
To excel as a growth investor, one should be aware of the following:
Investors should not only focus on expected growth but also on the company’s investments to achieve that growth and the returns on those investments.
Understanding the intricacies of company valuations, especially in technology and services where R&D expenditures may be obscured in financial statements, is critical.
Consider identifying catalysts that could shift investor sentiment to reduce the price-value gap in growth investing.
While the overarching evidence suggests that value investing tends to outperform growth investing, there are scenarios where growth strategies can yield profitable outcomes. Competent active management in growth investing often proves more effective than in value investing, highlighting the importance of rigorous analysis and understanding market dynamics.
This session discusses trading strategies based on information, marking a departure from traditional value and growth investing. Unlike previous philosophies that emphasized identifying undervalued stocks, this approach focuses on how market prices are influenced by information.
Investors possess varying information sources:
Public company announcements (simultaneous access to all investors)
Private or insider information (may be legal/illegal)
Special relationships leading to information advantages
Even with identical information, differing interpretations lead to variability in perceived value. Market prices reflect the balance of supply and demand driven by this information asymmetry.
In an efficient market:
Prices reflect all available information.
New information has a 50-50 chance of being classified as good or bad.
Price reactions to new information are instantaneous.
The potential reactions to new information are depicted as:
New Price = Old Price + ΔP
In inefficient markets, reactions to new information can vary:
Slow Learning Markets: Prices adjust slowly over time. The degree of adjustment depends on market inefficiency.
Overreacting Markets: Initial price reactions are excessive, leading to subsequent price corrections.
For a slow learning market, price behavior can be represented as:
P(t) → P(t + Δt) (gradual drift)
For an overreacting market:
P(t) = P(t − 1) + ΔP (initial jump) → P(t + k) = P(t − 1) − ΔP′ (correction)
The following strategies can be used for information-based trading:
To exploit upcoming news, investors may:
Leverage insider information (where legal).
Monitor rumor mills for potential news events.
Analyze trading volume spikes as signals of forthcoming news.
Investment decisions will vary depending on the reliability of sources and the level of conviction about the news.
Investors can react to the announcement itself:
Price Reaction: Buying after positive news or selling after negative news, particularly in slow learning or overreacting markets.
Volatility Reaction: Trading options based on shifts in expected volatility post-announcement.
For a positive news event, price and volatility reactions can be summarized as:
Pnew = f(Pold, News Quality)
If markets are inefficient:
Buy stocks after good news and hold until the price fully reflects market learning.
Short sell after bad news and hold until prices stabilize.
In an overreacting market, an investor would:
Sell immediately after good news, anticipating a price correction.
Buy immediately after bad news to take advantage of subsequent price recovery.
Trading based on information requires a strategic approach that considers how markets respond to news events. By understanding market inefficiencies, investors can exploit price adjustments, ultimately enhancing their trading success. Future discussions will delve deeper into evidence supporting information-based trading strategies.
Insider trading involves tracking information from insiders—those with access to confidential information about a company—rather than waiting for public announcements. This practice includes monitoring stock trades made by these insiders to make informed investment decisions.
Insiders are individuals who possess material non-public information about a company. This definition extends beyond the classic SEC definition (officers, directors, and major shareholders) to include:
Investment bankers
Traditional bankers
Suppliers
Research analysts (though their status as insiders is waning)
Ultimate Insiders: Employees working for the company with direct access to sensitive information.
Equity Research Analysts: Traditionally considered insiders, their roles have shifted due to regulations limiting their access to information.
To determine if insider trading can predict stock price movements, researchers analyze the correlation between insider trading activities and subsequent stock returns.
The behavior of insiders—buying or selling stock—serves as signals for potential price movements:
Insider Buying: Typically precedes stock price increases.
Insider Selling: Often precedes stock price decreases.
Research typically examines returns following insider trading disclosures submitted to the SEC:
Stocks where insiders bought saw an average increase of 35% over 20 months.
Stocks with insider selling saw an average increase of only 5% over the same period.
Let R be the return after insider trading within T months, typically analyzed for:
Rbuy = 0.35 (average return after insider buying)
Rsell = 0.05 (average return after insider selling)
However, not all signals are reliable:
Approximately 40% of stocks with insider buying saw a decrease in price.
Studies have noted differences in returns based on the size of the company:
Small Companies: Stronger correlation between insider trading and stock returns.
Large Companies: More information available, weakening the predictive power of insider trading signals.
Over the last 15-20 years, changes include:
Expansion of the SEC’s definition of insiders.
Increased scrutiny and monitoring by companies over employee trades.
Decreased price effects following legal insider trading activities.
This implies that public access to insider information diminishes the potential for profit from such trades.
A critical insight is the timing of information availability. Although the SEC receives filings, public access may lag, meaning:
Lag Effect = Time from filing → Public Awareness
Signals may be too delayed for effective trading.
Focusing on trades by top executives yields more predictive insights than considering all insiders, particularly for large transactions.
Today’s market allows for diverse trading strategies beyond direct stock trading, including:
Options and derivatives
Exchange-traded funds (ETFs)
These avenues may also reflect insider behavior.
While legal insider trading can be tracked via SEC filings, illegal insider trading takes place undetected, often indicated by:
Increases in trading volume before significant announcements.
Price movements showing trends prior to disclosures.
This highlights the profitable potential of understanding not just legal practices but also illegal activity in the market.
While insider trading offers valuable insights, the effectiveness has decreased over time due to regulatory changes and increased information accessibility. Tracking illegal insider trading indicators, such as unusual trading volumes, may provide opportunities for profit.
This session focuses on trading based on public information, specifically earnings reports. Publicly traded companies are required to disclose various forms of information, including:
Earnings Reports
Dividend Announcements
Acquisitions
Other News Announcements
When this information is released, investors react by buying or selling stocks, leading to price fluctuations:
Good news typically causes stock prices to increase.
Bad news typically causes stock prices to decrease.
In the U.S., companies issue at least four earnings announcements per year, one every quarter. These reports are critical as they reveal how well a company is performing compared to market expectations. The significance lies in:
The actual earnings relative to expectations, rather than the absolute values.
Positive surprises (actual earnings much higher than expected) lead to stock price increases.
Negative surprises (actual earnings much lower than expected) lead to stock price decreases.
The market’s reaction to earnings reports can be summarized as follows:
Earnings announcements convey important news regarding market performance indicators, including revenue and margin information.
Some companies’ stock prices drift upward or downward prior to announcements, indicating possible insider trading.
Post-announcement trends show continued price movements, suggesting that markets may not be fully efficient.
Data shows the following trends:
Positive Surprises: Prices tend to continue to rise after the report.
Negative Surprises: Prices tend to continue to fall after the report.
The post-announcement price drift can yield significant returns over time, even if the immediate movements are small:
Price Change ≈ 3%Increase/Decrease
Earnings announcements follow predictable patterns: - Companies report on similar dates each year. - Delayed announcements (beyond six days) often indicate negative news.
As an investor:
Track previous announcement dates for potential delays.
Be cautious if earnings reports are delayed, as they may contain bad news.
Research shows that the stock prices exhibit specific responses immediately after earnings reports:
Immediate reactions show a significant price change:
Negative surprises cause price drops of up to 25%
Positive surprises cause price jumps of around 10%
By one hour post-announcement, approximately 55% of positive price reactions and 70% of negative price reactions are captured.
Price Reaction (Positive Surprise) ≈ 10% (immediate)
Not all earnings surprises carry the same weight. Factors to consider include:
Quality of earnings: earnings driven by genuine operational performance versus accounting changes.
The analysis of cash earnings versus accrual earnings.
Companies that show higher accrual earnings without corresponding cash inflows are usually at greater risk and have lower quality earnings.
To maximize returns from earnings announcements, consider the following strategies:
Play the Drift: Wait to trade until after the earnings announcement, but act quickly.
Focus on Smaller Companies: Smaller, less liquid companies may exhibit greater price drifts.
Select Companies with Quality Earnings: Prioritize those with positive revenue growth alongside positive earnings surprises.
Pre-emptive Trading: Analyze data to predict positive surprises ahead of announcements.
In conclusion, understanding and analyzing publicly available information through earnings reports can provide significant opportunities for investors. Timing and quality of information are paramount when dealing with earnings announcements.
In recent sessions, we have explored various types of information trading, focusing primarily on earnings announcements. In this session, we will extend our discussion to other significant public announcements such as acquisitions, stock splits, and dividend changes.
When a company is acquiring another or being acquired, this represents a major announcement that can influence stock prices.
Target Company: The stockholders of the target company typically experience substantial gains.
Acquiring Company: Historical data show that acquiring companies have mixed results; stock prices may increase slightly or even decrease.
The stock price movement often starts well before the actual acquisition announcement (Day 0), indicating potential information leakage about the deal.
Different structures for acquisitions yield varying returns for target stockholders:
Tender Offers vs. Mergers: Tender offers generally yield higher returns.
Cash Offers vs. Stock Offers: Cash offers lead to greater gains compared to stock offers.
Hostile vs. Friendly Acquisitions: Hostile acquisitions typically lead to higher returns than friendly transactions.
Studies indicate that acquiring companies do not consistently show positive returns post-acquisition:
Average returns may be around zero or slightly positive.
In many cases (up to 60%), acquiring company stock prices drop.
Investing Pre-Acquisition: Identifying potential target companies can yield significant returns.
Post-Announcement Trading: Buying target companies upon announcement to take advantage of price adjustments.
refers to the practice of speculating on merger transactions, aiming to profit from price increases when deals progress to closure.
Common traits of companies likely to become acquisition targets include:
Underperformance in stock price in comparison to peers.
Lower profitability margins.
Lower insider ownership.
Lower price-to-book and price-to-earnings ratios.
Stock splits generally do not significantly affect stock value. Market perception can vary:
Often viewed as a negative signal, indicating a plateau in growth potential.
The overall market response to dividend changes is generally polarized:
Dividend Cuts: Typically result in a decline in stock prices.
Dividend Increases: On average, lead to increases in stock prices.
Recent trends suggest the significance of dividend changes in influencing stock prices is diminished over time, possibly due to increased corporate reliance on stock buybacks instead of dividends.
When formulating an information-based trading strategy, consider the following key factors:
Definition of Information: Clearly specify what type of public information will be utilized for trading.
Information System: Set up mechanisms to receive information quickly, ensuring access prior to the broader market.
Quick Execution: Prioritize rapid execution of trades immediately following the receipt of actionable information.
Control Transaction Costs: Manage transaction costs to maintain positive returns, given the typically small price movements associated with information trading.
Sell Strategy: Predefine conditions under which to sell acquired stocks based on observable metrics.
Trading based on public information can yield returns if executed strategically. Understanding the nuances of acquisition announcements, stock splits, and dividend changes is essential for identifying profitable opportunities. Additionally, maintaining discipline and speed in execution can enhance trading success.
In finance, arbitrage refers to the practice of taking advantage of a price difference between two or more markets. The key concept in arbitrage is to exploit these discrepancies with minimal or no risk.
Pure arbitrage is defined as a situation where two identical assets with the same cash flows are trading at different prices. It carries a guarantee of price convergence in the future, making it virtually risk-free. However, finding such perfect conditions in practice is extremely rare.
Near arbitrage refers to situations that are not completely risk-free and may involve slight risks, despite the risks being small. This can occur when:
Two similar but not identical assets are found.
Identical assets are trading at different prices without guaranteed convergence.
Consider a multinational company whose shares are listed on various exchanges (e.g., London, New York, Tokyo). The expectation is that these stocks, when converted to a common currency, should trade at the same price. Factors influencing this include:
Exchange rate discrepancies.
Transaction costs associated with trading on different exchanges.
A study analyzed 84 stocks traded between the Prague Stock Exchange and another market, revealing price differences of up to 2% at times. This discrepancy was larger for less liquid stocks.
Depository receipts (e.g., American Depository Receipts (ADRs) or Global Depository Receipts (GDRs)) represent shares of companies from emerging markets listed on developed markets. The implications include:
An ADR may represent a fixed number of local shares.
Price discrepancies can persist due to:
Non-freely convertible currencies.
Differences in voting rights and other shareholder privileges.
The expected relationship, presuming an ADR represents 20 local shares, is:
PADR = 20 × Plocal
Where: - PADR is the price of the ADR. - Plocal is the price of the local shares.
However, mispricing can occur due to factors mentioned above, leading to sustained price differences.
Closed-end funds are mutual funds that trade on the market, resulting in a market price that does not always match the net asset value (NAV). Observations include:
The average closed-end fund trades at a discount of 10% to 15% relative to its NAV.
Theoretically, one could:
Buy the closed-end fund and liquidate the underlying securities to claim the difference.
However, challenges include:
Difficulty forcing the fund to open-end or liquidate due to corporate governance issues.
Tax liabilities that may offset gains from liquidation.
Convertible arbitrage involves various capital raising methods (e.g., stocks, bonds, convertible bonds). Here, investors look for mispricings between:
Regular bonds and convertible bonds.
Stocks and options.
By taking long positions in undervalued securities and shorting overvalued ones, investors can profit as prices converge.
Although pure arbitrage opportunities are rare, near arbitrage can provide feasible strategies for astute investors. Key considerations when engaging in near arbitrage include:
Transaction costs.
The necessity for significant capital investment.
Identification of catalysts that may lead to price convergence.
Arbitrage refers to the simultaneous purchase and sale of an asset in different markets to profit from discrepancies in the price. This session distinguishes between several forms of arbitrage, including pure, near, and pseudo (or speculative) arbitrage.
Definition: Involves two identical assets in terms of cash flows trading at different prices, with a guarantee of convergence.
Profit Mechanism: The trader profits by exploiting the price differential.
Definition: Involves similar or closely identical assets trading at different prices without a guarantee of convergence.
Risk Factor: Nearly riskless but not completely free of risk.
Definition: A blend of traditional investing with an element of arbitrage, characterized as low-risk but actually speculative.
Risk Level: Not riskless; speculative in nature.
Historical Analysis: Identifies pairs of stocks that have historically correlated (e.g., Ford and GM).
Price Discrepancy: When the actual price difference diverges from historical levels, an investor buys the cheaper stock and sells the more expensive one.
Objective: To profit when historical price relationships revert.
Average Excess Returns: Studies have shown returns from paired trading strategies can yield returns around 6% above required returns.
Influence of Industry Group: Constraining pairs to the same industry yields smaller excess returns.
Not Riskless: Pairs can widen rather than narrow, leading to potential losses.
Historical Performance: The profitability of the strategy has declined over time as more investors adopt it.
Process: Invest once a merger announcement is made, betting on the increase in stock price from the announcement price to the ultimate offer price.
Risks: If the merger fails, the stock price can revert to pre-announcement levels, resulting in potential losses.
Annual Returns: Historically, merger arbitrage yields about 9.25% annually but suffers from high transaction costs and significant price impact.
High Risk: Potential for large losses in case of a merger failure.
Pure Arbitrage: Can involve 100% leverage due to risklessness.
Near Arbitrage: Can accommodate leverage ratios up to 80-90%.
Speculative Arbitrage: Leverage should be controlled due to inherent risks; lower leverage is advised.
Background: Involved talented individuals but mismanaged leverage during speculative investment phases.
Lesson: Importance of adjusting leverage when switching from low-risk to higher-risk strategies.
Flexibility: Can adopt various strategies including long and short positions, aiming for higher returns.
Performance Metrics: While average hedge fund returns hover around 13.26%, these are lower than the S&P 500’s performance during the same period but come with lower volatility.
Sharpe Ratio: Hedge funds present a better payoff-to-risk ratio ( ≈ 1.4) than S&P 500 ( ≈ 1.0).
Finding: Many hedge funds do not survive long-term, skewing the perception of average returns downward when filtering for survival.
The various forms of arbitrage, from pure to pseudo, illustrate a spectrum of risk and reward. Investors must navigate these strategies with an understanding of their risks, particularly those associated with leverage. Hedge funds can leverage arbitrage strategies but also face significant market competition and variable performance.
In various sessions, we’ve explored different investment philosophies:
Value Investors: Seek companies underpriced relative to their assets and prior investments.
Growth Investors: Look for companies with growth assets that are undervalued, focusing on obtaining growth at a reasonable or low price.
Arbitrage Investors: Attempt to find and exploit mispriced stocks within the market.
Information Traders: Take advantage of the market’s improper reactions to individual stock information.
Commonality: All these strategies involve selecting individual stocks and do not focus on market timing.
This session focuses on a higher-level investment philosophy where the emphasis is on market timing rather than stock selection.
Starts with the client (tax preferences, risk tolerance, investment horizon).
Involves three main steps:
Asset Allocation Decision:
A = f(S, C, B, R)
where A is the allocation to assets S (stocks), C (cash), B (bonds), and R (real assets).
Risk aversion, time horizon, and tax status determine the allocation.
Market timing is the strategy of adjusting asset allocation based on the perceived value of stocks versus bonds.
Research indicates that a significant portion of return differences among investors is attributed to market timing rather than stock selection.
In a 1986 study, researchers found that 93.6% of the quarterly performance variation across money managers could be explained by their asset mix (stocks, bonds, and cash).
Robert Shiller’s 1992 study revealed that by avoiding the worst 50 months in the market (1946-1991), an investor’s annual return could have been increased dramatically. For example, the return could have increased from 11.2% to 9%.
Mis-timing: The possibility of being out of the market during beneficial periods (e.g., good years).
Transaction Costs: Frequent trading incurs higher transaction costs.
Tax Liabilities: Capital gains taxes may increase due to necessary sales when attempting market timing.
The payoff for successful market timing can be immense, but the cost if done poorly can also be significant. Investors must weigh potential benefits against risks and costs.
Five primary methods of market timing include:
Non-Financial Indicators: Ranging from social sentiment to more analytical indicators.
Technical Indicators: Utilization of charts, support/resistance lines for market predictions.
Mean Reversion Indicators: Assumes that variables (e.g., P/E ratios, interest rates) revert to historical norms.
$$P/E_t \rightarrow \bar{P/E}$$
Macroeconomic Variables: Assessing economic indicators (GDP growth, inflation) to anticipate market performance.
Intrinsic Value Analysis: Valuing the market as a whole akin to valuing individual stocks, determining overpricing or underpricing.
It is essential for investors to acknowledge whether they consciously or unconsciously engage in market timing as part of their investing strategy. By doing so, they can approach market timing in a more systematic and informed manner.
Market timing approaches are strategies that attempt to predict future market movements based on various indicators. These indicators are broadly classified into two categories: non-financial indicators and technical indicators.
Non-financial indicators can be categorized into three main groups:
Spurious Indicators:
These indicators may make for interesting stories but lack predictive power.
Example: The Super Bowl Indicator claims that the winning team predicts stock market performance.
Feel Good Indicators:
Measure the confidence of investors, correlating positive sentiment with rising stock prices.
Example: The number of patrons at high-end restaurants in New York City could indicate banker confidence.
Contrarian Indicators (Hype Indicators):
Measure the levels of market "hype" and investor behavior.
Example: The Cocktail Party Chart analyzes how quickly investors begin discussing stocks at social events.
Spurious indicators lack an economic basis.
Although historical data points may show correlation, this can arise from chance.
They often only indicate the direction of markets without estimating magnitude.
These indicators measure changes in consumer sentiment and spending behaviors.
Often contemporaneous, observing correlations between current market moves and their impact.
These indicators can also revert to serve as poor predictive metrics when sentiment shifts and may become "feel bad" indicators.
Hype indicators are contrarian by nature.
They are founded on the observation that excessive enthusiasm often leads to market corrections.
Example: Social media sentiment analysis through platforms like Twitter.
Technical indicators rely on historical price movements and trading volume.
Momentum: Stocks that perform well tend to continue performing well, while those that decline may further decline.
Calendar Effects: "As January goes, so goes the year" suggests that January performance foreshadows yearly market performance.
January’s market performance can influence expectations, however, its predictive power weakens considerably when examining the following months.
These indicators gauge the strength of price movements.
Price increases accompanied by high trading volume are more likely to continue.
High volume on a down day may indicate a reversal, termed as a "selling climax."
The put/call ratio can also act as a contrarian indicator: a high ratio indicates market pessimism, possibly signaling a buying opportunity.
Money flow quantifies the difference between uptick and downtick volume, used to gauge market positivity.
Studies show mixed predictive power of money flow; while it correlates with past performance, long-term trends show slightly better predictive validity.
Indicators like the VIX measure market volatility, suggesting a relationship where increasing volatility can precede falling stock prices but lead to higher returns subsequently.
Chart patterns, sentiment indicators, and the confidence index provide additional data points for market predictions.
The confidence index involves the yield ratio of bonds, which reflects risk perception in the market.
Despite numerous indicators, evidence suggests that their predictive power is often limited and can be noisy. Investors should use these indicators with caution and not rely solely on them for making financial decisions.
Market timing involves making investment decisions based on predictions about future market movements. Two common approaches for stock valuation, which can also be adapted for market valuation, are:
Intrinsic (Discounted Cash Flow) Valuation
Relative Valuation
This session explores the applicability of these valuation methodologies to the overall market, specifically the S&P 500 index.
Intrinsic valuation involves estimating the present value of expected cash flows from an investment.
To value the S&P 500 using intrinsic valuation, start with the cash flows from the constituent companies.
$$CF_{total} = \sum_{i=1}^{n} CF_i$$
where CFi represents the cash flow from each of the 500 companies in the index.
In this analysis:
Cash flows from dividends and stock buybacks are considered.
As of January 1, 2011, the collective cash flow (CF) was approximately $53.96.
Given that analysts projected a growth rate of 6.95% for the next 5 years, we apply this growth rate to the cash flows:
CFt = CF0 × (1 + g)t
For t = 1, 2, …, 5 and g = 6.95%.
After 5 years, we assume the growth rate stabilizes to a risk-free rate of 3.29%, based on the following reasoning:
glong − term = rf = 3.29%
The required return (cost of equity) for investing in the market is calculated as follows:
r = rf + ERP
where:
rf = Risk-free rate ($3.29%)
ERP = Equity Risk Premium ($5%)
r = 3.29% + 5% = 8.29%
The terminal value (TV) at the end of Year 5, using the Gordon Growth Model, is computed as:
$$TV = \frac{CF_5 \times (1 + g_{long-term})}{r - g_{long-term}}$$
where CF5 is the cash flow at Year 5.
We sum the present values of the cash flows for the first 5 years and the terminal value:
$$PV = \sum_{t=1}^{5} \frac{CF_t}{(1 + r)^t} + \frac{TV}{(1 + r)^5}$$
The computed value of the S&P 500 based on the given assumptions and calculations leads to a value of $13,074, compared to its actual price of $1,257.64, indicating that the market is perceived as undervalued.
Relative valuation can be applied to determine if the market price is fair compared to historical standards or against other markets.
The earnings-to-price ratio (E/P Ratio) can be compared to long-term T-bond rates to determine relative valuation trends.
Correlation: E/P ∼ T − bond Rate
A regression analysis shows that the earnings-to-price ratio is correlated significantly with T-bond rates.
Given the T-bond and T-bill rates, we can derive expected Earnings-to-Price Ratios.
Comparative analysis can also be done across different markets using P/E ratios while considering other economic factors like interest rates and macroeconomic risks.
$$\text{P/E Ratio} = \frac{\text{Price}}{\text{Earnings}}$$
In the example where Argentina has a P/E of 14, when controlled for high interest rates and low economic growth, it was shown to be fairly valued.
Using intrinsic and relative valuation methods offers valuable insights into market timing. While historical models are useful, constantly evolving macroeconomic factors should be taken into consideration when evaluating market conditions.
Market timing involves the ability to predict future movements in the financial markets and adjust investment strategies accordingly. This analysis will explore whether market timing is a viable strategy by examining three groups:
Mutual Fund Managers
Investment Newsletters
Market Strategies from Investment Banks
Mutual fund managers typically do not invest all funds in equities; they hold a portion in cash.
The cash position is often seen as an implicit indicator of the manager’s market outlook:
Bullish outlook: Lower cash holdings.
Bearish outlook: Higher cash holdings.
Studies suggest mutual funds often peak cash holdings after market downturns, indicating poor timing.
Example from 1990: Cash positions peaked following a poor year for stocks.
Contrarian behavior noted: Mutual funds tend to hold cash before markets rise, indicating they are not effective market timers.
Comparison of Tactical Asset Allocation Funds to:
100% Invested in S&P 500
Couch Potato Strategy (e.g., 50/50 stocks to bonds)
Underperformance of Tactical Asset Allocation Funds
Evidence shows some hedge funds have demonstrated timing ability, particularly in:
Bond markets
Currency markets
Few hedge funds displayed timing ability in equity markets.
Recent studies suggest hedge funds manage market exposure more effectively before liquidity changes.
Study analyzed 237 newsletters.
Found that 183 newsletters performed poorer than a simple buy-and-hold strategy.
58% of the time, newsletters advised increasing stock allocation before market upturns.
53% did the same before downturns, indicating no significant predictive ability.
Investment banks offer market strategies with asset allocation advice.
A Wall Street Journal study revealed that:
100% equity investments outperformed most market strategies.
A robotic or passive investment plan often matched or exceeded average strategist performance.
Adjust Asset Allocation: Allocate more to stocks if perceived as undervalued and vice versa.
Switch Investment Styles: Tailor strategies across market conditions (e.g., value vs. growth investing).
Sector Rotation: Invest in sectors based on their performance in different economic cycles.
Speculation: Use financial instruments like options and futures. High potential returns but also high risk of losses.
Missing returns while out of markets can lead to significant losses.
Costs can erode potential advantages from market timing.
Overall, the evidence indicates that consistent market timing success is rare across mutual funds, hedge funds, and investment newsletters.
For those aspiring to time the market, it may be worthwhile to blend market timing with security selection based on performance feedback:
Evaluate which strategy (market timing or security selection) yields better returns over time.
Adjust focus accordingly based on self-assessment of skills.
In this session, we explore the case for passive investing, contrasting it with various active investment strategies such as:
Value Investing
Growth Investing
Charting
Trading on Information
Arbitrage
Market Timing
Understanding the performance of active investing is essential to appreciating the potential benefits of passive investing. We will analyze both individual investors and professional fund managers.
The average individual investor fails to beat the market after accounting for trading costs.
A study covering the years 1991-1996 showed:
S&P 500 Index Fund Return: 17.8%
Average Individual Investor Return at Brokerage House: 16.4%
Return Loss Due to Trading Activity:
Loss = 17.8% − 16.4% = 1.4%
Additional Findings:
Increased trading frequency correlates with lower returns.
Investment clubs do not significantly improve performance; they average a return of 14.1%, underperforming both the S&P 500 and individual investors.
The top quartile of individual investors outperformed the market by 6%. However, this group is highly variable and does not consistently include the same individuals.
Investors tend to achieve better returns when:
Investing in companies geographically close to them.
Maintaining concentrated portfolios rather than widely diversified ones.
Professional managers are assumed to have better information, yet studies reveal their performance is often disappointing:
Michael Jensen’s study in the 1960s showed that about two-thirds of mutual funds failed to beat the market.
Jensen’s Alpha (α) was introduced as a measure of performance:
α = Rp − (Rf+β(Rm−Rf))
where Rp = portfolio return, Rf = risk-free rate, β = beta of the portfolio, and Rm = market return.
Subsequent studies found that both active stock and bond funds underperform their respective indices.
Survivorship Bias:
Failed funds tend to have lower average returns than surviving funds.
Excluding these funds leads to inflated average returns when assessing mutual fund performance.
An analysis of fund performance by market capitalization found:
Large-cap funds: 43% beat their index.
Mid-cap funds: 36% - 37% beat their indices.
Small-cap funds: Lowest percentage of outperformers.
Investment styles (Growth vs. Value vs. Yield):
Yield funds had the highest percentage of managers beating their index at 56%, while Growth and Value performed worse.
Across various categorizations (age, load vs. no-load, institutional vs. retail):
Funds consistently underperform their indices.
Performance does not significantly improve with factors such as fund age or institutional backing.
There is overwhelming evidence suggesting active investment strategies generally underperform compared to passive strategies.
The results highlight the challenge of achieving consistent outperformance in active management and propose passive investing as a more reliable alternative.
In previous discussions, we examined investor performance and mutual funds relative to market indices. The key findings indicated an overall trend of underperformance:
Individual investors tend to underperform market indices.
Mutual funds, on average, also underperform.
Transition probabilities provide a framework for analyzing whether the performance rankings of mutual fund managers are stable across time periods.
Mutual fund managers can be ranked into quartiles based on their performance:
Top 25% (1st quartile)
25%-50% (2nd quartile)
50%-75% (3rd quartile)
Bottom 25% (4th quartile)
If performance is stable, we would expect a diagonal distribution where 100% of managers in each quartile stay in that quartile in the subsequent period:
$$P_{i,j} =
\begin{cases}
100\% & \text{if } i = j \\
0\% & \text{if } i \neq j
\end{cases}$$
However, studies indicate randomness rather than stability in performance rankings.
Even when accounting for the survival bias (i.e., poorer-performing funds being liquidated), the consistency in mutual fund performance remains low, often below 27% continuity.
Investors often look at Morningstar ratings as a heuristic for fund evaluation. However, earlier studies indicated:
No significant difference in performance between top-rated and lower-rated funds.
In response to critiques, Morningstar adjusted its rating systems, leading to improved predictive validity:
Funds increasingly show a positive correlation between ratings and future performance.
Evidence suggests some funds demonstrate "hot hands," or persistence in performance, particularly over short time intervals:
P(winner repeats) ≈ 65% (1971-1979)
This statistic, though diminishing to 52% in the 1980-1990 interval, detects some momentum effect.
Several factors affect the performance of active mutual funds, including:
High turnover costs can severely affect returns. On average, mutual funds underperform by 1.5% to 2% due to transaction costs.
Active trading often incurs significant tax liabilities, leading to lower after-tax returns:
After-tax return (Active Fund) < After-tax return (Index Fund)
Excessive trading can negatively impact returns. Studies suggest:
Frozen Portfolio Return > Active Portfolio Return
These findings indicate that “buy and hold” strategies could outperform actively managed strategies.
Active managers often attempt market timing but perform poorly when compared to steady investment strategies.
Manager behavior can lead to:
Lack of consistency in investment style.
Herding behavior, where fund managers mimic popular trends.
Window dressing strategies that incur costs without added benefits.
Despite numerous potential market beating strategies, active managers consistently fail to outperform passive index funds. Causes for this include transaction costs, taxes, behavioral biases, and difficulty in timing the market. The evidence suggests a preference for passive investing strategies over active management.
This document summarizes the distinction between active and passive investing strategies, discussing the merits and challenges of both approaches as well as a variety of investment options available for passive investors.
Active investing has been analyzed through various perspectives, including:
Performance: The average active investor typically does not outperform the market.
Market Efficiency: The lack of performance cannot solely be attributed to poor individual choices; it is a systemic issue across the active investing landscape.
Passive investing has become a popular alternative due to the challenges faced in active investing. When transitioning to passive investing, investors have several options:
Classic Index Funds
Enhanced Index Funds
Exchange-Traded Funds (ETFs)
Classic index funds aim to replicate the performance of a specific market index by investing in all or a sample of the stocks within that index.
To construct a classic index fund, the following steps are taken: 1. Identify the index to replicate (e.g., S&P 500). 2. Invest in each constituent stock based on their market capitalization.
$$w_i = \frac{M_i}{\sum_{j=1}^{n} M_j}$$
Where wi is the weight of stock i, and Mi is the market capitalization of stock i.
Low maintenance: Once established, a classic index fund requires minimal adjustments unless companies are added or removed from the index.
Self-correcting: If a stock’s value increases in the index, its value automatically adjusts in the fund.
Enhanced index funds aim to mirror the index while attempting to achieve higher returns, possibly through minor adjustments to the index-specific strategy.
Utilizing Derivatives: Combining options and futures to exploit pricing inefficiencies.
Active Stock Selection: Removing underperforming stocks from the index and replacing them with better alternatives based on fundamental analysis.
Re = Ri + ϵ
where Re is the expected return of the enhanced fund, Ri is the return of the index, and ϵ is the additional return generated through active management.
Mean-Variance Optimization: Using historical return data to select a subset of stocks from the index that maximizes expected returns for a certain risk level.
ETFs are funds that track a specific index, sector, or asset class and trade like individual stocks on an exchange.
High liquidity: ETF prices update throughout the trading day.
Flexibility: Allows for rapid adjustments to positional exposure in various market segments.
Enhanced index funds can potentially deliver slightly higher but not guaranteed returns compared to classic index funds. The additional costs and risk involved may offset potential benefits.
Expected Return = Risk-Free Rate + β(Market Return − Risk-Free Rate)
Where β represents the volatility of the investment relative to the market.
Investors should carefully analyze their investment styles and preferences between active and passive strategies. Passive investment choices have broadened significantly, allowing for diversified exposure without the necessity to actively manage stock selections.
Investment philosophies vary greatly among individuals, and there is no one-size-fits-all approach. The key to successful investing lies in choosing a philosophy that aligns with one’s personal and financial characteristics.
Before selecting an investment philosophy, individuals should conduct a self-assessment based on several personal characteristics:
Patience: Are you more patient or impatient? This trait determines suitability for long-term strategies.
Risk Aversion: Identify the level of risk that makes you comfortable. Consider how much risk is acceptable versus what is too risky.
Thinking Style: Are you an individual thinker or influenced by group dynamics? This determines your inclination towards contrarian or momentum strategies.
Time Commitment: Evaluate how much time you can dedicate to investing. Busy lifestyles require less active strategies.
Age: Your age can influence your risk tolerance and investment horizon.
To ensure that your selected investment philosophy matches your requirements, consider the following tests:
Sleep Test: Can you sleep well knowing your portfolio’s contents? If not, reconsider your investment choices.
Life Change Test: Could a market downturn significantly alter your lifestyle? If so, your portfolio may not be aligned with your risk tolerance.
Second Guessing Test: Are you frequently doubting your investment decisions? This indicates a potential mismatch in your investment strategy.
Your choice of investment philosophy will inevitably depend on your financial situation:
Job Security: Higher earnings and stable jobs allow for riskier investments.
Investable Funds: The amount available for investment limits or expands your choices. Consider all assets collectively.
Cash Needs: Unpredictable cash demands can constrain your investment choices and time horizons.
Tax Status: Different tax rates on various income types influence investment strategy selection.
Every investment philosophy is grounded in certain beliefs regarding market behavior. The development of these beliefs can be informed through:
Ongoing investment experiences (both profits and losses).
Research and learning from financial literature and discussions.
Adapting your philosophy based on practical lessons learned in the field.
Investment philosophies can be categorized by their time frames and approach:
Short-Term: Momentum, Contrarian, and Opportunistic strategies.
Medium-Term: Similar strategies with a slightly longer horizon.
Long-Term: Active Growth, Passive Growth, Active Value, and more.
Short-Term Momentum: Technical indicators, buying after positive earnings.
Medium-Term Contrarian: Market timing strategies based on mean reversion.
Long-Term Value Investing: Targeting undervalued companies with potential for turnaround.
When selecting an investment philosophy, consider:
Whether the philosophies harmonize, avoiding contradictions in market assumptions.
Choosing a primary philosophy and a secondary one for a comprehensive approach.
The essence of successful investing is to align your investment philosophy with your personal characteristics, financial situation, and beliefs about market behavior. Regularly reflect on your strategies and remain receptive to evolving your approach based on real-world experiences.
Thank you for participating in this investment education journey.