contents

Intro to Financial Markets

Introduction

Core Themes

Course Perspective

Purpose of the Course

Ethical Considerations in Finance

Financial Institutions and Crises

Course Structure

Conclusion and Purpose in Finance

Lecture Notes on Probability and Finance

Introduction to Probability in Finance

This lecture focuses on the role of probability theory in understanding financial crises, particularly emphasizing the 2007 crisis, which is considered the most significant financial crisis since the Great Depression.

Basic Concepts

Key Areas of Discussion

Basic Financial Returns

Definition of Return

The return on an investment is defined mathematically as:
$$R_t = \frac{P_{t+1} - P_t + D}{P_t}$$
where:

Gross Return

The gross return can be expressed as:
Gross Return = 1 + R
where returns can be positive or negative but are bounded between -100% and +infinity.

Statistical Measures

Expected Value and Mean

The expected value (mean) of a random variable X is given by:
$$E[X] = \sum_{i=1}^{n} x_i P(x_i)$$
for discrete variables, or:
E[X] = ∫ − ∞xf(x) dx
for continuous variables, where f(x) is the probability density function.

Variance and Standard Deviation

The variance of a random variable X is defined as:
Var(X) = E[(X − E[X])2]
This measures the spread of the random variable’s values. The standard deviation is the square root of the variance:
$$\sigma_X = \sqrt{Var(X)}$$

Covariance and Correlation

Covariance between two random variables X and Y is given by:
Cov(X, Y) = E[(X − E[X])(Y − E[Y])]
The correlation ρ is defined as
$$\rho_{X,Y} = \frac{Cov(X,Y)}{\sigma_X \sigma_Y}$$

Risk Management Concepts

Value at Risk (VaR)

Value at Risk provides a measure of the risk of loss on a portfolio:
VaRα = inf {x ∈ ℝ : P(X ≤ x) ≥ α}
indicating that there is a α probability that the loss will not exceed x.

Law of Large Numbers

States that as the number of trials increases, the sample average will converge to the expected value:
$$E\left[\frac{1}{n} \sum_{i=1}^{n} X_i\right] \to E[X] \quad \text{as } n \to \infty$$

Critical Issues in Financial Modeling

Independence and Risk

Fat-Tailed Distributions


$$P(|X| > k) \sim \frac{1}{k^\alpha} \quad (\alpha < 2)$$
suggests that extreme events are more common than predicted by normal distributions.

Conclusion

Understanding the complex interplay of probability, risk, and uncertainty is crucial for financial theorists and practitioners. Emphasis on robust statistical methodology is necessary given the inconsistencies observed in traditional models during significant financial events.

Lecture Notes on Financial Invention

The Engineering Perspective

Review of the Last Lecture

Key Concepts

The Central Limit Theorem

The central limit theorem states that:
$$\text{If } X_1, X_2, \ldots, X_n \text{ are independent and identically distributed (i.i.d.) random variables with finite variance, then the distribution of the sample mean } \bar{X} = \frac{1}{n} \sum_{i=1}^{n} X_i \text{ approaches a normal distribution as } n \to \infty.$$

Failures of Independence Assumption

Inventions in Finance

Historical Context

Reflection on Financial Inventions

The Concept of Risk

Key Themes in Financial Invention

Framing

Devices in Finance

Examples of Financial Innovations

Limited Liability Corporation

Inflation-Indexed Bonds

Credit Default Swaps

Case Study: Chile’s Unidad de Fomento

Conclusion

Notes on Financial Markets

Introduction

This lecture focuses on fundamental concepts in portfolio management, specifically the relationship between risk and return, leading to an introduction to the Capital Asset Pricing Model (CAPM).

Recap of Previous Lecture

Key Concepts

The VOC and Its Innovations

Risk and Return


Ravgstocks = 6.8% (after inflation)  vs.  Ravgbonds = 2.8%

The Equity Premium Puzzle

Standard Answer: Risk

The high return on stocks equivalently comes with greater risk, represented statistically via standard deviation.

Harry Markowitz and Portfolio Theory

Diversification and Portfolio Management


E(Rp) = x1E(R1) + x2E(R2) + … + xnE(Rn)
Where E(Rp) is the expected return of the portfolio, and xi represents the fraction of total investment in asset i.

Pure Leverage

Defined leverage and utilized an example with the VOC:


$$E(R_{por}) = \frac{Investment\ in\ VOC + Borrowed\ funds - Interest\ payment}{Total\ Investment}$$

Constructing the Efficient Frontier

Finding the Tangency Portfolio


E(Ri) = rf + βi(E(Rm) − rf)
Where:

Capital Asset Pricing Model (CAPM)

Sharpe Ratio

Defined as:
$$Sharpe\ Ratio = \frac{E(R_p) - r_f}{\sigma_p}$$
Where:

Conclusion

Introduction to Insurance and Risk Management

Overview of Insurance

Insurance is an important institution for managing risk, often considered separate from finance. However, the principles of risk management apply equally to both fields. Key concepts include:

Historical Background

Mathematical Foundation

Probability Theory

The insurance model assumes independence of risks. If we consider n trials of an event that occurs with probability p, the standard deviation of the proportion of occurrences is given by:
$$\sigma = \sqrt{\frac{p(1-p)}{n}}$$
As n increases, the standard deviation decreases, leading to more predictable outcomes when a large number of policies are sold.

Types of Insurance

Insurance generally falls into the following categories:

Challenges of Insurance

Creating a reliable insurance system involves overcoming several challenges:

Moral Hazard

Moral hazard arises when insured individuals alter their behavior, increasing their risk exposure. For example, with fire insurance, one might be tempted to deliberately cause a fire to collect benefits.

Selection Bias

Selection bias occurs when individuals with higher risk are more likely to purchase insurance. This can lead to disproportionately high claims, making insurance provision unviable.

Regulatory Environment

The insurance industry is heavily regulated. Key regulations include:

Case Study: American International Group (AIG)

AIG, once the world’s largest insurance company, provides a crucial example of the principles discussed. Its systematic risk exposure led to its bailout during the 2008 financial crisis:

Innovations in Insurance

Recent innovations include:

Conclusion

The insurance industry continues to evolve as it manages diverse and significant risks affecting lives and businesses. Key areas of improvement include:

The insurance industry plays a vital role in societal functioning and economic stability, constantly adapting to new challenges and improving its models.

References

Notes on the Yale Investment Approach: The Swensen Model

Introduction

The lecture features Professors David Swensen and Robert Shiller discussing the Yale Investment Approach, which has transformed Yale’s endowment from less than $1 billion in 1985 to $16.7 billion by June 2010. Swensen is notably recognized for his role in financial innovations, particularly the development of swap transactions.

Key Concepts

Diversification

Asset Allocation

Market Timing

Security Selection

Performance Metrics

Sharpe Ratio

The Sharpe ratio, defined as:
$$S = \frac{R_p - R_f}{\sigma_p}$$
where Rp is the portfolio return, Rf is the risk-free rate, and σp is the standard deviation of the portfolio return, is used to assess risk-adjusted returns. However, it is often criticized for not adequately capturing risk.

Investment Philosophy

Swensen emphasizes:

Yale’s investment strategy produced an annualized return of 8.9% over a decade compared to an average of 4.0% for other institutions.

Critique of the Yale Model

The Barron’s article criticized the Swensen Approach, arguing it emphasized alternatives too heavily, thereby lacking diversification. Swensen countered these claims by highlighting the superior long-term returns of alternative investments.

Conclusion

Future Outlook

The Yale model is structured to adapt and respond to market changes while focusing on the long-term goals of asset preservation and growth.

Discussion Points

Key takeaways from the talk include:

Lecture Notes on Efficient Markets Hypothesis

Introduction to Efficient Markets

The Efficient Markets Hypothesis (EMH) is a theory that suggests that financial markets efficiently incorporate all public information. The implications of this hypothesis are profound:

David Swensen’s Case

David Swensen, the chief investment officer at Yale University, has been noted for consistently "beating the market" since 1985, raising questions about the validity of EMH:

Sharpe Ratio

The Sharpe ratio is defined as:


$$Sharpe \, Ratio = \frac{E(R_p) - R_f}{\sigma_p}$$

where:

The goal of the Sharpe ratio is to adjust returns for the risk taken. Swensen challenges its practicality, especially with the illiquidity of certain assets in his portfolio, such as private equity and real estate.

Market Manipulation via Sharpe Ratio

There are strategies to manipulate the Sharpe ratio to create the appearance of high performance without true risk-adjusted returns:

  1. Selling Off Tails: This involves selling the higher tail of return distributions (unlikely high returns) and concentrating on the lower tail (higher risk of loss).

  2. Options Trading: By selling out-of-the-money calls and writing puts, fund managers can manipulate their return distributions for a brief period while leaving unhedged risks.

Case Study: Integral Investment Management

The case of Integral Investment Management illustrates the dangers of high Sharpe ratios that mask underlying risk. They experienced significant losses during market downturns, leading to legal actions and discussions about mandatory disclosures.

Historical Perspective on EMH

George Gibson’s work in 1889 established early ideas of market efficiency, expressing that markets reflect collective intelligence. Subsequent work by Charles Conant in 1904 expanded on this concept, establishing a theoretical framework around market speculation.
The evolution of the EMH gained momentum in the 1960s with Eugene Fama’s formal studies, culminating in his influential paper:

"Efficient Capital Markets: A Review" (1969)

Fama stated that security prices reflect all relevant information, discrediting many active management strategies.

Random Walk Theory

The Random Walk hypothesis posits that stock prices follow a random path due to unforecastable news events. The mathematical representation is:


Xt = Xt − 1 + ϵt

where:

This principle suggests that price movements are purely random, challenging theories that rely on patterns (e.g., Technical Analysis techniques like "Head and Shoulders").

Technical Analysis and its Limitations

Technical analysis relies on price patterns to forecast future movements. However, empirical studies (most notably by Burton Malkiel in A Random Walk Down Wall Street) demonstrate a lack of predictive power in these charts. Malkiel’s primary claims include:

Autoregressive Models

A comparison of Random Walk models versus Autoregressive (AR) models reveals that:


Xt = μ + ϕXt − 1 + ϵt,
where ϕ is a coefficient representing the influence of the previous time period.

If |ϕ| < 1, the process is stationary, indicating mean-reverting behavior. A ϕ close to 1 indicates prolonged trends with less revertive power, resembling Random Walk behavior. Such a process may misrepresent actual market dynamics, creating a sense of predictability that could be exploited.

Conclusion

The Efficient Markets Hypothesis remains a foundational concept in finance, often viewed as a "half-truth." While it provides essential insights regarding the behavior of markets, the emergence of behavioral finance and criticisms of traditional notions of market efficiency challenge its absoluteness.

Theory of Debt and Interest Rates

Introduction

Historical Context

Eugen von Boehm-Bawerk’s Explanations

Irving Fisher’s Contributions

Robinson Crusoe Economy

Two-Period Model

Present Values and Discount Bonds

Discount Bond Formula

Compounding

Present Discounted Value (PDV)

Annuities and Perpetuities

Forward Rates and Term Structure

Forward Rate Formula

Expectations Theory of Term Structure

Conclusion

Notes on Corporate Stocks

Introduction to Corporate Stocks

Personal Experience with Corporations

Market Capitalization

Dividends and Earnings

Ownership Structures

Corporate Governance

Financial Metrics and Analysis

Equity Financing and the Pecking Order Theory

Conclusion

Notes on Mortgage Lending

Introduction

This lecture discusses the history and modern principles of mortgage lending, focusing on both commercial and residential real estate finance.

Historical Context of Mortgages

Etymology of ’Mortgage’

The term "mortgage" comes from the Latin phrase mortuus vadium, meaning "death pledge". In Middle Ages France, the term was adapted to gage, which means "pledge". The Oxford English Dictionary states that the term entered the English language around 1283.

Ancient Practices

Yale historian Valerie Hansen’s research into documents from the Tang Dynasty in China indicates early forms of loans financed through trade, while some documents imply agreements resembling mortgages.

Evolution of Mortgage Systems

Development until the 19th Century

Modern Emerging of Mortgages

Hernando de Soto argues in Mystery of Capital that property rights issues persist globally, inhibiting mortgage finance.

Commercial Real Estate Finance in the U.S.

Ownership Structures

Most commercial real estate is owned through partnerships rather than corporations to avoid double taxation. Key points include:

Real Estate Investment Trusts (REITs)

Created in 1960, REITs allow for public investment in real estate while avoiding corporate profits taxes. These must comply with specific regulations:

Residential Real Estate Finance

U.S. Homeownership Rates

Approximately two-thirds of households in the U.S. own their own homes, largely due to government policies promoting mortgage lending.

Historical Crises and Innovations

The Great Depression led to a housing crisis with rising defaults. The government established the Homeowners Loan Corporation to bail out distressed homeowners. Key innovations included:

Amortizing Mortgages

The formula for mortgage payments is derived from the present value of annuities. The monthly payment x satisfies:
$$P = x \cdot \frac{1 - (1 + r)^{-n}}{r}$$
where P is the initial loan amount, r is the monthly interest rate, and n is the number of months.

Securitization of Mortgages

Government Involvement

The Federal National Mortgage Association (Fannie Mae) was established in 1938 to buy mortgages and support the housing market. In 1968, it was privatized.

Freddie Mac

Created in 1970, it also aims to support mortgage markets through securitization. Both Fannie Mae and Freddie Mac issue mortgage-backed securities.

Crisis of 2008

The mortgage market collapsed due to the failure of subprime mortgages, leading to a government bailout for both Fannie Mae and Freddie Mac, despite previous assertions that they would not be bailed out.

Conclusion

The lecture concludes by highlighting the evolution of mortgage finance and the lessons learned from historical crises. Emphasis is placed on the importance of regulations and the ongoing development of financial institutions to prevent past mistakes.

Lecture Notes on Behavioral Finance

Introduction to Behavioral Finance

Behavioral Finance, or Psychology and Finance, combines insights from psychology into the mechanics of financial markets. While traditional economics often relies on rational behavior as a foundational principle, Behavioral Finance acknowledges that human behavior is far more complex.

Key Points

Historical Context

Adam Smith

Selfishness vs. Altruism

Smith questioned whether humans are completely selfish and concluded that they are not. Instead, people crave moral standing from their communities.

Personality Types in Finance

Antisocial Personality Disorder (APD)

Roughly 3% of males and 1% of females exhibit characteristics of APD, which includes:

Implications for Finance

Understanding that a minority of individuals may possess exploitative tendencies is vital for assessing risks in financial behavior.

Behavioral Economic Theories

Prospect Theory

Developed by Kahneman and Tversky, Prospect Theory describes how people evaluate potential losses and gains in uncertain situations.

Value Function

The value function is S-shaped:

Graphically, the value function is illustrated as:


$$\text{Value} = \begin{cases} \text{concave down} & \text{(for gains)} \\ \text{concave up} & \text{(for losses)} \end{cases}$$

Weighting Function

The function describes how individuals perceive probabilities:

Graphically, it can be illustrated, and it exhibits considerable nonlinear behavior, leading to decision-making errors regarding rare events (e.g., airplane crashes).

Human Biases and Errors

Overconfidence

Cognitive Dissonance

Individuals prefer consistency in their beliefs and will ignore contradictory evidence to avoid the discomfort of being wrong.

Social Behavior in Finance

Herd Behavior

Investors often follow group behavior without rational deliberation, leading to stock market bubbles and crashes.

Moral and Ethical Considerations

Conclusion

The understanding of Behavioral Finance is influenced by the ongoing learning about psychology, personality types, and moral imperatives in finance. Although there are inherent human weaknesses in decision-making, financial institutions are evolving to mitigate these issues through regulation and ethical considerations.

Regulation and Human Misbehavior in Financial Markets

Introduction

This lecture continues the discussion from a previous session focused on behavioral finance and human misbehavior, specifically addressing regulation in financial markets and institutions.

Purpose of Regulation

Regulation in financial markets is aimed at addressing psychological issues and mitigating the exploitation of human weaknesses, alongside ensuring the efficiency of the financial system.

Key Issues Addressed by Regulation

Too Big to Fail (TBTF)

The TBTF phenomenon arises when large firms receive implicit government guarantees during failures due to their systemic importance. This creates moral hazard, leading to increased risk-taking by these firms.

Types of Regulation

Two primary forms of regulation exist:

Analogy of Regulators

Regulators are analogous to referees in sports, enforcing rules, making decisions on rule violations, and ensuring fair play in the financial arena.

Levels of Regulation

The lecture discusses five levels of regulation:

  1. Within Firm Regulation: Internal rules and regulations established by firms.

  2. Trade Groups: Self-regulatory organizations formed by groups of firms.

  3. Local Government Regulation: Regulation at the city or state level.

  4. National Regulation: Regulation at the country level.

  5. International Regulation: Cross-border regulatory coordination.

Within Firm Regulation

Within firms, boards of directors play a regulatory role, providing oversight to ensure ethical operations and deterring malfeasance such as tunneling.

Tunneling

Tunneling is the act of diverting resources from shareholders for personal benefit, demonstrated in types such as:

Duties of Board Members

Board members have two primary duties:

Trade Groups and Self-Regulation

Trade groups like the New York Stock Exchange exemplify early forms of self-regulation. Post-1792 stock market crash, the "Buttonwood Agreement" established basic ethical standards for trading among brokers.

Changing Nature of Self-Regulation

Significant regulatory changes occurred with the abolition of fixed commissions after the May Day of 1975, promoting greater competition and the rise of discount brokerage models.

Local and National Regulation

Before federal regulation, financial oversight was largely local through state laws, with notable events such as the implementation of Blue Sky laws aimed at protecting investors.

Creation of the SEC

The Securities and Exchange Commission (SEC) was established in 1934 during the New Deal era, aiming to enhance transparency and protect investors through rigorous disclosure requirements.

Dodd-Frank Act

The Dodd-Frank Act of 2010 aimed to address systemic risks and enhance consumer protection, establishing entities like the Financial Stability Oversight Council (FSOC) to oversee systemic risks.

International Regulation

With globalization, international regulatory cooperation is critical to prevent regulatory arbitrage. Institutions like the Bank for International Settlements (BIS) and the Financial Stability Board (FSB) address global financial stability.

Basel Frameworks

The Basel Committee provides recommendations for banking regulation, resulting in Basel I, II, and III frameworks, aimed at enhancing the resilience of the international banking system.

G20 and Financial Regulation

The G20, formed in response to the financial crises, includes major global economies and focuses on coordinated regulatory responses to enhance international financial stability.

Conclusion

Regulations at various levels are essential to safeguarding financial systems against vulnerabilities and unethical practices. The ongoing evolution of regulations reflects the complexities introduced by globalization and the necessity for effective oversight.

Notes on Banking

Introduction

This lecture covers the topic of banks and banking, emphasizing traditional banks that take deposits and lend money, rather than investment banks or central banks.

Outline of the Lecture

Definitions and Characteristics of Banks

Definition of a Bank

A bank can be defined as an institution that:

Key Functions of Banks

Origins of Banking

Ancient Practices

Development in Italy

The first true banking practices emerged during the Renaissance in Italy, with Banca Monte dei Paschi di Siena, founded in 1472, known as the oldest surviving bank.

Theory of Banks

Diamond-Dybvig Model

The Diamond-Dybvig model highlights:

Risks Managed by Banks

Banks solve two main problems:

Deposit Insurance

Originally proposed in the 1600s in Italy, deposit insurance protects depositors and helps maintain trust in the banking system:
InsuranceDeposit mitigates Bank Runs

Bank Regulation

Basel Regulations

The Basel Committee introduces guidelines for international bank regulations to maintain stability across countries:

Risk-Weighted Assets

The concept of risk-weighted assets (RWA) is critical to Basel regulations. A simplified classification is as follows:

If a bank has Total Assets = 400 million divided as follows:

Then, the RWA calculation is:
RWA = (100 × 0) + (100 × 0.20) + (100 × 0.50) + (100 × 1) = 0 + 20 + 50 + 100 = 170 million

Conclusion

The role of banks is essential in creating liquidity, funding businesses, and maintaining economic stability through effective regulation. Historical patterns show that failures in the banking system often lead to wider economic crises. Continuous adjustments in regulations, such as those in the Basel agreements, are deemed necessary to adapt to financial innovations and complexities in banking practices.

Comprehensive Notes on the Discussion Between Professor Robert Shiller and Maurice "Hank" Greenberg

Introduction

This document outlines the key insights from a discussion led by Professor Robert Shiller with Maurice "Hank" Greenberg, focusing on Greenberg’s remarkable life story, his experiences in the insurance industry, and the lessons derived from his tenure as CEO of AIG.

Background of Hank Greenberg

Early Career in Insurance

AIG and Its Transformation

Initial Challenges

Creation of AIG

Organizational Culture and Management

Financial Products and Crisis Management

Expansion into Financial Services

Regulatory Environment Post-Enron

The 2008 Financial Crisis

Key Lessons and Future of Insurance

Concluding Thoughts

Hank Greenberg’s journey illustrates the complexities of leading a large multinational corporation within the fluctuating landscapes of global economics and governance. His stories impart critical lessons about leadership, ethics, and the imperatives of risk management.

Lecture Notes on Futures Markets

Introduction to Futures Markets

Futures markets are organized platforms for trading standardized contracts that represent agreements to buy or sell a particular asset at a predetermined future date. These contracts predict future prices, and they are integral to financial and commodity markets.

Forward vs. Futures Markets

Futures and forwards are both considered derivatives since their prices derive from another underlying asset’s price.

Important Definitions

Mechanics of Futures Markets

Futures markets originated from the need to mitigate risks associated with price fluctuations in physical commodities. Professor Shiller discusses agricultural futures, which serve as foundational examples. For example, rice futures began in 1673 in Osaka, Japan, marking the first organized futures trading.

Counterparty Risk in Forward Markets

Counterparty risk exemplifies a significant challenge in forward contracts, as illustrated by potential failures:

Transition to Futures Markets

To minimize issues seen in forward markets, futures markets standardize contracts and centralize trading, enhancing market reliability.

The Role of Speculation

Speculation involves anticipating future market movements and adjusting trading strategies accordingly. Despite public hostility towards speculation, it plays a critical role in future price forecasting:

Pricing of Futures Contracts

The price of any futures contract can be derived from the spot price and adjusted for storage costs and interest rates. The formula is:


Pf = Ps(1 + r + s)

where:

Examples of Futures Markets

Agricultural Futures

Futures markets were initially developed for agricultural products. The interaction between harvest cycles and storage capabilities illustrates how price stability can be maintained through futures trading.

Modern Futures Markets: Oil

The crude oil futures market is pivotal due to oil’s essential role in the global economy. Recent crises, such as geopolitical conflicts, have led to significant price fluctuations, which can be tracked through futures pricing.

For instance, the futures curve for light sweet crude oil may exhibit:

Financial Futures

Financial futures, such as those relating to the S&P 500 index, employ a similar pricing mechanism:
Pf = Ps(1 + r − y)
where:

Conclusion

Futures markets serve as crucial mechanisms in modern economies, aiding in risk management, price discovery, and providing avenues for speculation. The mathematical framework that underpins futures pricing contributes to the efficient operation of these markets.

Future discussions will delve into options pricing, continuing the exploration of derivatives in financial markets.

Overview of Financial Markets and Regulatory Frameworks

Introduction

Career Overview

Private Sector vs Public Sector

Private Sector

Public Sector

Role of Regulators

Market Development in Hong Kong

Corporate Governance in China

Internationalization of Finance

Regulatory Changes and Financial Crises

Conclusion

Laura Cha emphasized the critical roles that both sectors play in ensuring robust and transparent financial markets and highlighted the value of diverse career paths. She called for bright graduates to consider roles in public service, which serve societal good and regulatory support.

Notes on Options

Introduction

The subject of today’s lecture is options, which are financial instruments not commonly encountered in daily life but are important in economic theory and practice.

Definition of Options

An option is a financial contract that provides the holder with the right, but not the obligation, to buy or sell an asset at a specified price within a specified time period. There are primarily two types of options:

Key Terms

Types of Options

Historical Background

Options have existed for thousands of years, dating back to ancient contracts that allowed individuals to secure rights to purchase goods or property in the future without immediate financial commitment.

Real-World Applications of Options

Options are used not just in stocks but also in other scenarios such as:

Purposes of Options

Theoretical Purpose

Options are important for the efficiency of financial markets:

Behavioral Purpose

Options also influence how individuals interact with financial markets:

Options Pricing

Pricing of options is crucial for effectively evaluating and trading them.

Basic Price Relationship

The price of an option, particularly a call option, can be visualized as:
C = max (0, S − E)
where:

Put-Call Parity

The relationship between call and put options is expressed by the put-call parity:
C − P = S − E ⋅ e − rT
where:

The put-call parity holds true until the expiration date of the options.

Black-Scholes Option Pricing Model

The famous Black-Scholes formula for pricing European call options is:
C = S ⋅ N(d1) − E ⋅ e − rT ⋅ N(d2)
where:

Implied Volatility

Implied volatility is a measure derived from the market price of options. It reflects the market’s expectation of future volatility. It can be computed as follows:
Implied Volatility = solve for σ in the Black-Scholes equation

Conclusion

Options are essential financial tools that allow for risk management, price discovery, and improved decision-making in financial markets. Understanding both their practical applications and theoretical foundations is crucial for financial literacy and informed trading strategies.

Lecture Notes on Central Banks

Introduction

In this lecture, Professor Robert Shiller discusses the role and history of central banks. He emphasizes the importance of financial innovations in shaping the banking system, comparing it to engineering inventions.

Definition of Central Banks

Historical Context

Origins of Banking

Bank of England

U.S. Banking Evolution

Functions of Central Banks

Lender of Last Resort

Monetary Policy

Interest Rates and Inflation Control

Regulatory Framework

Reserve Requirements and Capital Requirements

Basel III

Challenges Facing Central Banks

Conclusion

Investment Banking

Introduction to Investment Banking

Investment banking is a distinct sector within the finance industry that primarily focuses on helping corporations, governments, and other entities raise capital by underwriting and issuing securities. Key functions include:

Differences Between Investment Banking and Other Banking Facilities

Investment banking differs from commercial banking in the following ways:

Types of Banking:

Key Functions of Investment Banks

Underwriting

Investment banks manage the issuance of new shares. The common processes involved include:

Important equations related to stock issuance include:
Market Capitalization = Price per Share × Total Shares Outstanding

Types of Underwriting Deals

Regulatory Framework

Investment banks operate under strict regulations imposed by governing bodies like the Securities and Exchange Commission (SEC). These regulations are aimed at ensuring transparency, fairness, and protecting investors.

Historical Context and Changes Post-Financial Crisis

The Glass-Steagall Act

Passed in 1933, the Glass-Steagall Act separated commercial and investment banking. This law was largely repealed by the Gramm-Leach-Bliley Act in 1999, allowing the two business models to merge.

The Financial Crisis of 2007-2009

The financial crisis led to increased scrutiny of investment banks, with a focus on shadow banking practices, which refer to non-bank financial intermediaries that provide services similar to traditional commercial banks but operate outside regulatory oversight.

The Volcker and Lincoln Rules

Post-crisis regulations included:

Core Values of Investment Banks

A significant component of the success within investment banking firms is the adherence to core values such as:

Investment Banking Career Path

Typically, professionals in investment banking serve as analysts and then can progress to senior levels. Skills valued in this career include strong analytical abilities, numerical proficiency, and the capacity to work under pressure.

Education and Skills

Relevant educational backgrounds include finance, economics, mathematics, or engineering. Essential skills include:

Concluding Thoughts

Investment banking continues to evolve, especially in response to regulation and market dynamics. While traditional practices persist, embracing change and ongoing education will remain vital for success in the industry.

Notes on Institutional Investors

Introduction

Wealth Overview in the United States

Total Assets

Liabilities

National and Global Wealth Perspectives

Human Capital

Institutional Investing

Role of Institutional Investors

Prudent Person Rule

Types of Institutional Investors

Family Offices and Foundations

Conclusion

Notes on Financial Exchanges and Clearinghouses

Introduction

Overview of Exchanges

Definitions of Economics

According to Kenneth Boulding, one definition of economics is:

Economics is the study of exchange.

This is further emphasized by the focus on prices and quantities, which are fundamental aspects of exchange.

The Concept of Exchange

Karl Polanyi’s Point of View

Types of Exchange in Early Societies

Brokers vs. Dealers

Definitions

Examples

Market Types

History of Stock Exchanges

Development Timeline

Impact of Electronic Trading

Types of Trading Orders

Order Book and Bid-Ask Spread

Bid-Ask Spread Concept

The bid-ask spread is the difference between the highest price a buyer is willing to pay (bid) and the lowest price a seller will accept (ask).
Spread = Ask Price − Bid Price

Dealer and Risk Management

Probability of Ruin

If a dealer starts with S dollars and has a win probability p, the probability of eventual ruin is given by:
$$P(\text{Ruin}) = \begin{cases} 1 & \text{if } p \leq \frac{1}{2} \\ 1 - \left(\frac{1-p}{p}\right)^S & \text{if } p > \frac{1}{2} \end{cases}$$

Modern Problems in High-Frequency Trading

Market Crashes and Regulations

Case Study: May 6, 2010

Conclusion

The evolution of exchanges from physical marketplaces to modern electronic systems highlights significant changes in trading dynamics and financial markets. Understanding the mechanics of exchanges, brokers, dealers, order types, and trading technologies is crucial for navigating today’s financial landscape.

Notes on Nonprofit and Government Finance

Introduction

Teamwork and Individual Contribution

Nonprofit Organizations

Examples of Nonprofits

  1. Doorways to Dreams (D2D): Founded by Peter Tufano, aimed at improving personal finance.

    • Proposal: Automatic check-off on tax forms for saving through U.S. savings bonds.

    • Another innovative idea: Create lottery-like savings plans.

  2. Innovations for Poverty Action (IPA): Founded by Dean Karlan in 2002.

    • Focuses on alleviating poverty through research and action.

    • In 2010, IPA generated $25 million in income and employed 500 people globally.

  3. Ashoka Foundation: Founded by Bill Drayton, promotes social entrepreneurship.

  4. Teach for America: Founded by Wendy Kopp to recruit college graduates for teaching in low-income areas.

    • Raised $2.5 million in her first year (1989) to launch the program.

Government Involvement in For-Profits

Examples

Municipal and State Finance

Government Social Insurance

History of Social Insurance

Conclusion

Notes on Financial Markets: Finding Your Purpose in a World of Financial Capitalism

Introduction

This lecture concludes the course titled “Financial Markets." The objective is to summarize the course and discuss the significance of financial tools in the context of personal and societal purposes.

Importance of Finance

Finance serves as a language, rich in jargon, reflecting underlying concepts essential for navigating business and society. Key purposes of finance include:

These functions contribute significantly to the development of societies.

Central Themes of the Lecture

Seven central themes will be discussed during this concluding lecture:

  1. Morality in finance.

  2. The concept of hopelessness.

  3. Insights into financial theory.

  4. Wealth and poverty dynamics.

  5. The future world economy.

  6. The democratization of finance.

  7. Career paths in finance.

Morality of Finance

The morality of finance encapsulates the ethical implications of financial actions and decisions.

Key References

Key Arguments

The Concept of Hopelessness

Unger’s Perspective

Discusses rationalizations like futility, which can lead to inaction.

Malthusian Critique

Thomas Malthus’ essay (1798) posits:

“Population increases in a geometrical ratio while subsistence grows in an arithmetical ratio."

This suggests expected resource limitations due to population pressures.

Insights into Financial Theory

Combining mathematical finance with behavioral finance is essential for understanding market phenomena. This synergy aids in addressing client needs and market behaviors.

Wealth and Poverty Dynamics

The course emphasizes socioeconomic disparities and the impact of financial institutions on welfare.

Hacker and Pearson’s Winner-Take-All Politics

Explores increasing wealth polarization and the political influence of the financial sector.

Future World Economy

Forecasts the democratization of finance as an emergent trend influenced by innovations in information technology.

Career Paths in Finance

Consideration of various career trajectories, both within and beyond finance, focusing on meaningful contributions to society.

Inspirational Figures

Conclusion

The course imparts the notion that finance is a tool for societal betterment rather than an end in itself. It advocates for:

Final Thoughts

Students are encouraged to view their careers as part of a larger narrative, contributing to the evolving landscape of finance and its intersection with societal ethical imperatives.