Open Yale Lecture 8

Human Foibles, Fraud, Manipulation, and Regulation

CLASS NOTES:

Today’s topic was Regulation.

1.                Wishful thinking – i.e. Election, game, investment

2.                Attention Anomalies  - Social bases,

3.                Anchoring

4.                Representativeness Heuristic

5.                Gambling behavior

6.                Magical thinking   - BF Skinner

7.                Quasi Magical thinking  Shafir + Tversky

Temptations of Market

1.                Oversell

2.                Hide info

3.                Loyalty to friends

Regulation

Louis Brandeis

1914 Other people’s money

Disclosure of truth

ð  States “Blue Sky Laws”

1920s Telephone  spread

Boiler Rooms

1934 Securities  + Exchange Commission  (SEC)   

                        Business ßà SEC

William O Douglas

“Democracy and Finance” 1940  - Finance for people

Legal Realism

Public + Private Securities

Public Company à Must disclose info (Regulation by SEC.gov)  Edgar

Hedge Fund – Private investment company  -- Low profile

3C1

99 investors

Accredited investors

3C7

500 investors

Qualified purchasers

Insider + Outsider

Regulation FD - 2000 … Full Disclosure - SCC

Market Surveillance

Example

1995 IBM – Lotus … Insider trading

Financial Accounting regulation

Standard Board FASB - 1975

GAAP

Net Income

Operating income

Other Standards

Core earning

Pro form

EBITDA

Balance Sheet : Asset T Liabilities

Off-balance sheet accounting … Enron Corp

                … Remove risky investment from the balance sheet by putting them in balance sheet of child/dummy companies

SIV – Structured Investment Vehicles

SIPC

Securities Investor protection Corporation  - 1970

FDIC Fed Dep Ins Corp – 1934

Currently $100,000

Conclusion: Need to keep improving regulation to protect small investors.

Open Yale Lecture 7

Behavioral Finance: The Role of Psychology

http://www.youtube.com/watch?v=0ZLNbxWH8Lc&list=PL8F7E2591EE283A2E&index=7&feature=plpp_video

CLASS NOTES:

Newer revolution of finance

Behavioral finance = Reaction against to 1) Mathematical finance 2) Efficient market

Over confidence

Kahneman + Tversky

Prospect Theory  (1979)

How people make choices

Replaces Expected Utility Theory  

Weighting Function

Distort probability

Expected Util Theory çà Prospect Theory

Mental Compartment 

SUMMARY:

If coin is head – you get $200

If coin is tail – you pay $100

Probability 50% Gain > Loss

Would people buy the rotary ticket?

Today’s topic was behavioral finance.

The theory is replacing the previously presented theories such as 1) Math modeling of expected returns 2) Efficient market hypothesis – information based random algorithms

Behavioral finance theory in another word, prospect theory (Daniel Kahneman et all won Nobel Prize) claims that market behavior (decision making of buy-sell) is heavily incorporated with individual physiologic effect between returns and probability and then it can be modeled as a curve with a reference point. Figure 1 has the reference point in probability so the returns becomes flat after the point.

Cumulative prospect theory 

This is also by Kahneman. For the 2nd figure, buyers’ decision depends on prospect of probability/risk (individual feeling you might win or not) and return is not linear but discrete as shown.  The figure shows people seemed to over react for 2 extreme cases of probability but does not change reaction much for mid probabilities.

Open Yale Lecture 6

Efficient Markets vs. Excess Volatility

http://www.youtube.com/watch?v=pXJb29s3nmY&list=PL8F7E2591EE283A2E&index=6&feature=plpp_video


CLASS NOTES:

Efficient Markets:

Harry Roberts (1967)

Market price incorporated with:

Weak Form – info on past prices

Semi Strong – all public info

Strong – all info 

Random Walk Theory 

Random Walk Theory for Stock Market  - Karl Person

  Xt = Xt-1 + Et

  Et : Noise

  News (about values) appeared randomly so it creates fluctuation （noise） --> stock price up/down as random walk

The First Order Auto-regressive Model 

y = a+bx+u

è Forecast of Stock Market 

SUMMARY:


First the class talked about what is efficient market. (Market is a price of something. For instance, stock price) There are some definition historically but one talked was by Harry Roberts (1967). The theory models the types of information and based on them, efficient market is classified to weak, semi strong, and strong. For example, "Strong efficiency" is depends on all information available. Normally stock market is semi-strong (means depending on public info) 

Next the class discussed prediction (of price behavior in the market) as a security. 2 algorithms (math formulas) such as Random walk and Auto regression, were introduced and these theories has been not  only applied for economics but also applied to predict any natural random phenomenon under study. However in my opinion, the application of these theory seemed to be difficult and as professor Shiller himself said, not many are succeeded. (If easy, too many rich people?) This was one of HW for Yale students and I thought it is really hard -_-);;

Open Yale Lecture 5

Insurance 

http://www.youtube.com/watch?v=PhLjCfjpYeY&list=PL8F7E2591EE283A2E&index=5&feature=plpp_video

CLASS NOTES:

Insurance = A risk management device ßà security

Equity Premium Puzzle

Puscott + Mehra

(positive) 4% premium (US)

Selection Bias

Stock Market disruption                               Russia + China

Corporate profit tax, personal income tax

Dividends 90% WWII

15%

Risk Pooling -à Independent  x: num of accidents n: policies p: prob of accidents

F(x) = binominal distribution

Mean(x/n) = p

Sigma(x/n) = Root{p(1-p)/n}

Normal Approximation

Bell shape curve

Probability theory

Insurance as Invention

Contract design

Risks and Exclusions (moral hazard and selection bias)

Mathematical model

Corporate or Mutual

Government regulation

                Reserves

Classifying of Insurance companies

Multiline / Mono-line

Property + casualty $1.4 Trillion

                Automobiles >> home owners

Health

Life $4.9 Trillion 

SUMMARY:

The concept of insurance was invented as early in 17C. Now a day the concept became very important to secure one's family and properties, but its growth has been very slow. The problem was mainly in early history, insurance companies could not sell their products to the customers (especially life insurance was rejected, was thought bad luck? Did not sound right, etc.). So historically insurance companies’ efforts were 1) how to convince customers in nice way 2) how to prevent from canceling. Eventually they developed more attractive policies such as the insurance with cash values. 

Open Yale Lecture 4

Portfolio Diversification and 

Supporting Financial Institutions

http://www.youtube.com/watch?v=efPKwxZuLKY&list=PL8F7E2591EE283A2E&index=4&feature=plpp_video 

CLASS NOTES: 

Portfolio can help hardship

Part of risk management

Math:

Capital asset and pricing model

Correction of assets = portfolio (à portfolio management)

Return vs. variance

n independent assets

Sigma = Std dev of return

r = expected return

Square root rule

Sigma_portfolio = sigma/square(n)

Equally Weighted

r_portfolio = r

Two Asset Case: n = 2 not independent

Asset1 r1= E(return1) Sigma1 = Std dev(return1)

Asset 2 r2 = E(return2) Sigma2 = Std dev(return2)

Cov(r1, r2) = Sigma12

X1 = in asset 1

1-X1 in asset 2

X2= 1-X1

Portfolio Exp return

r = SUM(xiri) = x1rx + x2r2 = x1r1+(1-x1)r2

x1 = (r-r2)/(r1-r2) 

Riskless asset

Sigma_f = 0: straight line

Tangency portfolio

The tangency portfolio combines the optimal combination of risky assets with a risk-free asset.

Mutual fund theorem

Capital asset pricing model

CAPm

Tobin, Sharpe, Lintner, Markowls

Assume everyone is rational, holds tangency portfolio.

Tangency portfolio = Actual market portfolio

r1=rf + Bi*(rm-rf)

rm: expected ret on market portfolio

SUMMARY:

Financial modeling has been researched and invented for part of risk management. The result from these equations can be useful information for decision making of investors whether they should invest. Efficient frontier (Harry Markowitz and others) which is a concept in modern portfolio theory has been explained mainly. The figure of Standard [Deviation vs Expected Returns] is explained. Top straight line of the hyperbola is called “efficient Frontier” and it has optimum returns for the investment under the given set of risks.

Open Yale Lecture 3

Technology and Invention in Finance

http://www.youtube.com/watch?v=1nVRW8o7J0w&list=PL8F7E2591EE283A2E&index=3&feature=plpp_video

CLASS NOTES:

History of finance is copies of various invention (in the world) to manage long term risk

Need Invention

Long term risk theme (for risk management)

Backus Kchoe

(Perfect) Correlation of Consumption -> elimination of risk

Socialism – R. Owen

Moral hazard problem

(Complete) Sharing, risk sharing, equality  

Karl Marcus

ð  Public finance

Tax and welfare system (government) è Worked (Invention)

History of Taxes

Income Tax during civil war, progressive tax  (Invention)

Insurance (good invention)

Framing issue: Money Frame, money terms

Real Frame – Index to price

IT à economic dislocation and opportunities

Insurance Policy as invention, must exclude hazard cases to make it works

Develop statistics

Topics: Wheel, Patent (examples of innovation)

19C IT innovation for financial opportunity

Paper (mass-production) è record keeping

Carbon paper, typewriter, standardized forms, civil service, firms, postal service

Social security (Germany) over 100 years old

SUMMARY:

Historically human has been trying to find a way for (financial) risk management. The process went through trial-and-error. Ones very success are considered innovations which are for instance, tax and welfare, income tax, insurance, money framing, and social security. The financial system development were also closely related and depending on IT development in the era. (i.e. Paper->Carbon paper->Printing technology->Postal service-> etc. etc. -> Computers/Database so on)