Download A Brief History of FE

A Brief Introduction of FE
What is FE?
• Financial engineering (quantitative finance,
computational finance, or mathematical finance):
– A cross-disciplinary field which uses quantitative methods
developed in math or engineering to solve financial
problems.
Time and Risk
• A typical financial problem concerns how to allocate
and deploy economic resources, both spatially and
across time, in an uncertain environment.
• Example: Investment for retirement
• Time and risk
A Brief Review of the History of FE
(EMH)
• 1930’s: Statistical tools were introduced to analyze
financial data.
• 1950-1960’s: Efficient market hypothesis (EMH) :
(Maurice Kendall (1953), Harry Roberts (1959), Eugene Fama (1965))
– Market information, such as the information reflected in the
past record or the information published in financial press,
must be absorbed and reflected quickly in the stock price.
More about EMH: a Thought
Experiment
• Let us start with a thought experiment:
Assume that Prof. Chen had invented an formula
which we can use to predict market movements very
accurately. What would happen if this formula was
unveiled to the public?
More about EMH: a Thought
Experiment
• Suppose that it predicted that stock XYZ would rise
dramatically in three days to $110 from $100. The
prediction must induce a great wave of immediate buy
orders. Huge demands on stock XYZ will push its
price to jump to $110 immediately.
• The formula fails!
EMH: From Random Walk to
Stochastic Calculus
• EMH points out the riskiness is an intrinsic attribute
to financial markets.
• EMH is a starting point where more advanced
mathematics steps in:
– Random walk
– Robert Merton in 1969 introduced stochastic calculus to
understand how prices are set in financial markets through
“equilibriums”.
A Brief Review of the History of FE
(Portfolio Theory)
• Then, the problem is how to manage financial risk:
– Diversification: “Do not put all the eggs in one basket”.
• 1952: Harry Markowitz and portfolio theory
• 1962: William Sharpe and Capital Asset Pricing
Model (CAPM)
• 1970’s: Index funds appeared.
Building More Complex Financial
Instruments: Black and Scholes
• The work of Markowitz and Sharpe gave a birth to
the area of quantitative finance. People can utilize the
theory they invented to construct new financial
instruments fine-tuned to their risk appetites.
• Starting from 1970’s, the development in the theory
of quantitative finance stimulates the prosperity of
derivative markets.
Building More Complex Financial
Instruments: Black and Scholes
• A derivative is a financial instrument that has a value
determined by the price of something else.
• Example:
– A gallon of gasoline is not a derivative.
– However, the following agreement is a derivative:
• You enter into an agreement with a friend that says: when the price
of a gallon of gasoline in 1 year is greater than $20, you will pay
him $1; when the price is less than $20, he will pay you $1.
A Brief Review of the History of FE
(Black Scholes Theory)
• 1973: Black and Scholes developed their celebrated
option pricing formula.
– One price (no arbitrage) principle
• 1979-1983: Harrison, Kreps, and Pliska used a
general theory of continuous-time martingales to
extend the Black-Scholes work to price numerous
other “derivative” securities.
Political Impetus: Regan and Thatcher
• A serious stagflation fatigued the entire capitalism
world during the period of 1970s and early 1980s.
• That stimulated several major western countries, led
by Regan in US and Thatcher in UK, to switch away
from the Keynesian economics to the New Classical
Doctrine.
• The new classical economics emphasizes less
government intervention and free market principle.
The Rise and Decline of FE
• A friendly political environment and the
corresponding academic preparation prompted a rapid
growth in the derivative markets and in turn the
demand for more sophisticated mathematical tools.
• However, the credit crisis in 2007-2009 casts doubt
on the philosophy behind financial engineering.
• What is the next step?
– My interest: liquidity-caused market inefficiency and its
implication in asset pricing