economics:financial_economics

**Financial Economics**- with concentration on monetary activities (monetary economics), it centers on decision making under uncertainty in the context of the Financial Markets (microeconomics). It is also concerned with deriving testable or policy implications from acceptable assumptions (microeconomics). In the study of Asset Pricing, Portfolio choice Theory, and Forecasting, Mathematics (linear algebra, real analysis, optimization) and Probability & Statistics are commonly used.- Like economics, it is concerned with “the allocation and deployment of economic resources, both spatially and across time, in an uncertain environment”, with concentration on “monetary activities”, since money is likely to appear on both sides of a trade.
- Emphasize compatibility with
**economic theory**rather than mathematical consistency (c.f. Mathematical Finance) - Decision making
**under uncertainty**in the financial markets, with**financial variables**(rather than real) - such as prices, interest rates - Essentially explores how rational investors would apply decision theory to the problem of investment -
**Investment theory**encompasses the body of knowledge used to support the decision-making process of choosing investments for various purposes. It includes portfolio theory, the capital asset pricing model, arbitrage pricing theory, efficient-market hypothesis, and rational pricing. - Derive testable or policy implications from acceptable assumptions.
- Financial economics models are typically framed in terms of;
- Money over Time - money now is traded for money in the future.
- Uncertainty - The amount of money to be transferred in the future is uncertain.
- Information - Knowledge of the future can reduce, or possibly eliminate, the uncertainty associated with future monetary value (FMV).
- Intertemporal decision - one party to the transaction can make a decision at a later time that will affect subsequent transfers of money.

- Combining
**probabilities**with**present value**leads to the**expected value**criterion which sets asset value as a function of the sizes of the expected payouts and the probabilities of their occurrence. - St. Petersburg paradox, suggested that valuation is instead subjective and must incorporate Utility.
- The Expected utility hypothesis states that, if certain axioms are satisfied, the subjective value associated with a gamble by an individual is that individual's
**statistical expectation**of the valuations of the outcomes.

- Assume that asset prices will reflect the arbitrage-free price of the asset, as any deviation from this price will be “arbitraged away”. Where an arbitrage opportunity does exist, then prices can be expected to change, and are, therefore, not in equilibrium.
- useful in pricing fixed income securities and derivatives

- Deals with the behavior of supply, demand, and prices in a whole economy with several or many interacting markets, by seeking to prove that a set of prices exists that will result in an overall equilibrium (this is in contrast to partial equilibrium, which only analyzes single markets.)
- Arrow-Debreu model - under certain economic conditions, there must be a set of prices such that aggregate supplies will equal aggregate demands for every commodity in the economy.
- The analysis here is often undertaken assuming a Representative agent.

- Originating from the Arrow–Debreu model is the concept of a state price security (i.e. an Arrow-Debreu security) - a contract that agrees to pay one unit of a numeraire (a currency or a commodity) if a particular state occurs at a particular time in the future and pays zero numeraire in all the other states.
- The state price vector is the vector of state prices for all states. As such, any derivatives contract whose settlement value is a function of an underlying asset whose value is uncertain at contract date can be
*decomposed as a linear combination*of its Arrow-Debreu securities, and thus as a weighted*sum*of its state prices. For a continuous random variable indicating a continuum of possible states, the value is found by*integrating*over the state price density (Stochastic discount factor) - Martingale pricing and the related Risk-neutral measure.

For “choice under uncertainty”, the twin assumptions of rationality and market efficiency lead to modern portfolio theory and the Capital asset pricing model (CAPM) — an equilibrium-based result — and to the Black–Scholes–Merton theory (BSM; often, simply Black-Scholes) for option pricing — an arbitrage-free result.

Is a financial market efficient? What does the “efficient” mean?

The assumption of market efficiency is associated with the notion of the unpredictability of financial markets.

If financial markets are efficient, then the markets are unpredictable.

Mainstream finance theory has traditionally held that - markets must be unpredictable, because if markets were predictable they could not be efficient and returns in excess of market returns could be made without taking additional risk. Markets embed a risk-return trade-off in which investors demand, and markets supply, excess expected returns for taking risk. In efficient market, there holds 'absence of arbitrage' - that is, one cannot make a sure profit with no investment (There is no free lunch). Thus, markets cannot be beaten. Although excess returns might indeed be achieved, they are considered to be, on average, proportional to risk.

Although financial theory states that investors cannot beat the market without risk, it does admit that an investor can beat the market, on average, by taking risk beyond the risk inherent in the market benchmark. Taking this additional risk means, of course, that the investor will suffer periods of underperformance as well as periods of superior performance relative to the market benchmark. In practice, the market downturn after 20000 forced asset management firms to evaluate that the trade-off between risk and return is dynamic and does not exclude the possibility that asset returns are, to some extent, forecastable. How can we attempt to capture the limited forecastability in financial markets?

- beta - a measure of exposure to market risk (a market part)
- alpha - a measure of return in excess of the market return, which can be interpreted as measuring sill in stock picking or asset allocation (a nonmarket part)

- Asset pricing (Time-series)
- Asset Pricing (Cross-sectional)
- Portfolio Choice
- Term Structure
- Derivative Pricing
- Multi-factor models such as the Fama-French three-factor model and the Carhart four-factor model, propose factors other than market return as relevant in pricing. The Intertemporal CAPM, Black–Litterman model, and arbitrage pricing theory similarly extend modern portfolio theory. See also: Post-modern portfolio theory; Mathematical finance#Risk and portfolio management: the P world.

economics/financial_economics.txt · Last modified: 2016/09/21 17:07 by admin

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