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18

 

Princeton University Press (Visit publisher website)

2001

English

 

 

 

Advanced

 

 

Investment management, quantitative analysis, portfolio theory, stochastic processes, estimation, arbitrage,state-price vector, risk-neutral probability, utility function, asset pricing, efficiency, complete markets, first welfare theorem, representative agents, Riesz representation theorem, linear regression, correlation

 

Excerpt from book - This chapter introduces the basic ideas in a finite-state one-period setting. In many basic senses, each subsequent chapter merely repeats this one from a new perspective. The objective is a characterization of security prices in terms of “state prices,” one for each state of the world. The price of a given security is simply the state-price weighted sum of its payoffs in the different states. One can treat a state price as the “shadow price,” or Lagrange multiplier, for wealth contingent on a given state of the world. We obtain a characterization of state prices, first based on the absence of arbitrage, then based on the first-order conditions for optimal portfolio choice of a given agent, and finally from the first-order conditions for Pareto optimality in an equilibrium with complete markets.

 

A Arbitrage and State Prices
B Risk-Neutral Probabilities
C Optimality and Asset Pricing
D Efficiency and Complete Markets
E Optimality and Representative Agents
F State-Price Beta Models
Exercises
Notes

 

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This is a thoroughly updated edition of Dynamic Asset Pricing Theory, the standard text for doctoral students and researchers on the theory of asset pricing and portfolio selection in multiperiod settings under uncertainty. The asset pricing results are based on the three increasingly restrictive assumptions: absence of arbitrage, single-agent optimality, and equilibrium. These results are unified with two key concepts, state prices and martingales. Technicalities are given relatively little emphasis, so as to draw connections between these concepts and to make plain the similarities between discrete and continuous-time models.

Readers will be particularly intrigued by this latest edition`s most significant new feature: a chapter on corporate securities that offers alternative approaches to the valuation of corporate debt. Also, while much of the continuous-time portion of the theory is based on Brownian motion, this third edition introduces jumps in order to accommodate surprise events such as bond defaults. Applications include term-structure models, derivative valuation, and hedging methods. Numerical methods covered include Monte Carlo simulation and finite-difference solutions for partial differential equations. Each chapter provides extensive problem exercises and notes to the literature. A system of appendixes reviews the necessary mathematical concepts. With this new edition, Dynamic Asset Pricing Theory remains at the head of the field.