A Test Of The Intertemporal Asset Pricing Model

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

A simple valuation model that allows for time variation in investment opportunities is developed and estimated. The model assumes that the investment opportunity set is completely described by two state variables, the real interest rate and the maximum Sharpe ratio, which follow correlated Ornstein-Uhlenbeck processes. The model parameters and time series of the state variables are estimated using data on US Treasury bond yields and inflation for the period January 1952 to December 2000. The estimated state variables are shown to be related to the equity premium and to the level of stock prices as measured by the dividend yield. Innovations in the estimated state variables are shown to be related to the returns on the Fama-French arbitrage portfolios, HML and SMB, providing a possible explanation for the risk premia on these portfolios. When tracking portfolios for the state variable innovations are constructed using returns on 6 size and book-to market equity sorted portfolios, the tracking portfolios explain the risk premia on HML and SMB, and these state variable tracking portfolios perform about as well as HML and SMB in explaining the cross-section of returns on the 25 size and book-to market equity sorted value weighted portfolios. An additional test of the ICAPM using returns on 30 industrial portfolios does not reject the model while the CAPM and the Fama-French 3 factor model are rejected using the same data.

In the mid-eighties Mehra and Prescott showed that the risk premium earned by American stocks cannot reasonably be explained by conventional capital market models. Using time additive utility, the observed risk pre mium can only be explained by unrealistically high risk aversion parameters. This phenomenon is well known as the equity premium puzzle. Shortly aft erwards it was also observed that the risk-free rate is too low relative to the observed risk premium. This essay is the first one to analyze these puzzles in the German capital market. It starts with a thorough discussion of the available theoretical mod els and then goes on to perform various empirical studies on the German capital market. After discussing natural properties of the pricing kernel by which future cash flows are translated into securities prices, various multi period equilibrium models are investigated for their implied pricing kernels. The starting point is a representative investor who optimizes his invest ment and consumption policy over time. One important implication of time additive utility is the identity of relative risk aversion and the inverse in tertemporal elasticity of substitution. Since this identity is at odds with reality, the essay goes on to discuss recursive preferences which violate the expected utility principle but allow to separate relative risk aversion and intertemporal elasticity of substitution.