Accounting data and asset valuation: Theory

Firms and divisions which are not traded on organized exchanges are often valued without the benefit of market data. Accounting data is used instead. One suggested approach is to use accounting beta as a proxy for market return beta. In the context of the Arbitrage Pricing Theory, we provide a theoretical justification for such a procedure. Our results provide a set of sufficient conditions so that return betas and accounting betas are equal. Our results also suggest a general methodology for evaluating projects and untraded firms using accounting data. The method underlying the derivation here is very general and can be applied in deriving testable restrictions between fundamentals, broader in context than that of accounting variables.     

Production and the Real Rate of Interest: A Sample Path Equilibrium

This paper examines a multiperiod production economy where investorsdo not observe the realizations of productivity factors or securityexpected returns. Unlike previous work, which expresses theequilibrium conditions as functions of unobservable (to bothreal-world investorsand empiricists) moments of the distributionsof returns, we express the equilibrium real rate asa functionof the observable sample paths of realizations of returns. Weprovide a framework for empirically testing this and other assetpricing models without outside-the-model econometric assumptionsneeded for producing the unobservable moments of returns. Weconstruct versions of the restrictions for any time intervalbetween observations. JEL codes: E43, G12, D92, D80, D51     

Production and the Real Rate of Interest: A Sample Path Equilibrium

This paper examines a multiperiod production economy where investors do not observe the realizations of productivity factors or security expected returns. Unlike previous work, which expresses the equilibrium conditions as functions of unobservable (to both real-world investors and empiricists) moments of the distributions of returns, we express the equilibrium real rate as a function of the observable sample paths of realizations of returns. We provide a framework for empirically testing this and other asset pricing models without outside-the-model econometric assumptions needed for producing the unobservable moments of returns. We construct versions of the restrictions for any time interval between observations.     

Alternatives to the normal model of stock returns: Gaussian mixture, generalised logF and generalised hyperbolic models

Simple parametric models of the marginal distribution of stock returns are an essential building block in many areas of applied finance. Even though it is well known that the normal distribution fails to represent most of the “stylised” facts characterising return distributions, it still dominates much of the applied work in finance. Using monthly S&P 500 stock index returns (1871–2005) as well as daily returns (2001–2005), we investigate the viability of three alternative parametric families to represent both the stylised and empirical facts: the generalised hyperbolic distribution, the generalised logF distribution, and finite mixtures of Gaussians. For monthly return data, all three alternatives give reasonable fits for all sub-periods. However, the generalised hyperbolic distribution fails to describe some features of the marginal distributions in some sub-periods. The daily return data are much more symmetric and expose another problem for all three distributions: the parameters describing the behaviour of the tails also influence the scale so that simpler alternatives or restricted parameterisations are called for.