The Black-Scholes call option pricing model exhibits systematic empirical biases. The Merton call option pricing model, which explicitly admits jumps in the underlying security return process, may potentially eliminate these biases. We provide statistical evidence consistent with the existence of lognormally distributed jumps in a majority of the daily returns of a sample of NYSE listed common stocks. However, we find no operationally significant differences between the Black-Scholes and Merton model prices of the call options written on the sampled common stocks.

ABSTRACT The Black‐Scholes call option pricing model exhibits systematic empirical biases. The Merton call option pricing model, which explicitly admits jumps in the underlying security return process, may potentially eliminate these biases. We provide statistical evidence consistent with the existence of lognormally distributed jumps in a majority of the daily returns of a sample of NYSE listed common stocks. However, we find no operationally significant differences between the Black‐Scholes and Merton model prices of the call options written on the sampled common stocks.

Abstract Relying on a simple general equilibrium model of the term structure, we show that both nominal yields and real consumption growth rates can be affine in the unobservable state variables. We can then express real consumption growth rates in terms of nominal yields rather than the unobservable state variables with the coefficients of the resultant forecasting relation being endogenously determined by the term structure model. Using term structure data over the 1985 to 2000 sample period, the empirical evidence is consistent with our model more accurately predicting real consumption growth rates than a regression model based on the term spread.

This paper investigates the behavior of the term structure of interest rates over the business cycle. In contrast to the simple change in aggregate economic activity used in previous research, we use a more appropiate measure of the business cycle: the deviation of aggregate economic activity from its potentially stochastic trend. Stochastically detrending Gross Domestic Product (GDP) by Watson's [1986] UC-ARMA methodology significantly improves the term spread's informativeness regarding future economic activity. We also investigage the implications of the UC-ARIMA representation of aggregate consumption dynamics for a linear consumption based model of the term structure. The presence of an unobserved by independent cyclical component in aggregate consumption also allows for the more efficient estimation of consumption asset pricing models.

ABSTRACT This article investigates the behavior of the term structure of interest rates over the business cycle. In contrast to prior studies that measure the business cycle by the simple growth in aggregate economic activity, we consider the deviation of aggregate economic activity from its potentially stochastic trend. We show that incorporating both an independent trend and cyclical component in consumption improves the efficiency in estimating consumption‐based asset pricing models. We also find that the term spread is more informative about future changes in stochastically detrended real gross domestic product (GDP) than future growth rates in real GDP.

This paper estimates volatility changes in daily returns to the Dow Jones Industrial Average over the sample period 1897 through 1988. This allow a direct investigation of the reaction of the level of stock prices and subsequent expected returns to these estimated changes in volatility. The authors provide empirical evidence consistent with relatively large and systematic revisions in stock prices and subsequent expected returns to volatility changes. However, there appears to be an asymmetry in the market's reaction to volatility increases as opposed to volatility decreases. A majority of their volatility changes cannot be associated with the release of significant economic information.

Sheridan Titman, Walter Torous, Valuing Commercial Mortgages: An Empirical Investigation of the Contingent- Claims Approach to Pricing Risky Debt, The Journal of Finance, Vol. 44, No. 2 (Jun., 1989), pp. 345-373

ABSTRACT This paper empirically investigates a contingent‐claims model of commercial mortgage pricing. We find that the magnitude of the observed default premia for a sample of nonprepayable fixed rate bullet mortgages can be explained by the contingent‐claims model. In addition, the model explains a significant proportion of the period‐to‐period changes in the default premia. However, given an assumed negative correlation between building value changes and interest rate changes, the model's risk structure tends to increase less steeply with increasing maturity than the observed risk structure.

We investigate whether the returns of industry portfolios predict stock market movements. In the US, a significant number of industry returns, including retail, services, commercial real estate, metal, and petroleum, forecast the stock market by up to two months. Moreover, the propensity of an industry to predict the market is correlated with its propensity to forecast various indicators of economic activity. The eight largest non-US stock markets show remarkably similar patterns. These findings suggest that stock markets react with a delay to information contained in industry returns about their fundamentals and that information diffuses only gradually across markets.