We use the modified Black-Scholes model and a random variance option pricing model to study prices of European currency options traded in Geneva. The options, which cannot be exercised early, include calls and puts on the dollar/Swiss franc exchange rate. In the empirical analysis, we examine the model fit and the biases with respect to the strike price, time to maturity, and volatility. There is some evidence of mispricing and there are small gains available by trading with the random variance model.

A new asset pricing model that generalizes earlier results in the downside risk literature is developed and empirically tested using a multivariate approach. By specifying risk as deviations below any arbitrary target rate of return, the generalized Mean-Lower Partial Moment (MLPM) model overcomes the limited appeal of earlier formulations, and, moreover, a large class of extant pricing models using alternative risk measures (variance, semivariance, semideviation, probability of loss, etc.) becomes special cases of the new framework. Empirical tests indicate that the new model cannot be rejected against an unspecified alternative for a large set of target rates of return. The traditional CAPM, on the other hand, is rejected as a well-specified alternative. The MLPM target rates inferred from market data appear to be related to equity market mean returns rather than to the riskfree rate, the target rate that is implicit in the CAPM and explicit in earlier downside risk formulations.

This paper examines the determinants of commodity futures hedging and of risk premia arising from covariation of the futures price with stock market returns, and with the revenues of producers. Owing to supply shocks that stochastically redistribute real wealth (surplus) between producers and consumers, and to limited participation in the futures market, the total risk premium in the model is not proportional to the contract's covariance with aggregate consumption. Stock market variability interacts with the incentive to hedge, causing the producer hedging component of the risk premium to increase (decrease) with income elasticity, for a normal (inferior) good. Production costs that depend on output raise the premium. We argue that output and demand shocks will typically be positively correlated, raising the premium. High supply elasticity reduces the absolute heding premium by reducing the variability of spot price and revenue.

This paper provides a simple method to account for heteroskedasticity and cross-sectional dependence in samples with large cross sections and relatively few time-series observations. The method is motivated by cross-sectional regression studies in finance and accounting. Simulation evidence suggests that these estimators are dependable in small samples and may be useful when generalized least squares is infeasible, unreliable, or computationally too burdensome. We also consider efficiency issues and show that, in principle, asymptotic efficiency can be improved using a technique due to Cragg (1983).

This paper examines rational expectations in the Treasury bill market from 1961 to 1988 with a risk premium specified to be proportional to the volatility of excess returns using instrumental variables. From 1961 to 1972 and from 1972 to 1979, rational expectations cannot be rejected, and both the predictive power of the yield curve and the risk premium are highly significant. By contrast, with just a constant risk premium and with a risk premium proxied by moving averages of absolute interest rate changes, rational expectations are rejected for each subperiod, and the yield curve has significant predictive information only from 1972 to 1979.

This paper attempts to characterize liquidity-driven noise in the CRSP Government Bond price data set by comparing these price records to the independently collected Shearson Lehman Brothers (SLB) Bond Data Base. We argue that discrepancies between the data sets are due largely to liquidity-driven price errors, and we show that they are systematically related to certain bond characteristics. On the other hand, these discrepancies are small in magnitude and are approximately mean zero. We examine data filters based on observable bond characteristics and show that these filters can reduce the noise in price records while preserving their mean zero nature. The effects of these errors on performance evaluation are investigated by comparing results using filtered and unfiltered data.

Critics claim that theories of secured debt fail to explain the widespread use of collateral because they incorrectly predict when a loan will be secured. This paper provides the first rigorous statistical test of the transaction cost models of secured debt. Data from two samples of over 1,000 small business loans generally support the common set of predictions of these theories. The incidence of secured debt is positively related to probability of default, loan size, loan maturity, and marketability of assets. Changes in the legal and economic environment also alter firms' decisions regarding the pledging of collateral.

This paper examines the seasonal behavior of proportional dealer spreads for OTC NASDAQ common stocks. Results indicate there is seasonality in dealer spreads. Spreads tend to be larger in the second half of the calendar year, peaking in December. At the turn-ofthe-year, spreads tend to peak in mid- to late December and then recede during January. The last trading day in December produces the largest daily decline in spreads during the turn-of-the-year period.