The relationship between affine stochastic processes and bond pricing equations in exponential term structure models has been well established. We connect this result to the pricing of interest rate derivatives. If the term structure model is exponential affine, then there is a linkage between the bond pricing solution and the prices of many widely traded interest rate derivative securities. Our results apply to m-factor processes with n diffusions and I jump processes. The pricing solutions require at most a single numerical integral, making the model easy to implement. We discuss many options that yield solutions using the methods of the article.

This paper examines the optimal consumption and portfolio-choice problem of long-horizon investors who have access to a riskless asset with constant return and a risky asset (“stocks”) with constant expected return and time-varying precision—the reciprocal of volatility. Markets are incomplete, and investors have recursive preferences defined over intermediate consumption. The paper obtains a solution to this problem which is exact for investors with unit elasticity of intertemporal substitution of consumption and approximate otherwise. The optimal portfolio demand for stocks includes an intertemporal hedging component that is negative when investors have coefficients of relative risk aversion larger than one, and the instantaneous correlation between volatility and stock returns is negative, as typically estimated from stock return data. Our estimates of the joint process for stock returns and precision (or volatility) using U.S. data confirm this finding. But we also find that stock return volatility does not appear to be variable and persistent enough to generate large intertemporal hedging demands.

This paper examines the optimal consumption and portfolio-choice problem of long-horizon investors who have access to a riskless asset with constant return and a risky asset ("stocks") with constant expected return and time-varying precision–the reciprocal of volatility. Markets are incomplete, and investors have recursive preferences defined over intermediate consumption. The paper obtains a solution to this problem which is exact for investors with unit elasticity of intertemporal substitution of consumption and approximate otherwise. The optimal portfolio demand for stocks includes an intertemporal hedging component that is negative when investors have coefficients of relative risk aversion larger than one, and the instantaneous correlation between volatility and stock returns is negative, as typically estimated from stock return data. Our estimates of the joint process for stock returns and precision (or volatility) using U.S. data confirm this finding. But we also find that stock return volatility does not appear to be variable and persistent enough to generate large intertemporal hedging demands.

Cephalon Inc., a biotech firm, bought call options on its own stock to meet its conditional cash flow needs. We analyze this decision by using the cash flow hedging concepts of Froot et al., (1993. Journal of Finance 5, 1629–1658). We identify the managerial analyses necessary to apply this theory and discuss managerial considerations absent from the theory. We find that managers consider deadweight costs of risk management, which theory tends to ignore. Theory provides little guidance in how to measure these and other deadweight costs. Finally, uncertainty about the availability of external financing and accounting considerations are critical considerations by managers.

The relationship between affine stochastic processes and bond pricing equations in exponential term structure models has been well established. We connect this result to the pricing of interest rate derivatives. If the term structure model is exponential affine, then there is a linkage between the bond pricing solution and the prices of many widely traded interest rate derivative securities. Our results apply to m-factor processes with n diffusions and l jump processes. The pricing solutions require at most a single numerical integral, making the model easy to implement. We discuss many options that yield solutions using the methods of the article.

ABSTRACT This paper models transaction costs as the rents that a monopolistic market maker extracts from impatient investors who trade via limit orders. We show that limit orders are American options. The limit prices inducing immediate execution of the order are functionally equivalent to bid and ask prices and can be solved for various transaction sizes to characterize the market maker's entire supply curve. We find considerable empirical support for the model's predictions in the cross‐section of NYSE firms. The model produces unbiased, out‐of‐sample forecasts of abnormal returns for firms added to the S&P 500 index.

The liquidity shocks of ’08–’09 revealed that measures of liquidity risk being used in most financial institutions turned out to be woefully inadequate. The construction of long-short portfolios based on liquidity proxies introduces errors such as extraneous risk factors and hedging error. We develop a new measure for liquidity risk using exchange-traded funds (ETFs) that attempts to minimize this error. We form a theoretically-supported measure that is long ETFs and short the underlying components of that ETF, i.e., long and short a similar set of underlying securities with the same weights. Pricing discrepancies between the long and short positions are driven by liquidity differences between the ETF and its underlying components. Constructing liquidity risk factors in a number of markets, we undertake several tests to validate our new liquidity metric. The results show that our illiquidity measure is strongly related to other measures of illiquidity, explains bond index returns, and reveals a systematic illiquidity component across fixed-income markets.

We present a new measure of liquidity known as “latent liquidity” and apply it to a unique corporate bond database. Latent liquidity is defined as the weighted average turnover of investors who hold a bond, in which the weights are the fractional investor holdings. It can be used to measure liquidity in markets with sparse transactions data. For bonds that trade frequently, our measure has predictive power for both transaction costs and the price impact of trading, over and above trading activity and bond-specific characteristics thought to be related to liquidity. Additionally, this measure exhibits relationships with bond characteristics similar to those of other trade-based measures.