We derive the optimal investment policy of a risk-averse investor in a market where there is a textbook arbitrage opportunity, but where liabilities must be secured by collateral. We find that it is often optimal to underinvest in the arbitrage by taking a smaller position than collateral constraints allow. Even when the optimal policy is followed, the arbitrage portfolio typically experiences losses before the final convergence date. In fact, its initial performance may be indistinguishable from that of a conventional portfolio with a poor track record. These results have important implications for the role of arbitrageurs in financial markets.

We examine the lead–lag relation between intraday spot and futures prices for a stock index where the component stocks are floor traded while the futures contract is screen traded. We find that futures prices lead spot prices by nearly 20 min. This is much longer than in markets where both the index and index futures are floor traded. We show that this lead–lag relation is unlikely to be an artifact of differences in liquidity between the spot and futures markets. These results are consistent with the hypothesis that screen trading accelerates the price discovery process. Journal of Economic Literature Classification Numbers: F33, G15, G20, O31.

Thomas J. George, Francis A. Longstaff, Bid-Ask Spreads and Trading Activity in the S&P 100 Index Options Market, The Journal of Financial and Quantitative Analysis, Vol. 28, No. 3 (Sep., 1993), pp. 381-397

This article presents a simple yet powerful new approach for approximating the value of American options by simulation. The key to this approach is the use of least squares to estimate the conditional expected payoff to the optionholder from continuation. This makes this approach readily applicable in path-dependent and multifactor situations where traditional finite difference techniques cannot be used. We illustrate this technique with several realistic examples including valuing an option when the underlying asset follows a jump-diffusion process and valuing an American swaption in a 20-factor string model of the term structure.

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced. We examine this issue using an extensive proprietary data set of contemporaneous CDS transaction prices and quotes by 14 different CDS dealers selling credit protection on the same underlying firm. This unique cross-sectional data set allows us to identify directly how dealers' credit risk affects the prices of these controversial credit derivatives. We find that counterparty credit risk is priced in the CDS market. The magnitude of the effect, however, is vanishingly small and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.

The role that financial innovation plays in financial markets is very controversial. To provide insight into this role, we examine how market participants use the highly successful Treasury STRIPS program. We find that investors use the option to create Treasury‐derivative STRIPS primarily to make markets more complete and take advantage of tax and accounting asymmetries. Although liquidity‐related factors help explain differences in the prices of Treasury bonds and STRIPS, we find little evidence that the option to strip and reconstitute securities is used for speculative or arbitrage‐related purposes.

We use a unique sample of corporate bonds guaranteed by the full faith and credit of the US to test recent theories about why asset prices may diverge from fundamental values. A key feature of our study is access to proprietary data on the haircuts, funding costs, and inventory positions of the primary dealers making markets in the individual bonds. The results provide strong support for the cross-sectional implications of the safe-asset, intermediary-constraints, and search-frictions literatures. Furthermore, the results indicate that network topology may also play an important role in explaining mispricing.

How do differences of opinion affect asset prices? Do investors earn a risk premium when disagreement arises in the market? Despite their fundamental importance, these questions are among the most controversial issues in finance. In this paper, we use a novel data set that allows us to directly measure the level of disagreement among Wall Street mortgage dealers about prepayment speeds. We examine how disagreement evolves over time and study its effects on expected returns, return volatility, and trading volume in the mortgage-backed security market. We find that increased disagreement is associated with higher expected returns, higher return volatility, and larger trading volume. These results imply that there is a positive risk premium for disagreement in asset prices. We also show that volatility in and of itself does not lead to higher trading volume. Instead, only when disagreement arises in the market is higher uncertainty associated with more trading. Finally, we are able to distinguish empirically between two competing hypotheses regarding how information in markets gets incorporated into asset prices. We find that sophisticated investors appear to update their beliefs through a rational expectations mechanism when disagreement arises.

We conduct an empirical analysis of forward prices in the PJM electricity market using a high‐frequency data set of hourly spot and day‐ahead forward prices. We find that there are significant risk premia in electricity forward prices. These premia vary systematically throughout the day and are directly related to economic risk factors, such as the volatility of unexpected changes in demand, spot prices, and total revenues. These results support the hypothesis that electricity forward prices in the Pennsylvania, New Jersey, and Maryland market are determined rationally by risk‐averse economic agents.