This article analyzes optimal, dynamic portfolio and wealth/consumption policies of utility maximizing investors who must also manage market-risk exposure using Value-at-Risk (VaR). We find that VaR risk managers often optimally choose a larger exposure to risky assets than non-risk managers and consequently incur larger losses when losses occur. We suggest an alternative risk-management model, based on the expectation of a loss, to remedy the shortcomings of VaR. A general-equilibrium analysis reveals that the presence of VaR risk managers amplifies the stock-market volatility at times of down markets and attenuates the volatility at times of up markets.

Buying recent winners and shorting recent losers guarantees time-varying factor exposures in accordance with the performance of common risk factors during the ranking period. Adjusted for this dynamic risk exposure, momentum profits are remarkably stable across subperiods of the entire post-1926 era. Factor models can explain 95% of winner or loser return variability, but cannot explain their mean returns. Momentum strategies which base winner or loser status on stock-specific return components are more profitable than those based on total returns. Neither industry effects nor cross-sectional differences in expected returns are the primary cause of the momentum phenomenon.

We examine insider trading activities of all companies traded on the NYSE, AMEX, and Nasdaq during the 1975-95 period. In general, very little market movement is observed when insiders trade and when they report their trades to the SEC. Insiders in aggregate are contrarian investors. However, they predict market movements better than simple contrarian strategies. Insiders also seem to be able to predict cross-sectional stock returns. The result, however, is driven by insider's ability to predict returns in smaller firms. In addition, informativeness of insiders' activities is coming from purchases, while insider selling appears to have no predictive ability. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

Hedge fund strategies typically generate option-like returns. Linear-factor models using benchmark asset indices have difficulty explaining them. Following the suggestions in Glosten and Jagannathan (1994), this article shows how to model hedge fund returns by focusing on the popular “trend-following” strategy. We use lookback straddles to model trend-following strategies, and show that they can explain trend-following funds’ returns better than standard asset indices. Though standard straddles lead to similar empirical results, lookback straddles are theoretically closer to the concept of trend following. Our model should be useful in the design of performance benchmarks for trend-following funds.

This article shows how both technological and competitive risks affect the timing of private and initial public offerings in an emerging industry. Early private financing occurs in industries that are perceived to be risky, with high development costs and low probability of being displaced by technologically superior rivals. Early public financing occurs in industries perceived to be viable, with low development costs and low probability of displacement. Due to feedback effects between financial and product markets, the value of investors’ proprietary information is greater in private than in initial public offerings. This has implications for underpricing.

Journal Article Optimal Portfolio Choice and the Valuation of Illiquid Securities Get access Francis A. Longstaff Francis A. Longstaff University of California, Los Angeles Address correspondence to Francis A. Longstaff, Anderson School, UCLA, Box 951481, Los Angeles, CA 90095-1481, or e-mail [email protected]. Search for other works by this author on: Oxford Academic Google Scholar The Review of Financial Studies, Volume 14, Issue 2, April 2001, Pages 407–431, https://doi.org/10.1093/rfs/14.2.407 Published: 21 June 2015

This article systematically examines the importance of exchange rate movements and industry competition for stock returns. Common shocks to industries across countries are more important than competitive shocks due to changes in exchange rates. Weekly exchange rate shocks explain almost nothing of the relative performance of industries. Using returns measured over longer horizons, the importance of exchange rate shocks increases slightly and the importance of industry common shocks increases more substantially. Both industry and exchange rate shocks are more important for industries that produce internationally traded goods, but the importance of these shocks is economically small for these industries as well.

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.

Journal Article Financial Constraints and Stock Returns Get access Owen Lamont, Owen Lamont University of Chicago and NBER Address correspondence to Owen Lamont, Graduate School of Business, University of Chicago, 1101 E. 58th St., Chicago, IL 60637, or e-mail: [email protected]. Search for other works by this author on: Oxford Academic Google Scholar Christopher Polk, Christopher Polk Northwestern University Search for other works by this author on: Oxford Academic Google Scholar Jesús Saaá-Requejo Jesús Saaá-Requejo Vega Asset Management Search for other works by this author on: Oxford Academic Google Scholar The Review of Financial Studies, Volume 14, Issue 2, April 2001, Pages 529–554, https://doi.org/10.1093/rfs/14.2.529 Published: 21 June 2015

New York Stock Exchange specialists disseminate information to market participants by displaying price schedules consisting of bid prices, ask prices, bid depths, and ask depths. We examine how specialists update these price schedules in a simultaneous equations model. We find that changes in the best prices and depths on the limit order book have a significant impact on the posted price schedule, while the effects of transactions and order activity are secondary. Furthermore, we show that specialists revise prices and depths differently, but find no evidence that they revise the price schedule in response to changes in inventory.