When a company goes public, it is standard practice that the underwriting syndicate allocates more shares than are issued. The underwriter thus holds a short position that it commonly fills by aftermarket trading when market prices fall or, when prices rise, by executing the so-called overallotment option. This option is a standard feature of initial public offering (IPO) arrangements that allows the underwriter to purchase more shares from the issuer at the original offer price. We propose a theoretical model to study the implications of this combination of short position and overallotment option on the pricing of the IPO. Maximizing the sum of both the profits from their share of the offer revenue and the potential profits from aftermarket trading, we show that underwriters strategically distort the offer price. This results either in exacerbated underpricing when favorably informed underwriters lower prices to secure a signaling benefit, or in informationally inefficient offer prices when underwriters pool in offer prices irrespective of their information.

This paper performs specification analysis on the term structure of variance swap rates on the S&P 500 index and studies the optimal investment decision on the variance swaps and the stock index. The analysis identifies 2 stochastic variance risk factors, which govern the short and long end of the variance swap term structure variation, respectively. The highly negative estimate for the market price of variance risk makes it optimal for an investor to take short positions in a short-term variance swap contract, long positions in a long-term variance swap contract, and short positions in the stock index.

This paper numerically solves the decision problem of a multiperiod constant relative risk aversion individual who faces transaction costs and has access to two risky assets, both with predictable returns. With proportional transaction costs and independent and identically distributed returns, we numerically find the rebalancing rule to be a no-trade region for the portfolio weights with rebalancing to the boundary. The shape of the no-trade region depends on the correlation between the two risky assets. With predictable returns, there is instead a no-trade region for each state. We also examine several important economic questions, including the utility cost of not being able to buy on margin or short stock.

This paper compares downside risk measures that incorporate higher return moments with traditional risk measures such as standard deviation in predicting hedge fund failure. When controlling for investment strategies, performance, fund age, size, lockup, high-water mark, and leverage, we find that funds with larger downside risk have a higher hazard rate. However, standard deviation loses the explanatory power once the other explanatory variables are included in the hazard model. Further, we find that liquidation does not necessarily mean failure in the hedge fund industry. By reexamining the attrition rate, we show that the real failure rate of 3.1% is lower than the attrition rate of 8.7% on an annual basis during the period of 1995–2004.

Motivated by the effect on valuation of stopped or reduced debt coupon payments from a company in financial distress, we value a level-dependent annuity contract where the annuity rate depends on the value of an underlying asset process. The range of possible values of this asset is divided into a finite number of regions, with constant annuity rates within each region. We present closed-form formulas for the market value of level-dependent annuities contracts when the market value of the underlying asset is assumed to follow a geometric Brownian motion. Such annuities occur naturally in models of debt with credit risk in financial economics. Our results are applied for valuing both corporate debt with suspended interest payments under the U.S. Chapter 11 provisions and loans with contractual level-dependent interest rates.

Higher first-year post-issue returns are associated with a significantly higher probability of follow-on equity issuance over the next 5 years. This result holds when we control for pre-issue returns and other factors known to affect the probability of equity issuance. The result is most consistent with the market feedback hypothesis that a high post-issue return encourages managers to increase the firm’s investment because it implies that, in the market’s view, the marginal return to the project is high.

The value of American options depends on the exercise policy followed by option holders. Market frictions, risk aversion, or a misspecified model, for example, can result in suboptimal behavior. We study the sensitivity of American options to suboptimal exercise strategies. We show that this measure is given by the Gamma of the American option at the optimal exercise boundary. More precisely, “if B is the optimal exercise price, but exercise is either brought forward when or delayed until a price B̃ has been reached, the cost of suboptimal exercise is given by ½ × Γ(B) × (B − B̃)2, where Γ(B) denotes the American option Gamma.” Therefore, the cost of suboptimal exercise is second-order in the bias of the exercise policy and depends on Gamma. This result provides new insights on American options.

This paper investigates whether comovements between euro area equity returns at national and industry level changed after the introduction of the euro. By adopting a regression quantile-based methodology, we find that after 1999 the degree of comovements among euro area national equity markets was augmented. By explicitly controlling for the impact of global factors, we show that this result cannot be explained by recent worldwide trends. A more refined analysis based on an industry breakdown suggests that the increase in national index comovements is mainly driven by financial, industrial, and consumer services sectors.

This paper extends the affine class of term structure models to describe the joint dynamics of exchange rates and interest rates. In particular, the issue of how to reconcile the low volatility of interest rates with the high volatility of exchange rates is addressed. The incomplete market approach of introducing exchange rate volatility that is orthogonal to both interest rates and the pricing kernels is shown to be infeasible in the affine setting. Models in which excess exchange rate volatility is orthogonal to interest rates but not orthogonal to the pricing kernels are proposed and validated via Kalman filter estimation of maximal 5-factor models for 6 country pairs.

Option pricing models and longer-term value-at-risk (VaR) models generally require volatility forecasts over horizons considerably longer than the data frequency. The typical recursive procedure for generating longer-term forecasts keeps the relative weights of recent and older observations the same for all forecast horizons. In contrast, we find that older observations are relatively more important in forecasting at longer horizons. We find that the Ederington and Guan (2005) model and a modified EGARCH (exponential generalized autoregressive conditional heteroskedastic) model in which parameter values vary with the forecast horizon forecast better out-of-sample than the GARCH (generalized autoregressive conditional heteroskedastic), EGARCH, and Glosten, Jagannathan, and Runkle (GJR) models across a wide variety of markets and forecast horizons.

This paper reexamines, at a range of investment horizons, the asymmetric dependence between hedge fund returns and market returns. Given the current availability of hedge fund data, the joint distribution of longer-horizon returns is extracted from the dynamics of monthly returns using the filtered historical simulation; we then apply the method based on copula theory to uncover the dependence structure therein. While the direction of asymmetry remains unchanged, the magnitude of asymmetry is attenuated considerably as the investment horizon increases. Similar horizon effects also occur on the tail dependence. Our findings suggest that nonlinearity in hedge fund exposure to market risk is more short term in nature, and that hedge funds provide higher benefits of diversification, the longer the horizon.

Horizon-matched historical volatility is commonly used to forecast future volatility for option valuation under the Statement of Financial Accounting Standards (SFAS) 123R. In this paper, we empirically investigate the performance of using historical volatility to forecast long-term stock return volatility in comparison with a number of alternative forecasting methods. In analyzing forecasting errors and their impact on reported income due to option expensing, we find that historical volatility is a poor forecast for long-term volatility and that shrinkage adjustment toward comparable-firm volatility only slightly improves its performance. Forecasting performance can be improved substantially by incorporating both long memory and comovements with common market factors. We also experiment with a simple mixed-horizon realized volatility model and find its long-term forecasting performance to be more accurate than historical forecasts but less accurate than long-memory forecasts.

This paper provides a detailed analysis of the impact of daily mutual fund flow volatility on fund performance. I document a significant negative relationship between the volatility of daily fund flows and cross-sectional differences in risk-adjusted performance. This relationship is driven by domestic equity funds, as well as small funds, well-performing funds, and funds that experience inflows over the sample period. My results are consistent with performance differences arising from the transaction costs of nondiscretionary trading driven by daily fund flows, but not with performance differences arising from the suboptimal cash holdings that arise from fund flows.

This paper offers a rational explanation for the puzzling empirical fact that stock returns decrease with an increase in the volatility of liquidity. We model liquidity as a stochastic price impact process and define the liquidity premium as the additional return necessary to compensate a multiperiod investor for the adverse price impact of trading. The model demonstrates that a fully rational, utility maximizing, risk-averse investor can take advantage of time-varying liquidity by adapting his trades to the state of liquidity. We provide new empirical evidence supportive of the model.

This paper shows that prospect theory is unlikely to explain the disposition effect. Prospect theory predicts that the propensity to sell a stock declines as its price moves away from the purchase price in either direction. Trading data, on the other hand, show that the propensity to sell jumps at zero return, but it is approximately constant over a wide range of losses and increasing or constant over a wide range of gains. Further, the pattern of realized returns does not seem to stem from optimal after-tax portfolio rebalancing, a belief in mean-reverting returns, or investors acting on target prices.

In a recently published paper, Edmans, García, and Norli (2007) reveal a strong association between results of soccer games and local stock returns. Inspired by their work, we propose a novel approach to exploit this effect on the aggregate international level with the following three unique features: i) The aggregate effect does not depend on the games’ results; hence, the effect is an exploitable predictable effect. ii) The aggregate effect is based on many games; hence, it is very large and highly significant. We find that the average return on the U.S. market over the World Cup’s effect period is – 2.58%, compared to +1.21% for all-days average returns over the same period length. iii) Exploiting the aggregate effect is involved with trading in a single index for a relatively long period.

Do threats of pharmaceutical price regulation affect subsequent research and development (R&D) spending? This study uses the Clinton administration’s Health Security Act (HSA) of 1993 as a natural experiment to study this issue. We link events surrounding the HSA to pharmaceutical stock price changes and then examine the cross-sectional relation between firms’ stock price changes and their subsequent unexpected R&D spending changes. Results show that the HSA had significant negative effects on stock prices and firm-level R&D spending. Conservatively, the HSA reduced R&D spending by about $1 billion even though it never became law.