Harry J. Turtle

A barrier option framework for corporate security valuation

Abstract This paper proposes a framework for corporate security valuation based on path-dependent, barrier option models instead of the commonly used path-independent approach. We argue that path dependency is an intrinsic and fundamental characteristic of corporate securities because equity can be knocked out whenever a legally binding barrier is breached. A direct implication of this framework is that equity will be priced as a down-and-out call option. We provide empirical validation of the barrier model by showing that implied barriers are statistically and economically significant for a large cross-section of industrial firms. Additional robustness tests confirm that barriers remain significant over a wide range of input variable estimates. And finally, we apply the barrier option framework to bankruptcy prediction and find that implied failure probabilities dominate Z-scores in most cases.

Political elections and the resolution of uncertainty: The international evidence

Abstract We investigate the behavior of stock market indices across 33 countries around political election dates during the sample period 1974–1995. We find a positive abnormal return during the two-week period prior to the election week. The positive reaction of the stock market to elections is shown to be a function of a country’s degree of political, economic and press freedom, and a function of the election timing and the success of the incumbent in being re-elected. In particular, we find strong positive abnormal returns leading up to the elections (i) in less free countries won by the opposition, and (ii) called early and lost by the incumbent government. These results are consistent with the uncertain information hypothesis (UIH) of Brown et al. (Brown, K.C., Harlow, W.V., Tinic, S.M., 1988. Journal of Financial Economics 22, 355–385) and the model of election behavior of Harrington (Harrington, J.E., 1993. The American Economic Review 83, 27–42).

Tests of Conditional Asset Pricing with Time-Varying Moments and Risk Prices

This paper tests conditional capital asset pricing models in a multivariate GARCH framework employing both constant and time-varying prices of market and bond risk. Depending on the interpretation of the market portfolio, the ICAPM with one hedge portfolio or the two-factor myopic CAPM are supported using weekly data from July 1983 to December 1989. In contrast, we reject the myopic single-factor CAPM under a constant price of market risk. We find that interest rate risk is highly significant, which suggests that previous rejections of the conditional CAPM using only stock market data may be due to omitted hedge terms or an incomplete market factor.

Semiparametric ARCH Models: An Estimating Function Approach

We introduce the method of estimating functions to study the class of autoregressive conditional heteroscedasticity (ARCH) models. We derive the optimal estimating functions by combining linear and quadratic estimating functions. The resultant estimators are more efficient than the quasi-maximum likelihood estimator. If the assumption of conditional normality is imposed, the estimator obtained by using the theory of estimating functions is identical to that obtained by using the maximum likelihood method in finite samples. The relative efficiencies of the estimating function (EF) approach in comparison with the quasi-maximum likelihood estimator are developed. We illustrate the EF approach using a univariate GARCH(1,1) model with conditional normal, Student-t, and gamma distributions. The efficiency benefits of the EF approach relative to the quasi-maximum likelihood approach are substantial for the gamma distribution with large skewness. Simulation analysis shows that the finite-sample properties of the estimators from the EF approach are attractive. EF estimators tend to display less bias and root mean squared error than the quasi-maximum likelihood estimator. The efficiency gains are substantial for highly nonnormal distributions. An example demonstrates that implementation of the method is straightforward.

A Mean-Variance Analysis of Self-Financing Portfolios

This paper develops the analytics and geometry of the investment opportunity set IOS and the test statistics for self-financing portfolios. A self-financing portfolio is a set of long and short investments such that the sum of their investment weights, or net investment, is zero. This contrasts with a standard portfolio that has investment weights summing to one. Examples of self-financing portfolios are hedges, overlays, arbitrage portfolios, swaps, and long/short portfolios. A standard portfolio plus the IOS of self-financing portfolios form a restricted IOS hyperbola with restricted efficient set constants that differ from the usual constants. The restrictions affect statistical tests of portfolio efficiency, which are developed for the self-financing restrictions. As an application, we consider the self-financing portfolios formed by Fama and French 1992, 1993, 1995, based on market capitalization and value. In contrast to Fama and French 1992, 1993, 1995, we find that their restricted IOS is significantly different from the unrestricted IOS with the implication that the Fama-French tests are misspecified.

Hedge Fund Crowds and Mispricing

Recent models and the popular press suggest that large groups of hedge funds follow similar strategies resulting in crowded equity positions that destabilize markets. Inconsistent with this assertion, we find that hedge fund equity portfolios are remarkably independent. Moreover, when hedge funds do buy and sell the same stocks, their demand shocks are, on average, positively related to subsequent raw and risk-adjusted returns. Even in periods of extreme market stress, we find no evidence that hedge fund demand shocks are inversely related to subsequent returns. Our results have important implications for the ongoing debate regarding hedge fund regulation.

Variance Spillover and Skewness in Financial Asset Returns

Bond and stock returns have been observed in the literature to exhibit unconditional skewness and temporal persistence in conditional skewness. We demonstrate that observed persistence in conditional third central moments can be due to the spillover of conditional variance dynamics. The confounding of true skewness and a variance spillover effect is problematic for financial modeling. Using market data, we empirically demonstrate that a simple standardization approach removes the variance-induced skewness persistence. An important implication is that more parsimonious return and asset pricing models result if skewness persistence need not be modeled.

What's a Portfolio Manager Worth?

This article derives and applies a performance measure of a portfolio managers value–added called “style pricing.” The value–added is obtained by treating the per period payoffs from the managed portfolio as a financial claim, contingent on the payoffs from other marketed assets. The relevant marketed assets are those that describe the style of the managed portfolios returns in a precise way. The price of the contingent claim is obtained using martingale methods so that there is zero arbitrage between the portfolios payoffs and the payoffs from the replicating contingent claim. As the authors explain, the style pricing approach may be applied to any management style, is directly measured in dollars, and is readily comparable to the portfolio managers remuneration and the fees payable.

A Note on the Analytics and Geometry of Limiting Mean-Variance Investment Opportunity Sets

This paper extends the mathematics developed by Merton (1972) to the limiting investment opportunity set as smaller risk assets are added. Investment opportunity sets of risky assets are well-known to be described by hyperbolae in mean-standard deviation space. In practice, the asset classes in portfolios may vary from high risk common stocks to near cash assets. Low variability assets change the appearance of the investment opportunity set to the extent that a unique optimum risky asset portfolio disappears. The limiting result is similar to the investment opportunity set that arises when two assets are perfectly correlated. The location of the IOS is shown to mathematically depend upon the level of the riskless interest rate and one slope parameter. The slope parameter is estimable, using a finite number of assets, and represents a bound on market Sharpe ratios.

Temporal dependence in asset pricing models

Abstract Estimating and testing conditional models in an unconditional statistical context often results in model disturbances that display temporal dependence. This paper presents an economic explanation for temporal dependence found in disturbances of financial returns in many studies.