Knowledge that Transforms

As the usual normality assumption is firmly rejected by the data, investors encounter a data-generating process (DGP) uncertainty in making investment decisions. In this paper, we propose a novel way to incorporate uncertainty about the DGP into portfolio analysis. We find that accounting for fat tails leads to nontrivial changes in both parameter estimates and optimal portfolio weights, but the certainty–equivalent losses associated with ignoring fat tails are small. This suggests that the normality assumption works well in evaluating portfolio performance for a mean-variance investor.

This paper introduces the concept of statistical arbitrage, a long horizon trading opportunity that generates a riskless profit and is designed to exploit persistent anomalies. Statistical arbitrage circumvents the joint hypothesis dilemma of traditional market efficiency tests because its definition is independent of any equilibrium model and its existence is incompatible with market efficiency. We provide a methodology to test for statistical arbitrage and then empirically investigate whether momentum and value trading strategies constitute statistical arbitrage opportunities. Despite adjusting for transaction costs, the influence of small stocks, margin requirements, liquidity buffers for the marking-to-market of short-sales, and higher borrowing rates, we find evidence that these strategies generate statistical arbitrage.

We develop an equilibrium model of contracting, bargaining, and search in which the relative scarcity of venture capital affects the bargaining power of entrepreneurs and venture capitalists. This in turn affects the pricing, contracting, and value creation in start-ups. The relative scarcity of venture capital is endogenous and depends on the profitability of venture capital investments, entry costs, and transparency of the venture capital market. Supply and demand conditions also affect the incentives of venture capitalists to screen projects ex ante. We characterize both the short- and long-run dynamics of the venture capital industry, which provides us with a stylized picture of the Internet boom and bust periods. Our model is consistent with existing evidence and provides a number of new empirical predictions.

The returns to hedge funds and other alternative investments are often highly serially correlated. In this paper, we explore several sources of such serial correlation and show that the most likely explanation is illiquidity exposure and smoothed returns. We propose an econometric model of return smoothing and develop estimators for the smoothing profile as well as a smoothing-adjusted Sharpe ratio. For a sample of 908 hedge funds drawn from the TASS database, we show that our estimated smoothing coefficients vary considerably across hedge-fund style categories and may be a useful proxy for quantifying illiquidity exposure.

Which loss function should be used when estimating and evaluating option valuation models? Many different functions have been suggested, but no standard has emerged. We emphasize that consistency in the choice of loss functions is crucial. First, for any given model, the loss function used in parameter estimation and model evaluation should be the same, otherwise suboptimal parameter estimates may be obtained. Second, when comparing models, the estimation loss function should be identical across models, otherwise inappropriate comparisons will be made. We illustrate the importance of these issues in an application of the so-called Practitioner Black-Scholes model to S&P 500 index options.

This paper analyzes the role health status plays in household portfolio decisions using data from the Health and Retirement Study. The results indicate that health is a significant predictor of both the probability of owning different types of financial assets and the share of financial wealth held in each asset category. Households in poor health are less likely to hold risky financial assets, other things (including the level of total wealth) being the same. Poor health is associated with a smaller share of financial wealth held in risky assets and a larger share in safe assets. We find no evidence that the relationship between health status and portfolio allocation is driven by “third variables” that simultaneously affect health and financial decisions. Further, the relationship between health status and portfolio choice does not appear to operate through the effect of poor health on individuals’ attitudes toward risk, their planning horizons, or their health insurance status.

At the end of 1997, foreign companies with shares cross-listed in the U.S. had Tobin's q ratios that were 16.5% higher than the q ratios of non-cross-listed firms from the same country. The valuation difference is statistically significant and reaches 37% for those companies that list on major U.S. exchanges, even after controlling for a number of firm and country characteristics. We suggest that a U.S. listing reduces the extent to which controlling shareholders can engage in expropriation and thereby increases the firm's ability to take advantage of growth opportunities. We show that growth opportunities are more highly valued for firms that choose to cross-list in the U.S., particularly those from countries with poorer investor rights.