Knowledge that Transforms

This paper examines differences between risk-neutral and objective probability densities of future interest rates. The identification and quantification of these differences are important when risk-neutral densities (RNDs), such as option-implied RNDs, are used as indicators of actual beliefs of investors. We employ a multi-factor essentially affine modeling framework applied to German time-series and cross-section term structure data in order to identify both the risk-neutral and the objective term structure dynamics. We find important differences between risk-neutral and objective distributions due to risk premia in bond prices. Moreover, the estimated premia vary over time in a quantitatively significant way, which implies that the differences between the objective and the risk-neutral distributions also vary over time. We therefore conclude that one should be cautious in interpreting RNDs in terms of expectations. The method used in this paper provides an alternative approach to identifying objective probabilities of future interest rates.

Popular investment advice recommends that stock/bond and stock/wealth ratios should rise with investor risk tolerance and investment horizon respectively, prescriptions that are difficult to reconcile with the simple mean-variance model. We show that extending the mean-variance model to include human capital, without any other modifications, can simultaneously justify both recommendations, so long as the correlation between labour income and stock returns falls within a range determined by market and investor-specific parameters. Aggregate labour income data from 11 countries generally satisfy this requirement, as do plausible individual income processes. We also consider the implications of human capital for the optimal bond/wealth ratio over the investment horizon, and examine the sensitivity of the stock/bond mix to the volatility of labour income.

We provide a model of bookbuilding in IPOs, in which the issuer can choose to ration shares. Before informed investors submit their bids, they know that, in the aggregate, winning bidders will receive only a fraction of their demand. We demonstrate that this mitigates the winner's curse, that is, the incentive of bidders to shade their bids. It leads to more aggressive bidding, to the extent that rationing can be revenue-enhancing. In a parametric example, we characterize bid and revenue functions, and the optimal degree of rationing. We show that, when investors’information is diffuse, maximal rationing is optimal. Conversely, when their information is concentrated, the seller should not ration shares. We provide testable predictions on bid dispersion and the degree of rationing. Our model reconciles the documented anomaly that higher bidders in IPOs do not necessarily receive higher allocations.

We analyze the resiliency of a pure limit order market by investigating the limit order book (bid and ask prices, spreads, depth and duration), order flow and transaction prices in a window of best limit updates and transactions around aggressive orders (orders that move prices). We find strong persistence in the submission of aggressive orders. Aggressive orders take place when spreads and depths are relatively low, and they induce bid and ask prices to be persistently different after the shock. Depth and spread remain also higher than just before the order, but do return to their initial level within 20 best limit updates after the shock. Relative to the sample average, depths stay around their mean before and after aggressive orders, whereas spreads return to their mean after about twenty best limit updates. The initial price impact of the aggressive order is partly reversed in the subsequent transactions. However, the aggressive order produces a long-term effect as prices show a tendency to return slowly to the price of the aggressive order.

This paper provides an in depth analysis of an investor's reluctance to realize losses and his propensity to realize gains – a behavior known as the disposition effect. Together, sophistication (static differences across investors) and trading experience (evolving behavior of a single investor) eliminate the reluctance to realize losses. However, an asymmetry exists as sophistication and trading experience reduce the propensity to realize gains by 37% (but fail to eliminate this part of the behavior.) Our research design allows us to follow an individual's behavior from the start of his investing life/career. This ability makes it possible to track the evolution of the disposition effect as it is reduced and/or disappears.Our results are robust to alternative explanations including feedback trading, calendar effects, and frequency of observation.

This paper examines the price differences between very liquid on-the-run U.S. Treasury securities and less liquid off-the-run securities over the on/off cycle. Comparing pairs of securities in time-series regressions allows us to disregard any fixed cross-sectional differences between securities. Also, since the liquidity of Treasury notes varies predictably over time, we can distinguish between current and future liquidity. We compare a variety of (microstructure-based) direct measures of liquidity to compare their effects on prices. We show that the liquidity premium depends primarily on the amount of remaining future liquidity.

The literature has documented positive announcement effects for privately placed seasoned equity issues.This study shows positive announcement effects not only for private but also for public placements in Hong Kong. Our unique data offer new insights not obtainable from U.S. data as we examine the cross-sections of the announcement effects. Most importantly, we find that the announcement effect is more likely to be positive for smaller issuers, such as private placing firms and some public issuers where asymmetric information arises more from growth than from assets in place. This finding is consistent with the generalized Myers-Majluf model.

A liquidity trader wishes to trade a fixed number of shares within a certain time horizon and to minimize the mean and variance of the costs of trading. Explicit formulas for the optimal trading strategies show that risk-averse liquidity traders reduce their order sizes over time and execute a higher fraction of their total trading volume in early periods when price volatility or liquidity increases. In the presence of transaction fees, traders want to trade less often when either price volatility or liquidity goes up or when the speed of price reversion declines. In the multi-asset case, price effects across assets have a substantial impact on trading behavior.

This paper extends the Treynor performance ratio for a single index to the case of multiple indexes. The new measure, called the Generalized Treynor Ratio, preserves the same key geometric and analytical properties of the original Treynor Ratio. The Generalized Treynor Ratio is defined as the abnormal return of a portfolio per unit of premium-weighted average systematic risk, normalized by the premium-weighted averagesystematic risk of the benchmark. Numerical simulations reveal that the portfolio rankings produced with this measure are more precise and more stable than the ones provided by Jensen's alpha and the Information Ratio.

We investigate the way investors react to prior gains/losses. We directly examine investor reactions to different definitions of gains and losses (i.e., overall wealth, paper gains and losses, and realized capital gains and losses) and investigate how gains and losses in one category of wealth (e.g., real estate) affect holdings in other categories (e.g., financial assets). We show that investors change their holdings of risky assets as a function of both financial and real estate gains. Prior gains increase risk-taking, while prior losses reduce it. To interpret our results, we consider and compare three alternative hypotheses of investor behavior: prospect theory, house money effect and standard utility theory with decreasing risk aversion. Our evidence fails to support loss aversion, pointing in the direction of the house money effect or standard utility theory. Investors consider wealth in its entirety, and risk-taking in financial markets is affected by gains/losses in overall wealth, financial wealth, and real estate wealth.