Knowledge that Transforms

This study estimates a model of banking company equity returns taking into consideration book value and market value measures of their exposure to emerging markets debt. In this estimation, general systematic market factors, such as the rate of return on the S&P500 stock index and yields on a constant maturity 5-year Treasury note, are held constant such that the exposure variables are accounting for effects due to banks’ exposure to emerging market debt. The results, although not uniform among banking companies, support the hypothesis that the extent of exposure to emerging market debt are factored into the valuation of banking company equity contemporaneously. The inclusion of a market value indicator adds to the explanation of equity returns of some banks. It is also clear that knowing the extent of the exposure on a book value basis is important information alone that may allow investors to take account of or evaluate the effects of changes in banking company equity valuation from LDC debt exposures. We also perform an event study for three major debt crises to determine whether the market recognizes the effects of these events on bank valuation. The event study results show that there is little information from identifying the time period of the crises on banking company equity returns. Explanations for this are that the information of these possible crises has been embedded in bank changes in exposure and that the market valuation of the emerging market debt is already accounted for by our model.

Litterman et al. [Litterman, R., Scheinkman, J., Weiss, L., 1991. Volatility and the yield curve. Journal of Fixed Income 1 (June), 49–53] and Engle and Ng [Engle, R.F., Ng, V.K., 1993. Time-varying volatility and the dynamic behavior of the term structure. Journal of Money, Credit and Banking 25(3), 336–349] provide empirical evidence of a relation between yield curve shape and volatility. This study offers theoretical support for that finding in the general context of cross-sectional time series. We introduce a new risk measure quantifying the link between cross-sectional shape and market risk. A simple econometric procedure allows us to represent the risk experienced by cross-sections over a time period in terms of independent factors reproducing possible cross-sectional deformations. We compare our risk measure to the traditional cross-yield covariance according to their relative performance. Empirical investigation in the US interest rate market shows that (1) cross-shape risk factors outperform cross-yield risk factors (i.e., yield curve level, slope, and convexity) in explaining the market risk of yield curve dynamics; (2) hedging multiple liabilities against cross-shape risk delivers superior trading strategies compared to those stemming from cross-yield risk management.

We investigate the relation between option-based executive compensation and market measures of risk for a sample of commercial banks during the period of 1992–2000. We show that following deregulation, banks have increasingly employed stock option-based compensation. As a result, the structure of executive compensation induces risk-taking, and the stock of option-based wealth also induces risk-taking. The results are robust across alternative risk measures, statistical methodologies, and model specifications. Overall, our results support a management risk-taking hypothesis over a managerial risk aversion hypothesis. Our results have important implications for regulators in monitoring the risk levels of banks.

A number of mutual funds cater exclusively to institutional investors. Although institutional funds might be a natural place to look for “smart money”, agency costs associated with delegated monitoring may lead to less monitoring and worse overall performance. We split institutional funds based on proxies for the degree of investor oversight, and we find that institutional funds with low initial investment requirements and funds with retail mates perform significantly worse than other institutional funds both before and after adjusting for risk and expenses. Tracking error is especially important in the flow-performance relationship of institutional funds with high minimum investment requirements.

The empirical literature on credit risk has relied mostly on the corporate bond market to estimate losses in the event of default. The reason for this is that, as bank loans are private instruments, few data on loan losses are publicly available. The contribution of this paper is to apply mortality analysis to a unique set of micro-data on defaulted bank loans of a European bank. The empirical results relate to the timing of recoveries on bad and doubtful bank loans, the distribution of cumulative recovery rates, their economic determinants and the direct costs incurred by that bank on recoveries on bad and doubtful loans.

The risk inherent in the accumulation of investment capital depends on the true return distributions of the risky assets, the accuracy of estimated returns, and the investment strategy. This paper considers risk control with Value-at-Risk and Conditional Value-at-Risk, using control limits to determine times for portfolio rebalancing. Optimal strategies and control limits are determined for a geometric Brownian motion asset pricing model with random parameters. The approaches to risk control are applied to the fundamental problem of investment in stocks, bonds, and cash over time.

Stock prices tend to cluster at round numbers, a phenomenon observed in many markets. Using tick-by-tick transaction data, this article studies price clustering on the Tokyo Stock Exchange, which is a computerized limit order market. As for the intraday pattern, the degree of price clustering is greatest at the market opening. Then, it decreases during the first half hour and reaches a stable level. It does not increase again near the market closing. There is no clear difference in clustering between call auctions and continuous auctions.

In oligopolies, firms behave strategically and commit to actions that elicit favorable responses from rivals. Firm actions consequently are a function of the nature of these strategic interactions. In this paper, we develop a methodology for the empirical estimation of strategic interactions in product markets. We then apply our measure of strategic interactions to CEO compensation. We use quarterly data on profits and sales from Compustat to estimate the slope of firm’s reaction function. When the slope is negative and marginal profits decrease with an increase in the rival’s actions the firm is classified as a strategic substitute. When the slope is positive and marginal profits increase with an increase in the rival’s actions the firm is classified as a strategic complement. As predicted by theory, we find significant evidence that strategic substitutes decrease the pay for performance incentives of their CEOs. On the other hand, strategic complements significantly increase CEO pay for performance incentives. The empirical measure developed can be used to test a wide variety of strategic models.

We consider the 12-month moving average aggregate default rate of S&P-rated US-bonds. We estimate the conditional probability distribution of this default rate as a function of a weighted average bond rating, a lagged default rate and a preliminary predictor that is based on lagged new issuance. Our modeling approach is asymptotically optimal for an expected utility maximizing investor. The resulting conditional probability density is consistent with our intuition. We measure the model’s performance by the out-of-sample expected utility. According to this measure, our model clearly outperforms a simple regression model, a regression model with ARMA error terms and a Poisson model.