We consider the general n-factor Heath, Jarrow, and Morton model (1992) and provide a sufficient condition on the volatility structure for the spot rate process to be Markovian with 2n state variables. The price of a discount bond is also Markovian with the same state variables and, hence, claims against the term structure can be efficiently priced using standard simulation techniques. Our results extend earlier works such as Ritchken and Sankarasubramanian (1995) where the one-factor model is treated, and Carverhill (1994), where the volatility structure is non-random. Numerical experiments show that our model can explain the volatility smile observed in the interest rate options market and also overcome the biases noted by Flesaker (1993).

This paper examines the demand for municipal bond insurance in the context of a competitive signaling equilibrium model. The study compares the pricing of new bond issues that are insured to similar issues that are not insured. The results indicate that issuers who purchase bond insurance, on average, are able to reduce their new issue borrowing cost more than enough to offset the cost of the insurance premium. Furthermore, the net benefit to the issuer increases as the underlying credit quality of the bond declines.

We propose a market-based framework that exploits time-varying parameter vector autoregressions to estimate the dynamic network of financial spillover effects. We apply it to financials in the Standard & Poor’s 500 index and estimate interconnectedness at the sectoral and institutional levels. At the sectoral level, we uncover two main events in terms of interconnectedness: the Long-Term Capital Management crisis and the 2008 financial crisis. After these crisis events, we find a gradual decrease in interconnectedness, not observable using the classical rolling-window approach. At the institutional level, our framework delivers more stable interconnectedness rankings than other comparable market-based measures.

There is a false, but widely-held belief about orthogonal (“zero-beta”) portfolios: for a given market index, all zero-beta portfolios have the same expected return and the minimal-variance, zero-beta portfolio is unique. This is true only when the index is mean/variance efficient. Every nonefficient index possesses zero-beta portfolios at all levels of expected return. For a given index, minimal-variance zero-beta portfolios corresponding to different expected returns lie along an “orthogonal frontier” in the mean/variance space. The frontier has some unusual properties which turn out to be relevant for empirical work on asset pricing. It is functionally related to deviations about the “securities market line.”

We study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log dividend-price ratio. Next, we simulate various rational bubbles that have explosive conditional expectation, and we investigate the magnitude of the approximation error in those cases. We find that, surprisingly, the Campbell-Shiller approximation is very accurate even in the presence of large explosive bubbles. Only in very large samples do we find evidence that bubbles generate large approximation errors. Finally, we show that a bubble model in which expected returns are constant can explain the predictability of stock returns from the dividend-price ratio that many previous studies have documented.

This article investigates the impact of political uncertainty on contractual lending terms using a large sample of syndicated loans and a within-firm estimation approach to achieve identification. Firms pay 7 basis points (bps) more on loans originated when their lenders are undergoing an election relative to when their lenders are not undergoing an election. Lenders from less financially developed countries are more likely to pass political uncertainty costs to borrowers. Consistent with electoral uncertainty driving this premium, the most contested elections have the largest impact (17 bps). Overall, political uncertainty leads to a tangible increase in firms’ financing costs.

The stock price literature abounds with applications of the Markowitz [16] – Sharpe [18] market model to American stock price data. There is a lack of corresponding studies for non-American securities, due primarily to the absence of generally available machine readable data bases (see, however, [1], [2], [8, Section 9.5], [11], [17], and [20]. The purpose of this paper is to present the results of some initial tests of the market model for a broad cross-section of the European common stocks. Our data base consists of daily price and dividend data for 229 stocks from seven European countries. In addition, for comparison purposes we have included a sample of 65 American securities.

This paper tests whether there is a difference in the stock price reactions to industrial straight debt offerings of different risk. Using bond ratings at the time of announcement as a measure of risk, we find that there is no monotonic relation between stock price impact and rating and no statistically significant difference across risk classes, even though the sample includes low-rated debt issues from recent years. This confirms earlier evidence on straight debt issues, but differs from the evidence on convertible securities. The paper also finds that the results for straight debt are not affected by shelf registrations or by the issuing firms' involvement in merger and acquisition-related activity.

Individual decisions about investment may be regarded as choices among alternative probability distributions of net returns. It is assumed that these distributions are completely known and independent of initial wealth positions, and that individuals determine the preferred portfolio of investment in accordance with a given, consistent set of preferences.

We construct a simple economy with consumption only at the final date in which we “endogenize” the stochastic behavior of prices assumed in the Black-Scholes model. Certain preferences (constant proportional risk aversion) and beliefs are shown to be sufficient and necessary, in certain respects, for the existence of such an equilibrium. The analysis is then generalized to a continuous-consumption framework, in which we embed the Merton proportional dividend model.

I investigate how distraction affects the trading behavior of professional asset managers. Exploring detailed transaction-level data, I show that managers with a large fraction of portfolio stocks that have an earnings announcement are significantly less likely to trade in other stocks, suggesting that these announcements divert attention from trading decisions for other stocks. This distraction effect is more pronounced for nonpassive managers who engage in active stock selection choices. Finally, I identify three channels through which distraction hurts managers’ performance: Distracted managers trade less profitably, incur slightly higher transaction costs, and are less likely to close losing positions.

We study individual portfolio choice in a laboratory experiment and find strong evidence for heuristic behavior. The subjects tend to focus on the marginal distribution of an asset, while largely ignoring its diversification benefits. They follow a conditional 1/n diversification heuristic as they exclude the assets with an “unattractive” marginal distribution and divide the available funds equally between the remaining “attractive” assets. This strategy is applied even if it leads to allocations that are dominated in terms of first-order stochastic dominance and is clearly irrational. In line with these findings, we find that framing and problem presentation have substantial influence on portfolio decisions.

We identify large discontinuous changes, known as jumps, in daily stock prices and explore the role of jumps in cross-sectional stock return predictability. Our results show that small and illiquid stocks have higher jump returns to the extent that cross-sectional differences in jumps fully account for the size and illiquidity effects. Based on value-weighted portfolios, jumps also account for the value premium. On the other hand, jumps are not the cause of momentum or net share issue effects. The findings of our study shed new light on stock return dynamics and present challenges to conventional explanations of stock return predictability.

Hull and White (1993) introduced a method to extend lattice-based contingent claim valuation techniques to problems with path-dependent payoffs. This paper builds upon their method in the process of valuing two types of commodity purchase contracts that exhibit a form of timing flexibility not previously analyzed in the literature. The techniques demonstrated take advantage of characteristics of claims that simplify incorporation of path dependencies. Possible uses for the methods demonstrated include the valuation of: portfolios of mortgages, capital projects where intensity of use affects productivity of the asset, and capital projects with storage characteristics.

The theory of choice under conditions of certainty has been extended by Von Neumann and Morgenstern [8], Friedman and Savage [5], Marschak [13], and others to conditions involving risk by assuming that individuals maximize their expected utility. The application of this theory to portfolio selection, to efficiency criteria, and to the explanation of the well-known phenomenon of diversification of assets has been carried further by Markowitz [11 and 12], Tobin [17], Samuelson [15], Sharpe [16], and Lintner [10], and more recently by Hadar and Russell [5] and Hanoch and Levy [8].

This paper studies seasonal predictability in the cross section of international stock returns. Stocks that outperform the domestic market in a particular month continue to outperform the domestic market in that same calendar month for up to 5 years. The pattern appears in Canada, Japan, and 12 European countries. Global trading strategies based on seasonal predictability outperform similar nonseasonal strategies by over 1% per month. Abnormal seasonal returns remain after controlling for size, beta, and value, using global or local risk factors. In addition, the strategies are not highly correlated across countries. This suggests they do not reflect return premiums for systematic global risk.

We examine whether industry product market conditions are important in assessing the benefits and costs of chief executive officer (CEO) power. We find that firms are more likely to have powerful CEOs in high demand product markets where firms are facing entry threats. In these markets, investors react favorably to announcements granting more power to CEOs, and CEO power is associated with higher market value, sales growth, investment, advertising, and the introduction of more new products. Our results remain significant when addressing the endogeneity of CEO power by instrumenting CEO power with past non-CEO executive and director sudden deaths.

In this paper prices of corporate bonds are decomposed into elements associated with (1) the pure price of time, (2) the default risk of the agency rating class to which the bond is assigned, and (3) the unique risk and ancillary features of the bond itself.

This paper presents empirical tests of the constant volatility version of the Heath, Jarrow, and Morton model, which is also the continuous time limit of the Ho and Lee model. Using a generalized method of moments (GMM) test on three years of daily data for Eurodollar futures and futures options, the model can be rejected for most subperiods. Various biases in the fitted option prices relative to the market prices are documented through a regression study. The small sample properties and power of the GMM framework to this setting are also studied through simulations.

This paper reexamines the explanatory power of beta, firm size, book-to-market equity, and the earnings-price ratio for average stock returns, correcting two currently controversial biases: selection bias in COMPUSTAT and the errors-in-variables (EIV) bias. After filling in the missing data on COMPUSTAT with the Moody's sample, I do not find any significantly different results for book-to-market equity from using the COMPUSTAT sample only. After correcting for the EIV bias, I find stronger support for the beta pricing theory than previous studies. Regardless of the presence of firm size, book-to-market equity, and earnings-price ratios, betas have significant explanatory power for average stock returns. In particular, firm size is barely significant using monthly returns, but no longer significant using quarterly returns. However, book-to-market equity still has significant explanatory power for average stock returns, even though the EIV bias is corrected.