Dynamic term structure models explain the yield curve variation well but perform poorly in pricing and hedging interest rate options. Most existing option pricing practices take the yield curve as given, thus having little to say about the fair valuation of the underlying interest rates. This paper proposes an m + n model structure that bridges the gap in the literature by successfully pricing both interest rates and interest rate options. The first m factors capture the yield curve variation, whereas the latter n factors capture the interest rate options movements that cannot be effectively identified from the yield curve. We propose a sequential estimation procedure that identifies the m yield curve factors from the LIBOR and swap rates in the first step and the n options factors from interest rate caps in the second step. The three yield curve factors explain over 99% of the variation in the yield curve but account for less than 50% of the implied volatility variation for the caps. Incorporating three additional options factors improves the explained variation in implied volatilities to over 99%.

This paper documents an increase in the comovement between credit default swap (CDS) spread changes during the 2007–2009 crisis and investigates the source of that increase. One possible explanation is that comovement increased because fundamental values became more correlated. However, I find that changes in fundamentals account for only 23% of the increase in covariance. The remaining increase is attributed to changes in liquidity and the market price of default risk. In contrast, counterparty risk played an insignificant role. Although both contributed, the increase in covariance was driven more by variation in exposures than factor variance–covariance.

Several theoretical studies suggest that coordination problems can cause arbitrageur crowding to push asset prices beyond fundamental value as investors feedback trade on each others’ demands. Using this logic, we develop a crowding model for momentum returns that predicts tail risk when arbitrageurs ignore feedback effects. However, crowding does not generate tail risk when arbitrageurs rationally condition on feedback. Consistent with rational demands, our empirical analysis generally finds a negative relation between crowding proxies constructed from institutional holdings and expected crash risk. Thus our analysis casts both theoretical and empirical doubt on crowding as a stand-alone source of tail risk.

I develop an analytically tractable model that integrates the risk-shifting problem between bondholders and shareholders with the moral-hazard problem between shareholders and the manager. An optimal contract binds shareholders and the manager, and this contract’s flexibility allows shareholders to relax the manager’s incentive constraint following a “good” profitability shock. Thus, the optimal contract amplifies the upside and thereby increases shareholder appetite for risk shifting. Whereas some empirical studies find a positive relation between risk shifting and leverage, others find a negative relation. This model predicts a non-monotonic relation between risk shifting and leverage and can reconcile these contradictory empirical findings.

There have been a large number of tests assessing the performance of U.S. mutual funds. Most of the performance measures have been either explicitly or implicitly based on only two moments of the distribution of returns: the mean and variance. For example, the performance measure suggested and employed by Sharpe [10] is the fund's ex-post reward (return) to variability ratio, while the capital asset pricing measures employed by Treynor [11], Jensen [4] and others relate the fund's returns to those expected, given its level of systematic risk [β]. The risk [β] and excess return [α] measures themselves are directly derived from an underlying mean-variance model of asset choice. When these performance measures are used to compare fund performance vis a vis the market (index), no consensus of opinion appears to have materialized, although most studies find that funds in general perform worse than the market. Indeed, as Carlson ([2, p. 22]) notes in the conclusion of an article reviewing a number of U.S. mutual fund studies, “The issue of whether mutual funds outperform ‘the market’ depends in large degree on the selection of both the time period and market proxy.”

Intelligent corporate financial planning has been necessary for as long as the corporate form of business enterprise has existed. Only in recent years, however, have computer technology and academic theorizing been harnessed to meet this practical need. Without wishing to minimize the impact and value of these efforts on the practice of corporate finance, we do think there are grounds for believing that the new finance “tools” have been less than maximally effective. In this article we contrast typical financial modeling theory in order to interpret the gap between the two. Then we describe a financial policy model whose characteristics might be expected to be more acceptable in practice. Finally, we discuss the implications of the theory/practice gap and our experience with this model for future scholarly activities in the modeling of financial policies.

This paper examines data from 45 world markets and shows that the previously documented relation between mean returns and idiosyncratic volatility arises because of biases in volatility estimates that we can attribute to the bid–ask bounce in trade prices. We show that no significant relation exists between mean returns and idiosyncratic volatility estimated from quote-midpoint returns. Further, there is no significant relation between mean returns and the portion of transaction-price-based idiosyncratic volatility that is orthogonal to bid–ask spreads. The pricing of idiosyncratic volatility is due to the negative pricing of the bid–ask spread.

The existence of risk aversion in portfolio theory can be explained by positing a concave utility function of wealth. In some cases it is useful to construct some measure of risk aversion rather than merely accept its existence.

In recent years a number of papers have been concerned with the determination of necessary and sufficient conditions for portfolio separation and for myopia. As a result of these earlier investigations, it is known that a necessary and sufficient condition both for portfolio separation and for myopia is that the investor's utility function exhibit risk tolerance, that is a linear function of wealth. What is lacking in the existing literature is a clear demonstration of the economic relevance of linear risk tolerance for portfolio separation and myopia. It is hoped that this paper will help to fill the gap by an analysis of separation and myopia using the standard tools of price theory: indifference curves, budget lines, and Engel curves. Viewed in this perspective, a substantial part of the analysis can be amplified and clarified in terms of the geometry of the situation.

We distinguish among the signaling, free cash flow, and wealth transfer hypotheses in explaining the stock price reaction to specially designated dividend (SDD) announcements. In a direct test of the signaling power of SDDs, we find both a larger stock price reaction and a significant upward revision of earnings forecasts for firms with Tobin's q less than one, but not for other firms. Our results support the conditional signaling hypothesis, which predicts greater effects of favorable information for low q firms. Taken together, our results for stock price effects and earnings forecast revisions do not support either the free cash flow or wealth transfer hypotheses.

We study a regulatory change that led to over 300 shareholder proposals to instate proxy access and more than 250 firms adopting proxy access from 2012 to 2016. The firms expected to benefit most from proxy access have the most positive market reaction to receiving a proposal, but adoptions are not concentrated at these firms. We find that proposing and voting shareholders do not discriminate between firms that would or would not benefit and that management resists proxy access at the firms that stand to benefit most. This process results in the concentration of adoptions at large, already-well-governed firms.

In a model where investors disagree about the fundamentals of two stocks, the state-price density depends on investor disagreements for both stocks, especially the larger stock. This implies that disagreement among investors in a large firm has a spillover effect on the pricing of other stocks owned by these investors. The pricing effects of investor disagreements crucially depend on the average belief biases. Empirical findings support the novel model prediction of a disagreement spillover effect and help reconcile some mixed evidence in the literature.

This study investigates whether financial data providers serve as information intermediaries in capital markets. To this end, I examine whether the timeliness of earnings information disseminated by First Call (Thomson Reuters) affects the market’s reaction to earnings announcements. I document that the immediate price and volume response is weaker and the post-earnings-announcement drift stronger for earnings news disseminated with a delay by First Call. To mitigate endogeneity concerns, I study the market reaction on the day of the delayed dissemination and show that a significant part of the stronger drift is clustered around this day.

The issue of capital structure has been intensively examined in the finance literature, particularly after the appearance of the landmark 1958 paper by Modigliani and Miller [8], hereafter MM. In that paper, MM derived a relationship in terms of the expected return on equity of a levered and unlevered firm, known as MM Proposition II. Their analysis was extended later by researchers such as Hamada [5] and Rubinstein [9] who derived the corresponding relationship in terms of the systematic risk (beta). Both these risk-return relationships have been derived for the case of perfect capital markets and the case in which corporate income taxes are the only type of market imperfection. Although effects of other types of market imperfections such as personal income taxes and bankruptcy costs have been examined in numerous studies, neither MM Proposition II nor the “beta” relationship were extended to include the effects of personal income taxes and bankruptcy costs.

This study is an ex post performance test comparing the accuracy of an American model to a European model for valuing listed options. Specifically, the Geske and Johnson American put valuation model is compared with the Black and Scholes European put model. On average, both models undervalue, relative to market prices, put options. However, the Geske and Johnson model values are significantly closer to market prices than are the Black and Scholes values.

The financial manager of the multinational corporation (MNC) is faced with various tax structures, changing exchange rates, barriers to capital flows, and the possibility of financial market segmentation. The manager must be concerned with determining an optimal capital structure as well as identifying the sources of the relevant funds. Likewise, the manager must be concerned not only with funds flows, but also with the risk that the value of these flows will change owing to changing exchange rates. Finally, the manager must be concerned with operating under widely differing governmental philosophies.

The mathematical difficulties encountered when attempting to express the internal rate of return (IRR) of a combination of two or more investments as a weighted algebraic sum of the individual investments' IRRs has been recognized in the financial literature for some time. However, in a recent issue of this journal, Professors Reilly and Wecker (hereafter R-W) [3] apply the well-known mathematical impossibility of expressing the root(s) of a polynomial as an algebraic combination of the roots of related polynomials to question the validity of the weighted cost of capital (kw) concept.

Foreign exchange risk and hence the demand for foreign assets depend on the objective and habitat of investors. The investment objective, in turn, is contingent upon how the consumption basket or its price is defined. If the investor is “domestic” in the sense that he or she spends all income on domestic goods, then the domestic price index should be used in defining the investment objective in real terms, regardless of whether returns are generated at home or abroad. However, for an investor who consumes a mix of foreign and home products, or for multinational firms with extensive operations outside their home countries, some sort of world price reflective of the relative importance of home and foreign goods in their consumption basket is the proper deflator.

We propose a multifactor model in which the spot rate, LIBOR, follows a lognormal process, with a stochastic conditional mean, under the risk-neutral measure. In addition to the spot rate factor, the second factor is related to the premium of the first futures rate over the spot LIBOR. Similarly, the third factor is related to the premium of the second futures rate over the first futures rate. We calibrate the model to the initial term structure of futures rates and to the implied volatilities of interest rate caplets. We then apply the model to price interest rate derivatives such as European and Bermudan-style swaptions, and yieldspread options. The model can be employed to price more complex interest rate derivatives such as path-dependent derivatives or multi-currency-dependent derivatives because of its Markovian property.

We consistently show that in large equity markets, the dividend–price ratio is significantly related to the growth of future dividends. To uncover this relation, we use monthly dividends and a mixed data sampling technique, which allows us to address within-year seasonality. Our approach avoids the use of overlapping observations and at the same time reduces the impact of price volatility on the dividend–price ratio. An empirical analysis using market-level data from the United States, United Kingdom, Canada, and Japan strongly supports the dividend growth predictability hypothesis, suggesting that time aggregation of dividends eliminates significant information.