This paper is an initial attempt to bridge the gap that presently exists between the theoretical and empirical literature on the instability of equity beta. We focus on two factors from the joint Option Pricing Model/Capital Asset Pricing Model framework—leverage and unexpected changes in the risk-free rate—which are hypothesized to influence the instability of equity beta across firms and over time. Using alternative variable parameter regression models, we find that highly leveraged firms exhibit greater equity beta instability than firms with lower leverage. Over time, equity betas exhibit greater instability during periods of large unexpected changes in the risk-free rate when compared to periods with small unexpected changes in the risk-free rate.

A recent study by Larner [11] concluded that the managerial revolution analyzed earlier by Berle and Means [4] was close to completion because a large percentage of the nation's 200 largest nonfinancial corporations was controlled by nonowner managers. This finding makes more significant any substantial differences in financial performance that may exist between owner-controlled and manager-controlled firms, and it increases the potential impact of numerous related theories; for example, see Berle [3], Donaldson [5], Gordon [6, 7 ], Mason [14], Monsen and Downs [16], Williamson [21], and others.

The existence of seasonality in security rates of return has implications for both the study of market efficiency and tests involving return models. The existence of seasonal asset returns may be an indicator of market inefficiencies. In an efficient market, investor arbitrage should remove any excess seasonal return an asset receives over a comparable asset of equal risk. The presence of seasonal returns, however, does not necessitate market inefficiency. For example, an expected seasonal return may exist in an efficient market simply because of anticipated seasonal patterns embedded in its underlying determinants. Tax regulations, government monetary policy, seasonal information lags, or risk adjustments have all been advanced as determinants of seasonal movements in return. No matter what the basis for return seasonality or the extent of market efficiency, if seasonality in asset returns exists, then these returns do not follow a strict stationary process within the year. Statistical models analyzing asset returns may use this information to improve model specification. For instance, Kinney and Rozeff [16] have shown that large efficiency gains in estimating portfolio betas can be achieved using time stratified estimates which explicitly incorporate seasonality in 4 stock returns.

The leading explanation for the post-issue long-run stock return underperformace of seasoned equity offering firms is that investors have optimistic expectations regarding future earnings and the underperformance occures as these expectations are corrected over time. To directly test this hypothessis, we examine investors' reaction to quarterly earnings announcements over a five-year period following the offering for a large sample of seasoned equity issuing firms. In general, our evidence suggests that investorsare not disappointed by earnings announcements that follow seasoned equity offerings. This result is not sensitive to widening the windown over which earnings announcement returns are computed. This result also holds true for subsets of equity issuing firms. The choice fo these three subsets is predicated by extant evidence that these firms are likely to convey relatively more unfavorable information throung their earnings announcements. Overall, our findings are inconsistent with the optimistic expectations hypotgesis.

Pricing models for American call and put options on futures contracts are derived herein. These models are used to investigate the efficiency of the market for options on Standard & Poor 500 and German Mark futures. The evidence presented here indicates that market prices for these options deviate substantially from their corresponding model prices. In addition, it is shown that a hedging strategy originated at prices that indicate a deviation of market from model is successful in translating the observed mispricing into excess profits after transactions costs. However, these net profits are eliminated if the origination of the strategy is delayed by one trade, or if bid-ask spreads are accounted for.

This paper derives and tests a new linear programming (LP) approach to bond portfolio management. The model elicits possible tax-clientele effects in the pricing of U.S. Government coupon bonds and simultaneously derives the optimal tax-specific bond portfolio. Analytically, the model derives these results by exploiting, for a given tax bracket, the price differential of an after-tax stream of cash flows. It accomplishes this objective by purchasing at the ask price “underpriced” bonds (for the specific tax bracket), while simultaneously selling at the bid price “overpriced” bonds. The model requires that the net cash flow, inclusive of purchased and sold bonds, be nonnegative at all future dates; the problem's formulation standardizes the position taken in each bond to a maximum of one unit. One of the model's appealing features is the parsimonious number of required calculations: only one LP program need be run per tax bracket. In addition to obtaining an “optimally” chosen tax-specific bond portfolio, the model also measures the after-tax term structure of spot U.S. Government interest rates for both tax-exempt and taxable investors. Finally, the superior monthly holding-period rates of return on the optimal taxspecific bond portfolio demonstrate an important property of the model's output.

We document that heightened public attention to gender equality is associated with an increase in board gender diversity. Improvements in diversity are more pronounced in firms with a corporate culture that is already sympathetic to gender equality. When public attention to gender equality increases, firms reach out to a larger pool of women, such as women without industry experience or outside their network, but female director appointments do not appear to be dilutive of the board’s skills. Instead, we observe less reliance on connections for director appointments and a decrease in the propensity to appoint connected men.

In an earlier paper [1] a model of securities markets was introduced which implies that the ratio of transaction volume to price change is greater for transactions on which price rises than for those on which price falls. Examination of individual transactions data for a sample of corporate bonds showed that price changes and transaction volumes for those securities appears to behave in a manner consistent with the theory. However, the paper raised the question of whether the same is true for stocks. The positive dependence on share price of broker commissions for stocks could easily eliminate, or even reverse the sign of, the predicted positive difference between the absolute values of slopes of buyers' and sellers' reservation demand functions; and it is this difference which leads the model to predict the inequality of the ratios of volume to price change on upticks and downticks. This note records the results of tests of the model with stock data, using volumes and price changes pertaining both to individual transactions and to trading days. The tests indicate that the ratios of volume to price change exhibit the predicted relationship, when one of the two possible measures of volume is employed.

In the capital structure literature, speed of adjustment (SOA) estimates are similar whether book or market leverage is used. This robustness is suspect, given the survey evidence that firms target their book leverage and the empirical evidence that they don’t issue securities to offset market leverage changes caused by stock price changes. We show that existing market SOA estimates are substantially upward biased due to the passive influence of stock price fluctuations. Controlling for this bias, the SOA estimate is 16% for book leverage and 10% for market leverage, implying that the trade-off theory is less important than previously thought.

Numerous studies in recent years have emphasized the importance of accounting properly for abandoment value in capital budgeting (see [1], [4], [7], [10], and [11]). For a variety of reasons, a project need be neither physically exhausted nor have negative cash flows to be abandoned. Robichek and Van Home [10] suggested that a project should be abandoned in any period in which the present value of future cash flows does not exceed its abandonment value. In a modification of this rule, Dyl and Long [4] proposed that the firm give consideration to all possible future abandonment opportunities. They argued that abandonment need not occur at the earliest possible date that the abandonment condition is satisfied, but rather at the date that yields the highest NPV over all future abandonment possibilities. A generalization of these models was offered by Bonini [1], who developed a dynamic programming model to analyze investment projects with abandonment possibilities and uncertain cash flows. More recently, Gaumnitz and Emery [7] compared the abandonment decision to the like-for-like replacement decision and noted that the correct model for a particular case depends on the suitability of the assumptions.

Received monetary theory supports the existence of a strong relationship between monetary activity and stock prices. Following the work of Friedman and Schwartz [8], relating money supply to aggregate economic activity, some researchers have examined the more specific connection between changes in the rate of growth of money supply and associated movements in stock prices (see [6], [10], [11], [14], [17], [18], [19], [20], [22], and [28]). These studies use a variety of monetary aggregate measures to functionally relate the level of stock market indices to contemporaneous and lagged monetary growth rates. In general, the findings indicate a direct relationship between money supply and stock returns.

The National Association of Security Dealers alleges that professional-trader use of the Small Order Execution System (SOES) causes greater security price volatility. We document bidirectional Granger causality between a proxy for professional SOES trading (the frequency of maximum-sized SOES trades) and a measure of stock price volatility. We find that high levels of volatility precede high levels of maximum-sized SOES trades, suggesting that volatility causes more frequent large SOES trades. Likewise, over a one-minute time interval, high levels of maximum-sized SOES trades cause high volatility. Over longer periods, however, intense maximum-sized SOES trading causes lower volatility. Interpreted in conjunction with Harris and Schultz (1997), these results suggest that high levels of maximum-sized SOES trades lead to more efficient price discovery. In light of these results, we believe that efforts to eliminate SOES based on volatility considerations are unwarranted.

We construct a unique data set that includes all reported institutional block trades on the London Stock Exchange and analyze the market reaction to buy and sell trades. We find that the type of investors behind the trade and the combination of the trade's size and the trader's resulting level of ownership are the major determinants of the information effects and the asymmetry between price impacts of buy and sell trades. In particular, large trades undertaken by fund managers, the most active investors in our sample, have strong information content, while, for the remaining trades, we report limited support for the information and the price impact asymmetry hypotheses. These results hold even after accounting for trade complexity and volatility effects in the regressions.

This paper examines the stationarity of beta coefficients, especially in regard to recent, major stock market trends. In addition to the usual correlation tests for stationarity, this paper describes a more direct method for testing the stationarity of portfolio betas. The method involves the use of paired t-tests which show separately the degree of stationarity for each portfolio beta. In the process of testing for stationarity, the portfolio betas also are adjusted for measurement error using a formulation suggested by Blume [3].

In a recent paper Joy and Porter [4] used the concept of stochastic dominance to address the question of whether or not mutual funds outperform the Dow Jones Industrial Average (DJIA). Since that time Meyer [5] has proven a theorem in the area of stochastic dominance which allows one to make further application of stochastic dominance to this question. The major purpose of this paper is to demonstrate the power and relevance of the recently developed stochastic dominance theorem in ordering investments for groups of investors. In doing so, some evidence is presented concerning mutual funds and the DJIA.

The properties and characteristics of financial ratios have received considerable attention in recent years with interest primarily focused on determining the predictive ability of financial ratios and related financial data. Principal areas of investigation have included the prediction of corporate bond ratings [13, 20, 23, 34], and the anticipation of financial impairment [1, 2, 3, 5, 6, 7, 18, 19, 29, 32, 33, 35]. Related studies have examined the characteristics of merged firms [25, 28], the differencesin financial ratio averages among industries [9, 10], whether firms seek to adjust their financial ratios toward industry averages [15], the relationship between accounting-determined and market-determined risk measures [4, 8, 24], and the influence of financial ratios on analysts' judgments about impending bankruptcy [14, 17]. The general conclusion to emerge from these various research efforts is that a number of financial ratios have predictive and descriptive utility when properly employed.

We examine two hypotheses to explain stock mispricing: i) the money illusion hypothesis (Modigliani and Cohn (1979)) and ii) the resale option hypothesis (Scheinkman and Xiong (2003)). We find that the money illusion hypothesis may explain the level, but not the volatility, of mispricing in the U.S. market. In contrast, the stock resale option hypothesis, which stems from heterogeneous beliefs about future dividend growth rates and short-sale constraints, can explain both the level and the volatility of mispricing. The evidence suggests that while the two hypotheses complement each other in explaining the level of mispricing, the resale option hypothesis provides a more coherent explanation for asset price bubbles, in which extraordinarily high price levels are often accompanied by excessive volatility and frenzied trading.

This paper argues that inferring long-horizon asset return predictability from the properties of vector autoregressive (VAR) models on relatively short spans of data is potentially unreliable. We illustrate the problems that can arise by reexamining the findings of Bekaert and Hodrick(1992), who detected evidence of in-sample predictability in international equity and foreign exchange markets using VAR methodology for a variety of countries from 1981–1989. The VAR predictions are significantly biased in most out-of-sample forecasts and are conclusively outperformed by a simple benchmark model at horizons of up to six months. This remains true even after corrections for small sample bias and the introduction Bayesian parameter restrictions. A Monte Carlo analysis indicates that the data are unlikely to have been generated by a stable VAR. This conclusion is supported by an examination of structural break statistics. We show that implied long-horizon statistics calculated from the VAR parameter estimates are very unreliable.

The forward premium anomaly (exchange rate changes are negatively related to interest rate differentials) is one of the most robust puzzles in financial economics. We recast the underlying parity relation in terms of lagged forward interest rate differentials, documenting a reversal of the anomalous sign on the coefficient in the traditional specification. We show that this novel evidence is consistent with recent empirical models of exchange rates that imply exchange rate changes depend on two key variables: the interest rate differential and the magnitude of the deviation of the current exchange rate from that implied by purchasing power parity.

In this article, we use volatility surface data from options contracts to document a strong, robust, and positive cross-sectional relation between risk-neutral skewness (RNS) and subsequent stock returns. The differential return between high- and low-RNS stocks amounts to 0.17% per week. Preannouncement RNS is positively related to earnings announcement returns, and the positive RNS–return relation is more pronounced for other nonscheduled news releases. This suggests that it is informed trading that drives the positive relation between RNS and subsequent stock returns. We also find that RNS contains incremental information beyond trading signals captured by option-implied volatility and volume.