Knowledge that Transforms

Ex‐dividend day returns vary over time. The ex‐day returns of high‐yield stocks are persistently positive for some time periods and negative for others; in contrast, ex‐day returns of low‐yield stocks are always positive and less variable. We are unable to explain the variation with changes in the tax code, but we do find a strong effect for the introduction of negotiated commissions. We find evidence that corporate dividend capturing is affecting ex‐day returns and confirm the findings of Gordon and Bradford (1980) that the price of dividends is countercyclical.

This article presents a procedure for evaluating collateralized mortgage obligation (CMO) tranches. The solution procedure is in the spirit of a dynamic programming problem in which an individual mortgagor's decision to prepay is the feedback control variable―the mortgagor seeks to minimize the value of the mortgage subject to refinancing costs. We employ a two‐step procedure to solve this dynamic programming problem. The first step uses an implicit finite difference backward solution procedure to determine the “optimal” prepayment boundary for a class of mortgagors, each of whom confronts the same proportional refinancing cost. This step is repeated for several different classes of mortgagors that differ in the level of refinancing costs that they confront. The outcome of this first step is a series of prepayment boundaries―one set of boundaries for each level of refinancing costs (i.e., one set of boundaries for each refinancing cost category of mortgagors). In the second step, the prepayment boundaries determined in the first step are used in conjunction with Monte Carlo simulation to value the CMO tranches. The essence of the second step is that when the simulated interest rate hits the boundary for a particular class, it triggers a prepayment scenario for that class of mortgagors. We conduct extensive sensitivity analysis to determine the robustness of this approach (and our solution procedure) to alternative single‐factor models of the term structure of interest rates and to alternative specifications of the distribution of refinancing cost levels confronted by mortgagors. The sensitivity analysis indicates that CMO tranche valuation is not particularly sensitive to alternative models of the term structure so long as the models are consistent with the current yield curve, but, even when alternative specifications of the refinancing cost categories generate nearly identical values for the collateral underlying the CMO (i.e., the generic mortgage‐backed securities), the resulting tranche values can differ widely between the two specifications. The results point out the importance of accurate estimation of the distribution of refinancing costs when the rational valuation model is used for the analysis of CMO tranches.

This article tests for the relations between trading volume and subsequent returns patterns in individual securities' short-horizon returns that are suggested by such articles as Blume, Easley, and O'Hara (1994) and Campbell, Grossman, and Wang (1993). Using a variant of Lehmann's (1990) contrarian trading strategy, we find strong evidence of a relation between trading activity and subsequent autocovariances in weekly returns. Specifically, high-transaction securities experience price reversals, while the returns of low-transactions securities are positively autocovarying. Overall, information on trading activity appears to be an important predictor of the returns of individual securities.

This article shows that some of the wealth gains from financial decisions involving changes in security form occur on predictable ex dates. For a sample of 113 spinoffs during 1964 to 90, we document an average excess return of 3.0 percent on ex dates, roughly the same magnitude as the average announcement‐date return. We conjecture that the spinoff ex‐date return arises because the parent and subsidiary stocks attract different investors who prefer to buy the separated shares after the ex date. We also document that, on average, the target shareholders in stock‐for‐stock mergers earn an excess return of 1.5 percent on merger ex dates.

A new empirical model for intertemporal capital asset pricing is presented that allows both time‐varying risk premia and betas where the latter are identified from the dynamics of the conditional covariance of returns. The model is more successful in explaining the predictable variations in excess returns when the returns on the stock market and corporate bonds are included as risk factors than when the stock market is the single factor. Although changes in the covariance of returns induce variations in the betas, most of the predictable movements in returns are attributed to changes in the risk premia.

The trading mechanism for equities on the Tokyo Stock Exchange (TSE) stands in sharp contrast to the primary mechanisms used to trade stocks in the United States. In the United States, exchange‐designated specialists have affirmative obligations to provide continuous liquidity to the market. Specialists offer simultaneous and tight quotes to both buy and sell and supply sufficient liquidity to limit the magnitude of price changes between consecutive transactions. In contradistinction, the TSE has no exchange‐designated liquidity suppliers. Instead, liquidity is provided through a public limit order book, and liquidity is organized through restrictions on maximum price changes between trades that serve to slow down trading. In this article, we examine the efficacy of the TSE's trading mechanisms at providing liquidity. Our analysis is based on a complete record of transactions and best‐bid and best‐offer quotes for most stocks in the First Section of the TSE over a period of 26 months. We study the size of the bid‐ask spread and its cross‐sectional and intertemporal stability; intertemporal patterns in returns, volatility, volume, trade size, and the frequency of trades; and market depth based on the response of quotes to trades and the frequency of trading halts and warning quotes.