It is well known that firms are more likely to issue equity when their market values are high, relative to book and past market values, and to repurchase equity when their market values are low. We document that the resulting effects on capital structure are very persistent. As a consequence, current capital structure is strongly related to historical market values. The results suggest the theory that capital structure is the cumulative outcome of past attempts to time the equity market. IN CORPORATE F INANCE, “equity market timing” refers to the practice of issuing shares at high prices and repurchasing at low prices. The intention is to exploit temporary f luctuations in the cost of equity relative to the cost of other forms of capital. In the efficient and integrated capital markets studied by Modigliani and Miller ~1958!, the costs of different forms of capital do not vary independently, so there is no gain from opportunistically switching between equity and debt. In capital markets that are inefficient or segmented, by contrast, market timing benefits ongoing shareholders at the expense of entering and exiting ones. Managers thus have incentives to time the market if they think it is possible and if they care more about ongoing shareholders. In practice, equity market timing appears to be an important aspect of real corporate financial policy. There is evidence for market timing in four different kinds of studies. First, analyses of actual financing decisions show that firms tend to issue equity instead of debt when market value is high, relative to book value and past market values, and tend to repurchase equity when market value is low. 1 Second, analyses of long-run stock returns fol

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Market Timing and Capital Structure

Modeling the conditional distribution of interest rates as a regime-switching process

In this paper, we explore the features of affine term structure models that are empirically important for explaining the joint distribution of yields on short and long-term interest rate swaps. We begin by showing that the family of N-factor affine models can be classified into N+1 non-nested sub-families of models. For each sub-family, we derive a maximal model with the property that every admissible member of this family is equivalent to or a nested special case of our maximal model. Second, using our classification scheme and maximal models, we show that many of the three-factor models in the literature impose potentially strong over-identifying restrictions on the joint distribution of short- and long-term rates. Third, we compute simulated method-of-moments estimates for several members of one of the four branches of three-factor models, and test the over-identifying restrictions implied by these models. We conclude that many of the extant affine models in the literature fail to describe important features of the distribution of long- and short- term rates. The source of the model misspecification is shown to be overly strong restrictions on the correlations among the state variables. Relaxing these restrictions leads to a model that passes several goodness-of-fit tests over our sample period.

Specification Analysis of Affine Term Structure Models

This paper explores the structural differences and relative goodness-of-fits of affine term structure models ~ATSMs!. Within the family of ATSMs there is a tradeoff between f lexibility in modeling the conditional correlations and volatilities of the risk factors. This trade-off is formalized by our classification of N-factor affine family into N 1 1 non-nested subfamilies of models. Specializing to three-factor ATSMs, our analysis suggests, based on theoretical considerations and empirical evidence, that some subfamilies of ATSMs are better suited than others to explaining historical interest rate behavior. IN SPECIFYING A DYNAMIC TERM STRUCTURE MODEL—one that describes the comovement over time of short- and long-term bond yields—researchers are inevitably confronted with trade-offs between the richness of econometric representations of the state variables and the computational burdens of pricing and estimation. It is perhaps not surprising then that virtually all of the empirical implementations of multifactor term structure models that use time series data on long- and short-term bond yields simultaneously have focused on special cases of “affine” term structure models ~ATSMs! .A n ATSM accommodates time-varying means and volatilities of the state variables through affine specifications of the risk-neutral drift and volatility coefficients. At the same time, ATSMs yield essentially closed-form expressions for zero-coupon-bond prices ~Duffie and Kan ~1996!!, which greatly facilitates pricing and econometric implementation. The focus on ATSMs extends back at least to the pathbreaking studies by Vasicek ~1977! and Cox, Ingersoll, and Ross ~1985!, who presumed that the instantaneous short rate r~t! was an affine function of an N-dimensional state vector Y~t!, r~t! 5 d 0 1 d y ’ Y~t!, and that Y~t! followed Gaussian and square-root diffusions, respectively. More recently, researchers have explored formulations of ATSMs that extend the one-factor Markov represen

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Forward exchange rate unbiasedness is rejected in tests from the current floating exchange rate era. This paper surveys advances in this area since the publication of Hodrick's (1987) survey. It documents that the change in the future exchange rate is generally negatively related to the forward discount. Properties of the expected forward forecast error are reviewed. Issues such as the relation of uncovered interest parity to real interest parity, and the implications of uncovered interest parity for cointegration of various quantities are discussed. The modeling and testing for risk premiums is surveyed. Included in this area are tests of the consumption CAPM, tests of the latent variable model, and portfolio-balance models of risk premiums. General equilibrium models of the risk premium are examined and their empirical implications explored. The survey does not cover the important areas of learning and peso problems, tests of rational expectations based on survey data, or the models of irrational expectations and speculative bubbles.

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w5312.pdf?abstractid=225376&mirid=1

The Forward Discount Anomaly and the Risk Premium: A Survey of Recent Evidence

This paper introduces, analyzes, and values a new form of contingent convertible (CoCo), a Call Option Enhanced Reverse Convertible (COERC). Issued as a bond, it converts to new shareholders’ equity if a bank’s market value of capital falls below a pre-specified trigger. The COERC avoids the problems with market based triggers such as “death spirals” as a result of manipulation or panic. A bank that issues COERCs also has a smaller incentive to choose investments that are subject to large losses. Furthermore, COERCs reduce the problem of “debt overhang,” the disincentive to replenish shareholders’ equity following a decline. The low risk of COERCS should increase their appeal to risk-averse bondholders.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1785380_code58387.pdf?abstractid=1785380

Contingent Capital: The Case for COERCs

Varying-parameter estimation techniques based on recursive application of the Kalman filter are used to improve the predictive performance of a class of monetary exchange rate models. I find that allowing estimated parameters to vary over time enhances the models' forecasting performance for the dollar–pound, dollar–mark, and dollar–yen exchange rates. Contrary to earlier results in the literature, ex-post forecasts for the dollar-mark rate compare favorably with those obtained from the naive random walk forecasting rule.

Time-Varying Parameters and the Out-of-Sample Forecasting Performance of Structural Exchange Rate Models

Varying-parameter estimation techniques based on recursive application of the Kalman filter are used to improve the predictive performance of a class of monetary exchange rate models. I find that allowing estimated parameters to vary over time enhances the models' forecasting per- formance for the dollar-pound, dollar-mark, and dollar-yen exchange rates. Contrary to earlier results in the literature, ex-post forecasts for the dollar-mark rate compare favorably with those obtained from the naive random walk forecasting rule. This article deals with the out-of-sample forecasting performance of a class of empirical models of exchange rate determination. Although the literature has been flooded with in-sample studies of empirical exchange rate models since the breakdown of the Bretton Woods fixed-parity system in the early 1970s, systematic studies of the forecasting performance of structural or reduced- form models are relatively scarce. Meese and Rogoff (1983a) studied the forecasting performance of several important monetary models. Although in-sample studies of these models usually show quite satisfactory fits, Meese and Rogoff's out-of-sam- ple results were not very encouraging: the structural models failed to improve on the simple random walk forecasting rule, even though the models' forecasts were based on actual, realized values of future explanatory variables. A number of potential explanations for the unimpressive out-of-sample forecasting performance of the models have been offered in the literature (Isard 1983; Meese and Rogoff 1983a,b; Saidi 1983). In this article I take up the possibility of parameter variation over time. The forecasting performance of a class of monetary exchange rate models is studied em- ploying a methodology that allows for parameter vari- ation. A number of different factors could lead to parameter instability. Some important ones are the following:

Time-Varying Parameters and the Out-of-Sample Forecasting

In this paper, we implement a methodology to identify and measure premia in the pricing of forward foreign exchange that involves application of signal-extraction techniques from the engineering literature. Diagnostic tests indicate that these methods are quite successful in capturing the essence of the time-series properties of premium terms. The estimated premium models indicate that premia show a certain degree of persistence over time and that more than half the variance in the forecast error that results from the use of current forward rates as predictors of future spot rates is accounted for by variation in premium terms. The methodology can be applied straightforwardly to the measurement of unobservables in other financial markets. THERE EXISTS A GROWING body of empirical research on premia in the pricing of forward foreign exchange. Conditional on the hypothesis that the foreign exchange market is efficient or rational, the existence of time-varying premia has been documented in the literature by Fama [6], Hansen and Hodrick [10, 11], Hodrick and Srivastava [15, 16], Hsieh [171, and Korajczyk [20]. Frankel [9] fails to identify such premia, and Domowitz and Hakkio [51 obtain different results for different currencies.

Forward Foreign Exchange Rates, Expected Spot Rates, and Premia: A Signal-Extraction Approach

In this article we reconsider the Foot and Frankel results on the sources of forward discount bias. We question the economic validity of some estimation restrictions that they impose and, thus, are led to question some of their results. We employ a new exchange rate survey database that includes European Monetary System currencies and use univariate and pooling estimation techniques that impose fewer restrictions than those of Froot and Frankel to test our hypotheses. We find that the bias in the forward discount to BOTH (author emphasis) the failure of rational expectations and the existence of time-varying risk premia.

Christian C. P. Wolff

Papers

Contingent Capital: The Case for COERCs

Time-Varying Parameters and the Out-of-Sample Forecasting Performance of Structural Exchange Rate Models

Time-Varying Parameters and the Out-of-Sample Forecasting

Forward Foreign Exchange Rates, Expected Spot Rates, and Premia: A Signal-Extraction Approach

On the Biasedness of Forward Foreign Exchange Rates: Irrationality or Risk Premia?