Returns to scale and asset prices

The q‐theory of investment is proposed to explain firm growth effects, where previous papers identify a negative effect of firm growth, including asset growth, real investment and net share issuance, on future stock returns. This paper uses returns to scale from the production function to test the dynamic q‐theory, which predicts that the firm growth effect is theoretically weaker for firms with decreasing returns to scale (DRS) than for non‐DRS firms. Our empirical results generally support the prediction of dynamic q‐theory. However, we find that the dynamic q‐theory explains little of the value, momentum and ROE effects from the standpoint of returns to scale.     

On the equivalence of the static and dynamic asset allocation problems

A classic dynamic asset allocation problem optimizes the expected final-time utility of wealth, for an individual who can invest in a risky stock and a risk-free bond, trading continuously in time. Recently, several authors considered the corresponding static asset allocation problem in which the individual cannot trade but can invest in options as well as the underlying. The optimal static strategy can never do better than the optimal dynamic one. Surprisingly, however, for some market models the two approaches are equivalent. When this happens the static strategy is clearly preferable, since it avoids any impact of market frictions. This paper examines the question: when, exactly, are the static and dynamic approaches equivalent? We give an easily tested necessary and sufficient condition, and many non-trivial examples. Our analysis assumes that the stock follows a scalar diffusion process, and uses the completeness of the resulting market model. A simple special case is when the drift and volatility depend only on time; then the two approaches are equivalent precisely if (μ (t)? r)/σ²(t) is constant. This is not the Sharpe ratio or the market price of risk, but rather a nondimensional ratio of excess return to squared volatility that arises naturally in portfolio optimization problems.     

Efficient Option Replication in the Presence of Transactions Costs

In the presence of transaction costs, a risk-return trade-off exists between the quality and the cost of a replicating strategy. In that context, I show how to expand the set of all possible time-based strategies through the introduction of a multi-scale class of strategies, which consist in rebalancing different fractions of an option portfolio at different time frequencies. The method, based on time-scale diversification, is to dynamic replication what investment in diversified portfoliosis to static portfolio selection: in a dynamic context, one may enjoy the benefits of diversification by using different time scales in trading the same asset. This revised version was published online in November 2006 with corrections to the Cover Date.     

Dynamic Capital Structure Choice: Theory and Tests

This paper develops a model of dynamic capital structure choice in the presence of recapitalization costs. The theory provides the optimal dynamic recapitalization policy as a function of firm-specific characteristics. We find that even small recapitalization costs lead to wide swings in a firm's debt ratio over time. Rather than static leverage measures, we use the observed debt ratio range of a firm as an empirical measure of capital structure relevance. The results of empirical tests relating firms' debt ratio ranges to firm-specific features strongly support the theoretical model of relevant capital structure choice in a dynamic setting.     

Dynamic regulation of quality

We develop a dynamic regulation model of quality provision where maintenance efforts and quality shocks have a durable impact. When the regulator contracts with a sequence of agents, asymmetric information can lead to overprovision of quality, reflecting a dynamic rent extraction effect. When the regulator contracts with a single agent, the efficiency of their relationship depends on the regulator’s ability to transfer rents across periods. Hiring a single agent with unlimited liability is socially preferable to hiring a sequence of agents, even when no commitment is feasible. By contrast, shorter franchises are socially preferable if the agent has limited liability.     

Dynamic factor long memory volatility

In this paper, we develop a long memory orthogonal factor (LMOF) multivariate volatility model for forecasting the covariance matrix of financial asset returns. We evaluate the LMOF model using the volatility timing framework of Fleming et al. [J. Finance, 2001, 56, 329–352] and compare its performance with that of both a static investment strategy based on the unconditional covariance matrix and a range of dynamic investment strategies based on existing short memory and long memory multivariate conditional volatility models. We show that investors should be willing to pay to switch from the static strategy to a dynamic volatility timing strategy and that, among the dynamic strategies, the LMOF model consistently produces forecasts of the covariance matrix that are economically more useful than those produced by the other multivariate conditional volatility models, both short memory and long memory. Moreover, we show that combining long memory volatility with the factor structure yields better results than employing either long memory volatility or the factor structure alone. The factor structure also significantly reduces transaction costs, thus increasing the feasibility of dynamic volatility timing strategies in practice. Our results are robust to estimation error in expected returns, the choice of risk aversion coefficient, the estimation window length and sub-period analysis.     

An approximate dynamic programming approach to solving dynamic oligopoly models

In this article, we introduce a new method to approximate Markov perfect equilibrium in large‐scale Ericson and Pakes (1995)‐style dynamic oligopoly models that are not amenable to exact solution due to the curse of dimensionality. The method is based on an algorithm that iterates an approximate best response operator using an approximate dynamic programming approach. The method, based on mathematical programming, approximates the value function with a linear combination of basis functions. We provide results that lend theoretical support to our approach. We introduce a rich yet tractable set of basis functions, and test our method on important classes of models. Our results suggest that the approach we propose significantly expands the set of dynamic oligopoly models that can be analyzed computationally.     

Prediction of Individual Bond Prices via a Dynamic Bond Pricing Model: Application to Japanese Government Bond Price Data

In this paper, we propose a dynamic bond pricing model and report the usefulness of our bond pricing model based on analysis of Japanese Government bond price data. We extend the concept of the time dependent Markov (TDM) model proposed by Kariya and Tsuda (Financial Engineering and the Japanese Markets, Kluwer Academic Publishers, Dordrecht, The Netherlands, Vol. 1, pp. 1–20) to a dynamic model, which can obtain information for future bond prices. A main feature of the extended model is that the whole stochastic process of the random cash-flow discount functions of each individual bond has a time series structure. We express the dynamic structure for the models by using a Bayesian state space representation. The state space approach integrates cross-sectional and time series aspects of individual bond prices. From the empirical results, we find useful evidence that our model performs well for the prediction of the patterns of the term structure of the individual bond returns.     

Size effect,methodological issues and ‘risk-to-default’: evidence from the UK stock market

The hedging effectiveness of dynamic strategies is compared with static (traditional) ones using futures contracts for the five leading currencies. The traditional hedging model assumes time invariance in the joint distribution of spot and futures price changes thus leading to a constant optimal hedge ratio (OHR). However, if this time-invariance assumption is violated, time-varying OHRs are appropriate for hedging purposes. A bivariate GARCH model is employed to estimate the joint distribution of spot and futures currency returns and the sequence of dynamic (time-varying) OHRs is constructed based upon the estimated parameters of the conditional covariance matrix. The empirical evidence strongly supports time-varying OHRs but the dynamic model provides superior out-of-sample hedging performance, compared to the static model, only for the Canadian dollar.     

Automobile replacement: a dynamic structural approach

This article specifies and estimates a structural dynamic model of consumer demand for new and used durable goods. Its primary contribution is to provide an explicit estimation procedure for transaction costs. Identification of transaction costs is achieved from the variation in the share of consumers choosing to hold a given car type each period, and from the share of consumers choosing to purchase the same car type that period. Specifically, I estimate a random‐coefficient discrete‐choice model that incorporates a dynamic optimal stopping problem. I apply this model to evaluate the impact of scrappage subsidies on the Italian automobile market.     

Dynamic Agency and the q Theory of Investment

We develop an analytically tractable model integrating dynamic investment theory with dynamic optimal incentive contracting, thereby endogenizing financing constraints. Incentive contracting generates a history‐dependent wedge between marginal and average q, and both vary over time as good (bad) performance relaxes (tightens) financing constraints. Financial slack, not cash flow, is the appropriate proxy for financing constraints. Investment decreases with idiosyncratic risk, and is positively correlated with past profits, past investment, and managerial compensation even with time‐invariant investment opportunities. Optimal contracting involves deferred compensation, possible termination, and compensation that depends on exogenous observable persistent profitability shocks, effectively paying managers for luck.     

Where is the GE? Consumption Dynamics in DSGEs

We offer a partial equilibrium perspective on the behavior of consumption in dynamic stochastic general equilibrium (DSGE) models. We consider a benchmark dynamic general equilibrium model and show that a standard calibration implies that the real interest rate is essentially fixed. One manifestation of this feature is that, with separable preferences, the reaction of consumption to total factor productivity (TFP) shocks is flat: the random‐walk permanent income hypothesis holds almost exactly, pretty much as in a partial equilibrium consumption‐savings problem. These results help explain the prominent role of aggregate demand, and how it is achieved, in modern DSGE analysis.     

Tangent Lévy market models

In this paper, we introduce a new class of models for the time evolution of the prices of call options of all strikes and maturities. We capture the information contained in the option prices in the density of some time-inhomogeneous Lévy measure (an alternative to the implied volatility surface), and we set this static code-book in motion by means of stochastic dynamics of It?’s type in a function space, creating what we call a tangent Lévy model. We then provide the consistency conditions, namely, we show that the call prices produced by a given dynamic code-book (dynamic Lévy density) coincide with the conditional expectations of the respective payoffs if and only if certain restrictions on the dynamics of the code-book are satisfied (including a drift condition à la HJM). We then provide an existence result, which allows us to construct a large class of tangent Lévy models, and describe a specific example for the sake of illustration.     

Swap variance hedging and efficiency: The role of high moments

In this article, we propose a new theoretical approach for developing hedging strategies based on swap variance (SwV). SwV is a generalized risk measure equivalent to a polynomial combination of all moments of a return distribution. Using the S&P 500 index and West Texas Intermediate (WTI) crude oil spot and futures price data, as well as simulations by varying the distribution of asset returns, we investigate the dynamic differences between hedge ratios and portfolio performances based on SwV (with high moments) and variance (without high moments). We find that, on average, the minimizing-SwV hedging suggests more short futures contracts than minimizing-variance hedging; however, when market conditions deteriorate, the minimizing-SwV hedging suggests fewer short positions in futures. The superior posthedge performances of the mean-SwV hedged portfolios over the mean-variance hedged portfolios in highly volatile or extremely calm markets confirm the efficiency of the mean-SwV hedging strategy.     

Managing The Volatility Of Gaap Earnings

Abstract

The adoption of Statement of Financial Accounting Standards No. 97 (SFAS 97) eliminated the “lock-in” concept introduced in SFAS 60. Since many of the actuarial assumptions used in the calculation of the deferred acquisition cost (DAC) asset are difficult to predict over an extended period of time, “dynamic unlocking” was a sensible solution. Although this “dynamic unlocking” keeps the assumptions in line with recent experience, it comes at a cost—increased volatility of GAAP earnings. Some of the causes of this volatility are warranted since it accentuates the effects on earnings due to certain changes in the underlying experience. Other causes of this volatility may be unwarranted because of a misapplication of the principles underlying SFAS 97 and SFAS 120 or the manner in which changes in experience were reflected. In addition, most analysts expect the amortization of deferred acquisition costs to increase when earnings are better than expected. Conversely, analysts expect the amortization of deferred acquisition costs to decrease when earnings are worse than expected. Often the amortization of deferred acquisition costs behaves in a manner contrary to their expectations. This article analyzes what causes this volatility, explains why the amortization can behave contrary to expectations, and suggests several techniques for minimizing these unwarranted results.     

Production targets

We analyze a dynamic model of quantity competition, where firms continuously adjust their quantity targets, but incur convex adjustment costs when they do so. Quantity targets serve as a partial commitment device and, in equilibrium, follow a hump‐shaped pattern. The final equilibrium is more competitive than in the static analog. We then use data on monthly production targets of the Big Three U.S. auto manufacturers and show a similar empirical hump‐shaped dynamic pattern. Taken together, this suggests that strategic considerations may play a role in setting auto production schedules, and that static models may misestimate the industry's competitiveness.     

Advertising dynamics and competitive advantage

Can advertising lead to a sustainable competitive advantage? To answer this question, we propose a dynamic model of advertising competition where firms repeatedly advertise, compete in the product market, and make entry as well as exit decisions. Within this dynamic framework, we study two different models of advertising: in the first model, advertising influences the goodwill consumers extend toward a firm (“goodwill advertising”), whereas in the second model it influences the share of consumers who are aware of the firm (“awareness advertising”). We show that asymmetries may arise and persist under goodwill as well as awareness advertising. The basis for a strategic advantage, however, differs greatly in the two models of advertising. We show that tighter regulation or an outright ban of advertising may have anticompetitive effects and discuss how firms use advertising to deter and accommodate entry and induce exit in a dynamic setting.     

A Lintner Model of Payout and Managerial Rents

We develop a dynamic agency model in which payout, investment, and financing decisions are made by managers who attempt to maximize the rents they take from the firm, subject to a capital market constraint. Managers smooth payout to smooth their flow of rents. Total payout (dividends plus net repurchases) follows Lintner's (1956) target adjustment model. Payout smooths out transitory shocks to current income and adjusts gradually to changes in permanent income. Smoothing is accomplished by borrowing or lending. Payout is not cut back to finance capital investment. Risk aversion causes managers to underinvest, but habit formation mitigates the degree of underinvestment.     

Labor-supply shifts and economic fluctuations

We propose a new VAR identification scheme that distinguishes shifts of and movements along the labor demand schedule to identify labor-supply shocks. According to our VAR analysis of post-war US data, labor-supply shifts account for about 30 percent of the variation in hours and about 15 percent of the output fluctuations at business cycle frequencies. To assess the role of labor-supply shifts in a more structural framework, estimates from a dynamic general equilibrium model with stochastic variation in home production technology are compared to those from the VAR.     

Delegation and dynamic incentives

Using an agency model, we show how delegation, by generating additional private information, improves dynamic incentives under limited commitment. It circumvents ratchet effects and facilitates the revelation of persistent private information through two effects: a play‐hardball effect, which mitigates an efficient agent's ratchet incentive, and a carrot effect which reduces an inefficient agent's take‐the‐money‐and‐run incentive. Although delegation entails a loss of control, it is optimal when uncertainty about operational efficiency is large. Moreover, delegation is more effective with production complementarity. We also consider different modes of commitment to yield insights into optimal organizational boundaries.