Asymmetric loss functions and the rationality of expected stock returns

We combine the innovative approaches of Elliott, Komunjer, and Timmermann (2005) and Patton and Timmermann (2007) with a block bootstrap to analyze whether asymmetric loss functions can rationalize the S&P 500 return expectations of individual forecasters from the Livingston Surveys. Although the rationality of these forecasts has often been rejected, earlier studies have relied on the assumption that positive and negative forecast errors of identical magnitudes are equally important to forecasters. Allowing for homogenous asymmetric loss, our evidence still strongly rejects forecast rationality. However, if we allow for variation in asymmetric loss functions across forecasters, not only do we find significant differences in preferences, but also we can often no longer reject forecast rationality. Our conclusions raise serious doubts about the homogeneous expectations assumption often made in asset pricing, portfolio construction and corporate finance models.     

The term structure of volatility predictability

Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities. Still, little is known about the accuracy of volatility forecasts and the horizon of volatility predictability. This paper aims to fill these gaps in the literature. We begin this paper by introducing the notions of spot and forward predicted volatilities and propose describing the term structure of volatility predictability by spot and forward forecast accuracy curves. Then, we perform a comprehensive study of the term structure of volatility predictability in stock and foreign exchange markets. Our results quantify the volatility forecast accuracy across horizons in two major markets and suggest that the horizon of volatility predictability is significantly longer than that reported in earlier studies. Nevertheless, the aforesaid horizon is observed to be much shorter than the longest maturity of traded derivative contracts.     

The affine arbitrage-free class of Nelson-Siegel term structure models

We derive the class of affine arbitrage-free dynamic term structure models that approximate the widely used Nelson-Siegel yield curve specification. These arbitrage-free Nelson-Siegel (AFNS) models can be expressed as slightly restricted versions of the canonical representation of the three-factor affine arbitrage-free model. Imposing the Nelson-Siegel structure on the canonical model greatly facilitates estimation and can improve predictive performance. In the future, AFNS models appear likely to be a useful workhorse representation for term structure research.     

Excessive risk taking and the maturity structure of debt

This paper analyses the effect of short term debt on equityholders' risk taking decisions. We show that if short term debt limits the expropriation of debtholders, it also implies a lower leverage, which prevents the firm from increasing tax shields. We then examine the incentive of equityholders to increase the firm risk when debtholders hold the option to swap a perpetual coupon bond with short term debt. We find that this option mitigates equityholders' risk shifting incentives. Compared to standard short term debt, this restructuring option deters debtholders expropriation, it increases leverage and it reduces the loss in tax shields due to asset substitution.     

Assessing and valuing the nonlinear structure of hedge fund returns

Several studies have put forward that hedge fund returns exhibit a nonlinear relationship with equity market returns, captured either through constructed portfolios of traded options or piece‐wise linear regressions. This paper provides a statistical methodology to unveil such nonlinear features with respect to returns on benchmark risk portfolios. We estimate a portfolio of options that best approximates the returns of a given hedge fund, account for this search in the statistical testing of the nonlinearity, and provide a reliable test for a positive valuation of the fund. We find that not all fund categories exhibit significant nonlinearities, and that only a few strategies provide significant value to investors. Our methodology helps identify individual funds that provide value in an otherwise poorly performing category. Copyright © 2010 John Wiley & Sons, Ltd.     

The expected life of mobile homes

This article reports empirical evidence on the expected life of mobile homes. Three sources, using three different definitions of loss, are drawn upon: published studies, proprietary data from Foremost Insurance Company and Census data. The Census data are analyzed using logit analysis, and a life table for mobile homes is produced. Based on these analyses, implications are drawn for policy-makers and consumers, for the insurance, financing and manufactured housing industries, and for researchers.     

The term structure of cross-sectional dispersion of expectations in a Learning-to-Forecast Experiment

In this paper, we present the results of a Learning-to-Forecast Experiment (LtFE) where we eliciting short- as well as long-run expectations regarding the future price dynamics in markets with positive and negative expectations feedback. Comparing our results on short-run expectations with the LtFE literature, we prove that eliciting long-run expectations has no impact on the price dynamics nor on short-run expectations formation. In particular, we confirm that the Rational Expectation Equilibrium (REE) is a good benchmark only for the markets with negative feedback. Interestingly, our data show that while the term structure of the cross-sectional dispersion of expectations is convex in positive feedback markets, it is concave in negative feedback markets. Differences in the slope of the term structure stem from diverse degrees of uncertainty regarding the evolution of prices in the two feedback systems: (1) in the negative feedback system, the convergence of the price to the REE reflects a tendency for coordination of long-run expectations around the fundamental value; (2) conversely, oscillatory price dynamics observed in the positive feedback system is responsible for the diverging pattern of long-run expectations. Finally, we propose a new measure of heterogeneity of expectations based on the scaling of the dispersion of expectations over the forecasting horizon.

     

Estimation of affine term structure models with spanned or unspanned stochastic volatility

We develop new procedures for maximum likelihood estimation of affine term structure models with spanned or unspanned stochastic volatility. Our approach uses linear regression to reduce the dimension of the numerical optimization problem yet it produces the same estimator as maximizing the likelihood. It improves the numerical behavior of estimation by eliminating parameters from the objective function that cause problems for conventional methods. We find that spanned models capture the cross-section of yields well but not volatility while unspanned models fit volatility at the expense of fitting the cross-section.     

Forecasting the term structure of government bond yields

Despite powerful advances in yield curve modeling in the last 20 years, comparatively little attention has been paid to the key practical problem of forecasting the yield curve. In this paper we do so. We use neither the no-arbitrage approach nor the equilibrium approach. Instead, we use variations on the Nelson–Siegel exponential components framework to model the entire yield curve, period-by-period, as a three-dimensional parameter evolving dynamically. We show that the three time-varying parameters may be interpreted as factors corresponding to level, slope and curvature, and that they may be estimated with high efficiency. We propose and estimate autoregressive models for the factors, and we show that our models are consistent with a variety of stylized facts regarding the yield curve. We use our models to produce term-structure forecasts at both short and long horizons, with encouraging results. In particular, our forecasts appear much more accurate at long horizons than various standard benchmark forecasts.     

Tests of international CAPM with time-varying covariances

We perform maximum-likelihood estimation of a model of international asset pricing based on CAPM. We test the restrictions imposed by CAPM against a more general asset pricing model. The ‘betas’ in our CAPM vary over time as the supplies of assets change and as the conditional covariances or returns on those assets change. We let the covariances change over time as a function of macroeconomic data, and an alternative model allows the covariances to follow a multivariate ARCH process. We also can identify a modified CAPM model with measurement error. We find that the estimated CAPM performs much better when variances are not constant over time. Nonetheless, CAPM is rejected in favour of the lessrestricted model of asset pricing.     

The rational expectation dynamics of a model for the term structure and monetary policy

Decisions in Economics and Finance - We describe in this paper a variance reduction method based on control variates. The technique uses the fact that, if all stochastic assets but one are replaced...     

The joint continuity of the expected payoff functions

Glicksberg [Glicksberg, I.L., 1952. A further generalization of the Kakutani fixed point theorem, with applications to Nash equilibrium points. In: Proceedings of the American Mathematical Society 3, pp. 170–174] generalized the Kakutani fixed point theorem to the setting of locally convex spaces and used it to prove that every k-person strategic game with action sets convex compact subsets of locally convex spaces and continuous payoff functions has a Nash equilibrium. He subsequently used this result to establish the following fundamental theorem of game theory: Every k-person strategic game with action sets metrizable compact topological spaces and continuous payoff functions has a mixed strategies equilibrium. However, in his proof of the latter result, Glicksberg did not show that the expected payoff functions were jointly continuous, something that was required for the existence of a mixed strategies equilibrium.     

The limiting distribution of extremal exchange rate returns

Several nonnested fat-tailed distributions have been advocated for modelling exchange rate returns. Instead of directly estimating these nonnested distributions we investigate the extremal distribution of the returns. The advantage is that the parameter which characterizes the amount of tail fatness can be estimated without maintaining a specific distribution, and hence enables one to test hypotheses. The parameter of the limit law is estimated by employing nonparametric procedures based on order statistics. The appropriateness of these procedures is assessed. Given this estimate one can derive bounds on the returns for very low probabilities on an excess. Such information is useful in evaluating the volatility of exchange rates.     

Identification and estimation of Gaussian affine term structure models

This paper develops new results for identification and estimation of Gaussian affine term structure models. We establish that three popular canonical representations are unidentified, and demonstrate how unidentified regions can complicate numerical optimization. A separate contribution of the paper is the proposal of minimum-chi-square estimation as an alternative to MLE. We show that, although it is asymptotically equivalent to MLE, it can be much easier to compute. In some cases, MCSE allows researchers to recognize with certainty whether a given estimate represents a global maximum of the likelihood function and makes feasible the computation of small-sample standard errors.     

Adaptive estimation of autoregressive models with time-varying variances

Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution or combinations of the two. This paper develops kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. Simulations show that efficiency gains are achieved by the adaptive procedure.     

The robustness of calendar anomalies in daily stock returns

This paper investigates the robustness of the major calendar anomalies in stock returns with respect to the choice of return measure, estimation procedure, and time period. For daily returns from 1972 to 1994, the size and statistical significance of the anomalies differ more across return measure than across estimation procedure. For the returns on small-firm stocks, there is robust evidence of weekend effects, pre-holiday effects, and January effects. For the returns on large-firm stocks, calendar anomalies are weaker and essentially disappear after 1986.     

Evolving macroeconomic perceptions and the term structure of interest rates

We explore the role of evolving beliefs regarding the structure of the macroeconomy in improving our understanding of the term structure of interest rates within the context of a simple macro-finance model. Using quarterly vintages of real-time data and survey forecasts for the United States over the past 40 years, we show that a recursively estimated VAR on real GDP growth, inflation and the nominal short-term interest rate generates predictions that are more consistent with survey forecasts than a benchmark fixed-coefficient counterpart. We then estimate a simple term structure model under the assumption that investor risk attitude is driven by near-term expectations of the three state variables. When we allow for evolving beliefs about the macroeconomy, the resulting term structure model provides a better fit to the cross section of yields than the benchmark model, especially at longer maturities, and exhibits better performance in out-of-sample predictions of future yield movements.     

Testing affine term structure models in case of transaction costs

We empirically analyze the impact of transaction costs on the performance of essentially affine interest rate models. We test the implied Euler restrictions and calculate the specification error bound of Hansen and Jagannathan to measure model misspecification. Using both short-maturity and long-maturity bond return data we find, under the assumption of frictionless markets, strong evidence of misspecification of affine yield models with up to three factors. Next, we incorporate transaction costs in our tests. The results show that the evidence of misspecification of essentially affine yield models disappears in case of monthly holding periods at market size transaction costs.