Time-varying Alpha Research Articles

Improved inference for fund alphas using high-dimensional cross-sectional tests

Abstract The traditional fund-by-fund alpha inference suffers from various econometric problems (e.g., cross-sectional independence assumption, lack of power, time-invariant coefficient assumption, multiple-hypothesis-testing). Recognizing the panel nature of fund industries, we tailor four high-dimensional cross-sectional tests to shed light into both the zero-alpha hypothesis and ratio of non-zero alphas. Particularly, we augment Gagliardini et al. (2016) with a time-varying alpha estimator. Our results reject the zero-alpha joint hypothesis as the statistical significance of alphas is too high to be explained by luck. After controlling for luck, our empirical studies show that the power enhancement helps to identify a large portion of significant fund alphas, which cannot be achieved using the usual Wald test. Meanwhile, the time-varying approach shows that fund alphas diverge during the late 2000s Global Financial Crisis, which cannot be observed using the time-invariant model. Overall, relative to the literature, we draw a more accurate and complete picture, and provide several powerful tools for future research.

Disrupted Neural Synchrony Mediates the Relationship between White Matter Integrity and Cognitive Performance in Older Adults.

Our main goal was to determine the influence of white matter integrity on the dynamic coupling between brain regions and the individual variability of cognitive performance in older adults. Electroencephalography was recorded while participants performed a task specifically designed to engage working memory and inhibitory processes, and the associations among functional activity, structural integrity, and cognitive performance were assessed. We found that the association between white matter microstructural integrity and cognitive functioning with aging is mediated by time-varying alpha and gamma phase-locking value. Specifically, better preservation of the inferior fronto-occipital fasciculus in older individuals drives faster task-related modulations of alpha and gamma long-range phase-locking value between the inferior frontal gyrus and occipital lobe and lower local phase-amplitude coupling in occipital lobes, which in turn drives better cognitive control performance. Our results help delineate the role of individual variability of white matter microstructure in dynamic synchrony and cognitive performance during normal aging.

Asset pricing model uncertainty

Abstract This paper provides a unified calendar-time portfolio methodology for assessing whether returns following an event are abnormal which efficiently handles asset pricing model uncertainty and allows for time-varying alpha and factor exposures. The approach disciplines researchers’ use of asset pricing factors and assigns a probability measure to the appropriateness of (dynamically) selecting a single model that best approximates the true factor structure or whether model averaging across an asset pricing universe is desired. It is applied to the long-horizon effect of dividend initiations and resumptions in the 1980 to 2015 period. Resulting post-announcement conditional abnormal returns are generally significant, statistically and economically, which contrasts recent evidence, and exhibits a break in mean from positive until the mid-1990s and negative onwards. We document substantial time-variation in the dimensionality and composition of the factor structure in expected returns, which goes beyond what captured by conditional versions of the CAPM and Fama–French specifications. This also generalizes to a large panel of 202 characteristics-sorted portfolios.

Examining the dynamics of illiquidity risks within the phases of the business cycle

The Fama-French (FF) five-factor model is cast into a dynamic setting to capture the impact of illiquidity over the phases of the business cycle on the returns of the passive FF twelve sector portfolios. We use two dynamic approaches, Kalman filtering and a recursive/rolling robust instrumental variables (IV) algorithm cast into a GMM framework, to determine time-varying alpha and beta estimates. Our principal result is that the Kalman filter approach supports the hypothesis that illiquidity is an important risk factor in a dynamic context. However, the only factor found to matter in the dynamic GMM approach is the market risk premium. Nevertheless, illiquidity may be prescient with respect to financial crises.

Alpha Beta Risk and Stock Returns—A Decomposition Analysis of Idiosyncratic Volatility with Conditional Models

The variance of stock returns is decomposed based on a conditional Fama–French three-factor model instead of its unconditional counterpart. Using time-varying alpha and betas in this model, it is evident that four additional risk terms must be considered. They include the variance of alpha, the variance of the interaction between the time-varying component of beta and factors, and two covariance terms. These additional risk terms are components that are included in the idiosyncratic risk estimate using an unconditional model. By investigating the relation between the risk terms and stock returns, we find that only the variance of the time-varying alpha is negatively associated with stock returns. Further tests show that stock returns are not affected by the variance of time-varying beta. These results are consistent with the findings in the literature identifying return predictability from time-varying alpha rather than betas.

Robust tests for change in intercept and slope in linear regression models with application to manager performance in the mutual fund industry

Financial as well as economic theory have developed models which can be used to evaluate performance of mutual funds and that can assist regulators in monitoring performance of financial markets. These models make use of linear regressions models to provide this information. In particular, interest lies with the intercept parameter of these models and whether it is time varying. In applications to mutual fund performance, time varying alpha indicates a change in manager's stock selecting abilities. In applications to regulation of financial markets, time-varying alpha indicates potential changes to equity returns based on undisclosed information. These are importance concerns and emphasize the need to have accurate methods to disentangle changes in intercept from slope in these models. Here, a novel bivariate statistic is developed that can be used for this purpose. It has many attractive features. For example, the use of weight functions improves its power for discrete changes in intercept/slope that occur late/early in the sample, allows intercept/slope to change at different dates, allows for control of global error rates; and avoids trimming.

A semiparametric conditional capital asset pricing model

Abstract This paper proposes using a functional coefficient regression technique to estimate time-varying betas and alpha in the conditional capital asset pricing model (CAPM). Functional coefficient representation relaxes the strict assumptions regarding the structure of betas and alpha by combining the predictors into an index. Appropriate index variables are selected by applying the smoothly clipped absolute deviation penalty. In such a way, estimation and variable selection can be done simultaneously. Based on the empirical studies, the proposed model performs better than the alternatives in explaining asset returns and we find no strong evidence to reject the conditional CAPM.

A Conditional Single Index model with Local Covariates for detecting and evaluating active portfolio management

The intercept of standard Single Index and Conditional Single Index models, the so-called alpha, is often used to evaluate the long-run performance of managed portfolios. However, this measure is not always appropriate for detecting the presence and impact of active management strategies. Based on the conditional factor models literature, we introduce a Conditional Single Index model where the time-varying alpha and beta parameters depend only on the past history of the underlying portfolio returns and of the benchmark returns. The dynamics of the parameters have two components: the first describes the long-term behaviour of the alpha and beta, whereas the second is associated with the short-term performance of the underlying portfolio. The interpretation of parameters allows the identification of portfolio managers who implement active management strategies. An application on a set of 1300 U.S. mutual funds shows how widespread active management is on the U.S. market.

Portfolio Optimization for Hedge Funds Through Time-Varying Coefficients

In this paper, we show the interest of the time-varying coefficient model in hedge fund performance assessment and selection. We argue that the alpha of hedge funds is dynamic and that the time-varying alpha captures this dynamic behavior. Therefore, forming portfolios based on their time-varying alpha should lead to outperforming portfolios. Using a persistence analysis, we check this conjecture and show that contrary to top performers in terms of OLS alpha, the top performers in terms of past time-varying alpha generate superior and significant ex-post performance. Additionally, this analysis shows that persistence exists in the hedge fund industry and can be as long as 3 years. Secondly, building on the conclusion that the time-varying analysis gives a better picture of the alpha of the manager at a certain point in time, we use the time-varying analysis to obtain estimates of the expected returns of hedge funds. Using those estimates to construct a mean-variance optimal portfolio enhances the performance of this portfolio, suggesting that in terms of hedge fund performance detection, the time-varying model is superior to the OLS analysis.

A Conditional CAPM Model with Local Covariates for Detecting and Evaluating Active Management

The intercept of the standard CAPM and Conditional CAPM model, the alpha, is used to evaluate the long-run performance of managed portfolios. However, this measure is not always appropriate for detecting the presence and impact of active management strategies. In this paper, we introduce a Conditional CAPM model where the time-varying alpha and beta parameters depend only on the past history of the underlying portfolio returns and of the benchmark returns. The dynamics of the parameters has two components: the first describes the long-term behavior of the alpha and beta, whereas the second is associated with the short-term performance of the underlying portfolio. The interpretation of parameters allows the identification of portfolio managers who implement active management strategies. We provide an empirical application based on a large set of U.S. mutual funds showing how widespread active management approaches are, even if only a minor fraction persistently beats the benchmark. We also show that the recent financial crisis has had negative effects on mutual fund performances.

The Performance of European Equity Mutual Funds

Despite the significant growth in the European fund industry in recent years, the performance of European equity mutual funds is a largely unexplored area of research. This paper shows that macroeconomic state variables can be used to identify a significant time-varying alpha component among a large sample of Pan-European, European country and sector funds. State variables such as the default yield spread, the term spread, the dividend yield and the short risk-free rate as well as macroeconomic variables tracking consumer price in ation and economic sentiment prove valuable in ex-ante identification of superior performance among funds. Most of the alpha that these state variables help produce comes from their ability to select superior Pan-European funds and generate returns from country selection.

Time-varying alpha and particle physics.

We argue that models in which an observable variation of the fine structure constant is explained by motion of a cosmic scalar field are not stable under renormalization and require massive fine-tuning that cannot be explained by any known mechanism.