Allan Timmermann

• University of California, San Diego

We revisit the Phillips curve, applying new Bayesian panel methods with structural breaks to US and EU disaggregate data. Our approach lets us estimate both the number and timing of breaks and to determine the existence of clusters of industries, cities, or countries whose Phillips curves display similar patterns. We find evidence of a flattening f...

For many benchmark predictor variables, short‐horizon return predictability in the U.S. stock market is local in time as short periods with significant predictability (“pockets”) are interspersed with long periods with no return predictability. We document this result empirically using a flexible time‐varying parameter model that estimates predicti...

We revisit time-variation in the Phillips curve, applying new Bayesian panel methods with breakpoints to US and European Union disaggregate data. Our approach allows us to accurately estimate both the number and timing of breaks in the Phillips curve. It further allows us to determine the existence of clusters of industries, cities, or countries wh...

We develop a new housing search index (HSI) extracted from online search activity on a limited set of keywords related to the house-buying process. We show that HSI has strong predictive power over subsequent changes in house prices, both in-sample and out-of-sample and after controlling for the effect of commonly used predictors, and relate our fi...

We establish conditions under which forecasting performance can be improved by rotating between a set of underlying forecasts whose predictive accuracy is tracked using a set of time-varying monitoring instruments. We characterize the properties that the monitoring instruments must possess to be useful for identifying, at each point in time, the be...

This paper develops new methods for pairwise comparisons of predictive accuracy with cross-sectional data. Using a common factor setup, we establish conditions on cross-sectional dependencies in forecast errors which allow us to test the null of equal predictive accuracy on a single cross-section of forecasts. We consider both unconditional tests o...

We apply a new methodology for identifying pervasive and discrete changes (“breaks”) in cross-sectional risk premia. Size, value, and investment risk premia have fallen off to the point where they are insignificantly different from zero at the end of the sample period. The market risk premium has also declined systematically over time but remains s...

Every year, the Society for Financial Econometrics celebrates the fundamental contributions to econometric theory and practice made by our late colleague and friend Hal White. Central to these celebrations is a lecture presented by an established scholar during a plenary session of the Society’s Annual Conference. This lecture is subsequently publi...

We develop a new approach to modeling and predicting stock returns in the presence of breaks that simultaneously affect a large cross-section of stocks. Exploiting information in the cross-section enables us to detect breaks in return prediction models with little delay and to generate out-of-sample return forecasts that are significantly more accu...

We present a new approach to selecting actively managed mutual funds that uses both portfolio holdings and fund return information to eliminate funds with predicted inferior performance through a sequence of pairwise fund comparisons. Our methodology determines both the number of skilled funds and their identities and locates funds with substantial...

The method for testing equal predictive accuracy for pairs of forecasting models proposed by Giacomini and White (2006) has found widespread use in empirical work. The procedure assumes that the parameters of the underlying forecasting models are estimated using a rolling window of fixed width and incorporates the effect of parameter estimation in...

We study investor redemptions and portfolio rebalancing decisions of prime money market mutual funds (MMFs) during the Eurozone crisis. We find that sophisticated investors selectively acquire information about MMFs’ risk exposures to Europe, which leads managers to withdraw funding from information-sensitive European issuers. That is, MMF managers...

We develop a Bayesian approach that performs variable selection in panel regression models affected by breaks. Our approach enables deactivation of pervasive regressors and activation of weak regressors for short periods (regimes). We establish theoretical results on the concentration properties of the posterior as well as the rate of convergence f...

THE ET INTERVIEW: PROFESSOR HASHEM PESARAN - Volume 35 Issue 4 - Allan Timmermann

Our review highlights some of the key challenges in financial forecasting problems and opportunities arising from the unique features of financial data. We analyze the difficulty of establishing predictability in an environment with a low signal-to-noise ratio, persistent predictors, and instability in predictive relations arising from competitive...

We show a positive relation between network centrality and risk-adjusted performance in a delegated investment management setting. More connected managers take more portfolio risk and receive higher investor flows, consistent with these managers improving their ability to exploit investment opportunities through their network connections. Greater n...

Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such as volatility dynamics and unspanned macro factors. A t...

We study daily money market mutual fund flows at the individual share class level during September 2008. This fine granularity of data allows new insights into investor and portfolio holding characteristics conducive to run risk in cash-like asset pools. We find that cross-sectional flow data observed during the week of the Lehman failure are consi...

Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economi...

We study investor redemptions and portfolio rebalancing decisions of money market mutual funds (MMFs) during the Eurozone crisis. We exploit the multiple shareclass structure of the MMF industry and the detailed portfolio holdings disclosure required by 2010 regulatory changes to highlight costs and benefits of increased transparency in short-term...

We compare different approaches to accounting for parameter instability in the context of macroeconomic forecasting models that assume either small, frequent changes versus models whose parameters exhibit large, rare changes. An empirical out-of-sample forecasting exercise for U.S. GDP growth and inflation suggests that models that allow for parame...

We propose a new method for constructing the hedge component in Merton's ICAPM that uses a daily summary measure of economic activity to track time-varying investment opportunities. We then use nonparametric projections to compute a robust estimate of the conditional covariance between stock market returns and our daily economic activity index. We...

Since their introduction into economics by Hamilton (1989), Markov switching models have become very popular in both applied and theoretical works in finance.

We analyze the relation between the location of a pension fund in its network and the investment performance, risk taking, and flows of the fund. Our approach analyzes the centrality of the fund's management company by examining the number of connections it has with other management companies through their commonality in managing for the same fund...

Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such as time varying parameters and volatility dynamics. A t...

We propose a new approach to predictive density modeling that allows for MIDAS effects in both the first and second moments of the outcome and develop Gibbs sampling methods for Bayesian estimation in the presence of stochastic volatility dynamics. When applied to quarterly U.S. GDP growth data, we find strong evidence that models that feature MIDA...

Convergence trades exploit temporary mispricing by simultaneously buying relatively underpriced assets and selling short relatively overpriced assets. This paper studies optimal convergence trades under both recurring and nonrecurring arbitrage opportunities represented by continuing and “stopped” cointegrated price processes and considers both fix...

Survey data on expectations and economic forecasts play an important role in providing better insights into how economic agents make their own forecasts and why agents disagree in making them. Using data from the European Survey of Professional Forecasters (SPF), we consider measures of uncertainty and disagreement at both aggregate and individual...

This paper derives the asymptotic distribution of the F-test for the significance of linear regression coefficients as both the number of regressors, k, and the number of observations, n, increase together so that their ratio remains positive in the limit. The conventional critical values for this test statistic are too small, and the standard vers...

Predictability of the mean and volatility of stock returns over the course of the business cycle have generated considerable interest in the financial community. This chapter studies the patterns and magnitude of variations in the mean and volatility of US stock returns around turning points of the business cycle. During the brief spell from the pe...

Forecast combinations have frequently been found in empirical studies to produce better forecasts on average than methods based on the ex ante best individual forecasting model. Moreover, simple combinations that ignore correlations between forecast errors often dominate more refined combination schemes aimed at estimating the theoretically optimal...

This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that accounting for both regimes in interest rate dynamics and combining forecasts from different models helps improve the out-of-sample forecasting performance for US short-...

This paper characterizes the term structure of risk measures such as Value at Risk (VaR) and expected shortfall under different econometric approaches including multivariate regime switching, GARCH-in-mean models with student-t errors, two-component GARCH models and a non-parametric bootstrap. We show how to derive the risk measures for each of the...

This chapter examines and assesses the benchmarks that are currently used by institutional investors in the UK. Performance benchmarks are important for three key reasons—they help measure the investment performance of institutional fund managers, they provide clients/trustees with a reference point for monitoring that performance, and they can hav...

On economic grounds we would expect a feedback from the endogenous variable to the forcing variable in many present value models. In this paper we show that feedback can change the dynamical properties of the solution(s) to present value models very substantially. Feedback in a present value model can generate multiple solutions. It can also change...

Apparently the answer is yes! We compare standard univariate time series models and multi-variate factor models in terms of their ability to forecast the weekly realized variances of 33 international stock exchanges. We also try to assess to which extent adopting common pure variance factors -which exploit the comovements across markets -helps in f...

Thesis (Ph. D.)--University of Cambridge, 1991.