This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...

We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and...

I provide evidence that risks in macroeconomic fundamentals contain valuable information about bond risk premia. I extract factors from a set of quantile-based risk measures estimated for US macroeconomic variables and document that they account for up to 31% of the variation in excess bond...

This paper solves the dynamic asset allocation problem under stock return predictability based on the dividend price ratio with regime shifts and parameter uncertainty in a fully Bayesian framework. Intertemporal hedging demands are simultaneously induced by predictability, regime shifts,...

This paper evaluates in-sample and out-of-sample stock return predictability with inflation and output gap, the variables that typically enter the Federal Reserve Bank's interest rate setting rule. To examine the role of monetary policy fundamentals for stock return predictability, we introduce...

This article comprehensively reviews the predictability of six equity factors. These factors are the market excess return, size, value, momentum, low beta and quality. I find predictability for the low beta factor and moderate predictability for the size factor. The results for other factors are...

As some recent studies have shown empirically, future gold price fluctuations are especially difficult to forecast. Against this background, this study evaluates the forecasting power of three methods that have been applied successfully in a stock market prediction context: 1) technical...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...

This paper suggests a novel approach for predicting aggregate stock returns at quarterly and annual frequencies. Weak return predictability is consistent with the view that a stationary component of stock prices is highly persistent. In such cases, expected returns are time-varying but also...