This paper investigates international index return predictability using daily-updated option-implied information in predictive regressions and out-of-sample forecasts. We document the significant predictive power of the variance risk premium (VRP), Generalized Riskiness (GR), and higher-order...

Financial Times Series such as stock price and exchange rates are, often, non-linear and non-stationary. Use of decomposition models has been found to improve the accuracy of predictive models. The paper proposes a hybrid approach integrating the advantages of both decomposition model (namely,...

This paper aims at improved accuracy in testing for long-run predictability in noisy series, such as stock market returns. Long-horizon regressions have previously been the dominant approach in this area. We suggest an alternative method that yields more accurate results. We find evidence of...

The predictability of long-term asset returns increases with the time horizon as estimated in regressions of aggregated-forward returns on aggregated-backward predictive variables. This previously established evidence is consistent with the presence of common slow-moving components that are...

We argue that high-frequency return predictability can be explained by delays in prices, providing another explanation for why paper profits often do not materialize. We investigate predictability in the US (and international) stock market from 2005 to 2012 and in 2020. We find that 1-minute...

We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily forecasts. The parsimonious set up of our approach allows to...

Suppose a fund manager uses predictors in changing port-folio allocations over time. How does predictability translate into portfolio decisions? To answer this question we derive a new model within the Bayesian framework, where managers are assumed to modulate the systematic risk in part by...

Theory suggests a relationship between both volatility of volatility, variance risk premium, and the equity risk premium. We empirically investigate the relationship between volatility of volatility and the equity risk premium, and the relationship between the variance risk premium and the...

This paper studies standard predictive regressions in economic systems governed by persistent vector autoregressive dynamics for the state variables. In particular, all - or a subset - of the variables may be fractionally integrated, which induces a spurious regression problem. We propose a new...

In this paper, we provide evidence that the small stock premium is predictable both in-sample and out-of-sample through the use of a set of lagged macroeconomic variables. We find that it is possible to forecast the size premium over time horizons that range from one month to one year. We...