Gold futures returns and realized moments : a forecasting experiment using a quantile-boosting approach

TLDR: The German Science Foundation (Project Macroeconomic Forecasting in Great Crises; Grant number: FR 2677/4/1) as mentioned in this paper has provided a grant for the project.

About: This article is published in Resources Policy.The article was published on 2018-08-01 and is currently open access. It has received 8 citations till now. The article focuses on the topics: Realized variance & Futures contract.

Figures

Figure 3: Inclusion of Realized Moments Across Quantiles in the Forecasting Model

Figure 4: Rolling Fair-Shiller Regressionens (Five-Days-Ahead Returns)

Figure 1: Gold Futures Returns and Realized Moments

Figure 5: Rolling Fair-Shiller Regressionens (Ten-Days-Ahead Returns)

Figure 2: Results for Alternative Forecast Horizons

Frequently asked questions

Q1. What have the authors contributed in "Gold futures returns and realized moments: a forecasting experiment using a quantile-boosting approach" ?

This paper proposes an iterative model-building approach known as quantile boosting to trace out the predictive value of realized volatility and skewness for gold futures returns. Controlling for several widely studied marketand sentiment-based variables, the authors examine the predictive value of realized moments across alternative forecast horizons and across the quantiles of the conditional distribution of gold futures returns. The authors find that the realized moments often significantly improve the predictive value of the estimated forecasting models at intermediate forecast horizons and across quantiles representing distressed market conditions. 

Q2. What future works have the authors mentioned in the paper "Gold futures returns and realized moments: a forecasting experiment using a quantile-boosting approach" ?

Furthermore, as Shrestha ( 2014 ) notes, one can expect price discovery to take place primarily in the futures market as the futures price responds to new information faster than the spot price due to lower transaction costs and ease of short selling associated with the futures contracts. The futures price data, in continuous format, are obtained from www. Based on the Jarque-Bera test statistic ( not reported ), the authors can reject normality of the sampling distribution of returns at the highest levels of significance, which provides some preliminary justification for modeling the quantiles rather than simply the mean of the conditional distribution of returns. By the same token, an analysis by means of the BDS test ( Brock et al., 1996 ; results are available upon request ) indicates, for various embedding dimensions, the presence of nonlinearity in the returns series, further strengthening the case for a quantiles-based modeling approach.