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 market- and sentiment-based variables, we examine the predictive value of realized moments across alternative forecast horizons and across the quantiles of the conditional distribution of gold futures returns. We 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. We argue that realized moments carry information that reflects investors’ tradeoff between diversification and skewed payoffs, particularly during periods of market stress, which may be especially relevant for gold as the traditional accepted safe haven.

[1]  Furno Marilena,et al.  Quantile Regression , 2018, Wiley Series in Probability and Statistics.

[2]  He Nie,et al.  Dynamic linkages among the gold market, US dollar and crude oil market , 2018 .

[3]  On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test , 2017 .

[4]  Christian Pierdzioch,et al.  Do Terror Attacks Predict Gold Returns? Evidence from a Quantile-Predictive-Regression Approach , 2017 .

[5]  D. Bams,et al.  Does Oil and Gold Price Uncertainty Matter for the Stock Market , 2017 .

[6]  Ana‐Maria Fuertes,et al.  The Skewness of Commodity Futures Returns , 2015 .

[7]  S. Vigne,et al.  Return spillovers between white precious metal ETFs: The role of oil, gold, and global equity , 2017 .

[8]  Rangan Gupta,et al.  The effect of investor sentiment on gold market return dynamics: Evidence from a nonparametric causality-in-quantiles approach , 2017 .

[9]  Dirk G. Baur,et al.  A melting pot — Gold price forecasts under model and parameter uncertainty , 2016 .

[10]  Xingguo Luo,et al.  The information content of implied volatility and jumps in forecasting volatility: Evidence from the Shanghai gold futures market , 2016 .

[11]  Isabel Figuerola‐Ferretti,et al.  The shine of precious metals around the global financial crisis , 2016 .

[12]  Christian Pierdzioch,et al.  Does Uncertainty Move the Gold Price? New Evidence from a Nonparametric Causality-in-Quantiles Test , 2016 .

[13]  Christian Pierdzioch,et al.  Are Precious Metals a Hedge Against Exchange-Rate Movements? An Empirical Exploration Using Bayesian Additive Regression Trees , 2016 .

[14]  Christian Pierdzioch,et al.  A Boosting Approach to Forecasting the Volatility of Gold-Price Fluctuations Under Flexible Loss , 2015 .

[15]  Christian Pierdzioch,et al.  A real-time quantile-regression approach to forecasting gold returns under asymmetric loss , 2015 .

[16]  R. Kräussl,et al.  Euro Crash Risk , 2015 .

[17]  Theo Berger,et al.  Does gold act as a hedge or a safe haven for stocks? A smooth transition approach , 2015 .

[18]  Christian Pierdzioch,et al.  A Quantile-Boosting Approach to Forecasting Gold Returns , 2015 .

[19]  Stephan Süss,et al.  Market Sentiment in Commodity Futures Returns , 2015 .

[20]  Andrew Urquhart How predictable are precious metal returns? , 2015 .

[21]  Jesus M. Salas,et al.  Why Do Firms Engage in Selective Hedging? Evidence from the Gold Mining Industry , 2015 .

[22]  Sen Yuan Random gradient boosting for predicting conditional quantiles , 2015 .

[23]  Christian Pierdzioch,et al.  Fluctuations of the real exchange rate, real interest rates, and the dynamics of the price of gold in a small open economy , 2015 .

[24]  Keshab Shrestha Price discovery in energy markets , 2014 .

[25]  Don Bredin,et al.  Does Gold Glitter in the Long-Run? Gold as a Hedge and Safe Haven Across Time and Investment Horizon , 2014 .

[26]  Juan C. Reboredo,et al.  Can gold hedge and preserve value when the US dollar depreciates , 2014 .

[27]  Christian Pierdzioch,et al.  On the efficiency of the gold market: Results of a real-time forecasting approach , 2014 .

[28]  D. Gounopoulos,et al.  Does gold offer a better protection against losses in sovereign debt bonds than other metals , 2014 .

[29]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[30]  Nicholas Apergis,et al.  Can gold prices forecast the Australian dollar movements , 2014 .

[31]  Peter F. Christoffersen,et al.  Does Realized Skewness Predict the Cross-Section of Equity Returns? , 2015 .

[32]  Patrick M. Stephan,et al.  The Gold Price in Times of Crisis , 2013 .

[33]  Juan C. Reboredo,et al.  Is gold a safe haven or a hedge for the US dollar? Implications for risk management , 2013 .

[34]  Juan C. Reboredo,et al.  Is gold a hedge or safe haven against oil price movements , 2013 .

[35]  J. Beckmann,et al.  Oil and gold price dynamics in a multivariate cointegration framework , 2013 .

[36]  M. Hood,et al.  Is gold the best hedge and a safe haven under changing stock market volatility , 2013 .

[37]  Zhi Da,et al.  The Sum of All FEARS: Investor Sentiment and Asset Prices , 2013 .

[38]  S. Davis,et al.  Measuring Economic Policy Uncertainty , 2013 .

[39]  B. Ewing,et al.  Volatility transmission between gold and oil futures under structural breaks , 2013 .

[40]  Ioannis D. Vrontos,et al.  A Quantile Regression Approach to Equity Premium Prediction , 2012 .

[41]  Songfeng Zheng,et al.  QBoost: Predicting quantiles with boosting for regression and binary classification , 2012, Expert Syst. Appl..

[42]  M. Schmid,et al.  The Importance of Knowing When to Stop , 2012, Methods of Information in Medicine.

[43]  T. Bollerslev,et al.  Risk and Return: Long-Run Relationships, Fractional Cointegration, and Return Predictability , 2013 .

[44]  Anastasios Malliaris,et al.  Are oil, gold and the euro inter-related? Time series and neural network analysis , 2011 .

[45]  Fulvio Corsi,et al.  Realizing Smiles: Options Pricing with Realized Volatility , 2011 .

[46]  R. Bhar,et al.  Commodities and financial variables: Analyzing relationships in a changing regime environment , 2011 .

[47]  Richard Roll,et al.  Gold and the Dollar (and the Euro, Pound, and Yen) , 2011 .

[48]  Torsten Hothorn,et al.  Identifying Risk Factors for Severe Childhood Malnutrition by Boosting Additive Quantile Regression , 2011 .

[49]  Dirk G. Baur,et al.  The Structure and Degree of Dependence - A Quantile Regression Approach , 2011 .

[50]  The Impact of Skewness and Fat Tails on the Asset Allocation Decision , 2011 .

[51]  Jui-Cheng Hung,et al.  Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns , 2011 .

[52]  B. Lucey,et al.  Hedges and Safe Havens: An Examination of Stocks, Bonds, Gold, Oil and Exchange Rates , 2013 .

[53]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[54]  Yi-Ming Wei,et al.  The crude oil market and the gold market: Evidence for cointegration, causality and price discovery , 2010 .

[55]  Gold and the U.S. Dollar: Tales from the Turmoil , 2010 .

[56]  Yuhang Xing,et al.  What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns? , 2010, Journal of Financial and Quantitative Analysis.

[57]  L. Blose,et al.  Gold prices, cost of carry, and expected inflation , 2010 .

[58]  Robert F. Dittmar,et al.  Ex Ante Skewness and Expected Stock Returns , 2009 .

[59]  D. Baur,et al.  Institute for International Integration Studies Is Gold a Safe Haven? International Evidence Is Gold a Safe Haven? International Evidence Is Gold a Safe Haven? International Evidence , 2022 .

[60]  Marco Rossi,et al.  The Effects of Economic News on Commodity Prices: Is Gold Just Another Commodity? , 2009, SSRN Electronic Journal.

[61]  B. Lucey,et al.  Institute for International Integration Studies Is Gold a Hedge or a Safe Haven? an Analysis of Stocks, Bonds and Gold Is Gold a Hedge or a Safe Haven? an Analysis of Stocks, Bonds and Gold , 2022 .

[62]  Shawkat Hammoudeh,et al.  Metal volatility in presence of oil and interest rate shocks , 2008 .

[63]  Turan G. Bali,et al.  The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR , 2008 .

[64]  Peter Buhlmann,et al.  BOOSTING ALGORITHMS: REGULARIZATION, PREDICTION AND MODEL FITTING , 2007, 0804.2752.

[65]  B. Kramer,et al.  Peirce, Youden, and Receiver Operating Characteristic Curves , 2007 .

[66]  R. Koenker,et al.  Regression Quantiles , 2007 .

[67]  Neil Shephard,et al.  Designing Realised Kernels to Measure the Ex-Post Variation of Equity Prices in the Presence of Noise , 2008 .

[68]  A. Worthington,et al.  Gold investment as an inflationary hedge: cointegration evidence with allowance for endogenous structural breaks , 2007 .

[69]  R. Faff,et al.  Do Precious Metals Shine? An Investment Perspective , 2006 .

[70]  Ming Huang,et al.  Stocks as Lotteries: The Implications of Probability Weighting for Security Prices , 2007 .

[71]  Terence C. Mills,et al.  Gold as a hedge against the dollar , 2005 .

[72]  M. Wohar,et al.  Macro variables and international stock return predictability , 2005 .

[73]  Todd Mitton,et al.  Equilibrium Underdiversification and the Preference for Skewness , 2004 .

[74]  Lan Zhang,et al.  A Tale of Two Time Scales , 2003 .

[75]  J. Friedman Greedy function approximation: A gradient boosting machine. , 2001 .

[76]  Mukesh Chaudhry,et al.  Do macroeconomics news releases affect gold and silver prices , 2000 .

[77]  M. Greiner,et al.  Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. , 2000, Preventive veterinary medicine.

[78]  T. Bollerslev,et al.  ANSWERING THE SKEPTICS: YES, STANDARD VOLATILITY MODELS DO PROVIDE ACCURATE FORECASTS* , 1998 .

[79]  B. LeBaron,et al.  A test for independence based on the correlation dimension , 1996 .

[80]  Ray C. Fair,et al.  Comparing Information in Forecasts from Econometric Models , 1990 .