Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper

Abstract

The characterization of return distributions and forecast of asset-price variability play a critical role in the study of financial markets. This study estimates four measures of integrated volatility-daily absolute returns, realized volatility, realized bipower volatility, and integrated volatility via Fourier transformation (IVFT)-for gold, silver, and copper by using high-frequency data for the period 1999 through 2008. The distributional properties are investigated by applying recently developed jump detection procedures and by constructing financial-time return series. The predictive ability of a GARCH (1, 1) forecasting model that uses various volatility measures is also examined. Three important findings are reported. First, the magnitude of the IVFT volatility estimate is the greatest among the four volatility measures. Second, the return distributions of the three markets are not normal. However, when returns are standardized by IVFT and realized volatility, the corresponding return distributions bear closer resemblance to a normal distribution. Notably, the application of financial-time sampling technique is helpful in obtaining a normal distribution. Finally, the IVFT and realized volatility proxies produce the smallest forecasting errors, and increasing the time frequency of estimating integrated volatility does not necessarily improve forecast accuracy.

Dynamic spillovers between commodity and currency markets

“…In line with previous studies (see, e.g. Khalifa et al, 2011), we use the absolute value of returns to define volatility, as it is one of the most common academic definitions of volatility and provides the most stable results given varying sample sizes (see, e.g. Zhang and Wang, 2014).…”

Impact of macroeconomic news on metal futures

“…A survey of the literature in the metals commodities markets reveals three major research streams: (a) characterization of the distributional properties of metal prices (Khalifa et al, 2011);(b) identification of dynamic relationships between futures and spot prices of various metals (Kocagil, 1997); and (c) examination of metals as a hedge against inflation, currency rate risk, and market uncertainty (Baur and Lucey, 2010). Our study on how metal futures market responds to macroeconomic news adds a new dimension to the literature and carries implications for market efficiency, risk premia, and the pricing and trade behavior of gold, copper and silver.…”

Risk management of precious metals

“…The paper offers new insights into how commodity and equity markets relate at an industry level and documents implications for multicommodity hedging. Khalifa et al (2010) suggest that the characterization of return distributions and forecasts of asset-price variability plays a critical role in the analysis of financial markets.…”