Technical Indicators and Realized Volatility: What is the Source of Predictability?

Abstract

Forecasting Realized Volatility (RV) is of paramount importance for both academics and practitioners. During recent decades, academic literature has made substantial progress both in terms of methods and predictors under consideration. Despite the popularity of technical indicators, there has been only scarce reference to the effectiveness of this group of predictors in forecasting RV. This paper examines the out-of-sample forecasting performance of technical indicators for S&P500 RV relative to macroeconomic predictors. We contend that these sets of predictors impact volatility at different frequencies. We demonstrate that by generating economically motivated amalgamation forecasts from these predictors taking into account the frequency dimension leads to substantial improvements in forecast accuracy. Technical indicators perform especially strongly for forecasting the short frequency component which complements macroeconomic variables which perform strongly at longer frequencies. We extend our experiment by examining timing effects in the positive performance. We demonstrate that using both sets of predictors leads to consistent and robust outperformance of the benchmark during recessions and expansions, during high and low VIX periods and during different out-of-sample periods. The results indicate that the complementary nature of technical indicators and macroeconomic variables in RV forecasting should be taken into consideration by practitioners and policymakers.