‘Déjà vol’: Predictive regressions for aggregate stock market volatility using macroeconomic variables

Abstract

Aggregate stock return volatility is both persistent and countercyclical. This paper tests whether it is possible to improve volatility forecasts at monthly and quarterly horizons by conditioning on additional macroeconomic variables. I find that several variables related to macroeconomic uncertainty, time-varying expected stock returns, and credit conditions Granger cause volatility. It is more difficult to find evidence that forecasts exploiting macroeconomic variables outperform a univariate benchmark out-of-sample. The most successful approaches involve simple combinations of individual forecasts. Predictive power associated with macroeconomic variables appears to concentrate around the onset of recessions.JEL classification: G12; C22

Macro-Driven VAR Forecasts: From Very High to Very Low-Frequency Data

“…A subject of particular interest concerns the joint-behavior of volatility and the economy with a special emphasis on their lead-lag pattern and on the cyclical behavior of stock market volatility. Many contributions, including Hamilton and Lin (1996), Perez-Quiros and Timmermann (2000), Christiansen et al (2012), Corradi et al (2013), and Paye (2012), reported evidence of the counter-cyclical behavior of the long-run market volatility. Hence, if the economy shrinks, stock market volatility is expected to increase in response to concerns about future market conditions.…”

The Long Memory of Equity Volatility: International Evidence

“…It is argued in the literature that changes in macroeconomic variables do not directly impact the real economy and the stock market, but it takes several months or more. Paye (2012) investigates the predictability of stock return volatility by multiple macroeconomic variables including up to two lags while Engle et al (2013) show that macroeconomic fundamentals are important for both short-and long-horizon forecasting of stock market volatility. We hence repeat our time-series analysis but investigate a lagged relationship rather than a contemporaneous one for the U.S.…”

An Intertemporal CAPM with Stochastic Volatility

“…However, the focus has mostly been on univariate models, such as the GARCH class of models (Engle 1982, Bollerslev 1986), or univariate …ltering methods that use realized high-frequency volatility (Barndor¤-Nielsen andShephard 2002, Andersen et al 2003). A much smaller literature has, like us, looked directly at the information in other economic and …nancial variables concerning future volatility (Schwert 1989, Christiansen, Schmeling, and Schrimpf 2012, Paye 2012, Engle, Ghysels, and Sohn 2013.…”