On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks

By Lawrence R. Glosten, Ravi Jagannathan, D. Runkle. 1993

The authors find support for a negative relation between conditional expected monthly return and conditional variance of monthly return using a GARCH-M model modified by allowing (1) seasonal patterns in volatility, (2) positive and negative innovations to returns having different impacts on conditional volatility, and (3) nominal interest rates to predict conditional variance. Using the modified GARCH-M model, they also show that monthly conditional volatility may not be as persistent as was thought. Positive unanticipated returns appear to result in a downward revision of the conditional volatility, whereas negative unanticipated returns result in an upward revision of conditional volatility. Copyright 1993 by American Finance Association.

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Citations in the corpus

Stock Market Risk and Return: An Equilibrium Approach (2000, methodology): “Recent empirical studies [e.g., Glosten, Jagannathan, and Runkle (1993) , Whitelaw (1994), and Boudoukh, Richardson, and Whitelaw (1997)] document two puzzling results with regard to the intertemporal relation between equity risk and return at the market level.1 First, they provide evidence of a we”
The Ten Commandments for Optimizing Value-at-Risk and Daily Capital Charges (2009, unknown): “(1986), GJR by Glosten, Jagannathan and Runkle (1992) , EGARCH by Nelson (1991), and”
Good Times or Bad Times? Investors' Uncertainty and Stock Returns (2009, unknown): “Finally, the returns to momentum strategies of buying winner stocks and selling loser stocks over intermediate horizons, documented first by Jegadeesh and Titman (1993), have remained to date as one of the greatest anomalies of the asset pricing literature.”
GARCH option pricing: A semiparametric approach (2008, background): “Therefore, we consider two GARCH models for volatility: (i) the simple GARCH and (ii) the threshold GARCH (TGARCH) model introduced by Glosten et al (1993) ht = α0 + α1ε2t−1ht−1 + β1ht−1 (23) ht = α0 + α1ε2t−1ht−1 + γI(εt−1 0)ε 2 t−1ht−1 + β1ht−1 (24) where I is the indicator function.”
Systemic Risk in Europe (2013, unknown): “To deal with heteroskedasticity, we assume a univariate asymmetric GARCH model (Glosten, Jagannathan, and Runkle, 1993), where, as before, the volatility is conditional on the information set at date t 1: "k,t+1 = k,t+1 (zk,t+1 + ✓k zk,t), (13) where 2k,t+1 = !k + ↵k" 2 k,t 1 + k 2 k,t + k" 2 k,t…”
Stock Index Futures Trading and Volatility in International Equity Markets (2000, unknown): “[9] Glosten, Lawrence R, Ravi Jagannathan and David E.”