Time-varying risk aversion and international stock returns

IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE
Massimo Guidolin , Erwin Hansen , Gabriel Cabrera
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引用次数: 0

Abstract

We estimate aggregate, time-varying risk aversion inferred from options, stock returns and macroeconomic data for a panel of 8 countries. We document that, for most countries, the estimated risk aversion measure is counter-cyclical. Moreover, we show that estimated risk aversion forecasts monthly stock index returns up to 12 months ahead. This effect is statistically significant in panel regressions, and it survives the inclusion of additional control variables, such as an estimated of the variance risk premium, an investors’ sentiment index, and a measure of economic uncertainty. Finally, we show that risk aversion provides useful information to an investor who aims at timing the market. An investment strategy that uses the estimated time-varying risk aversion measure to solve a mean–variance asset allocation problem, delivers significantly positive returns.

时变风险规避与国际股票回报率
我们从期权、股票收益和宏观经济数据中推断出 8 个国家的总体时变风险厌恶程度。我们发现,对大多数国家而言,估计的风险规避措施是反周期的。此外,我们还表明,估计的风险规避可以预测长达 12 个月的月度股指回报。这种效应在面板回归中具有统计意义,并且在纳入额外的控制变量(如方差风险溢价估计值、投资者情绪指数和经济不确定性衡量指标)后仍然存在。最后,我们表明,风险规避为投资者把握市场时机提供了有用的信息。利用估算的时变风险规避度量来解决均值方差资产配置问题的投资策略能带来显著的正收益。
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来源期刊
CiteScore
7.30
自引率
8.30%
发文量
168
期刊介绍: The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.
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