Time-Varying Risk Aversion: Evidence from Near-Miss Accidents

2019 ◽  
Author(s):  
Matthew Shum ◽  
Yi Xin
Keyword(s):  
Risk Aversion ◽  
Near Miss ◽  
Time Varying

Time-Varying Risk Aversion? Evidence from Near-Miss Accidents

2020 ◽  
pp. 1-45
Author(s):  
Matthew Shum ◽  
Yi Xin
Keyword(s):  
Risk Aversion ◽  
High Frequency ◽  
Insurance Premium ◽  
Near Miss ◽  
Time Varying ◽  
Mobile Phone Application ◽  
Insurance Cost ◽  
Car Insurance ◽  
Increase In Risk ◽  
Unique Dataset

We present evidence consistent with time-varying risk preferences among automobile drivers. Exploiting a unique dataset of agents’ high-frequency driving behavior collected by a mobile phone application, we show that drivers drive more conservatively following “near-miss” accidents. In a preferred specification, a nearmiss triggers a reduction in driving distance of 12.98 kilometers, in-car cellphone use by more than 100%, and highway use by 43.24%. Structural estimation results indicate that such changes in behavior are consistent with an increase in risk aversion of 10.54–43.77% and a reduction in annual insurance cost amounting to 2.04–3.31% of the average car insurance premium.

Time-varying risk aversion and currency excess returns

2022 ◽  
Vol 59 ◽  
pp. 101555
Author(s):  
Riza Demirer ◽  
Asli Yuksel ◽  
Aydin Yuksel
Keyword(s):  
Risk Aversion ◽  
Time Varying ◽  
Excess Returns

scholarly journals Time-Varying Risk Aversion and the Profitability of Carry Trades: Evidence from the Cross-Quantilogram

Economies ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 18
Author(s):  
Riza Demirer ◽  
Rangan Gupta ◽  
Hossein Hassani ◽  
Xu Huang
Keyword(s):  
Risk Aversion ◽  
Predictive Power ◽  
Investor Sentiment ◽  
Time Varying ◽  
Carry Trade ◽  
Currency Markets ◽  
High Quantiles ◽  
Predictive Role ◽  
The Cross ◽  
Directional Predictability

This paper examines the predictive power of time-varying risk aversion over payoffs to the carry trade strategy via the cross-quantilogram methodology. Our analysis yields significant evidence of directional predictability from risk aversion to daily carry trade returns tracked by the Deutsche Bank G10 Currency Future Harvest Total Return Index. The predictive power of risk aversion is found to be stronger during periods of moderate to high risk aversion and largely concentrated on extreme fluctuations in carry trade returns. While large crashes in carry trade returns are associated with significant rises in investors’ risk aversion, we also found that booms in carry trade returns can be predicted at high quantiles of risk aversion. The results highlight the predictive role of extreme investor sentiment in currency markets and regime specific patterns in carry trade returns that can be captured via quantile-based predictive models.

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