Tail Risk and Asset Prices

By Bryan T. Kelly, Hao Jiang. 2014

749 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/1ccc584e35694a3c59dfcc9dbe077ae00cfdf27f

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Citations in the corpus

Tail index estimation: quantile driven threshold selection (2016, methodology): “The first row reproduces the approximately 4% risk premium that Kelly and Jiang (2014) originally identified for stocks with high covariance relative to those with low covariance.”
A Lottery Demand-Based Explanation of the Beta Anomaly (2017, positive): “Following Kelly and Jiang (2013) and Ruenzi and Weigert (2013), we define tail beta (TRISK) as the slope coefficient from a regression of stock excess returns”
Tail risk premia and return predictability (2014, background): “However, there is ample anecdotal as well as more rigorous empirical evidence that “large” sized jumps, or tail events, are viewed very differently by investors than more “normal” sized price fluctuations (see, e.g., Bansal and Shaliastovich, 2011 and the references therein).”
Downside Variance Risk Premium (2015, positive): “Along the timeseries dimension, BTZ, Drechsler and Yaron (2011), and Kelly and Jiang (2014), among others, show that the V RP can help forecast the temporal variation in the aggregate stock market returns with high (low) premia predicting high (low) future returns, especially in within-the-year…”
Disaster Risk and its Implications for Asset Pricing (2015, neutral): “Kelly and Jiang (2014) assume that tails of individual asset returns follow a power law, with parameters determined by overall market tail behavior.”
A Comparison of New Factor Models (2017, background): “…(6-month holding period) Ang, Chen, and Xing (2006) Ang, Chen, and Xing (2006) β−12 Downside beta (12-month holding period) Tail1 Tail risk (1-month holding period) Ang, Chen, and Xing (2006) Kelly and Jiang (2014) Tail6 Tail risk (6-month holding period) Tail12 Tail risk (12-month holding…”
Testing Stylized Facts of Bitcoin Limit Order Books (2019, background): “In recent decades a large body of literature has focused on how to determine a.4 Following Lux and Marchesi (2000) and Kelly and Jiang (2014), we set a to a fixed percentage p of data points, namely 10, 5 and 2.5 percent.”
ESG Shareholder Engagement and Downside Risk (2018, result): “This approach is similar to Kelly and Jiang (2014), who estimate the exposure of firm’s returns to an aggregate tail-risk factor derived from the cross-section of returns.”
Does Systemic Risk in the Financial Sector Predict Future Economic Downturns (2012, methodology): “…Shortfall (MES, see Acharya, Pedersen, Philippon, and Richardson (2010)), CoVaR (Adrian and Brunnermeier (2009)), conditional tail risk (CT R, Kelly (2011)), co-risk (Chan-Lau (2009)), a contingent claims approach (Gray and Jobst (2009)), Shapely values (Tarashev, Borio, and Tsatsaronis…”
Do Industry-Specialist Auditors Influence Stock Price Crash Risk? (2015, neutral): “In the fast-growing literature on tail risk, several studies (e.g., Gabaix 2012; Kelly and Jiang, 2014) have theoretically hypothesized and empirically documented that tail risk increases”