Conditional extreme risk, black swan hedging, and asset prices

S. Ghon RHEE; Feng Harry WU

doi:10.1016/j.jempfin.2020.07.002

Conditional extreme risk, black swan hedging, and asset prices

S. Ghon RHEE^*
, Feng Harry WU^*

^*Corresponding author for this work

Department of Accountancy

Research output: Journal Publications › Journal Article (refereed) › peer-review

3 Citations (Scopus)

Abstract

Motivated by the asset pricing theory with safety-first preference, we introduce and operationalize a conditional extreme risk (CER) measure to describe expected stock performance conditional on a small-probability market downturn (black swan). We document a significant CER premium in the cross-section of expected returns. We also demonstrate that CER explains the premia to downside beta, coskewness, and cokurtosis. CER provides distinct information regarding black swan hedging that cannot be captured by co-crash-based tail dependence measures. As we find that the pricing effect is stronger among black swan hedging stocks, this distinction helps explain the absence of premium to tail dependence.

Original language	English
Pages (from-to)	412-435
Number of pages	24
Journal	Journal of Empirical Finance
Volume	58
Early online date	6 Jul 2020
DOIs	https://doi.org/10.1016/j.jempfin.2020.07.002
Publication status	Published - Sept 2020

Bibliographical note

This paper was nominated for the “Best Paper Award” at 2015 Financial Management Association International (FMA) annual meeting. Thanks go to Andrew Ang, Jeffrey Callen, Agnes Cheng, Louis Cheng, Timothy Chue, Campbell Harvey, David Hirshleifer, Byoung Kang, George Jiang, Huiwen Lai, Gang Li, Ji-Chai Lin, William Megginson, James Ohlson, Baochun Peng, Jean-Guy Simonato (FMA discussant), Nancy Su, Wilson Tong, Steven Wei, Kevin Zhu and participants of the FMA annual meeting (Orlando) and the seminar at Hong Kong Polytechnic University. The usual disclaimers apply.

Funding

Feng (Harry) Wu gratefully acknowledges financial support from the General Research Fund (GRF) (No. 15507314) of the University Grants Committee of Hong Kong. This paper also benefits from the supports from General Research Fun (GRF), Hong Kong No. 15507015 , Hong Kong Polytechnic University research funds (1-ZE46 and G-YN81), and Lingnan University research funds, Hong Kong. Ghon Rhee is grateful for the 2018 Shidler College of Business Summer Research Grant.

Keywords

Asset pricing
Black swan hedging
Conditional extreme risk
Extreme value theory
Safety-first

Access to Document

10.1016/j.jempfin.2020.07.002

Cite this

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title = "Conditional extreme risk, black swan hedging, and asset prices",

abstract = "Motivated by the asset pricing theory with safety-first preference, we introduce and operationalize a conditional extreme risk (CER) measure to describe expected stock performance conditional on a small-probability market downturn (black swan). We document a significant CER premium in the cross-section of expected returns. We also demonstrate that CER explains the premia to downside beta, coskewness, and cokurtosis. CER provides distinct information regarding black swan hedging that cannot be captured by co-crash-based tail dependence measures. As we find that the pricing effect is stronger among black swan hedging stocks, this distinction helps explain the absence of premium to tail dependence.",

keywords = "Asset pricing, Black swan hedging, Conditional extreme risk, Extreme value theory, Safety-first",

author = "RHEE, \{S. Ghon\} and WU, \{Feng Harry\}",

note = "This paper was nominated for the {\textquotedblleft}Best Paper Award{\textquotedblright} at 2015 Financial Management Association International (FMA) annual meeting. Thanks go to Andrew Ang, Jeffrey Callen, Agnes Cheng, Louis Cheng, Timothy Chue, Campbell Harvey, David Hirshleifer, Byoung Kang, George Jiang, Huiwen Lai, Gang Li, Ji-Chai Lin, William Megginson, James Ohlson, Baochun Peng, Jean-Guy Simonato (FMA discussant), Nancy Su, Wilson Tong, Steven Wei, Kevin Zhu and participants of the FMA annual meeting (Orlando) and the seminar at Hong Kong Polytechnic University. The usual disclaimers apply.",

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N2 - Motivated by the asset pricing theory with safety-first preference, we introduce and operationalize a conditional extreme risk (CER) measure to describe expected stock performance conditional on a small-probability market downturn (black swan). We document a significant CER premium in the cross-section of expected returns. We also demonstrate that CER explains the premia to downside beta, coskewness, and cokurtosis. CER provides distinct information regarding black swan hedging that cannot be captured by co-crash-based tail dependence measures. As we find that the pricing effect is stronger among black swan hedging stocks, this distinction helps explain the absence of premium to tail dependence.

AB - Motivated by the asset pricing theory with safety-first preference, we introduce and operationalize a conditional extreme risk (CER) measure to describe expected stock performance conditional on a small-probability market downturn (black swan). We document a significant CER premium in the cross-section of expected returns. We also demonstrate that CER explains the premia to downside beta, coskewness, and cokurtosis. CER provides distinct information regarding black swan hedging that cannot be captured by co-crash-based tail dependence measures. As we find that the pricing effect is stronger among black swan hedging stocks, this distinction helps explain the absence of premium to tail dependence.

KW - Asset pricing

KW - Black swan hedging

KW - Conditional extreme risk

KW - Extreme value theory

KW - Safety-first

UR - https://www.scopus.com/pages/publications/85088831417

U2 - 10.1016/j.jempfin.2020.07.002

DO - 10.1016/j.jempfin.2020.07.002

M3 - Journal Article (refereed)

SN - 0927-5398

VL - 58

SP - 412

EP - 435

JO - Journal of Empirical Finance

JF - Journal of Empirical Finance

ER -

Conditional extreme risk, black swan hedging, and asset prices

Abstract

Bibliographical note

Funding

Keywords

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Conditional extreme risk, black swan hedging, and asset prices

Cite this