Frequency Dependent Risk

Andreas Neuhierl, Rasmus T. Varneskov

Research output: Contribution to conferencePaperResearchpeer-review

Abstract

This paper provides a new nonparametric framework for studying the dynamics of the state vector and its associated risk prices. Specifically, in a general setting where the SDF decomposes into permanent and transitory components, we analyze their contribution to the unconditional asset return premium using frequency domain techniques. We show analytically that the co-spectrum between returns and the SDF only displays frequency dependencies through its transitory components, that is, through the state vector. Moreover, we demonstrate that state vector dynamics and its risk prices can be uncovered by studying (transformations of) the covariance between (portfolios of) asset returns. We introduce two new frequency risk measures. We apply our framework to study frequency risk in the full cross-section of US stocks, utilizing the market, value, size and momentum factors as baseline portfolios to construct the risk measures. Our analysis uncovers the existence of, at least, two significantly priced low-frequency risk factors, one of which commands a large positive risk premium of 6% per year. Moreover, we document, at least, one high-frequency component in the state vector that is significantly priced. Importantly, we show that these frequency dependent risk factors are unspanned by a battery of appraised risk factors and characteristics. Our analysis demonstrates that multiple state vector components with varying persistence and risk prices are needed to be consistent with the cross-section. Throughout, we contrast our findings with the implications of the long-run risk model, the dynamic disaster model as well as a regime-switching CCAPM, providing new analytical results for such models.
Original languageEnglish
Publication date2019
Number of pages50
Publication statusPublished - 2019
EventMidwest Finance Association 2019 Annual Meeting - Radisson Blu Aqua Hotel, Chicago, United States
Duration: 7 Mar 20199 Mar 2019
Conference number: 68
https://www.openconf.org/MidwestFinance2019/modules/request.php?module=oc_program&action=program.php&p=program

Conference

ConferenceMidwest Finance Association 2019 Annual Meeting
Number68
LocationRadisson Blu Aqua Hotel
CountryUnited States
CityChicago
Period07/03/201909/03/2019
Internet address

Keywords

  • Asset pricing
  • Factor models
  • Nonparametric measures
  • Spectral analysis

Cite this

Neuhierl, A., & Varneskov, R. T. (2019). Frequency Dependent Risk. Paper presented at Midwest Finance Association 2019 Annual Meeting , Chicago, United States.
Neuhierl, Andreas ; Varneskov, Rasmus T. / Frequency Dependent Risk. Paper presented at Midwest Finance Association 2019 Annual Meeting , Chicago, United States.50 p.
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Neuhierl, A & Varneskov, RT 2019, 'Frequency Dependent Risk' Paper presented at, Chicago, United States, 07/03/2019 - 09/03/2019, .

Frequency Dependent Risk. / Neuhierl, Andreas; Varneskov, Rasmus T.

2019. Paper presented at Midwest Finance Association 2019 Annual Meeting , Chicago, United States.

Research output: Contribution to conferencePaperResearchpeer-review

TY - CONF

T1 - Frequency Dependent Risk

AU - Neuhierl, Andreas

AU - Varneskov, Rasmus T.

PY - 2019

Y1 - 2019

N2 - This paper provides a new nonparametric framework for studying the dynamics of the state vector and its associated risk prices. Specifically, in a general setting where the SDF decomposes into permanent and transitory components, we analyze their contribution to the unconditional asset return premium using frequency domain techniques. We show analytically that the co-spectrum between returns and the SDF only displays frequency dependencies through its transitory components, that is, through the state vector. Moreover, we demonstrate that state vector dynamics and its risk prices can be uncovered by studying (transformations of) the covariance between (portfolios of) asset returns. We introduce two new frequency risk measures. We apply our framework to study frequency risk in the full cross-section of US stocks, utilizing the market, value, size and momentum factors as baseline portfolios to construct the risk measures. Our analysis uncovers the existence of, at least, two significantly priced low-frequency risk factors, one of which commands a large positive risk premium of 6% per year. Moreover, we document, at least, one high-frequency component in the state vector that is significantly priced. Importantly, we show that these frequency dependent risk factors are unspanned by a battery of appraised risk factors and characteristics. Our analysis demonstrates that multiple state vector components with varying persistence and risk prices are needed to be consistent with the cross-section. Throughout, we contrast our findings with the implications of the long-run risk model, the dynamic disaster model as well as a regime-switching CCAPM, providing new analytical results for such models.

AB - This paper provides a new nonparametric framework for studying the dynamics of the state vector and its associated risk prices. Specifically, in a general setting where the SDF decomposes into permanent and transitory components, we analyze their contribution to the unconditional asset return premium using frequency domain techniques. We show analytically that the co-spectrum between returns and the SDF only displays frequency dependencies through its transitory components, that is, through the state vector. Moreover, we demonstrate that state vector dynamics and its risk prices can be uncovered by studying (transformations of) the covariance between (portfolios of) asset returns. We introduce two new frequency risk measures. We apply our framework to study frequency risk in the full cross-section of US stocks, utilizing the market, value, size and momentum factors as baseline portfolios to construct the risk measures. Our analysis uncovers the existence of, at least, two significantly priced low-frequency risk factors, one of which commands a large positive risk premium of 6% per year. Moreover, we document, at least, one high-frequency component in the state vector that is significantly priced. Importantly, we show that these frequency dependent risk factors are unspanned by a battery of appraised risk factors and characteristics. Our analysis demonstrates that multiple state vector components with varying persistence and risk prices are needed to be consistent with the cross-section. Throughout, we contrast our findings with the implications of the long-run risk model, the dynamic disaster model as well as a regime-switching CCAPM, providing new analytical results for such models.

KW - Asset pricing

KW - Factor models

KW - Nonparametric measures

KW - Spectral analysis

KW - Asset pricing

KW - Factor models

KW - Nonparametric measures

KW - Spectral analysis

M3 - Paper

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Neuhierl A, Varneskov RT. Frequency Dependent Risk. 2019. Paper presented at Midwest Finance Association 2019 Annual Meeting , Chicago, United States.