Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"West Virginia University" +contributor:("Naomi Boyd"). Showing records 1 – 2 of 2 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters

1. Li, Jingrui. Empirical Asset Pricing with Equity Tail Risk.

Degree: PhD, Finance, 2019, West Virginia University

This dissertation comprises three separate chapters on both risk-neutral and physical probability spaced equity tail risk for both the market index and in the cross-section of individual stocks. The first chapter is titled “Does VIX Truly Measure Return Volatility?” This chapter studies the bias of the VIX index as a volatility measure. Particularly, VIX undervalues (overvalues) volatility when market return is expected to be negatively (positively) skewed. Alternatively, we develop a model-free generalized volatility index (GVIX). This chapter further derives the risk-neutral tail risk estimated from the VIX index. The second chapter is titled “Decomposing the VIX: Implications for the Predictability of Stock Returns” This chapter studies the tail risk for the market index (S&P 500 index) in both risk-neutral and physical probability space and subsequently quantifies the market tail risk premium. Market tail risk premium also is a driving force of the VIX index, especially during a nervous market condition. The VIX decomposed market tail risk premium possesses significant prediction power for the equity market index (S&P500 index), Fama and French style portfolios, and industry portfolios with a prediction range that varies from one month to 12 months. The third chapter is titled “The Predictive Power of Tail Risk Premia on Individual Stock Returns” This chapter studies both the risk-neutral and physical probability space tail risk for the cross-section of individual stocks and examines the characteristics of this premium in the cross-section of stock returns. The tail risk premium for individual stocks is statistically and economically priced in the cross-section of individual stock returns. Specifically, the existence of a premium for bearing negative tail risk is significantly associated with negative returns up to one month in the future. In contrast, the premium for bearing positive tail risk has no significant predictive power. This phenomenon cannot be explained by size, book-to-market ratio, market beta, idiosyncratic volatility, momentum, illiquidity, or lottery effect (maximum and minimum monthly returns). Overall, the results from the three chapters indicate that equity tail risk is an important factor for the market index in both risk-neutral and physical probability spaces, and its premium carries strong return predictability for multiple market-level portfolio assets. Furthermore, equity tail risk and its premium carry significant return prediction power in the cross-section of individual stock returns. This phenomenon is robust to previously documented asset pricing factors. Advisors/Committee Members: K. Victor Chow, Naomi Boyd, Naomi Boyd.

Subjects/Keywords: VIX; Tail Risk; Risk Premium; Return Prediction; Cross-Section of Stock Returns; Return Prediction; Finance and Financial Management

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Li, J. (2019). Empirical Asset Pricing with Equity Tail Risk. (Doctoral Dissertation). West Virginia University. Retrieved from https://doi.org/10.33915/etd.4123 ; https://researchrepository.wvu.edu/etd/4123

Chicago Manual of Style (16th Edition):

Li, Jingrui. “Empirical Asset Pricing with Equity Tail Risk.” 2019. Doctoral Dissertation, West Virginia University. Accessed September 26, 2020. https://doi.org/10.33915/etd.4123 ; https://researchrepository.wvu.edu/etd/4123.

MLA Handbook (7th Edition):

Li, Jingrui. “Empirical Asset Pricing with Equity Tail Risk.” 2019. Web. 26 Sep 2020.

Vancouver:

Li J. Empirical Asset Pricing with Equity Tail Risk. [Internet] [Doctoral dissertation]. West Virginia University; 2019. [cited 2020 Sep 26]. Available from: https://doi.org/10.33915/etd.4123 ; https://researchrepository.wvu.edu/etd/4123.

Council of Science Editors:

Li J. Empirical Asset Pricing with Equity Tail Risk. [Doctoral Dissertation]. West Virginia University; 2019. Available from: https://doi.org/10.33915/etd.4123 ; https://researchrepository.wvu.edu/etd/4123


West Virginia University

2. Murdoch, Scott T. Three Essays on Forecasting in Nonlinear Models.

Degree: PhD, Economics, 2013, West Virginia University

Nonlinear models have many applications in the economic and financial fields. The following works focus on their use for forecasting. Neural networks, in conjunction with an Affine Term Structure Model, are used to discover possible yield curve arbitrage opportunities. A G/ARCH model is employed to test and forecast the conditional variance of state-level employment growth. A Space-Time Autoregressive (STAR) model is applied to state employment growth to ensure that any measure of volatility in the series is not misdirected as employment movements between neighboring states. Advisors/Committee Members: Stratford Douglas, Arabinda Basistha, Naomi Boyd.

Subjects/Keywords: Economics

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Murdoch, S. T. (2013). Three Essays on Forecasting in Nonlinear Models. (Doctoral Dissertation). West Virginia University. Retrieved from https://doi.org/10.33915/etd.531 ; https://researchrepository.wvu.edu/etd/531

Chicago Manual of Style (16th Edition):

Murdoch, Scott T. “Three Essays on Forecasting in Nonlinear Models.” 2013. Doctoral Dissertation, West Virginia University. Accessed September 26, 2020. https://doi.org/10.33915/etd.531 ; https://researchrepository.wvu.edu/etd/531.

MLA Handbook (7th Edition):

Murdoch, Scott T. “Three Essays on Forecasting in Nonlinear Models.” 2013. Web. 26 Sep 2020.

Vancouver:

Murdoch ST. Three Essays on Forecasting in Nonlinear Models. [Internet] [Doctoral dissertation]. West Virginia University; 2013. [cited 2020 Sep 26]. Available from: https://doi.org/10.33915/etd.531 ; https://researchrepository.wvu.edu/etd/531.

Council of Science Editors:

Murdoch ST. Three Essays on Forecasting in Nonlinear Models. [Doctoral Dissertation]. West Virginia University; 2013. Available from: https://doi.org/10.33915/etd.531 ; https://researchrepository.wvu.edu/etd/531

.