Loading...
ESSAYS ON DERIVATIVE PRICING AND CRYPTO FACTOR MODELS
Zhang, Zhaowei
Zhang, Zhaowei
Citations
Altmetric:
Genre
Thesis/Dissertation
Date
2025-05
Advisor
Committee member
Group
Department
Business Administration/Finance
Permanent link to this record
Collections
Research Projects
Organizational Units
Journal Issue
DOI
https://doi.org/10.34944/5zpc-7q13
Abstract
My dissertation explores option pricing and cryptocurrency within the context of asset pricing. The three chapters address different but related research topics.
Chapter 1, developed in collaboration with Gurdip Bakshi and Xiaohui Gao, investigates factor models in cryptocurrency markets. It explores three main questions: (i) What factors influence the performance of cryptocurrency portfolios? (ii) Which of these factors are associated with priced risks? (iii) Can these factors account for observed average returns? Using a cross-sectional approach involving 33 portfolios and 13 factors derived from multiple characteristics, this chapter employs machine-learning techniques to construct and evaluate models. The analysis addresses challenges such as complex interdependencies among characteristics, identifying economically meaningful factors, and handling overlapping attributes.
Chapter 2, drawn from my job market paper, develops a short-maturity model with stochastic jump intensities. The model examines the skewness of stock markets and market volatility at a 7-day-to-expiry (7DTE) horizon, ensuring consistency with out-of-sample observations from 7DTE VIX futures and VIX options. The study identifies a post-COVID-19 weakening in the explanatory power of 7DTE S&P 500 options data for VIX option prices. The proposed model provides a better fit for 7DTE S&P 500 index and VIX futures option prices compared with the existing models.
Chapter 3, also developed with Gurdip Bakshi and Xiaohui Gao, focuses on gold market modeling. It introduces a pricing framework that incorporates: (i) uncertainty from idiosyncratic, jump, unspanned, and spanned risks; (ii) a semi-analytical representation of option risk premiums and prices; and (iii) estimation methods utilizing quasi-maximum likelihood and Kalman filtering. The proposed models reflect key characteristics of the gold market, such as the negative magnitudes of put option risk premiums, which are consistent with the financialization of gold. These models contribute to understanding option pricing, return volatilities, and the behavior of VIXgold(t).
Description
Citation
Citation to related work
Has part
ADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu