本研究參考Martin (2017) 所提出之理論架構，探討以簡單報酬變異數交換下隱含風險中立變異數（SVIX）為基礎之資產定價因子是否能有效解釋個股橫斷面報酬，並進一步延伸至 SVIX 期限結構之研究。傳統資產定價模型多依賴歷史報酬估計風險暴露，然而 SVIX 可直接由選擇權價格推導，具有前瞻性資訊，能更即時反映市場對未來風險與報酬之預期。因此，本文以 SVIX 建構資產定價因子，並檢驗其對股票報酬之解釋能力。
本研究中首先利用不同到期日選擇權價格建構 30、91、182、365 與 730 日之個股SVIX 指標，並進一步建構以 SVIX 水準及期限結構為基礎之投資組合因子。此外，本文進一步利用主成分分析萃取期限結構中的 level、slope 與 curvature 因子，以探討不同期限風險結構所隱含之資產定價資訊。
在實證方法上，本文採用Fama-MacBeth 兩階段迴歸進行分析，並結合 Fama-French 五因子模型檢驗 SVIX 因子是否具有額外解釋能力。實證結果顯示，高 SVIX 股票與低 SVIX 股票之間存在顯著報酬差異，代表市場對高隱含風險股票要求較高風險溢酬。此外，SVIX 期限結構因子亦對股票報酬具有一定程度之預測能力，尤其在市場動盪期間，短天期 SVIX 上升速度通常高於長天期，顯示市場短期風險預期明顯升高。整體而言，本文結果支持風險中立變異數不僅能反映市場風險情緒，亦具有資產定價意涵，並可作為傳統因子模型之外的重要補充。

This study follows the theoretical framework of Martin (2017) to examine whether asset pricing factors constructed from the risk-neutral variance of simple variance swaps (SVIX) can explain the cross-section of stock returns, and further extends the analysis to the term structure of SVIX. Unlike traditional asset pricing models that rely on historical returns, SVIX is directly inferred from option prices and therefore contains forward-looking information about future risk and expected returns.
This study constructs individual-stock and market-level SVIX measures with maturities of 30, 91, 182, 365, and 730 days, and further develops portfolio factors based on SVIX levels and term structure. Principal component analysis (PCA) is also employed to extract the level, slope, and curvature components of the SVIX term structure.
Empirically, portfolio sorting methods and Fama-MacBeth cross-sectional regressions are adopted, together with the Fama-French five-factor model, to examine the explanatory power of SVIX-based factors. The results show that high-SVIX stocks earn significantly different returns from low-SVIX stocks, indicating that investors require higher risk premiums for stocks with greater implied risk. In addition, SVIX term structure factors exhibit predictive ability for stock returns, particularly during periods of market turbulence when short-term SVIX rises more rapidly than long-term SVIX. Overall, the findings suggest that risk-neutral variance contains important asset pricing information and provides a useful complement to traditional factor models.

Breeden, D. T. and Litzenberger, R. H. (1978). Prices of state-contingent claims implicit in option prices. Journal of business, pages 621–651.
Campbell, J. Y. (1987). Stock returns and the term structure. Journal of Financial Economics, 18(2), 373–399.
Carr, Peter, and Liuren Wu, 2009, Variance risk premiums, Review of Financial Studies, 22, 1311–1341.
Cochrane, J. H. (2009). Asset pricing: Revised edition. Princeton university press.
Eugene F. Fama, & James D. MacBeth (1973). Risk, return, and equilibrium: Empirical tests. Journal of Political Economy, 81(3), 607–636.
Fama, Eugene F., and Kenneth R. French, 1993, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics, 33, 3–56.
Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1–22.
Figlewski, S. (2009). Estimating the implied risk neutral density for the U.S. market portfolio. In T. Bollerslev, J. Russell, & M. Watson (Eds.), Volatility and time series econometrics: Essays in honor of Robert F. Engle (pp. 323–353).
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65–91.
Johnson, T. L. (2017). Risk premia and the VIX term structure. Journal of Financial and Quantitative Analysis, 52(6), 2461–2490.
Kelly, J. L., Jr. (1956). A new interpretation of information rate. Bell System Technical Journal, 35(4), 917–926.
Litterman, R., & Scheinkman, J. (1991). Common factors affecting bond returns. The Journal of Fixed Income, 1(1), 54–61.
Markowitz, H., 1952, Portfolio selection, Journal of Finance, March.
Martin, I. (2017). What is the expected return on the market? Quarterly Journal of Economics, 132(1), 367–433.
Martin, I. W. R., & Wagner, C. (2019). What is the expected return on a stock? Journal of Finance, 74(4), 1887–1929.
Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871–908.
Sharpe, W.F., 1964, Capital asset prices: A theory of market equilibrium under conditions of risk, Journal of Finance, 429-442
Stephen A. Ross, 1976. The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13(3), 341–360.
Turan G. Bali, and Armen Hovakimian, 2009, Volatility Spreads and Expected Stock Returns, Management Science, 55(11), 1797–1812.
Roll, Richard, 1973, Evidence on the “growth-optimum” model, Journal of Finance 28, 551–566.
Xing, Y., Zhang, X., & Zhao, R., 2010, What does the individual option volatility smirk tell us about future equity returns, Journal of Financial and Quantitative Analysis, 45(3), 641–662