Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/138889


Title: 探討牛熊市之市場狀態下波動度風險溢酬與預期報酬
Variance Risk Premium and Expected Returns in Bull and Bear Markets
Authors: 徐躍華
Hsu, Yueh-Hua
Contributors: 林士貴
Lin, Shih-Kuei
徐躍華
Hsu, Yueh-Hua
Keywords: 波動度風險溢酬
報酬可預測性
市場狀態依賴性
高頻資料
Variance risk premium
Return predictability
State dependence
High-frequency data
Date: 2022
Issue Date: 2022-02-10 12:54:51 (UTC+8)
Abstract: 在金融市場中最主要和關鍵的問題是如何預測市場的預期報酬,許多研究顯示預期報酬在很大程度上取決於經濟狀態。波動度風險溢籌已被證實對預期收益的可預測性,這是有個問題浮現在腦中,我們如何知道哪種市場狀態主導了波動度風險溢籌對預期報酬的預測能力?為了研究不同市場狀態下市場預期收益的可預測性差異,我們利用S&P500期貨的高頻數據,區分了20年來熊市或牛市市場狀態下波動度風險溢籌的可預測範圍。我們發現在不同的市場狀態下,市場的型態是截然不同的,它極大地影響了波動度風險溢籌對預期報酬的可預測性。在我們的實證結果中,熊市中的可預測回報時間長度要比牛市中的短。
The principal and critical issue in the financial market is how to predict the market’s expected return and many studies show expected returns depend strongly on the economic times. The variance risk premium has been proved its predictability of expected returns. However, a problem occurs, how do we know which market state dominates the predictability?
In order to investigate the difference in the predictability of expected market returns under different market states, we use high-frequency data of S&P500 futures to differentiate the forecast horizons of variance risk pre- mium in bullish and bearish for over two decades. We realize that mar- ket situations vary in different market states, which tremendously affects the predictability of variance premium. In our empirical investigation, the pre- dictable return horizons in bear markets are shorter than in bull markets.
Reference: Andersen, T. G., Bollerslev, T., Diebold, F. X., & Ebens, H. (2001). The distribution of realized stock return volatility. Journal of Financial Economics, 61(1), 43-76. Retrieved from https://www.sciencedirect.com/science/article/ pii/S0304405X01000551 doi: https://doi.org/10.1016/S0304-405X(01)00055-1

Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2001). The distribution of realized exchange rate volatility. Journal of the American Statistical Association, 96(453), 42-55. Retrieved from https://doi.org/10.1198/016214501750332965 doi: 10.1198/016214501750332965

Bali, T. G., & Zhou, H. (2016). Risk, uncertainty, and expected returns. Journal of Financial and Quantitative Analysis, 51(3), 707–735. doi: 10.1017/ S0022109016000417

Barndorff-Nielsen, O. E., & Shephard, N. (2002). Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society. Series B (Statistical Methodology), 64(2), 253-280. Retrieved from http://www.jstor.org/stable/3088799

Bekaert, G., & Hoerova, M. (2014). The vix, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192. Retrieved from https:// www.sciencedirect.com/science/article/pii/S0304407614001110 (Analysis of Financial Data) doi: https://doi.org/10.1016/j.jeconom.2014.05.008

Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of political economy, 81(3), 637.

Bollerslev, T., Marrone, J., Xu, L., & Zhou, H. (2014). Stock return predictability and variance risk premia: Statistical inference and international evidence. Journal of Financial and Quantitative Analysis, 49(3), 633–661. doi: 10.1017/ S0022109014000453

Bollerslev, T., Tauchen, G., & Zhou, H. (2009). Expected Stock Returns and Variance Risk Premia. The Review of Financial Studies, 22(11), 4463-4492. Retrieved from https://doi.org/10.1093/rfs/hhp008 doi: 10.1093/rfs/hhp008

Campbell, J. Y., & Hentschel, L. (1992). No news is good news: An asymmetric model of changing volatility in stock returns. Journal of Financial Economics, 31(3), 281-318. Retrieved from https://www.sciencedirect.com/science/article/pii/ 0304405X9290037X doi: https://doi.org/10.1016/0304-405X(92)90037-X

Cheema, M., Nartea, G., & Man, Y. (2018). Cross-sectional and time-series momentum returns and market states. International Review of Finance, 18, 705-715. doi: 10 .1111/irfi.12148

Choi, H., Mueller, P., & Vedolin, A. (2017). Bond Variance Risk Premiums*. Review of Finance, 21(3), 987-1022. Retrieved from https://doi.org/10.1093/rof/rfw072 doi: 10.1093/rof/rfw072

Cochrane, J. H. (2008). The dog that did not bark: A defense of return predictability. The Review of Financial Studies, 21(4), 1533-1575. Retrieved from http://www.jstor .org/stable/40056861

Dangl, T., & Halling, M. (2008). Predictive regressions with time-varying coefficients. Journal of Financial Economics, 106. doi: 10.2139/ssrn.971712

French, K. R., Schwert, G., & Stambaugh, R. F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19(1), 3-29. Retrieved from https://www.sciencedirect.com/science/article/pii/0304405X87900262 doi: https://doi .org/10.1016/0304-405X(87)90026-2

Hammerschmid, R., & Lohre, H. (2017). Regime shifts and stock return predictability. International Review of Economics Finance, 56. doi: 10.1016/j.iref.2017.10.021

Han, B., & Zhou, Y. (2011). Variance risk premium and cross-section of stock returns. SSRN Electronic Journal. doi: 10.2139/ssrn.1785540

Henkel, S., Martin, J., & Nardari, F. (2008). Time-varying short-horizon predictability. SSRN Electronic Journal. doi: 10.2139/ssrn.1177375

Kilic, M., & Shaliastovich, I. (2019). Good and bad variance premia and expected returns. Management Science, 65(6), 2522-2544. Retrieved from https://doi.org/10.1287/mnsc.2017.2890 doi: 10.1287/mnsc.2017.2890Lewellen, J. (2004). Predicting returns with financial ratios. Journal of Financial Economics, 74(2), 209-235. Retrieved from https://www.sciencedirect.com/science/ article/pii/S0304405X04000686 doi: https://doi.org/10.1016/j.jfineco.2002.11 .002

Li, X., & Zakamulin, V. (2020). Stock volatility predictability in bull and bear markets. Quantitative Finance, 20, 1-19. doi: 10.1080/14697688.2020.1725101

Lunde, A., & Timmermann, A. (2004). Duration dependence in stock prices: An analysis of bull and bear markets. Journal of Business & Economic Statistics, 22, 253-273. doi: 10.1197/073500104000000136
Merton, R. C. (1976). Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics, 3(1), 125-144. Retrieved from https:// www.sciencedirect.com/science/article/pii/0304405X76900222 doi: https:// doi.org/10.1016/0304-405X(76)90022-2

Newey, W. K., & West, K. D. (1994). Automatic lag selection in covariance matrix estimation. The Review of Economic Studies, 61(4), 631-653. Retrieved from http://www.jstor.org/stable/2297912

Prokopczuk, M., & Simen, C. (2013). Variance risk premia in commodity markets. SSRN Electronic Journal. doi: 10.2139/ssrn.2195691

Sossounov, K., & Pagan, A. (2003). A simple framework for analyzing bull and bear markets. Journal of Applied Econometrics, 18, 23-46. doi: 10.1002/jae.664

Welch, I., & Goyal, A. (2007). A Comprehensive Look at The Empirical Performance of Equity Premium Prediction. The Review of Financial Studies, 21(4), 1455-1508. Retrieved from https://doi.org/10.1093/rfs/hhm014 doi: 10.1093/rfs/hhm014

Whitelaw, R. F. (1994). Time variations and covariations in the expectation and volatility of stock market returns. The Journal of Finance, 49(2), 515-541. Retrieved from http://www.jstor.org/stable/2329161
Description: 碩士
國立政治大學
金融學系
109352009
Source URI: http://thesis.lib.nccu.edu.tw/record/#G0109352009
Data Type: thesis
Appears in Collections:[金融學系] 學位論文

Files in This Item:

File Description SizeFormat
200901.pdf610KbAdobe PDF0View/Open


All items in 學術集成 are protected by copyright, with all rights reserved.


社群 sharing