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題名 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作者 徐躍華
Hsu, Yueh-Hua貢獻者 林士貴
Lin, Shih-Kuei
徐躍華
Hsu, Yueh-Hua關鍵詞 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日期 2022 上傳時間 10-Feb-2022 12:54:51 (UTC+8) 摘要 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.參考文獻 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)00055-1Andersen, 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: 10.1198/016214501750332965Bali, T. G., & Zhou, H. (2016). Risk, uncertainty, and expected returns. Journal of Financial and Quantitative Analysis, 51(3), 707–735. doi: 10.1017/ S0022109016000417Barndorff-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/3088799Bekaert, 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.2014.05.008Black, 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/ S0022109014000453Bollerslev, 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/hhp008Campbell, 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-XCheema, 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.12148Choi, 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/rfw072Cochrane, 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/40056861Dangl, T., & Halling, M. (2008). Predictive regressions with time-varying coefficients. Journal of Financial Economics, 106. doi: 10.2139/ssrn.971712French, 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)90026-2Hammerschmid, R., & Lohre, H. (2017). Regime shifts and stock return predictability. International Review of Economics Finance, 56. doi: 10.1016/j.iref.2017.10.021Han, B., & Zhou, Y. (2011). Variance risk premium and cross-section of stock returns. SSRN Electronic Journal. doi: 10.2139/ssrn.1785540Henkel, S., Martin, J., & Nardari, F. (2008). Time-varying short-horizon predictability. SSRN Electronic Journal. doi: 10.2139/ssrn.1177375Kilic, 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 .002Li, X., & Zakamulin, V. (2020). Stock volatility predictability in bull and bear markets. Quantitative Finance, 20, 1-19. doi: 10.1080/14697688.2020.1725101Lunde, 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: 10.1197/073500104000000136Merton, 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)90022-2Newey, 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/2297912Prokopczuk, M., & Simen, C. (2013). Variance risk premia in commodity markets. SSRN Electronic Journal. doi: 10.2139/ssrn.2195691Sossounov, K., & Pagan, A. (2003). A simple framework for analyzing bull and bear markets. Journal of Applied Econometrics, 18, 23-46. doi: 10.1002/jae.664Welch, 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/hhm014Whitelaw, 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 描述 碩士
國立政治大學
金融學系
109352009資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109352009 資料類型 thesis dc.contributor.advisor 林士貴 zh_TW dc.contributor.advisor Lin, Shih-Kuei en_US dc.contributor.author (Authors) 徐躍華 zh_TW dc.contributor.author (Authors) Hsu, Yueh-Hua en_US dc.creator (作者) 徐躍華 zh_TW dc.creator (作者) Hsu, Yueh-Hua en_US dc.date (日期) 2022 en_US dc.date.accessioned 10-Feb-2022 12:54:51 (UTC+8) - dc.date.available 10-Feb-2022 12:54:51 (UTC+8) - dc.date.issued (上傳時間) 10-Feb-2022 12:54:51 (UTC+8) - dc.identifier (Other Identifiers) G0109352009 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/138889 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 金融學系 zh_TW dc.description (描述) 109352009 zh_TW dc.description.abstract (摘要) 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。 zh_TW dc.description.abstract (摘要) 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. en_US dc.description.tableofcontents 摘要 iAbstract iiContents iiiList of Figures vList of Tables vi1 Introduction 11.1 Related literatures 32 Methodology 62.1 Bull and bear market labeling algorithm 62.1.1 Bear market state switches to bull market state 62.1.2 Bull market state switches to bear market state 72.2 Variance risk premium 72.2.1 Implied variance 82.2.2 Realized variance 82.2.3 Variance risk premium 92.3 Predictability return regression 93 Empirical Results 113.1 Label bull and bear market states 113.2 Variance risk premium 123.3 Predictability in bull and bear markets 174 Conclusion and future works 194.1 Conclusion 194.2 Future works 20References 21 zh_TW dc.format.extent 625651 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109352009 en_US dc.subject (關鍵詞) 波動度風險溢酬 zh_TW dc.subject (關鍵詞) 報酬可預測性 zh_TW dc.subject (關鍵詞) 市場狀態依賴性 zh_TW dc.subject (關鍵詞) 高頻資料 zh_TW dc.subject (關鍵詞) Variance risk premium en_US dc.subject (關鍵詞) Return predictability en_US dc.subject (關鍵詞) State dependence en_US dc.subject (關鍵詞) High-frequency data en_US dc.title (題名) 探討牛熊市之市場狀態下波動度風險溢酬與預期報酬 zh_TW dc.title (題名) Variance Risk Premium and Expected Returns in Bull and Bear Markets en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 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)00055-1Andersen, 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: 10.1198/016214501750332965Bali, T. G., & Zhou, H. (2016). Risk, uncertainty, and expected returns. Journal of Financial and Quantitative Analysis, 51(3), 707–735. doi: 10.1017/ S0022109016000417Barndorff-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/3088799Bekaert, 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.2014.05.008Black, 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/ S0022109014000453Bollerslev, 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/hhp008Campbell, 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-XCheema, 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.12148Choi, 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/rfw072Cochrane, 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/40056861Dangl, T., & Halling, M. (2008). Predictive regressions with time-varying coefficients. Journal of Financial Economics, 106. doi: 10.2139/ssrn.971712French, 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)90026-2Hammerschmid, R., & Lohre, H. (2017). Regime shifts and stock return predictability. International Review of Economics Finance, 56. doi: 10.1016/j.iref.2017.10.021Han, B., & Zhou, Y. (2011). Variance risk premium and cross-section of stock returns. SSRN Electronic Journal. doi: 10.2139/ssrn.1785540Henkel, S., Martin, J., & Nardari, F. (2008). Time-varying short-horizon predictability. SSRN Electronic Journal. doi: 10.2139/ssrn.1177375Kilic, 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 .002Li, X., & Zakamulin, V. (2020). Stock volatility predictability in bull and bear markets. Quantitative Finance, 20, 1-19. doi: 10.1080/14697688.2020.1725101Lunde, 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: 10.1197/073500104000000136Merton, 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)90022-2Newey, 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/2297912Prokopczuk, M., & Simen, C. (2013). Variance risk premia in commodity markets. SSRN Electronic Journal. doi: 10.2139/ssrn.2195691Sossounov, K., & Pagan, A. (2003). A simple framework for analyzing bull and bear markets. Journal of Applied Econometrics, 18, 23-46. doi: 10.1002/jae.664Welch, 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/hhm014Whitelaw, 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 zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202200106 en_US
