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題名 整體信用違約交換之衡量：輔以自然語言分析新聞文本及FOMC會議情緒
Explaining Aggregate Credit Default Swap Spreads with News and FOMC Meetings Sentiment Based on Natural Language Analysis作者 張辰煜
Chang, Chen-Yu貢獻者 江彌修
Chiang, Mi-Hsiu
張辰煜
Chang, Chen-Yu關鍵詞 信用違約交換
CDX
BERT
FOMC
新聞情緒
金融危機
新冠肺炎
CDS
CDX
BERT
FOMC
News sentiment
Financial crisis
COVID-19日期 2023 上傳時間 6-Jul-2023 16:46:31 (UTC+8) 摘要 本研究以5年期北美投資等級信用違約交換指數利差變化作為主體，嘗試以BERT模型對財金文本進行領域遷移，分析FOMC政策聲明、會議記錄與不同頻率之新聞情緒，結合傳統模型的因子及債券利差、通膨等總體市場數據作為模型變數，並且切分次貸風暴與新冠肺炎期間，試圖更加全面地理解信用市場的機制。根據一般迴歸與分量迴歸的實證結果，發現利差的影響因子會隨著時段變化且敏感性差異巨大，結構模型的變數仍為利差變化的主導因子，又以S&P 500報酬率最為重要，且在市場動盪時具不對稱性。關於市場相關變數，於聯準會貨幣政策大幅激進的時段，美債利率與長短債利差可能產生不同於預期之正向影響，代理流動性的買賣價差在利差大幅緊縮或放寬時呈現非線性之結構，通膨方面的變數也顯示符合預期的正向影響。再者，FOMC會議記錄的情緒相較於政策聲明對解釋利差更具有貢獻性，短期的新聞情緒會有激勵信用市場的作用，但長期而言，FOMC與新聞情緒皆反應出較落後的訊息將會惡化信用市場，呈現正向的影響。最後，根據向量自我迴歸模型的結果來分析信用市場與股票市場之間的領先落後關係，可於金融危機前與疫情間觀察到相互的領先落後關係，而金融危機前信用市場資訊流進股票市場較為快速。並可於金融危機與金融危機後觀察到股票市場領先信用市場的情況，而金融危機後的領先速度又快於金融危機時。此結果顯示總體利差變化的確為股票市場的投資者提供了一定的訊息，或許也包含了關於金融系統性風險的相關衡量。
We examine risk factors that explain daily changes in CDX.NA.IG.5Y spreads before, during and after the 2007–2009 financial crisis and COVID-19 pandemic. We apply BERT model performing domain adaption for financial corpus to analyze the sentiment of FOMC statements, minutes, and news at different frequencies. Then, combine factors from traditional model and macroeconomic data as variables, aiming to gain a more comprehensive understanding of the mechanisms of the credit market.Based on the empirical results of OLS and quantile regression, the determinants of CDX spreads are varying through time and factor sensitivities changes significantly. Spread changes are mainly determined by structural model factors especially S&P 500 return. Regarding market variables, US bond yields and yield spreads have unexpected positive influence during periods of aggressive monetary policy by FED. Liquidity proxy variable shows some nonlinearities when the spread largely tightens or widens and factors about inflation possess positive effect as expected. Furthermore, the sentiment of FOMC minutes contributes more to explaining the spread than statements. Short-term news sentiment stimulates the credit market, but in the long term, both FOMC and news sentiment reflect that lagged information worsens the credit market, showing a positive effect.Finally, we examine the lead–lag relationship between spread changes and stock returns through VAR model. Stock market returns lead spread changes during and after the crisis period, while a bidirectional relationship emerges before the crisis period and during the pandemic. This suggests that aggregate spread changes are actually informative for equity market participants, possibly measuring systemic risk.參考文獻 Alexander, C., and Kaeck, A. (2008). Regime dependent determinants of credit default swap spreads. Journal of Banking and Finance, 32(6), 1008-21.Annaert, J., De Ceuster, M., Van Roy, P., and Vespro, C. (2013). What determines Euro area bank CDS spreads? Journal of International Money and Finance, 32, 444-461.Araci, D. (2019). Finbert: Financial sentiment analysis with pre-trained language models. arXiv preprint arXiv:1908.10063.Belke, A., and Gokus, C. (2011). Volatility patterns of CDS, bond and stock markets before and during the financial crisis-evidence from major financial institutions. Ruhr Economic Paper, 243.Benkert, C. (2004). Explaining credit default swap premia. Journal of Futures Markets, 24(1), 71–92.Blanco, R., Brennan, S., and Marsh, I. W. (2005). An empirical analysis of the dynamic relationship between investment grade bonds and credit default swap, Journal of Finance, 60(5), 2255-2281.Blei, D., NG, A., and Jordan, M. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993-1022.Bloomfield, R. (2008). Discussion of Annual Report Readability, Current Earnings, and Earnings Persistence. Journal of Accounting and Economics, 45(2)(3), 248-252.Boukus, E., and Rosenberg, J. V. (2006). The Information Content of FOMC Minutes. Working paper, Federal Reserve Bank of New York.Breitenfellner, B., and Wagner, N. (2012). Explaining aggregate credit default swap spreads. International Review of Financial Analysis, 22, 18-29.Byström, H. (2005). Credit Default Swaps and Equity Prices: The iTraxx CDS Index Market. Working Paper, Lund University, Department of Economics.Byström, H. (2006). CreditGrades and the iTraxx CDS Index Market. Financial Analysts Journal, 62, 65-76.Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605.Collin-Dufresne, P., Goldstein, R. S., and Martin, J. S. (2001). The determinants of credit spread changes. Journal of Finance, 56(6), 2177-207.Cossin, D., Hricko, T., Aunon-Nerin, D., and Huang, Z. (2002). Exploring for the determinants of credit risk in credit default swap transaction data: Is fixed-income markets’ information sufficient to evaluate credit risk? FAME Research Paper, 65.Davis, A. K., and Tama-Sweet, I. (2012). Managers’Use of Language Across Alternative Disclosure Outlets: Earnings Press Releases Versus MD&A. Contemporary Accounting Research. 29(3), 804-837.Devlin, J., Chang, M. W., Lee, K., and Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.Dzielinski, M. (2011). News sensitivity and the cross-section of stock returns. NCCR FINRISK 719, University of Zurich.Ericsson, J., Jacobs, K., and Oviedo, R. (2009). The determinants of credit default swap premia. Journal of Financial and Quantitative Analysis, 44(1), 109–132.Friewald, N., Wagner, C., and Zechner, J. (2014). The cross-section of credit risk premia and equity returns. Journal of Finance, 69(6), 2419-2469.Fung, H.G., Sierra, G. E., Yau, J., and Zhang, G. (2008). Are the U.S. stock market and credit default swap market related? Evidence from the CDX Indices. Journal of Alternative Investments, 11(1), 43-61.Garcia, D. (2013). Sentiment During Recessions. Journal of Finance, 68(3), 1267-1300.Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-Spectral Methods, Econometrica, 37(3), 424-438.Hannan, E., and Quinn, B. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society. Series B (Methodological), 41(2), 190–195.Hassan, M., Ngow, T., Yu, JS., and Hassan, A. (2013). Determinants of credit default swaps spreads in European and Asian markets. Journal of Derivatives & Hedge Funds, 19, 295–310.Henry, E. (2008). Are Investors Influenced by How Earnings Press Releases Are Written? Journal of Business Communication, 45(4), 363-407.Heston, S. L., and Sinha, N. R. (2015). News Versus Sentiment: Predicting Stock Returns from News Stories. Working paper, University of Maryland.Houweling, P., and Vorst, T., 2005. Pricing default swaps: Empirical evidence. Journal of International Money and Finance, 24 (8), 1200–1225.Huang, A. H., Lehavy, R., Zang, A. Y., and Zheng, R. (2015). Analyst Information Discovery and Interpretation Roles: A Topic Modeling Approach. Working paper, University of Michigan.Huang, J. Z., and Kong, W. (2007). Macroeconomic news announcements and corporate bond credit spreads. Working Paper, Penn State University.Koenker, R., and Bassett Jr, G. (1978). Regression quantiles. Econometrica, 46(1), 33-50.Koenker, R., and Hallock, K. F. (2001). Quantile regression. Journal of Economic Perspectives, 15(4), 143–156.Koenker, R., and Machado, A. F. (1999). Goodness of Fit and Related Inference Processes for Quantile Regression. Journal of the American Statistical Association, 94(448), 1296-1310.Li, F. (2008). Annual Report Readability, Current Earnings, and Earnings Persistence. Journal of Accounting and Economics, 45(2)(3), 221-247.Liao, S. L., and Chang, J. J. (2010). Economic determinants of default risks and their impacts on credit derivative pricing. Journal of Futures Markets, 30(11), 1058-1081.Liberti, J. M., and Petersen, M. A. (2019). Information: Hard and soft. Review of Corporate Finance Studies, 8(1), 1–41.Longstaff, F., and Rajan, A. (2008). An empirical analysis of the pricing of collateralized debt obligations. Journal of Finance, 63(2), 529–563.Loughran, T., and Mcdonald, B. (2011). When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks. Journal of Finance, 66(1), 35-65.Loughran, T., and Mcdonald, B. (2014). Measuring Readability in Financial Disclosures. Journal of Finance, 69(4), 1643-1671.Loughran, T., and McDonald, B. (2016). Textual analysis in accounting and finance: A survey. Journal of Accounting Research, 54(4), 1187-1230.Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2), 449–470.Price, S. M., Doran, J. S., Peterson, D. R., and Bliss, B. A. (2012). Earnings Conference Calls and Stock Returns: The Incremental Informativeness of Textual Tone. Journal of Banking & Finance, 36(4), 992-1011.Rosa, C. (2013). The financial market effect of FOMC minutes. Federal Reserve Bank of New York Economic Policy Review, 19(2), 67-81.Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1-48.Smales, L. A. (2016), News Sentiment and Bank Credit Risk, Journal of Empirical Finance, 38, 37-61.Tang, D.Y., and Yan, H. (2006). Macroeconomic conditions, firm characteristics, and credit spreads. Journal of Financial Services Research, 29(3), 177-210.Tang, D.Y., and Yan, H. (2010). Market conditions, default risk and credit spreads. Journal of Banking & Finance, 34(4), 743-753.Tetlock, P. (2007). Giving Content to Investor Sentiment: The Role of Media in the Stock Market. Journal of Finance, 62(3), 1139-1168.Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., and Polosukhin, I. (2017). Attention is all you need. In Advances in Neural Information Processing Systems, 6000–6010.Yang, S., Liu, Z., and Wang, X. (2020), News Sentiment, Credit Spreads, and Information Asymmetry, The North American Journal of Economics and Finance, 52, 101179. 描述 碩士
國立政治大學
金融學系
110352010資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110352010 資料類型 thesis dc.contributor.advisor 江彌修 zh_TW dc.contributor.advisor Chiang, Mi-Hsiu en_US dc.contributor.author (Authors) 張辰煜 zh_TW dc.contributor.author (Authors) Chang, Chen-Yu en_US dc.creator (作者) 張辰煜 zh_TW dc.creator (作者) Chang, Chen-Yu en_US dc.date (日期) 2023 en_US dc.date.accessioned 6-Jul-2023 16:46:31 (UTC+8) - dc.date.available 6-Jul-2023 16:46:31 (UTC+8) - dc.date.issued (上傳時間) 6-Jul-2023 16:46:31 (UTC+8) - dc.identifier (Other Identifiers) G0110352010 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/145858 - 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) 110352010 zh_TW dc.description.abstract (摘要) 本研究以5年期北美投資等級信用違約交換指數利差變化作為主體，嘗試以BERT模型對財金文本進行領域遷移，分析FOMC政策聲明、會議記錄與不同頻率之新聞情緒，結合傳統模型的因子及債券利差、通膨等總體市場數據作為模型變數，並且切分次貸風暴與新冠肺炎期間，試圖更加全面地理解信用市場的機制。根據一般迴歸與分量迴歸的實證結果，發現利差的影響因子會隨著時段變化且敏感性差異巨大，結構模型的變數仍為利差變化的主導因子，又以S&P 500報酬率最為重要，且在市場動盪時具不對稱性。關於市場相關變數，於聯準會貨幣政策大幅激進的時段，美債利率與長短債利差可能產生不同於預期之正向影響，代理流動性的買賣價差在利差大幅緊縮或放寬時呈現非線性之結構，通膨方面的變數也顯示符合預期的正向影響。再者，FOMC會議記錄的情緒相較於政策聲明對解釋利差更具有貢獻性，短期的新聞情緒會有激勵信用市場的作用，但長期而言，FOMC與新聞情緒皆反應出較落後的訊息將會惡化信用市場，呈現正向的影響。最後，根據向量自我迴歸模型的結果來分析信用市場與股票市場之間的領先落後關係，可於金融危機前與疫情間觀察到相互的領先落後關係，而金融危機前信用市場資訊流進股票市場較為快速。並可於金融危機與金融危機後觀察到股票市場領先信用市場的情況，而金融危機後的領先速度又快於金融危機時。此結果顯示總體利差變化的確為股票市場的投資者提供了一定的訊息，或許也包含了關於金融系統性風險的相關衡量。 zh_TW dc.description.abstract (摘要) We examine risk factors that explain daily changes in CDX.NA.IG.5Y spreads before, during and after the 2007–2009 financial crisis and COVID-19 pandemic. We apply BERT model performing domain adaption for financial corpus to analyze the sentiment of FOMC statements, minutes, and news at different frequencies. Then, combine factors from traditional model and macroeconomic data as variables, aiming to gain a more comprehensive understanding of the mechanisms of the credit market.Based on the empirical results of OLS and quantile regression, the determinants of CDX spreads are varying through time and factor sensitivities changes significantly. Spread changes are mainly determined by structural model factors especially S&P 500 return. Regarding market variables, US bond yields and yield spreads have unexpected positive influence during periods of aggressive monetary policy by FED. Liquidity proxy variable shows some nonlinearities when the spread largely tightens or widens and factors about inflation possess positive effect as expected. Furthermore, the sentiment of FOMC minutes contributes more to explaining the spread than statements. Short-term news sentiment stimulates the credit market, but in the long term, both FOMC and news sentiment reflect that lagged information worsens the credit market, showing a positive effect.Finally, we examine the lead–lag relationship between spread changes and stock returns through VAR model. Stock market returns lead spread changes during and after the crisis period, while a bidirectional relationship emerges before the crisis period and during the pandemic. This suggests that aggregate spread changes are actually informative for equity market participants, possibly measuring systemic risk. en_US dc.description.tableofcontents 摘要 iAbstract ii目錄 iii圖目錄 v表目錄 vi第一章 緒論 11.1 研究動機與背景 11.2 研究目的 21.3 研究架構與流程 3第二章 文獻回顧 52.1 信用風險衡量 52.1.1 信用違約交換 52.1.2 信用違約交換指數 72.2 文本情緒 92.2.1 文本分析模型 92.2.2 文本情緒應用 12第三章 研究方法 133.1 BERT模型 133.1.1 模型輸入處理 143.1.2 預訓練（Pre-training） 153.1.3 微調參數（Fine-tunning） 163.2 分量迴歸（Quantile Regression, QR） 183.2.1 模型介紹 183.3.2 模型評估 203.3 向量自我迴歸模型（Vector Autoregression, VAR） 21第四章 實證分析 234.1 資料處理 234.1.1 信用違約交換指數 234.1.2 市場資料 244.1.3 FOMC會議資料 264.1.4 新聞文本資料 284.2 情緒生成 304.2.1 訓練BERT模型 304.2.2 生成情緒分數 344.3 實證結果 374.3.1 結構性改變 374.3.2 信用違約交換指數之影響因子 394.3.3 分量迴歸 474.3.4 信用市場與股票市場 58第五章 結論與建議 715.1 結論 715.2 建議 73參考文獻 74 zh_TW dc.format.extent 2674430 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110352010 en_US dc.subject (關鍵詞) 信用違約交換 zh_TW dc.subject (關鍵詞) CDX zh_TW dc.subject (關鍵詞) BERT zh_TW dc.subject (關鍵詞) FOMC zh_TW dc.subject (關鍵詞) 新聞情緒 zh_TW dc.subject (關鍵詞) 金融危機 zh_TW dc.subject (關鍵詞) 新冠肺炎 zh_TW dc.subject (關鍵詞) CDS en_US dc.subject (關鍵詞) CDX en_US dc.subject (關鍵詞) BERT en_US dc.subject (關鍵詞) FOMC en_US dc.subject (關鍵詞) News sentiment en_US dc.subject (關鍵詞) Financial crisis en_US dc.subject (關鍵詞) COVID-19 en_US dc.title (題名) 整體信用違約交換之衡量：輔以自然語言分析新聞文本及FOMC會議情緒 zh_TW dc.title (題名) Explaining Aggregate Credit Default Swap Spreads with News and FOMC Meetings Sentiment Based on Natural Language Analysis en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Alexander, C., and Kaeck, A. (2008). Regime dependent determinants of credit default swap spreads. Journal of Banking and Finance, 32(6), 1008-21.Annaert, J., De Ceuster, M., Van Roy, P., and Vespro, C. (2013). What determines Euro area bank CDS spreads? Journal of International Money and Finance, 32, 444-461.Araci, D. (2019). Finbert: Financial sentiment analysis with pre-trained language models. arXiv preprint arXiv:1908.10063.Belke, A., and Gokus, C. (2011). Volatility patterns of CDS, bond and stock markets before and during the financial crisis-evidence from major financial institutions. Ruhr Economic Paper, 243.Benkert, C. (2004). Explaining credit default swap premia. Journal of Futures Markets, 24(1), 71–92.Blanco, R., Brennan, S., and Marsh, I. W. (2005). An empirical analysis of the dynamic relationship between investment grade bonds and credit default swap, Journal of Finance, 60(5), 2255-2281.Blei, D., NG, A., and Jordan, M. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993-1022.Bloomfield, R. (2008). Discussion of Annual Report Readability, Current Earnings, and Earnings Persistence. Journal of Accounting and Economics, 45(2)(3), 248-252.Boukus, E., and Rosenberg, J. V. (2006). The Information Content of FOMC Minutes. Working paper, Federal Reserve Bank of New York.Breitenfellner, B., and Wagner, N. (2012). Explaining aggregate credit default swap spreads. International Review of Financial Analysis, 22, 18-29.Byström, H. (2005). Credit Default Swaps and Equity Prices: The iTraxx CDS Index Market. Working Paper, Lund University, Department of Economics.Byström, H. (2006). CreditGrades and the iTraxx CDS Index Market. Financial Analysts Journal, 62, 65-76.Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605.Collin-Dufresne, P., Goldstein, R. S., and Martin, J. S. (2001). The determinants of credit spread changes. Journal of Finance, 56(6), 2177-207.Cossin, D., Hricko, T., Aunon-Nerin, D., and Huang, Z. (2002). Exploring for the determinants of credit risk in credit default swap transaction data: Is fixed-income markets’ information sufficient to evaluate credit risk? FAME Research Paper, 65.Davis, A. K., and Tama-Sweet, I. (2012). Managers’Use of Language Across Alternative Disclosure Outlets: Earnings Press Releases Versus MD&A. Contemporary Accounting Research. 29(3), 804-837.Devlin, J., Chang, M. W., Lee, K., and Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.Dzielinski, M. (2011). News sensitivity and the cross-section of stock returns. NCCR FINRISK 719, University of Zurich.Ericsson, J., Jacobs, K., and Oviedo, R. (2009). The determinants of credit default swap premia. Journal of Financial and Quantitative Analysis, 44(1), 109–132.Friewald, N., Wagner, C., and Zechner, J. (2014). The cross-section of credit risk premia and equity returns. Journal of Finance, 69(6), 2419-2469.Fung, H.G., Sierra, G. E., Yau, J., and Zhang, G. (2008). Are the U.S. stock market and credit default swap market related? Evidence from the CDX Indices. Journal of Alternative Investments, 11(1), 43-61.Garcia, D. (2013). Sentiment During Recessions. Journal of Finance, 68(3), 1267-1300.Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-Spectral Methods, Econometrica, 37(3), 424-438.Hannan, E., and Quinn, B. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society. Series B (Methodological), 41(2), 190–195.Hassan, M., Ngow, T., Yu, JS., and Hassan, A. (2013). Determinants of credit default swaps spreads in European and Asian markets. Journal of Derivatives & Hedge Funds, 19, 295–310.Henry, E. (2008). Are Investors Influenced by How Earnings Press Releases Are Written? 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