Effect of Real Estate News Sentiments on the Stock Returns of Swedbank and SEB Bank
This paper explores the effect of real estate news sentiment on the stock returns of Swedbank and SEB Bank, which are leading banks in Sweden and the Baltic region. For this purpose, we have selected sentiments from news about real estate in the markets of these banks in Sweden, Estonia, Latvia, and Lithuania between 4 January 2016 and 19 February 2019. Estimation results showed that sentiments about the housing market affect stock returns for both banks, and the effect is different for positive and negative news. We also found that there is a difference in the stock returns of these banks in terms of when and to what extent they react to news coming from the Baltic States and Sweden. Moreover, we found that the number of negative news affects the stock returns of the banks more than the strength of the news. We also apply several GARCH specifications to explore if negative and positive news affect the volatility processes to some extent. We found out that the volatilities are explained better by the GJR-GARCH and NA-GARCH models. Overall, the volatility of SEB stock returns depends more on the news sentiments compared to the volatility of Swedbank stock returns.
Acharya, V. V., Eisert, T., Eufinger, C., and Hirsch, C. (2018). Real Effects of the Sovereign Debt Crisis in Europe: Evidence from Syndicated Loans. The Review of Financial Studies, 31(8):2855–2896.
Antweiler, W. and Frank, M. Z. (2004). Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards. The Journal of Finance, 59(3):1259–1294.
Arik, A. (2011). Modeling Market Sentiment and Conditional Distribution of Stock Index Returns Under GARCH Process. Claremont Graduate University.
Asai, M. and McAleer, M. (2006). Asymmetric Multivariate Stochastic Volatility. Econometric Reviews, 25(2-3):453–473.
Bailey, M., Davila, E., Kuchler, T., and Stroebel, J. (2017). House Price Beliefs and Mortgage Leverage Choice.
Balasubramaniam, K. (2018). How to Calculate a Stock’s Adjusted Closing Price. https://www.investopedia.com.
Bauwens, L., Laurent, S., and Rombouts, J. V. K. (2006). Multivariate GARCH Models: A Survey. Journal of Applied Econometrics, 21(1):79–109.
Beetsma, R., De Jong, F., Giuliodori, M., and Widijanto, D. (2017). Realized (Co) Variances of Eurozone Sovereign Yields During the Crisis: The Impact of News and the Securities Markets Programme. Journal of International Money and Finance, 75:14–31.
Beetsma, R., Giuliodori, M., De Jong, F., and Widijanto, D. (2013). Spread the News: The Impact of News on the European Sovereign Bond Markets During the Crisis. Journal of International Money and finance, 34:83–101.
Bollen, J., Mao, H., and Zeng, X. (2011). Twitter Mood Predicts the Stock Market. Journal of Computational Science, 2(1):1–8.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3):307–327.
Bollerslev, T. and Wooldridge, J. M. (1992). Quasi Maximum Likelihood Estimation and Inference in Dynamic Models with Time Varying Covariances. Econometric Reviews, 11(2):143–172.
Box, G. E. P., Jenkins, G. M., and Reinsel, G. (1970). Time Series Analysis: Forecasting and Control Holden-Day San Francisco. BoxTime Series Analysis: Forecasting and Control Holden Day1970.
Bradley, M. M. and Lang, P. J. (1999). Affective Norms for English Words (ANEW): Instruction Manual and Affective Ratings. Technical report, Citeseer.
Braun, P. A., Nelson, D. B., and Sunier, A. M. (1995). Good News, Bad News, Volatility, and Betas. The Journal of Finance, 50(5):1575–1603.
Brook, C. and Burke, S. P. (2003). Information Criteria for GARCH Model Selection: An Application to High Frequency Data. European Journal of Finance, 9(6):557–580.
Carmichael, B. and Coen, A. (2018). Real Estate as a Common Risk Factor in Bank Stock Returns. Journal of Banking & Finance, 94:118–130.
Carnero, M. A. and Eratalay, M. H. (2014). Estimating VAR-MGARCH Models in Multiple Steps. Studies in Nonlinear Dynamics & Econometrics, 18(3):339–365.
Cepoi, C.-O. (2020). Asymmetric Dependence Between Stock Market Returns and News During COVID19 Financial Turmoil. Finance Research Letters.
De Almeida, D., Hotta, L. K., and Ruiz, E. (2018). MGARCH Models: Trade-off Between Feasibility and Flexibility. International Journal of Forecasting, 34(1):45–63.
De Long, J. B., Shleifer, A., Summers, L. H., and Waldmann, R. J. (1990). Noise Trader Risk in Financial Markets. Journal of Political Economy, 98(4):703–738.
Deng, S., Huang, Z. J., Sinha, A. P., and Zhao, H. (2018). The Interaction Between Microblog Sentiment and Stock Return: An Empirical Examination. MIS Quarterly, 42(3):895–918.
Ding, D., Huang, X., Jin, T., and Lam, W. R. (2017). Assessing China’s Residential Real Estate Market. International Monetary Fund.
Ederington, L. H. and Lee, J. H. (1993). How Markets Process Information: News Releases and Volatility. The Journal of Finance, 48(4):1161–1191.
Engelberg, J. E. and Parsons, C. A. (2011). The Causal Impact of Media in Financial Markets. The Journal of Finance, 66(1):67–97.
Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica: Journal of the Econometric Society, pages 987–1007.
Engle, R. F., Focardi, S. M., and Fabozzi, F. J. (2012). ARCH/GARCH Models in Applied Financial Econometrics. Encyclopedia of Financial Models.
Engle, R. F. and Ng, V. K. (1993). Measuring and Testing the Impact of News on Volatility. The Journal of finance, 48(5):1749–1778.
Engle, R. F. and Sheppard, K. (2001). Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH. Technical report, National Bureau of Economic Research.
Fama, E. F. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38(1):34–105.
Finansinspektionen (2018). The Swedish Mortgage Market.
Fisher, K. L. and Statman, M. (2000). Investor Sentiment and Stock Returns. Financial Analysts Journal, 56(2):16–23.
Ghosh, C., Guttery, R. S., and Sirmans, C. F. (1997). The Effects of the Real Estate Crisis on Institutional Stock Prices. Real Estate Economics, 25(4):591–614.
Ghysels, E., Harvey, A. C., and Renault, E. (1996). 5 Stochastic Volatility. Handbook of Statistics, 14:119–191.
Glosten, L. R., Jagannathan, R., and Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5):1779–1801.
Groß-Klußmann, A. and Hautsch, N. (2011). When Machines Read the News: Using Automated Text Analytics to Quantify High Frequency News-Implied Market Reactions. Journal of Empirical Finance, 18(2):321–340.
Gujarati, D. N. (2003). Basic Econometrics: Fourth Edition McGraw-Hill. New York.
Gupta, K. and Banerjee, R. (2019). Does OPEC News Sentiment Influence Stock Returns of Energy Firms in the United States? Energy Economics, 77:34–45.
Hansen, P. R. and Lunde, A. (2005). A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH (1, 1)? Journal of Applied Econometrics, 20(7):873–889.
Harris, Z. S. (1954). Distributional Structure. Word, 10(2-3):146–162.
Hausler, J., Ruscheinsky, J., and Lang, M. (2018). News-Based Sentiment Analysis in Real Estate: A Machine Learning Approach. Journal of Property Research, 35(4):344–371.
He, L. T., Myer, F. C. N., and Webb, J. R. (1996). The Sensitivity of Bank Stock Returns to Real Estate. The Journal of Real Estate Finance and Economics, 12(2):203–220.
Hu, M. and Liu, B. (2004). Mining Opinion Features in Customer Reviews. In AAAI, volume 4, pages 755–760.
Hutto, C. J. and Gilbert, E. (2014). Vader: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text. In Eighth International AAAI Conference on Weblogs and Social Media.
Hutto, C. J., Klein, E., Pantone, P., and Berry, G. (2019). Vader Lexicon. https://github.com/cjhutto/vaderSentiment/tree/master/vaderSentiment.
Igan, D. and Pinheiro, M. (2010). Exposure to Real Estate in Bank Portfolios. Journal of Real Estate Research, 32(1):47–74.
Kelly, S. (2016). News, Sentiment and Financial Markets: A Computational System to Evaluate the Influence of Text Sentiment on Financial Assets. PhD thesis, Trinity College Dublin.
Kosapattarapim, C., Lin, Y.-X., and McCrae, M. (2012). Evaluating the Volatility Forecasting Performance of Best Fitting GARCH Models in Emerging Asian Stock Markets.
Kothari, S. P. and Shanken, J. (1997). Book-to-Market, Dividend Yield, and Expected Market Returns: A Time-Series Analysis. Journal of Financial Economics, 44(2):169– 203.
Kwan, S. (2019). Banks’ Real Estate Exposure and Resilience. FRBSF Economic Letter, page 10.
Leon, A., Rubio, G., and Serna, G. (2005). Autoregresive Conditional Volatility, Skewness and Kurtosis. The Quarterly Review of Economics and Finance, 45(4-5):599–618.
Li, Q., Wang, T., Li, P., Liu, L., Gong, Q., and Chen, Y. (2014). The Effect of News and Public Mood on Stock Movements. Information Sciences, 278:826–840.
Liu, W. and Morley, B. (2009). Volatility Forecasting in the Hang Seng Index Using the GARCH Approach. Asia-Pacific Financial Markets, 16(1):51–63.
Maheu, J. M. and McCurdy, T. H. (2004). News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns. The Journal of Finance, 59(2):755–793.
Malik, F. (2011). Estimating the Impact of Good News on Stock Market Volatility. Applied Financial Economics, 21(8):545–554.
Martins, A. M., Serra, A. P., and Martins, F. V. (2016). Real Estate Market Risk in Bank Stock Returns: Evidence for 15 European Countries. International Journal of Strategic Property Management, 20(2):142–155.
Mei, J. and Lee, A. (1994). Is There a Real Estate Factor Premium? The Journal of Real Estate Finance and Economics, 9(2):113–126.
Mei, J. and Saunders, A. (1995). Bank Risk and Real Estate: An Asset Pricing Perspective. The Journal of Real Estate Finance and Economics, 10(3):199–224.
Mitchell, M. L. and Mulherin, J. H. (1994). The Impact of Public Information on the Stock Market. The Journal of Finance, 49(3):923–950.
Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica: Journal of the Econometric Society, pages 347–370.
NumFOCUS. Python Data Analysis Library. https://pandas.pydata.org/.
Olowe, R. A. (2009). Modelling Naira/Dollar Exchange Rate Volatility: Application of GARCH and Assymetric Models. International Review of Business Research Papers, 5(3):377–398.
Ranco, G., Aleksovski, D., Caldarelli, G., Grcar, M., and Mozetic, I. (2015). The Effects of Twitter Sentiment on Stock Price Returns. PLOS ONE, 10(9):e0138441.
Richardson, L. Beautiful Soup 4.4.0 documentation. https://www.crummy.com/ software/BeautifulSoup/bs4/doc/.
Robert, E. and Victor, N. (1993). Measuring and Testing the Impact of News on Volatility. The Journal of Finance, 48(5):1749–1778.
Sidorov, S. P., Date, P., and Balash, V. (2014). GARCH Type Volatility Models Augmented with News Intensity Data. In Chaos, Complexity and Leadership 2012, pages 199–207. Springer.
Sidorov, S. P., Revutskiy, A., Faizliev, A., Korobov, E., and Balash, V. (2014c). Stock Volatility Modelling With Augmented GARCH Model With Jumps. IAENG International Journal of Applied Mathematics, 44(4):212–220.
Soo, C. (2015). Quantifying Animal Spirits: News Media and Sentiment in the Housing Market. Ross School of Business Paper, (1200).
Soo, C. K. (2018). Quantifying Sentiment With News Media Across Local Housing Markets. The Review of Financial Studies, 31(10):3689–3719.
Soroka, S. N. (2006). Good News and Bad News: Asymmetric Responses to Economic Information. The Journal of Politics, 68(2):372–385.
Taylor, S. J. (1994). Modeling Stochastic Volatility: A Review and Comparative Study. Mathematical Finance, 4(2):183–204.
Tetlock, P. C. (2007). Giving Content to Investor Sentiment: The Role of Media in the Stock Market. The Journal of Finance, 62(3):1139–1168.
Tetlock, P. C., Saar-Tsechansky, M., and Macskassy, S. (2008). More Than Words: Quantifying Language to Measure Firms’ Fundamentals. The Journal of Finance, 63(3):1437–1467.
Tumarkin, R. and Whitelaw, R. F. (2001). News or Noise? Internet Postings and Stock Prices. Financial Analysts Journal, 57(3):41–51.
Verma, R. and Soydemir, G. (2009). The Impact of Individual and Institutional Investor Sentiment on the Market Price of Risk. The Quarterly Review of Economics and Finance, 49(3):1129–1145.
Walker, C. B. (2016). The Direction of Media Influence: Real-Estate News and the Stock Market. Journal of Behavioral and Experimental Finance, 10:20–31.
White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica: Journal of the Econometric Society, pages 817–838.
Whitle, P. (1951). Hypothesis Testing in Time Series Analysis, volume 4. Almqvist & Wiksells.
Yu, X. (2014). Analysis of New Sentiment and Its Application to Finance. PhD thesis.
Zhang, X., Fuehres, H., and Gloor, P. A. (2011). Predicting Stock Market Indicators Through Twitter “I hope it is not as bad as I fear”. Procedia-Social and Behavioral Sciences, 26:55–62.
Copyright (c) 2021 by the Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.