USE MACROECONOMICS OR MARKET INDICATORS TO UNDERSTAND RETURNS ON BRAZILIAN REAL ESTATE FUNDS?

Mathias Schneid Tessmann, Fabiano Nogueira Alves, Luiz Augusto Ferreira Magalhães

Resumo


The present work aims to apply the Dynamic Factor Model to extract common factors from real estate investment funds (FIIs) from 2013 to 2019. The values used were monthly closings of the funds' shares and a subset divided between brick-and-mortar funds. paper. For the analysis, dynamic factor models were created using economic and market indicators as explanatory variables, the dependent variables were the main factors extracted from the main components analysis for 78 selected funds, and the models were estimated by OLS (Ordinary Least Squares). This work's main findings were that most returns are given by idiosyncratic components, that the dynamic factors model is a method that can be applied as a form of forecasting, and that market indicators are more important for predicting FIIs than economic indices.

Palavras-chave


Forecast; Modeling; Real Estate Funds; Dynamic Factors.

Texto completo:

PDF (English)

Referências


BAI, J. Inferential theory for factor models of large dimensions. Econometrica, Wiley Online Library, v. 71, n. 1, p. 135–171, 2003.

BAI, J.; NG, S. Determining the number of factors in approximate factor models. Econometrica, Wiley Online Library, v. 70, n. 1, p. 191–221, 2002.

BAI, J.; NG, S. Confidence intervals for diffusion index forecasts and inference for factor-augmented regressions. Econometrica, Wiley Online Library, v. 74, n. 4, p. 1133–1150, 2006.

BAI, J.; NG, S. Determining the number of primitive shocks in factor models. Journal of Business and Economic Statistics, Taylor and Francis, v. 25, n. 1, p. 52–60, 2007.

BAI, J.; NG, S. Large dimensional factor analysis. [S.l.]: Now Publishers Inc, 2008.

BAńBURA, M. et al. Chapter 4 - now-casting and the real-time data flow. In: ELLIOTT, G.; TIMMERMANN, A. (Ed.). Handbook of Economic Forecasting. Elsevier, 2013, (Handbook of Economic Forecasting, v. 2). p. 195–237. Disponível em: .

BERTERO, E.; MAYER, C. Structure and performance: Global interdependence of stock markets around the crash of october 1987. European Economic Review, Elsevier, v. 34, n. 6, p. 1155–1180, 1990.

BLACKMAN, S. C.; HOLDEN, K.; THOMAS, W. A. Long-term relationships between international share prices. Applied Financial Economics, Taylor & Francis, v. 4, n. 4, p. 297–304, 1994.

BOUCHOUICHA, R.; FTITI, Z. Real estate markets and the macroeconomy: A dynamic coherence framework. Economic Modelling, v. 29, n. 5, p. 1820-1829, 2012.

CARVALHO, A. L. d. P. Modelagem econométrica para forecasting do IFIX. Tese (Doutorado) — FUNDAÇÃO GETÚLIO VARGAS, 2019.

CHAMBERLAIN, G.; ROTHSCHILD, M. Arbitrage, factor structure, and mean-variance analysis on large asset markets. Econometrica, v. 51, n. 5, p. 1281–304, 1983.

CHEUNG, Y.-W.; NG, L. K. Interactions between the US and Japan stock market indices. Journal of International Financial Markets, Institutions & Money, Taylor & Francis, v. 2, n. 2, p. 51–70, 1993.

CONCEIÇÃO, A. M. Modelo de fatores dinâmicos aplicado ao mercado brasileiro de ações. Tese (Doutorado) — FUNDAÇÃO GETÚLIO VARGAS, 2017.

CONNOR, G.; KORAJCZYK, R. A. Performance measurement with the arbitrage pricing theory: A new framework for analysis. Journal of financial economics, Elsevier, v. 15, n. 3, p. 373–394, 1986.

DAVIS, J. S.; HUANG, K. X. D.; SAPCI, A. Land price dynamics and macroeconomic fluctuations with imperfect substitution in real estate markets. Journal of Economic Dynamics and Control, v. 134, p. 104274, 2022.

DENG, Y.; ZENG, Y.; LI, Z. Real estate prices and systemic banking crises. Economic Modelling, v. 80, p. 111-120, 2019.

EUN, C. S.; SHIM, S. International transmission of stock market movements. Journal of financial and quantitative Analysis, JSTOR, p. 241–256, 1989.

FELÍCIO, W. R. d. O.; JÚNIOR, J. L. R. Common factors and the exchange rate: results from the Brazilian case. Revista Brasileira de Economia, SciELO Brasil, v. 68, p. 49–71, 2014.

FOCARDI, S. M.; FABOZZI, F. J.; MITOV, I. K. A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance. Journal of Banking & Finance, Elsevier, v. 65, p. 134–155, 2016.

FORNI, M. et al. The generalized dynamic-factor model: Identification and estimation. Review of Economics and statistics, MIT Press, v. 82, n. 4, p. 540–554, 2000.

FORNI, M.; REICHLIN, L. Let’s get real: a factor analytical approach to disaggregated business cycle dynamics. The Review of Economic Studies, Wiley-Blackwell, v. 65, n. 3, p. 453–473, 1998.

FURSTENBERG, G. M. V. et al. International stock price movements: links and messages. Brookings papers on economic activity, JSTOR, v. 1989, n. 1, p. 125–179, 1989.

GEWEKE, J. The dynamic factor analysis of economic time series. Latent variables in socio-economic models, North-Holland, 1977.

GIANNONE, D.; REICHLIN, L.; SMALL, D. Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics, v. 55, n. 4, p. 665–676, 2008.

GIANNONE, D.; REICHLIN, L.; SMALL, D. Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics, v. 55, n. 4, p. 665–676, 2008.

HAAS, G. P. et al. Existe value premium para os fundos imobiliários brasileiros? Uma análise para o período 2013 a 2018. Revista Brasileira de Economia de Empresas/Brazilian Journal of Business Economics, v. 21, n. 1, 2021.

HAMAO, Y.; MASULIS, R. W.; NG, V. Correlations in price changes and volatility across international stock markets. The review of financial studies, Oxford University Press, v. 3, n. 2, p. 281–307, 1990.

JOHANSEN, S. Statistical analysis of cointegration vectors. Journal of economic dynamics and control, Elsevier, v. 12, n. 2-3, p. 231–254, 1988.

MARIANO, R. S.; MURASAWA, Y. A new coincident index of business cycles based on monthly and quarterly series. Journal of applied Econometrics, Wiley Online Library, v. 18, n. 4, p. 427–443, 2003.

MASIH, A. M.; MASIH, R. A comparative analysis of the propagation of stock market fluctuations in alternative models of dynamic causal linkages. Applied Financial Economics, Taylor & Francis, v. 7, n. 1, p. 59–74, 1997.

MORAES, A. V. D.; SERRA, R. G. Diversificação dos fundos de investimento imobiliário brasileiros. Revista Base (Administração e Contabilidade) da UNISINOS, Universidade do Vale do Rio dos Sinos, v. 14, n. 1, p. 63–73, 2017.

NAVARRO, C.; RIVERA, D. Peña Sánchez de. Estimation of the common component in Dynamic Factor Models. [S.l.], 2018.

NG, V.; ENGLE, R. F.; ROTHSCHILD, M. A multi-dynamic-factor model for stock returns. Journal of Econometrics, v. 52, n. 1, p. 245–266, 1992.

NNEJI, Ogonna; BROOKS, Chris; WARD, Charles WR. House price dynamics and their reaction to macroeconomic changes. Economic Modelling, v. 32, p. 172-178, 2013.

NOWCASTING GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Release. [S.l.], 2007.

OLIVEIRA, J. M. de; MILANI, B. Variáveis que explicam o retorno dos fundos imobiliários brasileiros. Revista Visão: Gestão Organizacional, v. 9, n. 1, p. 17–33, 2020.

PAGAN, J. A.; SOYDEMIR, G. On the linkages between equity markets in Latin America. Applied Economics Letters, Taylor & Francis, v. 7, n. 3, p. 207–210, 2000.

PENA, D.; BOX, G. E. P. Identifying a simplifying structure in time series. Journal of the American Statistical Association, [American Statistical Association, Taylor & Francis, Ltd.], v. 82, n. 399, p. 836–843, 1987.

PLAKANDARAS, Vasilios et al. Time-varying role of macroeconomic shocks on house prices in the US and UK: evidence from over 150 years of data. Empirical Economics, v. 58, n. 5, p. 2249-2285, 2020.

ROCHA, B. de P.; SEKKEL, R. M. The dynamic factor model: an application to international stock market integration. Revista de economía, Banco Central del Uruguay, v. 13, n. 1, p. 91–116, 2006.

SADHWANI, R. et al. Does change in economic policy uncertainty affect real estate investment trusts (REITs)?. Annals of Financial Economics, v. 14, n. 04, p. 1950016, 2019.

SARGENT, T. J.; SIMS, C. A. et al. Business cycle modeling without pretending to have too much a priori economic theory. New methods in business cycle research, v. 1, p. 145–168, 1977.

SOTO, P. A. Arbitragem estatística no mercado brasileiro de ações: uma abordagem por VECM. Tese (Doutorado) — FUNDAÇÃO GETÚLIO VARGAS, 2016.

STOCK, J. H.; WATSON, M. Dynamic factor models. Oxford Handbooks Online, Oxford University Press, 2011.

STOCK, J. H.; WATSON, M. W. Testing for common trends. Journal of the American statistical Association, Taylor & Francis Group, v. 83, n. 404, p. 1097–1107, 1988.

STOCK, J. H.; WATSON, M. W. Forecasting using principal components from a large number of predictors. Journal of the American statistical association, Taylor & Francis, v. 97, n. 460, p. 1167–1179, 2002.

STOCK, J. H.; WATSON, M. W. Dynamic factor models, factor-augmented vector autoregressions, and structural vector autoregressions in macroeconomics. In: Handbook of macroeconomics. [S.l.]: Elsevier, v. 2, p. 415–525, 2016.

TABAK, B. M.; LIMA, E. J. A. Causality and cointegration in stock markets: the case of latin america. Revista Brasileira de Economia de Empresas, v. 3, n. 2, 2013.

TSE, C. B.; RODGERS, T.; NIKLEWSKI, J. The 2007 financial crisis and the UK residential housing market: Did the relationship between interest rates and house prices change?. Economic Modelling, v. 37, p. 518-530, 2014.

VALK, S. de; MATTOS, D. de; FERREIRA, P. Nowcasting: An R Package for Predicting Economic Variables Using Dynamic Factor Models. The R Journal, v. 11, n. 1, p. 230–244, 2019.

WU, M. C.; WANG, C. M. Revisiting the nexus of REITs returns and macroeconomic variables. Finance Research Letters, v. 59, p. 104837, 2024.


Apontamentos

  • Não há apontamentos.


Administração de Empresas em Revista, e-ISSN: 2316-7548

Rua Chile, 1678, Rebouças, Curitiba/PR (Brasil). CEP 80.220-181

Licença Creative Commons

Este obra está licenciado com uma Licença Creative Commons Atribuição-NãoComercial 4.0 Internacional.