Assessing the predictability of the stock market and reit returns: a cross-country analysis /

This thesis uses the ARMA model to assess the predictability of stock market and Real Estate Investment Trusts (REITs) returns across different countries. The primary goal is determining which asset classes are more predictable and how their predictability varies, especially before and after 2008. Extending the analysis of Serrano and Hoesli (2010), this study examines subsequent market developments and their impact on asset return predictability. Data was sourced from platforms like Bloomberg, using the FTSE EPRA NAREIT Global Index for securitized real estate and two stock market datasets. The study period was divided into pre-2008 and post-2008 to analyse and compare the predictability results. Key findings indicate significant variability in predictability based on period and market conditions. Pre-2008, REITs were generally more predictable than stocks in countries with mature REIT regimes (US, Australia, Sweden, France and the Netherlands). In contrast, stocks were more predictable in countries with younger REIT markets (e.g., Hong Kong, Japan, Singapore). Post-2008, stocks became more predictable than REITs across all countries following the financial crisis and the COVID-19 pandemic. Error metrics, including MAE and RMSE, supported these findings, showing lower error values for REITs pre-2008 and higher values post-2008. These findings have important implications for investors and policymakers, highlighting the need for dynamic and adaptive forecasting models. While the ARMA model provided valuable insights, future research could benefit from more sophisticated models, like GARCH, to better account for volatility clustering and time-varying volatility in asset returns.

Grantor dc:publisher

Institutional Repository of Vilnius University

Year dc:date

2024

Author dc:creator

• Jurgaitis, Augustinas,

• Predictability, Time Series models, ARMA, REITs, Securitized real estate.

Statement dc:rights

• info:eu-repo/semantics/openAccess

Language dc:language

eng

Repository record dc:identifier

https://repository.vu.lt/VU:ELABAETD210642829&prefLang=en_US

OAI identifier oai:identifier

oai:vu.lt:elaba:210642829