US Equity REIT Returns and Digitalization

Abstract: This licentiate thesis is a collection of two essays that utilize time-series econometric methods in real estate finance. The first essay applies econometric modelling on Real Estate Investment Trust (REIT) index returns, focusing on estimating the effect of the quantitative easing (QE) and quantitative tightening (QT) programmes on U.S. equity REIT index returns, while controlling for several other important macro-financial factors. The second essay instead focuses on forecasting U.S. equity REIT index returns empirically, where the performance of a traditional econometric model (ARIMA) is compared to a modern state-of-the-art deep learning-based model (LSTM).Digitalization, which encompasses a broad range of technological advancements, is the main factor that we study for its impact on REIT investments. One perspective on the impact of digitalization on REITs is its effect on inflation. Digitalization has the potential to increase productivity and reduce costs, which could help to keep inflation low. This, in turn, has in the recent decades provided a supportive environment for REIT investments through lower interest rates, which we partly investigate in the first essay.Another perspective is that digitalization has not only led, but is also expected to lead, to significant innovations in the field of artificial intelligence (AI) and machine learning (ML), including deep learning (DL), which is a subset of ML. Many researchers and market practitioners are currently working to develop models that can use large amounts of data to make better forecasts and investment decisions. If successful, these models could significantly improve the performance of REIT investments. Can DL models be trained to make better forecasts for making investments? This is a question we ask ourselves in the second essay.The study of digitalization and its effects on inflation has been a growing area of interest in recent years, with researchers exploring the potential impact of technological advancements on macroeconomic trends, which founded the base to our studies. However, recent developments in the global economy have shifted the focus of this research, as inflation levels have unexpectedly risen from what was previously believed to be a low and stable environment. As a result, the setting and framework for our research on digitalization and inflation have been significantly altered, as we have tried to adapt to this changing landscape.