Interpretable Deep Learning for REIT Return Forecasting: A Comparative Study of LSTM, TVP–VAR Proxy, and SHAP-Based Explanations

Forecasting returns in Real Estate Investment Trust (REIT) markets remains challenging because REIT performance is shaped by nonlinear and time-varying interactions with macro-financial conditions. This study evaluates the forecasting performance of Long Short-Term Memory (LSTM) neural networks rela...

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Bibliografiska uppgifter

Huvudupphov:	Eddy Suprihadi, Nevi Danila, Zaiton Ali, Gede Pramudya Ananta
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	MDPI AG 2026-03-01
Serie:	International Journal of Financial Studies
Ämnen:	REIT forecasting LSTM TVP–VAR proxy SHAP explainable AI financial econometrics
Länkar:	https://www.mdpi.com/2227-7072/14/3/73
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