Convolutional neural networks (CNN) and long short-term memory (LSTM) networks have become a staple of sequence learning. Due to the well-established fact that financial time series data exhibit exceptionally noisy characteristics, capital market anomalies are virtually impossible to detect. We...

This paper revisits the relationships among macroeconomic variables and asset returns. Based on recent developments in econometrics, we categorize competing models of asset returns into different "Equivalence Predictive Power Classes" (EPPC). During the pre-crisis period (1975-2005), some models...

We analyse the performance of financial market variables in nowcasting Finnish quarterly GDP growth. In particular, we assess if prediction accuracy is affected by the sampling frequency of the financial variables. Therefore, we apply MIDAS models that allow us to nowcast quarterly GDP growth...

We explore in this paper the use of deep signature models to predict equity financial time series returns. First, we use signature transformations to model the underlying shape of the input equity returns; further assuming the underlying shape remains the same, we predict future values based on...

We analyse the performance of financial market variables in nowcasting Finnish quarterly GDP growth. Especially, we assess if prediction accuracy is affected by the sampling frequency of the financial variables. Therefore, we apply MIDAS models that allow us to forecast quarterly GDP growth...

I argue that academic research often inadequately accounts for alpha decay. As an anomaly's alpha (i.e., the risk-adjusted expected excess return) and realized returns are negatively related, alpha decay coincides with positive realized returns. If the alpha decays at publication, observers may...

We investigate the cross-sectional pattern of stock returns for eight emerging markets using Vector Autoregressive Approach (VAR) to test whether dividend yields can predict stock returns through impulse response characteristics. Our results confirm that dividend yield shocks play an important...

In financial decisions, model risk has been recognized as an important source of uncertainty. The revision of the Basel II suggests that financial institutions quantify and manage their model risk. Focusing on risk forecasting literature, we identify two main approaches to quantify model risk:...