Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) approach without a requirement of rich expertise in financial risk....

This research addresses a simple but important unanswered question in the factor investing literature: how do the factor exposures of equity factor strategies decay over time? The answer to this question has two important practical consequences. Firstly, understanding how a strategy’s factor...

One of the most important factors to control for the achievements of investment portfolio returns is risk. If we only think that a 100% positive return is needed to recover a portfolio loss of 50%, we can understand why. With the advent of the exponential growth of technology usage in markets,...

The proliferation of factor investing strategies in recent years has highlighted the idea that a portfolio can harvest improved risk-adjusted returns through timed exposure to risk factors during times of elevated risk premia. While there is a large body of research on such risk factors and risk...

Both mathematical modelling and simulation methods in general have contributed greatly to understanding, insight and forecasting in many fields including macroeconomics. Never-theless, we must remain careful to distinguish model-land and model-land quantities from the real world. Decisions taken...

Both mathematical modelling and simulation methods in general have contributed greatly to understanding, insight and forecasting in many fields including macroeconomics. Nevertheless, we must remain careful to distinguish model-land and model-land quantities from the real world. Decisions taken...

Both mathematical modelling and simulation methods in general have contributed greatly to understanding, insight and forecasting in many fields including macroeconomics. Never-theless, we must remain careful to distinguish model-land and model-land quantities from the real world. Decisions taken...

Both mathematical modelling and simulation methods in general have contributed greatly to understanding, insight and forecasting in many fields including macroeconomics. Nevertheless, we must remain careful to distinguish model-land and model-land quantities from the real world. Decisions taken...

This study investigated the relationship between the informal economy and sustainable development, focussing on how the shadow economy influenced the achievement of the 17 Sustainable Development Goals (SDGs) formulated in the 2030 Agenda in Europe. The research used data extracted from the...