Abstract This paper reviews Artificial Intelligence (AI), Machine Learning (ML) and
associated algorithms in future Capital Markets. New AI algorithms are constantly emerging …

Systematic trading strategies are algorithmic procedures that allocate assets aiming to
optimize a certain performance criterion. To obtain an edge in a highly competitive …

This paper reviews the impact of data science and artificial intelligence (AI) on future
'datadriven'insurance markets. The impact of insurance automation (driven by so-called …

This paper presents a novel framework for analyzing the optimal asset and signal
combination problem. Our approach builds upon the dynamic portfolio selection problem …

Systematic financial trading strategies account for over 80% of trade volume in equities and
a large chunk of the foreign exchange market. In spite of the availability of data from multiple …

Systematic financial trading strategies account for over 80% of trade volume in equities and
a large chunk of the foreign exchange market. In spite of the availability of data from multiple …

This paper evaluates artificial intelligence's (AI's) foray into financial markets and the
resultant implications for theory and practice. I argue for reevaluating mainstream financial …

This paper pioneers an interdisciplinary framework integrating behavioral finance, ethics,
and cuttingedge machine learning to elucidate the promise and perils as AI proliferates in …

We present a novel framework for analyzing the optimal asset and signal combination
problem, which builds upon the dynamic portfolio selection problem of Brandt and Santa …

This paper reviews Artificial Intelligence (AI), Machine Learning (ML) and associated
algorithms in future Capital Markets. New AI algorithms are constantly emerging, with …