25 citations · 43 across the 4 of their papers we have counts for
6 papers
QuantNet: Transferring Learning Across Systematic Trading Strategies
Adriano Koshiyama, Sebastian Flennerhag, Stefano B. Blumberg +2
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…
Optimal Dynamic Strategies on Gaussian Returns
Nick Firoozye, Adriano Koshiyama
Dynamic trading strategies, in the spirit of trend-following or mean-reversion, represent an only partly understood but lucrative and pervasive area of modern finance. Assuming Gau…
Augmenting correlation structures in spatial data using deep generative models
Konstantin Klemmer, Adriano Koshiyama, Sebastian Flennerhag
State-of-the-art deep learning methods have shown a remarkable capacity to model complex data domains, but struggle with geospatial data. In this paper, we introduce SpaceGAN, a no…
Avoiding Backtesting Overfitting by Covariance-Penalties: an empirical investigation of the ordinary and total least squares cases
Adriano Koshiyama, Nick Firoozye
Systematic trading strategies are rule-based procedures which choose portfolios and allocate assets. In order to attain certain desired return profiles, quantitative strategists mu…
Generative Adversarial Networks for Financial Trading Strategies Fine-Tuning and Combination
Adriano Koshiyama, Nick Firoozye, Philip Treleaven
Systematic trading strategies are algorithmic procedures that allocate assets aiming to optimize a certain performance criterion. To obtain an edge in a highly competitive environm…
A Machine Learning-based Recommendation System for Swaptions Strategies
Adriano Soares Koshiyama, Nick Firoozye, Philip Treleaven
Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their…