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07/25/2023
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling
Deep hedging is a deep-learning-based framework for derivative hedging i...
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10/31/2022
Uncertainty Aware Trader-Company Method: Interpretable Stock Price Prediction Capturing Uncertainty
Machine learning is an increasingly popular tool with some success in pr...
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01/31/2022
Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics
This paper provides a unified perspective for the Kullback-Leibler (KL)-...
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11/15/2021
Contrastive Representation Learning with Trainable Augmentation Channel
In contrastive representation learning, data representation is trained s...
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06/08/2021
What Data Augmentation Do We Need for Deep-Learning-Based Finance?
The main task we consider is portfolio construction in a speculative mar...
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12/18/2020
Trader-Company Method: A Metaheuristic for Interpretable Stock Price Prediction
Investors try to predict returns of financial assets to make successful ...
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12/14/2020
Deep Portfolio Optimization via Distributional Prediction of Residual Factors
Recent developments in deep learning techniques have motivated intensive...
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04/04/2020
The equivalence between Stein variational gradient descent and black-box variational inference
We formalize an equivalence between two popular methods for Bayesian inf...
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02/11/2020
Smoothness and Stability in GANs
Generative adversarial networks, or GANs, commonly display unstable beha...
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05/06/2019
