activity
20192021
most citedDeep Sequence Modeling: Development and Applications in Asset Pricing

25 citations · 40 across the 2 of their papers we have counts for

collaborators

5 papers

econ.GN202115 cited

Crypto Wash Trading

Lin William Cong, Xi Li, Ke Tang +1

We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges featu…

cs.LG202125 cited

Deep Sequence Modeling: Development and Applications in Asset Pricing

Lin William Cong, Ke Tang, Jingyuan Wang +1

We predict asset returns and measure risk premia using a prominent technique from artificial intelligence -- deep sequence modeling. Because asset returns often exhibit sequential…

cs.LG2020

Interpreting Deep Learning Model Using Rule-based Method

Xiaojian Wang, Jingyuan Wang, Ke Tang

Deep learning models are favored in many research and industry areas and have reached the accuracy of approximating or even surpassing human level. However they've long been consid…

q-fin.TR2019

AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks

Jingyuan Wang, Yang Zhang, Ke Tang +2

Recent years have witnessed the successful marriage of finance innovations and AI techniques in various finance applications including quantitative trading (QT). Despite great rese…

stat.ME2019

Decision Making with Machine Learning and ROC Curves

Kai Feng, Han Hong, Ke Tang +1

The Receiver Operating Characteristic (ROC) curve is a representation of the statistical information discovered in binary classification problems and is a key concept in machine le…