Search Results
StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series
There has been growing interest in applying NLP techniques in the financial domain, however, resources are extremely limited.
Emotion Classification
Multivariate Time Series Forecasting
+2
Generative Meta-Learning Robust Quality-Diversity Portfolio
The weights of the model are updated using a gradient-based optimizer.
FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
In this paper, we introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies.
TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
Despite the availability of abundant financial data and advanced RL techniques, a remarkable gap still exists between the potential and realized utilization of RL in financial trading.
Temporal Relational Ranking for Stock Prediction
Our RSR method advances existing solutions in two major aspects: 1) tailoring the deep learning models for stock ranking, and 2) capturing the stock relations in a time-sensitive manner.
Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations
In this paper, we perform an in-depth analysis of pump and dump schemes organized by communities over the Internet.
Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction
Stock trend prediction plays a critical role in seeking maximized profit from stock investment.
Ranked #16 on
Stock Market Prediction
on Astock
Quantum Communications
The ability to control individual quantum systems for the purpose of information processing and communication is no longer a theoretical dream, but is steadily becoming routine in laboratories and startups around the world.
Quantum Physics
What You Say and How You Say It Matters: Predicting Stock Volatility Using Verbal and Vocal Cues
Prior research has shown that textual information in a firm{'}s financial statement can be used to predict its stock{'}s risk level.
EmTract: Extracting Emotions from Social Media
We develop an open-source tool (EmTract) that extracts emotions from social media text tailed for financial context.
