myvrml Goto Github PK

a-deep-learning-based-illegal-insider-trading-detection-and-prediction-technique-in-stock-market

Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf

a-dual-stage-attention-based-recurrent-neural-network-for-time-series-prediction

alphalens

Performance analysis of predictive (alpha) stock factors

apply-nlp-in-chinese-stocks-prediction

attention

some attention implements

attention_network_with_keras

An example attention network with simple dataset.

attentioned-dual-stage-stock-prediction

By PyTorch

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

backtrader

Python Backtesting library for trading strategies

backtrader_multifactors

BackTrader多因子回测框架 （Multi-factors backtesting framework for BackTrader）

bayesianoptimization

A Python implementation of global optimization with gaussian processes.

bert

TensorFlow code and pre-trained models for BERT

bert-keras

Keras implementation of BERT with pre-trained weights

bert-pytorch

Google AI 2018 BERT pytorch implementation

bnlstm

Batch normalized LSTM for tensorflow

btgym

Scalable, event-driven, deep-learning-friendly backtesting library

commodity-channel-index

My Final Project for Basic Algorithm and Programming

convolutional-neural-stock-market-technical-analyser

Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.

copper_price_forecast

copper price(time series) prediction using bpnn and lstm

cvxportfolio

Portfolio optimization and simulation in Python

deep-rl-trading

Playing trading games with deep reinforcement learning

deep_trader

This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.

deepdow

Portfolio optimization with deep learning.

deeplearningbook-chinese

Deep Learning Book Chinese Translation

deepstock

Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:

deeptrade_keras

dopamine

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

echostatenetworks

Materials related to the Medium article "Predicting Stock Prices with Echo State Networks".

equity-price-prediction

examples