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Name: jke

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jke's Projects

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

alphatrading

An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.

autodataupdater

This tool is designed to update data for Amibroker

finrl-library

A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, NeurIPS 2020 DRL workshop.

hands-on-machine-learning-for-algorithmic-trading

Hands-On Machine Learning for Algorithmic Trading, published by Packt

intelligent-quantitative-trading

Contains detailed and extensive notes on quantitative trading, leveraging NLP for finance, backtesting, alpha factor research, portfolio management and optimization.

jkkms

A KMS System

longshortmemorymodelnifty

LSTM model for Nifty - trained and tested from last 15 years (with all technical indicators and other key parameters)

machine-learning-for-algorithmic-trading-second-edition

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

machinelearningstocks

Using python and scikit-learn to make stock predictions

netty-socketio

Socket.IO server implemented on Java. Realtime java framework

news-sentiment-analysis

The spider crawls moneycontrol.com and economictimes.com to fetch news of input companies and also scores and classifies the companies to raise an early warning signal

nifty_50_stock_prediction

Predicting NIFTY_50 index price movement with LSTM Keras

nlp-models-tensorflow

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

nsepy

Python Library to get publicly available data on NSE website ie. stock quotes, historical data, live indices

nsetools

Realtime Data From National Stock Exchange (India)

oianalysis

NSE Nifty Derivatives OI analysis using Python and Excel.

option_chain_analysis

NSE Nifty Option chain analysis on the web page.

priceactionexpert

A trading robot with different candlestic patterns and Fibonacci Ratios

pynse

Library to extract publicly available real-time and historical data from NSE website.

python-nse-option-chain-analyzer

The NSE has a website which displays the option chain in near real-time. This program retrieves this data from the NSE site and then generates useful analysis of the Option Chain for the specified Index or Stock. It also continuously refreshes the Option Chain and visually displays the trend in various indicators useful for Technical Analysis.

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.

screeni-py

A Python-based stock screener to find stocks with potential breakout probability from NSE India.

spring-security-oauth

Just Announced - "Learn Spring Security OAuth":

stock-forecaster

:chart_with_upwards_trend: A web based stock forecaster in Django with predictive analysis

stock-prediction

Smart Algorithms to predict buying and selling of stocks on the basis of Mutual Funds Analysis, Stock Trends Analysis and Prediction, Portfolio Risk Factor, Stock and Finance Market News Sentiment Analysis and Selling profit ratio. Project developed as a part of NSE-FutureTech-Hackathon 2018, Mumbai. Team : Semicolon

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