suresh-guvvala Goto Github PK

algotrading

Algo Trading using Zerodha

automationwithjavaselenium

Selinium Java Automation

avro-serializer-java

Custom Avro serializer for reactive microservices architectures.

coinquantitave

Digital currency quantitative trading

elitequant

A list of online resources for quantitative modeling, trading, portfolio management

elitequant_python

Python quantitative trading and investment platform

fetching-financial-data

Fetching financial data for technical & fundamental analysis and algorithmic trading from a variety of python packages and sources.

fracdiff

Python library to perform fractional differentiation of time-series, a la "Advances in Financial Machine Learning" by M. Prado.

intuition

Quantitative trading kit, for hackers

machine_learning_in_finance

Built a trading algorithm in Python for the Tesla stocks returning in 39% higher returns than a simple buy and hold strategy, over a period of 2016-2018 . Designed random forest algorithm that combines CAPM, FAMA (French three factor model), Multi-Factor Linear Regression, Principal Component Analysis and Time series analysis to forecast stock prices . Generated trading signals using strategies such as Bollinger bands, Double crossover with evaluating risk and Sharpe ratio

neural-net-with-financial-time-series-data

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow

online-recurrent-extreme-learning-machine

Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python

options-trading-strategies-in-python

Developing Options Trading Strategies using Technical Indicators and Quantitative Methods

piggymetrics

Microservice Architecture with Spring Boot, Spring Cloud and Docker

piotroski-f-score

quant

Quantitative Finance and Algorithmic Trading

quant-resources

resources of quantitative trading

quantitative-notebooks

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

rlquant

Applying Reinforcement Learning in Quantitative Trading

sagan

The spring.io site and reference application

stanford-project-predicting-stock-prices-using-a-lstm-network

Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).

stock-performance-predictor-2.0

Stock Fundamental Analysis using Machine Learning Classification Models

stringcalculator

test

timeseriesoncryptocurrency

The case is financial time-series prediction with cryptocurrencies and it integrates knowledge from various sources - Crypto Currencies, Quantitative Finance, and Machine learning. The data consists of time-series of various cryptocurrencies with open, high, low, close prices and volumes from different crypto exchanges, but it could also be enriched during the Datathon by the teams. The goal is to build a successful investing/trading model on the cryptocurrency markets.

trading-with-python

Code that is (re)usable in in daily tasks involving development of quantitative trading strategies.

zerodha_live_automate_trading-_using_ai_ml_on_indian_stock_market-using-basic-python

Online trading using Artificial Intelligence Machine leaning with basic python on Indian Stock Market, trading using live bots indicator screener and back tester using rest API and websocket 😊

zerodhaatom

Zerodha Browser Atomation for Algo trading without subscribing Kite API

zerodhapythonscripts

All scripts are in python language to trade in zerodha using algorithms.

zerodhatech.github.io

The zerodha.tech blog