suresh-guvvala Goto Github PK
Name: Suresh Reddy Guvvala
Type: User
Location: Singapore
Name: Suresh Reddy Guvvala
Type: User
Location: Singapore
Algo Trading using Zerodha
Selinium Java Automation
Custom Avro serializer for reactive microservices architectures.
Digital currency quantitative trading
A list of online resources for quantitative modeling, trading, portfolio management
Python quantitative trading and investment platform
Fetching financial data for technical & fundamental analysis and algorithmic trading from a variety of python packages and sources.
Python library to perform fractional differentiation of time-series, a la "Advances in Financial Machine Learning" by M. Prado.
Quantitative trading kit, for hackers
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
This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow
Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python
Developing Options Trading Strategies using Technical Indicators and Quantitative Methods
Microservice Architecture with Spring Boot, Spring Cloud and Docker
Quantitative Finance and Algorithmic Trading
resources of quantitative trading
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Applying Reinforcement Learning in Quantitative Trading
The spring.io site and reference application
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 Fundamental Analysis using Machine Learning Classification Models
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.
Code that is (re)usable in in daily tasks involving development of quantitative trading strategies.
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 😊
Zerodha Browser Atomation for Algo trading without subscribing Kite API
All scripts are in python language to trade in zerodha using algorithms.
The zerodha.tech blog
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.