Pinned Repositories
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
suresh-guvvala's Repositories
suresh-guvvala/algotrading
Algo Trading using Zerodha
suresh-guvvala/AutomationWithJavaSelenium
Selinium Java Automation
suresh-guvvala/avro-serializer-java
Custom Avro serializer for reactive microservices architectures.
suresh-guvvala/CoinQuantitave
Digital currency quantitative trading
suresh-guvvala/EliteQuant
A list of online resources for quantitative modeling, trading, portfolio management
suresh-guvvala/EliteQuant_Python
Python quantitative trading and investment platform
suresh-guvvala/Fetching-Financial-Data
Fetching financial data for technical & fundamental analysis and algorithmic trading from a variety of python packages and sources.
suresh-guvvala/fracdiff
Python library to perform fractional differentiation of time-series, a la "Advances in Financial Machine Learning" by M. Prado.
suresh-guvvala/intuition
Quantitative trading kit, for hackers
suresh-guvvala/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
suresh-guvvala/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
suresh-guvvala/Online-Recurrent-Extreme-Learning-Machine
Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python
suresh-guvvala/Options-Trading-Strategies-in-Python
Developing Options Trading Strategies using Technical Indicators and Quantitative Methods
suresh-guvvala/PiggyMetrics
Microservice Architecture with Spring Boot, Spring Cloud and Docker
suresh-guvvala/Piotroski-F-Score
suresh-guvvala/quant
Quantitative Finance and Algorithmic Trading
suresh-guvvala/quant-resources
resources of quantitative trading
suresh-guvvala/Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
suresh-guvvala/RLQuant
Applying Reinforcement Learning in Quantitative Trading
suresh-guvvala/sagan
The spring.io site and reference application
suresh-guvvala/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).
suresh-guvvala/Stock-Performance-Predictor-2.0
Stock Fundamental Analysis using Machine Learning Classification Models
suresh-guvvala/StringCalculator
suresh-guvvala/test
suresh-guvvala/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.
suresh-guvvala/trading-with-python
Code that is (re)usable in in daily tasks involving development of quantitative trading strategies.
suresh-guvvala/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 😊
suresh-guvvala/ZerodhaAtom
Zerodha Browser Atomation for Algo trading without subscribing Kite API
suresh-guvvala/ZerodhaPythonScripts
All scripts are in python language to trade in zerodha using algorithms.
suresh-guvvala/zerodhatech.github.io
The zerodha.tech blog