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aiif

Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch.

algo_trading_and_quant_strategies

Supplemental Material for Algorithmic Trading and Quantitative Strategies

autogroq

building-machine-learning-systems-with-python-third-edition

Code repository for Building Machine Learning Systems with Python Third Edition, by Packt

deep-learning-machine-learning-stock

Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

fin-ml

This github repository contains the code to the case studies in the O'Reilly book Machine Learning and Data Science Blueprints for Finance

financial-machine-learning

A curated list of practical financial machine learning tools and applications.

hands-on-deep-learning-for-finance

Hands-on Deep Learning for Finance published by Packt.

hands-on-financial-trading-with-python

Hands-On Financial Trading with Python, published by Packt

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

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

implementing-machine-learning-finance

Source Code for 'Implementing Machine Learning for Finance' by Tshepo Chris Nokeri

learn-algorithmic-trading

Learn Algorithmic Trading, Published by Packt

python-for-finance-cookbook

Python for Finance Cookbook, published by Packt

python-machine-learning-book-3rd-edition

The "Python Machine Learning (3rd edition)" book code repository

python4finance

I get many questions about how to analyze the Stock Market with Python. I am creating a new playlist of videos that will completely cover Python for Finance.

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stock-price-prediction-and-forecasting-using-stacked-lstm

Stock-Market-Forecasting using DEEP LEARNING

stock-selection-using-sharpe-ratio

Higher is the Sharpe ratio for a stock, better are the chances for risk free returns.

stock-trends-prediction-with-macroeconomic-indicators

Stock markets are an essential component of the economy. Their prediction naturally arouses afascination in the academic and financial world. Indeed, financial time series, due to their widerange application fields, have seen numerous studies being published for their prediction. Some ofthese studies aim to establish whether there is a strong and predictive link between macroeconomicindicators and stock market trends and thus predict market returns. Stock market prediction howeverremains a challenging task due to uncertain noise. To what extent can macroeconomic indicatorsbe strong predictors of stock price ? Can they be used for stock trends modeling ? To answer thesequestions, we will focus on several time series forecasting models. We will on the one hand usestatistical time series models, more specifically the most commonly used time series approachesfor stock prediction : the Autoregressive Integrated Moving Average (ARIMA), the GeneralizedAutoregressive Conditional Heteroscedasticity (GARCH) and the Vector Autoregressive (VAR)approach. On the other hand, we will be using two deep learning models : the Long-Short TermMemory (LSTM) and the Gated Recurrent Unit (GRU) for our prediction task. In the final section ofthis paper, we look directly at companies to detect trends

stock_analysis_for_quant

Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau

stock_market

stocks

Programs for stock prediction and evaluation

tensorflow2_tutorials_chinese

tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials