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adialab-notebooks

advanced-deep-trading

Mostly experiments based on "Advances in financial machine learning" book

advanced_feature_engineering_of_raw_data_of_stocks-with_pyspark

Features and labels engineering of raw data of quotes of several stocks.

advances_in_financial_machine_learning

I tried to solve the questions in 'Advances in Financial Machine Learning' by Lopez de Prado. Many are cloned from other gits.

awesome-deep-trading

List of awesome resources for machine learning-based algorithmic trading

axial-lob-high-frequency-trading-with-axial-attention

Pytorch implementation of Axial-LOB from 'Axial-LOB: High-Frequency Trading with Axial Attention'

bokeh-candlestick

Simple and responsive candlestick chart in Python with Bokeh

candlestick-patterns

Candlestick patterns detector

ceemdan-lstm

deep-convolution-stock-technical-analysis

Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.

deep-portfolio-management

Source code for the blog post on the evolution of the asset allocation methods

deep-trading

Algorithmic trading with deep learning experiments

dl_forfinance

This git repository is based on the work of J.Heaton, N.Polson and J.Witte and their articleDeep Learning for Finance: Deep Portfolios. This paper let us explore the use of deeplearning models for problems in financial prediction and classification. Our goal isto show how applying deep learning methods to these problems can produce betteroutcomes than standard methods in finance or in Machine Learning

dqn-global-stock-market-prediction

eigenportfolios

In this project, we will explore the usage of Principal Component Analysis to model market behavior within an industry. Furthermore, we will explore the interpretation of top eigenvectors as portfolios to create trading strategies.

enhancing-price-momentum-with-rnn

This is a repository for a (working) master thesis seeking to enhance the conventional price momentum strategy by leveraging machine learning. Currently, we are examining LSTM, however, MLP and Random Forrest might also be leveraged.

f-ml

Code, Exercises, and Fun from Lopez de Prado's "Advances in Financial Machine Learning"

featurewiz

Use advanced feature engineering strategies and select best features from your data set with a single line of code.

fin-gan

Code to accompany the paper "Fin-GAN: Forecasting and Classifying Financial Time Series via Generative Adversarial Networks"

finance_ml

Advances in Financial Machine Learning

financial-algorithms

I propose here several algorithmic trading strategies on diverse asset classes

gdax-bot

HFT signals on GDAX

google-research

Google Research

graphembedding

Implementation and experiments of graph embedding algorithms.

gs-quantify-bond-prediction

Solution of the given task of predicting the buying and selling volume of the corporate bonds.

imaging_time_series

indexprediction

k-nearest-neighbors-with-dynamic-time-warping

Python implementation of KNN and DTW classification algorithm

kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

lstm_stock_modeling