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stackgan-pytorch

stacknet

StackNet is a computational, scalable and analytical Meta modelling framework

stargan

PyTorch Implemenation of "StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation"

stationarizer

Smart, automatic detection and stationarization of non-stationary time series data.

statistical-arbitrage-algorithmic-trading

A Project to identify statistical arbitrage opportunities between cointegrated pairs. This is referred to as 'Pairs Trading' which is a bet on the mean reversion property of the spread.

stochasticoptimization.jl

Implementations of stochastic optimization algorithms and solvers

stock-market-crashes

How to detect stock market crashes with topology.

stock-market-prediction-using-intrinsic-valuation

This is a data mining project carried out using Rapid Miner tool. This project is part of my ongoing Independent study and research in Data Mining. A data mining model in Rapid Miner tool was created, and Yahoo API as a data source was used. We trained on past stock market data with Stock Price as target and different Intrinsic Values which influence that stock price. Our model used two predictive algorithms and gave results of top 50 performing stocks, which should be bought. We have build a data mining model which uses the absolute stock valuation method(Intrinsic Stock Valuation) for determining if the stocks are undervalued or overvalued.

stock_market_prediction

Team Buffalox8 predicts directional movement of stock prices.

stock_prediction

make stock prediction model using Tensorflow, Python and web crawling

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

stockpredictionrnn

High Frequency Trading Price Prediction using LSTM Recursive Neural Networks

stockpredictions

Stock Predictions through NYTimes article headlines sentiment analysis.

stocktwits

Python client for StockTwits API

strategems.jl

Quantitative systematic trading strategy development in Julia

stream-anomaly-detect

Implementation of algorithms proposed by [Huang and Kasiviswanathan]

streamad

Online anomaly detection for streaming data.

streamalert

StreamAlert is a serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using datasources and alerting logic you define.

strtsmrt

Stock price trend prediction with news sentiment analysis using deep learning

structuredinference

Structured Inference Networks for Nonlinear State Space Models

subpixel

subpixel: A subpixel convolutional neural net implementation with Tensorflow

support-and-resistance

Differential equation that models the support and resistance strategy

supresgenerator

Automatically generate Support & Resistance Lines on charts

surpriver

Find big moving stocks before they move using machine learning and anomaly detection

swa

Stochastic Weight Averaging in PyTorch

swa_keras

Stochastic Weight Averaging in Keras

symplectic-gradient-adjustment

A colab that implements the Symplectic Gradient Adjustment optimizer from "The mechanics of n-player differentiable games"

ta

Technical analysis routines for Python

ta-lib

Python wrapper for TA-Lib (http://ta-lib.org/).

talks

Collection of Public Talks