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dxdp-quant's Projects

appsmith

Quickly build any custom business software like admin panels, internal tools, dashboards and more with pre-built UI widgets that connect to any database, GraphQL or REST API, controlling everything with Javascript.

autotrader

A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

backtesting.py

:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.

backtrader

Python Backtesting library for trading strategies

crypto-arbitrage

Crypto arbitrage trading

cufflinks

Productivity Tools for Plotly + Pandas

cyclotron

A web platform for constructing dashboards.

deep-learning-machine-learning-stock

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

financedatareader

Financial data reader

financial-analysis-stack

Demonstrating how various distributed data and parallel processing techniques could be used for financial analysis.

finrl

Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance. NeurIPS 2020 & ICAIF 2021. 🔥

fluentui

Fluent UI web represents a collection of utilities, React components, and web components for building web applications.

influxdb

Scalable datastore for metrics, events, and real-time analytics

influxdb-relay

Service to replicate InfluxDB data for high availability.

kiwoom-restful

Restful API bridge server/client for Kiwoom

metabase

The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:

neofinrl

Tens of market environments for quant finance.

numba

NumPy aware dynamic Python compiler using LLVM

py4fi2nd

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

pykiwoom

Python Wrapper for Kiwoom OpenAPI+

pykrx

KRX 주식 정보 스크래핑

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.

react-financial-charts

Charts dedicated to finance.

react-stockcharts

Highly customizable stock charts with ReactJS and d3

spectre

GPU-accelerated Factors analysis library and Backtester

stock-analysis-engine

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

stock-prediction-models

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

stock_analysis_for_quant

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

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.

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