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cjelsa's Projects

aialpha icon aialpha

Use unsupervised and supervised learning to predict stocks

botvana icon botvana

Botvana is high-performance and event-driven trading system built using Rust (in early development).

bpytop icon bpytop

Linux/OSX/FreeBSD resource monitor

ccapi icon ccapi

A header-only C++ library for interacting with crypto exchanges. Binding for Python is provided. A spot market making application is also provided as an end-to-end solution for liquidity providers.

ccxt icon ccxt

A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges

crypto-exchange-code-samples icon crypto-exchange-code-samples

This is a collection of simple asynchronous RESToverHTTP and JSON-RPCoverWebSocket examples of how to interact with a few Crypto Exchanges.

crypto-lob-data-pipeline icon crypto-lob-data-pipeline

I built a real-time streaming data pipeline using kafka, consuming deribit-api-v2 limit order book prices ๐Ÿ“ˆ and transforming them into an order flow imbalance indicator.

cryptofeed icon cryptofeed

Cryptocurrency Exchange Websocket Data Feed Handler

decentralizedexchange icon decentralizedexchange

No Fee, Spot Decentralized Exchange (Designed on Avalanache Network, Compatible with Any EVM backed Blockchain)

deribit_easy_api icon deribit_easy_api

A wrapper around Deribit cryptocurrency exchange API to make setup easier and async orders running as oneliners

dl-algo-trader icon dl-algo-trader

Training an Agent to make automated trading decisions in a simulated stochastic market environment using Reinforcement Learning or Deep Q-Learning

epymetheus icon epymetheus

Multi-asset backtesting framework. An intuitive API lets analysts try out their strategies right away. Fast execution of profit-take/loss-cut orders is built-in. Seamless with Pandas.

futu_algo icon futu_algo

Futu Algorithmic Trading Solution (Python) ๅŸบๆ–ผๅฏŒ้€”OpenAPIๆ‰€้–‹็™ผ้‡ๅŒ–ไบคๆ˜“็จ‹ๅบ

hft-price-prediction icon hft-price-prediction

A project of using machine learning model (tree-based) to predict short-term instrument price up or down in high frequency trading.

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