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quantxtz's Projects

arbitrage-bot icon arbitrage-bot

An arbitrage bot that detects arbitrage opportunities between pancake and bakery swaps and manages flash swap calls, to the flash swap contract

aws-fpga icon aws-fpga

Official repository of the AWS EC2 FPGA Hardware and Software Development Kit

botvs icon botvs

quantitative trading with javascript 用Javascript进行量化交易

cnn_alpha icon cnn_alpha

Derivative work from literature review on topics of Deep CNN and image-recognition, intending to serve as potential benchmark alpha for the research project developed. The underlying logic and technique follows through with the attached abstract.

community-china icon community-china

Resources and forum for the Chinese community, maintained and moderated by CoinSummer & PL.

crypto-database icon crypto-database

Database for crypto data, supporting several exchanges. Can be used for TA, bots, backtest, realtime trading, etc.

dataframe-go icon dataframe-go

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

exchanges-php icon exchanges-php

This is a virtual currency SDK that brings together multiple exchanges

goex icon goex

Exchange Rest And WebSocket API For Golang Wrapper support okcoin,okex,huobipro,hbdm,coinex,poloniex,bitfinex,bitstamp,binance,kraken,bithumb,zb,hitbtc,fcoin

hft icon hft

real high-frequency-trading system based on c++

hft-orderbook icon hft-orderbook

Limit Order Book for high-frequency trading (HFT), as described by WK Selph, implemented in Python3 and C

investool icon investool

Golang实现财报分析、个股基本面检测、基本面选股、4433法则基金筛选与检测、基金持仓相似度、股票选基、基金经理筛选

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

lstm- icon lstm-

LSTM长短期记忆模型预测股票涨跌

machine_learning_algorithm icon machine_learning_algorithm

机器学习,数据分析。基础算法jupyter实现,包含详细注释,可以直接运行。包含:线性回归的最小二乘法和梯度下降法,K近邻(knn),K均值(k_neans),信息加权(TF-IDF),隐语义模型(LFM)梯度下降等,不断补充吧!

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