quanttradered Goto Github PK

algorithm-trading-webapp

Algorithm Trading web application with Python, Django, PyQt5 and Javascript

alphago

A replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search," details of which can be found on their website.

anomaliesinoptions

In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.

aqtrader

AQTrader (AutoQuantTrader) is tool that gather a sub-penny coin fast (in front of roadroller).

bok_mp_minutes

BoK 금통위 의사록 / 기준금리 분석

chatgpt_stock_report

그날의 증권사 리포트를 챗 gpt를 활용해 요약하는 레포

chosunyepjeon

ChosunYepJeon (Korea Ancient Cryptocurrency technology)

courier

Courier is a simple, opinionated, source code dependency manager

data-course

djangocupcakeshop

website source code 장고컵케이크샵 소스코드

exchange-core

Ultra-fast exchange engine

fastlogger

Memory mapped logger

fedwatchtool_test

FedWatchTool 분석 및 테스트

ficc_report_scrapping

네이버 금융 / 채권 리포트 스크랩핑 / 텍스트 추출

financial-models-numerical-methods

Collection of notebooks about quantitative finance, with interactive python code.

finquant

A program for financial portfolio management, analysis and optimisation.

github-actions-test-workflow

hftbacktest

A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.

liquibook

Modern C++ order matching engine

ordermanagertest

pub-sub-python-zeromq-protobuf

Playing around with ZeroMQ (4), CurveMQ, Python3, Protobuf 3

pycoinone

Python wrapper for Coinone API

pykiwoom

Python Wrapper for Kiwoom OpenAPI+

real_estate_ml

Machine Learning for Real Estate

ruruki

spoqa-pycon-2015-codegolf

파이콘 코리아 2015 이벤트 페이지입니다.

stock_report_gpt_analytics

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.

switch-config-render

test