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adv-financial-ml-marcos-exercises

Exercises of the book: Advances in Financial Machine Learning by Marcos Lopez de Prado

adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

algotrading

Algorithmic trading framework for cryptocurrencies.

anomaly-detection-in-equity-markets

In this repo I conduct anomaly detection in the US equity market using deep learning and the price and volume of three major index etfs: SPY (S&P 500 etf), QQQ (NASDAQ etf), and DIA (Dow etf).

bqplot

Plotting library for IPython/Jupyter Notebooks

bsm

hello-world

my first repository

iaml2017

Introductory Applied Machine Learning (INFR09029)

implied-volatility-modelling

With real market data using Black Scholes and Brentq

intraday_nope_research

machine-learning-asset-management

Machine Learning in Asset Management (by @firmai)

mean-reversion

Various python scripts to introduce mean reversion concepts.

mlfinlab

MlFinlab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

options-trading-strategies-in-python

Developing Options Trading Strategies using Technical Indicators and Quantitative Methods

pytrendfollow

PyTrendFollow - systematic futures trading using trend following

renko_trend_following_strategy_catalyst

Example of adaptive trend following strategy based on Renko

research

Notebooks based on financial machine learning.

research_public

Quantitative research and educational materials

selfstudy-note-for-advances-in-financial-machine-learning

Notebook for <Advances in Financial Machine Learning> using Python 3.7

stochastic-volatility

three stochastic volatility model: Heston, SABR, SVI

stock-price-prediction

Use Machine Learning to create a stock price predictor. Improved my technical analysis skills in the process. This is my capstone project for Udacity's Data Scientist Nanodegree Program.

svi-volatility-surface-calibration

SVI volatility surface model and an example of China 50ETF option

tick_mean_reversion

tick价差套利（参考vnpy网友资料、vnpy论坛资料、windquant）： 1、按被动腿时间戳对齐 2、profile函数展示（需要py3） 3、平稳性检验 4、对冲手数计算 5、2sigma开仓，3sigma止损(或者赌价差扩散？)6、连续止损后cool down一段时间

time-series-analysis-statistical-arbitrage

This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.

time-series-momentum

treasuryfuturetrading

A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change

volatility-study

• Conducted a volatility study to develop pairs trading strategy by writing web crawlers that automated extracting 30 equity and ETF spot and options prices data from CBOE and Yahoo Finance • Utilized NumPy, Pandas, and SciPy packages to calculate implied volatility, realized volatility, and risk premiums to measure how the market prices risk • Gathered and plotted daily VIX futures data with Selenium, Seaborn and Matplotlib to study volatility term structure • Examined volatility clustering and built forecasting tools for market risk using correlations of daily absolute returns and volatility at different time lags

volatility-trading

A complete set of volatility estimators based on Euan Sinclair's Volatility Trading