Discover MickyDowns/fin_time_series_fundamentals Open Source project

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Created almost 9 years ago
Updated almost 9 years ago

MickyDowns

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implements basic time series analysis including: estimating IBM intra-day trade durations using Epanechnikov and GCV, fitting a MARS model for SP500 options and futures prices based on moneyness and days-to-exp, performing ADF unit-root test for a multivariate rate time series, finding and estimating cointegration vectors, and regressing COFI on selected rates.

deep-theano-rnn-lstm-car

Pack of Drones: Layered reinforcement learning (Q-learning w/ RNN) for complex "hunt" behaviors

Jupyter Notebook

deep-cnn-sat-image-time-series

Deep CNN and RNN for Satellite Image Time Series

Jupyter Notebook

fin_hft_analytics

analysis of high frequency quote and trade data for F ang GM. finds a variety of "seasonal" patterns using vwap and duration measures.

fin_portfolio_volatility

builds stock portfolios based on: 1. price momentum strategies as described by Jegadeesh and Titman (2001), 2. tripartite momentum as described by Lewellen (2002), and 3. volatility quantile as proposed by Han, Yang and Zhou (2013). reports sharpe, treynor, sortino, calmar, information, and capm alpha metrics and benchmarks against buy-and-hold strategy.

fin_equity_option_pricing

pricing european puts/calls and up-and-out puts using closed form and monte carlo simulation (cev process, euler and millstein discretization)