Discover YalDan/JumpDetectR Open Source project by @YalDan

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R
Created almost 4 years ago
Updated over 2 years ago

YalDan

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Scalable implementation of Lee / Mykland (2012), Ait-Sahalia / Jacod (2012) and Ait-Sahalia / Jacod / Li (2012) Jump tests for noisy high frequency data

hf.econometrics

Companion to publication "Understanding Jumps in High Frequency Digital Asset Markets". Contains scalable implementations of Lee / Mykland (2012), Ait-Sahalia / Jacod (2012) and Ait-Sahalia / Jacod / Li (2012) Jump tests for noisy high frequency data

icc.isvm

This library serves as a companion to the publication "Regime-based Implied Stochastic Volatility Model for Crypto Option Pricing". However it can also be used independently for clustering high dimensional datasets and fitting an implied stochastic volatility model.

ml_case_study

Machine Learning case study including an exploratory data analysis and fitting a Decision Tree, Random Forest, and XGBoost Model. Interactive notebook with outputs and visualizations: https://yaldan.github.io/ml_case_study/

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YalDan/JumpDetectR

YalDan

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