hf.econometrics
Unverified ML strategy on Crypto by YalDan. BotFinder score 18 out of 100.
Companion to publication "Understanding Jumps in High Frequency Digital Asset Markets". Contains scalable implementations of Lee / Mykland (2012), Ait-Sahalia / Jacod (2012) and Ai
Source: github
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hf.econometrics
High Frequency Econometrics Package in R ================ Saef, Danial 11/05/2022 This library serves as a companion to the publication “Understanding Jumps in High Frequency Digital Asset Markets”. However it can also be used independently for clustering high dimensional datasets and fitting an implied stochastic volatility model. 1 Methodology This library contains implementations of a few recent publications in the field of High Frequency Econometrics: - Lee & Mykland Jump Test (Lee and Mykland 2012) - Ait-Sahalia & Jacod Jump Test & Test for Jump Activity + variation estimation (Aït-Sahalia and Jacod 2012) - Ait-Sahalia, Jacod & Li Jump Test (Ait-Sahalia, Jacod, and Li 2012) - Pre-averaging approach ( Jacod et al. (2009), Jacod, Podolskij, and Vetter (2010) ) The methods can be used in a stand-alone fashion or when obtained from the Blockchain Research Center with additional functionalities. 2 Usage 2.1 Installing The usage is pretty simple. First, install the package with devtools. Note that this library is still experimental, s.t. no proper unit testing or object classes have b
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