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Published in Towards Data Science

·Feb 27, 2019

Preserving Memory in Stationary Time Series

Many predictive models require a certain consistency of time series called stationarity. The usual transformation, namely integer order differencing (in Finance e.g. modelling returns instead of absolute prices), eliminates memory in the data and hence affects the predictive power of the modelling. …

Machine Learning

8 min read

Preserving Memory in Stationary Time Series
Preserving Memory in Stationary Time Series

Published in Towards Data Science

·Jul 16, 2018

A Machine Learning framework for Algorithmic trading on Energy markets

New breakthroughs in AI make the headlines everyday. Far from the buzz of customer-facing businesses, the wide adoption and powerful applications of Machine Learning in Finance are less well known. In fact, there are few domains with as much historical, clean and structured data as the financial industry — making…

Machine Learning

11 min read

A Machine Learning framework for an algorithmic trading system
A Machine Learning framework for an algorithmic trading system
Simon Kuttruf

Simon Kuttruf

Deep Learner | AI for startups | Quant | "Every wall is a door"

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