Machine Learning and Quality Management of Quantitative Data - With an Application to Energy Finance

24 Pages Posted: 25 Jun 2019

See all articles by Richard Biegler-König

Richard Biegler-König

Evonik Steag GmbH; University of Duisburg-Essen - Department of Economics and Business Administration

Daniel Oeltz

RIVACON

Date Written: June 21, 2019

Abstract

In this study we propose a new application of Machine Learning techniques, namely the quality management of quantitative Financial data. The datasets in this field can include, amongst others, bootstrapped forward curves or volatility surfaces. They are provided by quantitative analysts and form the basis of trading decisions. Thus, they require very thorough quality management and plausibility checks. This tedious and non-trivial task is time-consuming and can only partially be assisted by traditional monitoring jobs. To address this problem, we propose a general framework of Machine Learning algorithms that learns from verified quantitative data and evaluates the validity of new data objects. The advantage of our approach is that it does not necessarily require domain knowledge of the data or additional model assumptions or fundamental insights. We will illustrate our idea with a study on bootstrapped forward curves from power markets and Energy Finance.

Keywords: quantitative data quality, machine learning, unsupervised learning, autoencoders, financial bootstrapping, energy finance, HPFC (Hourly Price Forward Curve)

Suggested Citation

Biegler-König, Richard and Oeltz, Daniel, Machine Learning and Quality Management of Quantitative Data - With an Application to Energy Finance (June 21, 2019). Available at SSRN: https://ssrn.com/abstract=3407885 or http://dx.doi.org/10.2139/ssrn.3407885

Richard Biegler-König (Contact Author)

Evonik Steag GmbH ( email )

Rellinghauser Straße 1-11
Essen, 45128
Germany

University of Duisburg-Essen - Department of Economics and Business Administration ( email )

Universitätsstr. 9
Essen, 45141
Germany

Daniel Oeltz

RIVACON ( email )

Im Apfelgrund 4
Friedrichsdorf, 61381
Germany

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