GRUENCY  /  Quantitative research

Quantitative research and econometrics

GRUENCY offers econometrics, time-series analysis, Monte Carlo simulation and forecasting for client problems. Sebastian Michalski applies the methodology he published as sole author in Physica A (Elsevier) and used in work for the National Bank of Poland.

Areas of work

  • Time-series and long-memory analysis: DFA, Hurst estimation, spectral methods
  • Monte Carlo simulation studies: estimator bias, variance and robustness
  • Forecasting models with stated uncertainty
  • Methodology review and replication of existing analyses
  • Decision-support modelling for founders and research teams
  • Second opinions on models and data work, also offered under Technical advisory

How the work is delivered

  • Brief: the question, the data and the decision it informs
  • Methodology and fixed scope agreed in writing before work starts
  • Analysis with reproducible code and stated assumptions
  • Written findings followed by a call to discuss them

Publications and awards

Elsevier / Physica A

Sole-author, peer-reviewed paper

A Monte Carlo study on reducing bias and variance in Detrended Fluctuation Analysis, a method used in econometrics, biomedical signal analysis and climate research.

NBP, National Bank of Poland

First-degree award presented by Prof. Leszek Balcerowicz

Cash-circulation optimisation and economic modelling at Poland's central bank.

SGH / PWN

Rector's First-Degree Award

For a contribution to "Econometrics and Operations Research", published by PWN.

Questions about quantitative research

Which fields do you work in?

Econometrics and finance-related problems, by background. By method, any field with time-series, simulation or estimation questions.

Can the work support publication?

Yes. The work follows the standard Sebastian uses in his own publications: reproducible code, stated assumptions and written reasoning.

How does confidentiality work?

A standard NDA is available on request. Findings and code belong to the client.

Request a consultation

Describe the question, the data and the decision it informs.

Or email info@gruency.com