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Simen Bjerkelund

Financial Analyst · Quantitative Researcher · Data Scientist

Algorithmic Trading Machine Learning Norwegian Markets Risk Analytics R · Python · Shiny

About Me

I am a financial analyst and quantitative researcher with a background spanning public sector finance management (Bærum Municipality, NOK 2.2bn budget), two master’s degrees in applied finance and intelligence systems, and independent algorithmic trading development.

I build analytics tools primarily in R and Shiny, covering trade performance attribution, ML-driven opportunity scanning, Monte Carlo risk simulation, and automated economic analysis of Norwegian SSB data. I also work with Python and SQL where needed, and I continuously explore how new AI tools can augment data analysis workflows.

The purpose of this site is to explore, learn, and publish my data projects. Publishing them gives the work some skin in the game and helps raise both the quality and volume of output. The projects are driven by my own interests, but also follow news and trending topics.

Featured Projects

Trading Analytics Platform

Comprehensive R Shiny app for trade performance analysis, ML-driven strategy development, and risk optimization. Processes data from Nordnet broker.

R Shiny XGBoost Random Forest Monte Carlo

SSB Daily Dashboard

Automated daily analysis of Statistics Norway (SSB) data — economic indicators, market trends, and macro signals — refreshed every morning via GitHub Actions.

PxWebApiData GitHub Actions Quarto SSB API

Opportunity Scanner

ML-powered scanner across major stock indices using adaptive filter indicators, temporal cross-validation, and ensemble predictions.

Logistic Regression Technical Indicators Yahoo Finance

Latest from the Blog

→ See all posts on the Blog


Built with Quarto · Hosted on GitHub Pages · Updated daily

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## About Me

I am a financial analyst and quantitative researcher with a background spanning public sector finance management (Bærum Municipality, NOK 2.2bn budget), two master's degrees in applied finance and intelligence systems, and independent algorithmic trading development.

I build analytics tools primarily in R and Shiny, covering trade performance attribution, ML-driven opportunity scanning, Monte Carlo risk simulation, and automated economic analysis of Norwegian SSB data. I also work with Python and SQL where needed, and I continuously explore how new AI tools can augment data analysis workflows.

The purpose of this site is to explore, learn, and publish my data projects. Publishing them gives the work some skin in the game and helps raise both the quality and volume of output. The projects are driven by my own interests, but also follow news and trending topics.

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## Featured Projects

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    <p>Comprehensive R Shiny app for trade performance analysis, ML-driven strategy development, and risk optimization. Processes data from Nordnet broker.</p>
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      <span class="tag">XGBoost</span>
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    <h3>SSB Daily Dashboard</h3>
    <p>Automated daily analysis of Statistics Norway (SSB) data — economic indicators, market trends, and macro signals — refreshed every morning via GitHub Actions.</p>
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    <p>ML-powered scanner across major stock indices using adaptive filter indicators, temporal cross-validation, and ensemble predictions.</p>
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      <span class="tag">Logistic Regression</span>
      <span class="tag">Technical Indicators</span>
      <span class="tag">Yahoo Finance</span>
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## Latest from the Blog

*→ See all posts on the [Blog](blog/index.qmd)*

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*Built with [Quarto](https://quarto.org) · Hosted on [GitHub Pages](https://pages.github.com) · Updated daily*

© 2025 Simen Bjerkelund · Built with Quarto