Niclas Wölner-Hanssen

Team leader - Trading & Quantitative Research at LINC - Lund University Finance Society
  • Claim this Profile
Contact Information
us****@****om
(386) 825-5501
Location
Greater Malmö Metropolitan Area, SE

Topline Score

Topline score feature will be out soon.

Bio

Generated by
Topline AI

You need to have a working account to view this content.
You need to have a working account to view this content.

Credentials

  • Machine Learning for Finance in Python
    DataCamp
    Jan, 2020
    - Nov, 2024
  • Quantitative Analyst with R
    DataCamp
    Dec, 2019
    - Nov, 2024
  • Ensemble Methods in Python
    DataCamp
  • Hyperparameter tuning in Python
    DataCamp
  • Intermediate Python
    DataCamp
  • Model Validation in Python
    DataCamp
  • Supervised Learning with scikit-learn
    DataCamp
  • Time Series Analysis in Python
    DataCamp

Experience

    • Sweden
    • Non-profit Organizations
    • 1 - 100 Employee
    • Team leader - Trading & Quantitative Research
      • Aug 2022 - Present

    • Sweden
    • Investment Management
    • 1 - 100 Employee
    • Summer Intern - Quantitative Research
      • Jun 2022 - Aug 2022

    • Sweden
    • Non-profit Organizations
    • 1 - 100 Employee
    • Analyst - Trading & Quantitative Research
      • Sep 2021 - Jun 2022

      • Sentiment Analysis project in collaboration with Lynx, a USD 7 billion AUM Quantitative Hedge fund. • Analysis of social media platforms and channels to use in systematic trading. • Analysis of data availability on these platforms and the usage of NLP models to quantify sentiment. • Creation of multiple social media sentiment trading signals and analyzing their predictability on US Equities. • Sentiment Analysis project in collaboration with Lynx, a USD 7 billion AUM Quantitative Hedge fund. • Analysis of social media platforms and channels to use in systematic trading. • Analysis of data availability on these platforms and the usage of NLP models to quantify sentiment. • Creation of multiple social media sentiment trading signals and analyzing their predictability on US Equities.

    • Sweden
    • Financial Services
    • 1 - 100 Employee
    • Analyst - Front Office
      • Jan 2021 - Jun 2021

      • My main assignment at the OQAM Front Office department was devoted to commodity price driver research. • Researched the fundamentals of selected commodities: producers, consumers, exports & imports. • Analyzed the portfolio perspective of selected commodities in terms of asset allocation and security selection. • Investigated alternative data sources & how the commodities are pitched by exchanges and media etc. • Presentation of selected drivers for each commodity to the Chief Investor Officer in a convenient format. Show less

    • Sweden
    • Non-profit Organizations
    • 1 - 100 Employee
    • Analyst - Trading & Quantitative Research
      • Sep 2020 - Mar 2021

      • Machine learning project in collaboration with OQAM, a SEK 250 million AUM Quantitative Hedge fund. • Developed a dynamic data-driven asset allocation strategy based on the Random Forest algorithm. • Investigated different machine learning models and methods and their application to financial time series. • Investigated methods to prevent backtest overfitting: feature importance analysis, purged cross-validation etc. • Conducted price driver research for the S&P 500 and refined these drivers into features based on human cognitive biases such as herd mentality. Show less

    • Finland
    • Banking
    • 700 & Above Employee
    • Serviceagent
      • Mar 2017 - Dec 2020

Education

  • Ekonomihögskolan vid Lunds universitet
    Master's degree, Statistics: Statistical Methods For Data Science
    2022 - 2023
  • Ekonomihögskolan vid Lunds universitet
    Filosofie kandidatexamen (fil.kand.), Statistik
    2018 - 2022
  • Copenhagen Business School
    Finance
    2019 - 2019

Community

You need to have a working account to view this content. Click here to join now