Yurii Handziuk

Welcome to my website!

I am a PhD Candidate in Finance at HEC Paris.
I am on the 2024-2025 academic job market.

My research interests are asset management, machine learning, asset pricing, and sustainable finance.

You can find my CV here

You can contact me at: yurii.handziuk@hec.edu

Asset Demand Systems via Data Augmentation: Competition and Differentiation in Asset Management

Abstract: Many institutional investors hold portfolios with few holdings. This makes it challenging to precisely estimate their individual demand. In this paper, I seek to make two contributions. First, I propose a data augmentation technique based on the generation of data-driven and economically interpretable synthetic assets. I show that this data augmentation acts as an adaptive nonlinear shrinkage which automatically adjusts the shape of the penalty to the cost of overfitting faced by the nonlinear demand function estimator. The resulting estimation technique leads to substantial improvement in cross-out-of-sample R² for estimation of both low-dimensional and high-dimensional demand functions. Second, I use the proposed methodology to construct a measure of investor differentiation. Using the Morningstar mutual fund ratings reform in 2002 as a shock to competition for alpha, I show that mutual funds escape the increased competition intensity by differentiating from their competitors.

Presentations: Hi! Paris Summer School on Artificial Intelligence & Data for Science, Business and Society, HEC Paris PhD Workshop, HEC Paris Brown Bag Seminar.

Carbon Information, Pricing, and Bans. Evidence from a Field Experiment
(with Stefano Lovo)

Abstract: How can we encourage the adoption of low carbon footprint (CF) consumption habits? In a large-scale field experiment at a university canteen, we find that adjusting dish prices to positively correlate with their carbon footprint is the most effective policy, leading to a 26.8% reduction in CF. This approach outperforms policies such as banning high-CF dishes once a week (10% CF reduction) or merely informing consumers of dishes’ CF (non-significant reductions). In a follow-up survey, when asked to choose between taking no action and these three policies, only 3.5% of respondents preferred no action, while 60% supported the price adjustment policy.

Presentations: 8th NTHU-UNSW Symposium on Sustainable Finance and Economics*, Economics seminar CRESE*, ESCP-UNEP Conference*, French Inter-Business School Workshop in Finance*, Neoma Sustainable Finance conference*, HKUST*, HEC Paris Foundation Meeting, 3rd Sustainable Finance Conference TSE*, HEC Paris Brown Bag Seminar*.
*: presentation by co-author.

Media coverage: Les Echos

Mutual Fund Holdings and Innovative Investment Strategies
(solo-authored)

Abstract: Using methodology based on regularized linear regression, I estimate the exposures of portfolios of active mutual funds to a large set of return predictors. Contrary to the previous studies which conclude that mutual funds tend to tilt their portfolios against the stocks that are predicted to have high return, I find that once the liquidity of the stocks is controlled for and less known definitions of characteristics are included into the set of studied characteristics, the exposure of mutual funds to return predictors becomes more salient. I further provide evidence that those funds that tilt their portfolio towards relatively more innovative predictors outperform the average fund, while funds that tilt their portfolios to relatively less innovative, "canonical" anomalies tend to underperform the average fund.

Presentations: HEC Paris Brown Bag Seminar.

Escape Competition Effect in Hedge Fund Industry

Data Analysis in Finance (Master in Data Science for Business), HEC Paris/École Polytechnique (Tutorial Instructor, 2024)
Financial Economics (Master in Management), HEC Paris (Lecturer, 2021)
Financial Economics (Master in Management), HEC Paris (Tutorial Instructor, 2020)