--- title: "Research" description: "Research papers on financial markets, machine learning and human behavior." updated: 2026-10-06 author: "Philipp D. Dubach" keywords: - "Philipp Dubach research" - "prediction market microstructure" - "Polymarket order book" - "glycemic response machine learning" - "Hacker News attention dynamics" - "portfolio optimization Python" - "SSRN working papers" - "quantitative finance papers" canonical_url: "https://philippdubach.com/research/" source_url: "https://philippdubach.com/research/index.md" --- # Research *Philipp D. Dubach ยท Updated October 6, 2026* --- ## Research profiles - [arXiv](https://arxiv.org/search/q-fin?searchtype=author&query=Dubach,+P+D) - [Google Scholar](https://scholar.google.com/citations?user=-69oS2wAAAAJ&hl=en) - [ResearchGate](https://www.researchgate.net/profile/Philipp-Dubach) - [SSRN](https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=9538192#form1) ## 2026 ### Measuring Trade Direction in a Prediction Market: Settlement Ground Truth and Trading-Cost Measurement on Polymarket Dubach, P. D. Dubach validates Polymarket's public trade direction against on-chain taker settlement, finding exact side and token agreement on 24.5 million matched pairs across twelve selected days. Comparing conventional trade-sign rules on the same cached tape shows how classification errors, sample selection and weighting change measured trading costs. - [Read on arXiv](https://arxiv.org/abs/2610.06412) - [Code](https://github.com/philippdubach/polymarket-trade-direction-replication) - [Dataset](https://zenodo.org/records/23164515) ### Synthetic Consumer Panels Without Microdata: Iterative Proportional Fitting from Open Aggregate Statistics Dubach, P. D. Dubach shows that a nationally representative synthetic consumer panel can be built from only freely published aggregate cross-tabulations via iterative proportional fitting, with no individual-level microdata seed. The method is instantiated for Switzerland from two free Federal Statistical Office cubes, producing 10,000 personas whose marginals reproduce the population register and validated against real Swiss human ratings from the ENERGYSCAPE panel. - [Read on SSRN](https://doi.org/10.2139/ssrn.7122180) ### The Anatomy of a Decentralized Prediction Market: Microstructure Evidence from the Polymarket Order Book Dubach, P. D. Dubach analyzes 30 billion Polymarket order-book events across 52 days to identify eight microstructure patterns, including a longshot spread premium and the finding that public-feed trade direction matches on-chain ground truth only 59% of the time. Under review at the Journal of Financial Markets. - [Read on arXiv](https://doi.org/10.48550/arXiv.2604.24366) - [The Anatomy of a Decentralized Prediction Market: Notes from the Polymarket Order Book](https://philippdubach.com/posts/the-anatomy-of-a-decentralized-prediction-market-notes-from-the-polymarket-order-book/) - [Code](https://github.com/philippdubach/polymarket-microstructure) ### The Online Gambling Fairness Paradox: Cryptographic Verification, Behavioral Harm, and Consumer Protection Dubach, P. D. Dubach presents a statistical analysis of 20,038 cryptocurrency crash game rounds, confirming cryptographic fairness while showing that mathematical fairness alone does not ensure consumer safety. - [Read on SSRN](https://doi.org/10.2139/ssrn.6065213) - [Against All Odds: The Mathematics of 'Provably Fair' Casino Games](https://philippdubach.com/posts/against-all-odds-the-mathematics-of-provably-fair-casino-games/) - [Code](https://github.com/philippdubach/stats-gambling) ## 2025 ### Attention Dynamics in Online Communities: Power Laws, Preferential Attachment, and Early Success Prediction on Hacker News Dubach, P. D. Dubach studies attention dynamics in online communities through 38 million Hacker News submissions, examining power laws in content visibility and early predictors of engagement. - [Read on SSRN](https://doi.org/10.2139/ssrn.5910263) - [65% of Hacker News Posts Have Negative Sentiment, and They Outperform](https://philippdubach.com/posts/65-of-hacker-news-posts-have-negative-sentiment-and-they-outperform/) ### Modeling Postprandial Glycemic Response in Non-Diabetic Adults Using XGBRegressor Dubach, P. D. Dubach applies a machine-learning approach to predict individual postprandial glycemic responses using continuous glucose monitoring data and meal composition. - [Read on SSRN](https://doi.org/10.2139/ssrn.5914902) - [Modeling Glycemic Response with XGBoost](https://philippdubach.com/posts/modeling-glycemic-response-with-xgboost/) - [Code](https://github.com/philippdubach/glucose-response-analysis) ## 2021 ### A Python Integration of Practical Asset Allocation Based on Modern Portfolio Theory and Its Advancements Dubach, P. D., Hilber, N. Dubach and Hilber present an open-source Python implementation of modern portfolio theory and its extensions, including Black-Litterman, risk parity, and hierarchical risk parity. - [Read on SSRN](https://doi.org/10.2139/ssrn.5915004) - [My First 'Optimal' Portfolio](https://philippdubach.com/posts/my-first-optimal-portfolio/) --- Canonical: https://philippdubach.com/research/ This file is the canonical machine-readable variant of https://philippdubach.com/research/. Author: Philipp D. Dubach (https://philippdubach.com/).