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financial-economics

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Replication package for 'The Anatomy of a Decentralized Prediction Market: Microstructure Evidence from the Polymarket Order Book.' Eight stylized facts on a pre-registered 600-market panel plus a methodological result: feed-inferred trade direction agrees with on-chain ground truth on ~59% of buckets vs ~80% Lee-Ready on equities.

  • Updated May 14, 2026
  • Python

In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.

  • Updated Dec 5, 2022
  • TeX

End-to-End Python implementation of Markov-Switching VAR framework for detecting endogenous financial fragility. Replicates Delli Gatti et al.'s (2025) methodology using EM algorithm, Hamilton filtering, and HP spectral decomposition to empirically test Minsky's Financial Instability Hypothesis in macroeconomic data.

  • Updated Nov 23, 2025
  • Jupyter Notebook

End-to-End Python framework reproducing Dolphin et al.'s (2026) grounded event extraction (from SEC 8-K filings) method. Extracts taxonomy-validated, quote-grounded event tags via LLMs, then proves economic significance through variance-standardized abnormal returns (SAR), Kruskal-Wallis tests, and bootstrap variance decomposition over CRSP data.

  • Updated Jul 11, 2026
  • Jupyter Notebook

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