MGT 595 coursework
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Updated
Dec 1, 2020 - Jupyter Notebook
MGT 595 coursework
Using high frequency bitcoin quotes from the bitcoincharts website. 🍎
Comprehensive Python analysis of Premier League betting market inefficiencies (2005–2024). Evaluates bookmaker biases, betting strategies, and market efficiency using statistical methods and Monte Carlo simulations.
Research-grade Polymarket BTC Up/Down 5m data pipeline, calibration analysis, hypothesis backtests, and execution robustness.
Statistical testing of the Random Walk Hypothesis on Bitcoin (BTC-USD) using ADF, Autocorrelation, Runs Test, Variance Ratio (Lo-MacKinlay), and GARCH(1,1) modelling - Python, statsmodels, arch
Alpha Asymmetry in Foreign Exchange Markets: An Investigation of Exploitability — a null result paper | DAI-2605 | Dissensus AI Working Paper
IC-Gated Deployment Framework (ICGDF): two-stage ML deployment filter for cross-sectional equity prediction. Under review at QFE (AIMS Press).
Event-study analysis of US government contract awards and stock-market reaction for defense and aerospace contractors. Tests semi-strong market efficiency using contract data and sector-matched (ITA) Benchmarking. Includes documentation and correction from SPY to ITA.
Compute the testing statistics proposed by Li and Yang (2026)
Python-based time-series analysis of stock market volatility and market efficiency in major emerging economies with GARCH-family models.
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