Archive
Synthesises perspectives across academic research, practitioner reports, and regulatory guidance to evaluate how ML models behave under distribution shift and what constitutes robustness in financial forecasting. Proposes an integrated framework for evaluating robustness in financial time-series forecasting.
Implements an automated system for detecting and analysing currency exchange arbitrage opportunities. Exchange rates are modelled as a directed weighted graph; the Bellman-Ford algorithm is applied in −log(rate) space for negative cycle detection, with a profit threshold to suppress floating-point false positives. Includes a live exchange rate pipeline via exchangeratesapi.io.
Detects currency exchange arbitrage opportunities and computes optimal conversion paths using graph-based algorithms. Models exchange rates as a directed weighted graph and applies Bellman-Ford in −log(rate) space for negative cycle detection. Includes a live data pipeline via exchangeratesapi.io.
Coursework projects spanning programming languages, algorithms, and applied computing — including a JavaScript interpreter in Racket, an Unlimited Register Machine in Java, a Binomial Options Pricing Model, and NZ crash data analysis.