Constructs fixed-income portfolios using stratified sampling to generate buy/sell orders that align a sampled bond portfolio with a target benchmark’s risk profile when full replication isn’t feasible.
C++
Fixed Income Analytics
Analyses fixed income instruments, including interest-rate curve construction, behavioural modelling, and asset-liability management (ALM) risk simulations for banking and balance-sheet analysis.
Python
FX Black-Scholes Pricer
Implements the Black-Scholes pricing model for European foreign-exchange options, computing vanilla call/put prices, Greeks, and implied volatility with continuous domestic and foreign discounting.
C++
GARCH Volatility Model
Applies a GARCH (Generalised Autoregressive Conditional Heteroskedasticity) model to historical S&P 500 returns for estimating volatility and model parameters.
C++
Macroeconomic Regime Detection
Detects macroeconomic regimes using hidden Markov models to identify shifts in economic states or volatility patterns over time.
Python
Multi-Class Statistical Learning Pipeline
Analyses high-dimensional, multi-class data using classic machine-learning classifiers with cross-validation and visualizations (e.g., PCA, t-SNE, violin plots) for classification and statistical insight.
Python
Monte Carlo Option Pricer
A Monte Carlo option pricer focused on pricing European call options using stochastic simulation.
C++
Nasdaq Insight Dashboard
A client insights dashboard built with Plotly that visualizes Nasdaq-related data for different clients, served via a simple web application.
Python
Operational Risk Capital Modelling (CCAR)
Performs Monte Carlo simulation of operational loss events (e.g., cyber, fraud, trading) with a loss distribution approach to generate aggregated loss distributions in a format similar to the U.S. Federal Reserve’s Comprehensive Capital Analysis and Review (CCAR) capital planning framework.
C++
Simulates dynamic investment strategies and uses Monte Carlo methods to price derivatives written on strategy indices while producing risk sensitivities.
C++
Retrieval-Augmented Generation (RAG) with LLM
A Retrieval-Augmented Generation (RAG) workflow using the LangChain framework to combine document retrieval with large language model generation.
Python
Risk Model Testing Framework
Automates testing and validation of quantitative risk models, featuring metrics such as RMSE, bias, hit-rate, and regulatory-style reporting in CSV and JUnit XML formats.
C++
S&P 500 Analysis
Performs S&P 500 analysis using moving averages and feature extraction techniques.
Python
SA-CCR Counterparty Credit Risk Analytics
A counterparty credit risk analytics prototype that simulates Monte Carlo exposure profiles for interest rate, FX, and equity derivatives under the Basel III SA-CCR framework.
C++/Python
Strategy Backtesting Engine
Evaluates rule-based trading strategies on historical price data with pluggable strategy interfaces and basic profit and loss tracking.
Java