Colan is available for hire

Colan Walsh

Verified Expert in Engineering

Software Developer

Location

London, United Kingdom

Toptal Member Since

March 3, 2020

Colan is an experienced senior financial quantitative developer and researcher with experience across various asset classes and trading venues. He has a multidisciplinary background, having worked in quant development, quant research, and derivatives trading for multiple investment banks and hedge funds. Colan has built and managed teams of quant researchers from the ground up on numerous occasions.

Futures Excel Reporting Quantitative Finance Data Analysis Stock Exchange Exploratory Data Analysis Statistical Data Analysis Statistical Analysis Data Scientist Data Wrangling Currency Exchange Algorithms IT Project Management Algorithmic Trading Artificial Intelligence (AI)

Portfolio

AmateMint Labs LLC

Python, Algorithmic Trading, Algorithmic Trading Analysis, Google Cloud...

Hedgix Management Limited

Architecture, Agile, SQL, Databases, Python, Hedge Funds, Assets, Investments...

TokenEdge

Python, Google Cloud Platform (GCP), Linux, Docker, Pandas, Scikit-learn...

Experience

Quantitative Finance - 15 years Derivatives - 13 years Algorithmic Trading - 11 years Python - 6 years Data Science - 6 years Machine Learning - 5 years Crypto - 3 years

Availability

Part-time

Preferred Environment

Jupyter, PyCharm, TensorFlow, Scikit-learn, Pandas, Python, Linux, SQL, Docker

The most amazing...

...quant research team I've built generated returns of 20-30% (unleveraged) from market-neutral algorithmic crypto trading.

Work Experience

Expert Fintech/Algorithmic Trading Developer

2023 - PRESENT

AmateMint Labs LLC

Built a live algorithmic trading platform, architected to be integrated with APIs from multiple futures brokers.
Developed a high-performance event-based backtesting engine to calibrate and optimize the client's trading strategy.
Worked closely with the client on iterative trading algorithm refinement and optimization of entry and exit levels for high-frequency trading strategy.

Technologies: Python, Algorithmic Trading, Algorithmic Trading Analysis, Google Cloud, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, High-frequency Trading (HFT), Backtesting Trading Strategies, Pine Script, Pandas

Financial Engineer and Tech Lead

2023 - 2023

Hedgix Management Limited

Architected a microservices-based cloud-hosted algorithmic trading platform (OMS/EMS) integrated with ChatGPT API, multiple brokers (e.g., IBKR), and market data services, supporting high-frequency trading and long-term investing strategies.
Designed a derivatives structuring validation engine, providing validation around complex derivatives structures generated by LLM before execution.
Prepared a detailed backlog and development estimates for the implementation of the trading architecture and validation engine.

Technologies: Architecture, Agile, SQL, Databases, Python, Hedge Funds, Assets, Investments, MySQL, Banking & Finance, Azure, Derivatives, Microservices, Algorithmic Trading, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Extraction, Data Wrangling, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Project Management, Entity Relationships, ETL, Generative Pre-trained Transformers (GPT), Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, Backtesting Trading Strategies, Stock Market, Technical Leadership, Pandas

Quant Researcher

2022 - 2023

TokenEdge

Performed large-scale cross-sectional modeling of NFT price time series dynamics, using PCA, across the top 500 collections on the Ethereum blockchain.
Built a predictive ensemble model for NFT price direction classification, incorporating SGD, KNN, and simple neural networks, among others.
Set up Google Cloud Platform-based quant research environment, with Docker deployment and GCS for data storage.
Evaluated various NFT/token market data vendors and built data pipeline integrations with the top choices.

Technologies: Python, Google Cloud Platform (GCP), Linux, Docker, Pandas, Scikit-learn, Matplotlib, Algorithmic Trading, Data Science, Machine Learning, Blockchain, Ethereum, SQLAlchemy, DataFrames, Visual Basic, Exchanges, Digital Asset Management, Stock Exchange, Fractionalization, Protobuf, Asynchronous I/O, Amazon S3 (AWS S3), Agile, Architecture, Assets, Investments, Banking & Finance, Amazon RDS, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Data Analysis, Data Visualization, Exploratory Data Analysis, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Extraction, Data Wrangling, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Non-fungible Tokens (NFT), Web3, Entity Relationships, ETL, Amazon Web Services (AWS), Cryptocurrency, Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, Backtesting Trading Strategies, Binance API, XLSX File Processing

Senior Quant Researcher and Algorithm Developer

2021 - 2022

SPS Trading

Recruited and managed a team of remote quant researchers and data scientists focused on crypto algorithmic trading strategies.
Managed a team focused on generating a portfolio of market-neutral strategies.
Architected and implemented a Python-based algorithmic trading and backtesting platform designed explicitly for crypto spot and derivatives trading.

Technologies: Python, Crypto, Machine Learning, Algorithmic Trading, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Microservices, Asyncio, Docker, WebSockets, Excel 2016, Data Engineering, Relational Databases, SQL, Git, GitHub, Bitcoin, Bots, Back-end, APIs, Team Leadership, MySQL, Amazon EC2, Amazon Web Services (AWS), Data Science, Databases, Deep Neural Networks, Data Reporting, REST, Docker Compose, AWS Lambda, GraphQL, Pytest, REST APIs, Redis, Non-fungible Tokens (NFT), Excel Macros, Finance, AWS Cloud Architecture, Cloud, Arbitrage, Forex, Trading Systems, Multithreading, Financial Market Data, Fixed Income, FX Risk Analysis, gRPC, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, SQLAlchemy, DataFrames, Excel Reporting, RDS, Exchanges, Digital Asset Management, Stock Exchange, Protobuf, Asynchronous I/O, CTO, Leadership, Blockchain, Amazon S3 (AWS S3), Flask, Agile, Architecture, Assets, Investments, Banking & Finance, Amazon RDS, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Exploratory Data Analysis, MQL4, MQL5, MQL, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Extraction, Data Wrangling, Serverless, API Integration, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Web3, Data Build Tool (dbt), Entity Relationships, Snowflake, ETL, Cryptocurrency, Machine Learning Operations (MLOps), Amazon SageMaker, Regression Modeling, Financial Modeling, Fintech, High-frequency Trading (HFT), Backtesting Trading Strategies, Binance API, Technical Leadership, Pine Script, Pandas, XLSX File Processing

Head of Quant Development and Research

2020 - 2021

Tickup

Recruited and managed a team of remote quant researchers and data scientists, working on delivering equity trading strategies using alternative datasets.
Worked with a Stockholm-based data team for onboarding and cleaning complex semi-structured alternative datasets such as Ravenpack (news feeds), ConsumerEdge/Yodlee (credit card data), Apptopia (app downloads), and Estimize (crowd-sourced estimates).
Led the development of alternative data-based quantitative trading strategies, delivering unleveraged returns of 20-40% per annum in backtesting.
Served as lead architect for a Python-based algorithmic trading and backtesting platform designed around alternative data and machine learning trading strategies (using Scikit-learn and TensorFlow).

Technologies: Python, Scikit-learn, Linux, Research, Management, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Microservices, Asyncio, Docker, WebSockets, Data Engineering, Relational Databases, SQL, Git, GitHub, Bitcoin, Bots, Back-end, APIs, Team Leadership, MySQL, Amazon EC2, Amazon Web Services (AWS), Data Science, Databases, Deep Neural Networks, Data Reporting, REST, Docker Compose, Pytest, REST APIs, PostgreSQL, Redis, Finance, Interactive Brokers API, AWS Cloud Architecture, Machine Learning, Cloud, Arbitrage, Forex, Trading Systems, Multithreading, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, SQLAlchemy, DataFrames, RDS, Exchanges, Digital Asset Management, Stock Exchange, Asynchronous I/O, CTO, Leadership, Blockchain, Flask, Agile, Architecture, Assets, Investments, Banking & Finance, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Exploratory Data Analysis, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Factor Analysis, Data Wrangling, FIX Protocol, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Project Management, Non-fungible Tokens (NFT), Web3, Entity Relationships, ETL, Apache Airflow, Cryptocurrency, Machine Learning Operations (MLOps), Regression Modeling, Financial Modeling, Fintech, High-frequency Trading (HFT), Backtesting Trading Strategies, Stock Market, Binance API, Technical Leadership, Pandas, XLSX File Processing

Freelance Python Quant Researcher and Developer

2018 - 2020

Achilleon Consulting

Created an algorithmic trading platform expressly designed to handle machine learning based trading strategies. The platform incorporates multi-threaded/asynchronous architecture, handling multiple data sources and trading venues simultaneously.
Implemented a machine learning (neural network) model for derivatives pricing, using Scikit-learn and TensorFlow, with hyperparameter optimization using Scikit-optimize.
Designed and implemented a standardized REST API for market data retrieval and transformation from multiple heterogeneous data sources. Built wrappers for Bloomberg, Reuters Eikon, IBKR, Quandl, Oanda, and FXCM.
Coded risk and P&L calculation tools for a long-short equity hedge fund, incorporating an Excel/VBA front end and a Python back end connected via xlwings.
Implemented an event screener framework for a long-short equity hedge fund to streamline the management of event-based trading.
Created an equity trading strategy simulator, incorporating what-if, optimization tools, and trade event visualizations.
Designed and trained machine learning models for equity trading to assist with momentum trading (especially entry and exit timing) and to optimize trailing stop implementation.
Created model for cross-market equity beta decomposition via unsupervised learning (Scikit-learn).
Coded a trading strategy optimization framework for VIX trading for a volatility trading hedge fund.

Technologies: Reuters Eikon, Bloomberg, Excel VBA, TensorFlow, Scikit-learn, xlwings, Django, Flask, Pandas, NumPy, Python, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Microservices, Asyncio, Docker, WebSockets, Excel 2016, Data Engineering, Django REST Framework, Relational Databases, SQL, Git, GitHub, Bitcoin, Bots, Back-end, APIs, Team Leadership, Amazon EC2, Amazon Web Services (AWS), Microsoft Excel, Data Science, Databases, Deep Neural Networks, Data Reporting, REST, Docker Compose, Pytest, REST APIs, PostgreSQL, Redis, Excel Macros, Finance, Interactive Brokers API, AWS Cloud Architecture, Machine Learning, Cloud, Arbitrage, Trading Systems, Multithreading, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, SQLAlchemy, DataFrames, Visual Basic, Excel Reporting, RDS, Exchanges, Stock Exchange, Asynchronous I/O, Blockchain, Amazon S3 (AWS S3), Agile, Architecture, Assets, Investments, Banking & Finance, Algorithmic Trading Analysis, Automated Trading Software, Mathematical Finance, Mathematics, Exploratory Data Analysis, MQL4, MQL5, MQL, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Startups, Data Extraction, Data Wrangling, FIX Protocol, DevOps, Artificial Intelligence (AI), Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Cryptocurrency, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, High-frequency Trading (HFT), Stock Market, XLSX File Processing

Rate Derivatives Desk Quant

2016 - 2018

Nomura

Fully refactored risk and P&L tools for swaptions trading in London and New York, covering EUR, USD, and GBP. Included overhaul of scenario generation, and generation of real-time risks intraday.
Fully refactored risk, P&L, pricing tools, for inflation derivatives (EUR, GBP, USD), covering inflation swaps, bonds, options. Included refinement of inflation RV trade screening tools.
Refactored position monitoring and pricing tools for STIRT and FX Forward trading desk in London and New York. Included configuring price publication to downstream customer-facing systems via Tibco bus.
Coded an optimum vega hedging algorithm for swaptions trading, identifying the best P&L hedging trades given an input vega grid.
Refactored curve and volatility surface builders for swaptions and inflation options.
Built a PCA-based framework for alternative rates delta/gamma risk and P&L explanation.

Technologies: Reuters Eikon, Bloomberg, Analytics, Excel VBA, Python, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Data Science, Databases, Data Reporting, REST, REST APIs, Jira, Excel Macros, Finance, Arbitrage, Trading Systems, Financial Market Data, Fixed Income, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Optimization, Linear Optimization, DataFrames, Power Query, Excel Reporting, Exchanges, Stock Exchange, Fractionalization, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Exploratory Data Analysis, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, FIX Protocol, Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Regression Modeling, Financial Modeling, Fintech, XLSX File Processing

Rate Derivatives Quant Trader

2015 - 2016

Caxton Associates

Executed derivatives trades (exchange and OTC) on behalf of portfolio manager with $500 million AUM; fed funds futures, eurodollar/euribor futures, FRAs, OIS, swaps, and basis.
Developed portfolio risk and P&L calculation tool, using ALIB quant analytics. Included position and market data retrieval, risk & P&L calculation. Capable of retroactively generating risk/P&L for any past date.
Created market data retrieval/processing/storage framework, sourcing data from third-party APIs: Bloomberg, BAML, JPM, Citi, and Barclays.
Coded relative-value market monitor for spot and forward swap and basis rates; including the charting of historic rolldown/carry/range/correlation.
Built "short-end" market monitor: a live and historic analysis tool for Libor and OIS futures/swaps; including Libor/basis predictive analytics.
Created a dashboard tool to display results of various econometric/technical analyses, continuously updated from Bloomberg/Haver DLX. For example, bund scarcity analysis, MACD-based TY price tracking, 5y5y equilibrium modeling.
Created a knowledgebase tool: hashtag-based PDF/text research organizing framework, integrated with multiple other tools (e.g. SignalMonitor, Dashboard).
Created the SignalMonitor tool: realtime monitoring of market data levels (or any arbitrary function of levels) for trade entry/exit signals, with email/desktop/text alerts. Integrated with KnowledgeBase to automatically send appropriate research.

Technologies: Adobe, FINCAD, Bloomberg, Excel VBA, VBScript, Python, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, REST APIs, Excel Macros, Finance, Arbitrage, Trading Systems, Financial Market Data, Fixed Income, Computational Finance, Quantitative Finance, Hedge Funds, Data Analysis, Time Series, Time Series Analysis, Optimization, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Predictive Modeling, Predictive Analytics, ETL, Regression Modeling, Financial Modeling, Fintech, XLSX File Processing

Derivatives Quant Trader

2012 - 2015

Royal Bank of Scotland

Contributed as part of a two-person trading team involved in the creation of a new trading desk to algorithmically market-make exchange-traded bond options, including dynamic-VAR-based automated hedging, and on-the-fly SABR volatility surface calibration.
Implemented technology platform for RBS Strategic Hedging program, to reduce bank-wide RWA/SVAR using vanilla options to hedge tail risk, including designing the algorithms to solve for optimal RWA-reducing vanilla options hedges.
Risk-managed the FX/Rates Hybrid Derivatives trading portfolio, including calculation and hedging of FX/Rates Delta/Gamma/Vega, using options, futures, swaps, and FX. It also included involved and executing customer requests for exotic derivatives.
Managed algorithmic FX/Rates cross gamma hedging algorithms for the Hybrids portfolio using the RBS Agile algorithmic trading platform.
Managed NPV valuations for portfolio auctions to other banks (PRDCs, TEC10 CMTs, structured notes). This also included driving risk compressions for a large portfolio of long-dated FX options.
Worked closely with Dynamic Strategies desk on VAR-based algorithmic hedging framework for custom index options.
Developed trading strategy backtesting engine, used to discover and optimize trading strategies for the Dynamic Strategies (Custom Index) trading desk.

Technologies: XML, R, Excel VBA, Visual Basic, Reuters Eikon, Bloomberg, Algorithmic Trading, Libraries, Analytics, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Stock Trading, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, Excel Macros, Finance, Arbitrage, Forex, Trading Systems, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Fractionalization, Leadership, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Predictive Modeling, Predictive Analytics, ETL, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, XLSX File Processing

FX and Rates Derivatives Desk Quant

2010 - 2012

Royal Bank of Scotland

Completely refactored legacy risk and P&L management tools for FX/IR hybrid derivatives (including long-dated FX options), covering traders in London, New York, and Tokyo, and reducing the start-of-day process from two hours (in Tokyo) to 30 seconds.
Implemented a new FX and Rates cross-gamma scenario analysis toolkit, covering six rate curves and volatility surfaces and ten FX forward curves and volatility surfaces.
Contributed to the "RBS Agile" algorithmic platform to implement automated hedging for FX and Rates cross-gamma.
Created an Excel VBA-based risk aggregation framework, used by six trading desks across the bank, which provided PV/risk/scenario aggregation or drill down to individual trade levels.
Coded an Excel add-in used extensively across the Royal Bank of Scotland, containing utility array manipulation functions.
Developed and improved curve-building tools: FX-forwards; swaps; bond, funding, and credit spreads; CMS/CMT cross-currency adjusted discounting; equity dividends; and correlation term-structure.
Revised volatility surface building tools for swaptions, cap floors, FX options, equity, and commodity index primarily using SABR, and incorporating implied vol event-weighting.
Built a set of tools to publish structured note prices to Reuters and Bloomberg, used by several trading desks across the Royal Bank of Scotland.
Created a trading strategy simulation engine, used for custom index strategy research.
Implemented the "Generic Position Sheet," an automatically configurable risk management tool that could be used transparently by any trading desk in the bank.

Technologies: XML, Excel VBA, Visual Basic, Reuters Eikon, Bloomberg, Algorithmic Trading, Libraries, Analytics, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, REST APIs, Jira, Excel Macros, Finance, Arbitrage, Forex, Trading Systems, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Fractionalization, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, XLSX File Processing

Exotic Rates and FX Derivatives Quant Developer

2008 - 2010

Credit Suisse

Maintained 12 complex trading risk and position workbooks, built on the Credit Suisse GMAG quant library, covering inflation, exotic rates, rate/FX hybrids, commodity/FX hybrids, and counterparty credit risk.
Migrated numerous VBA-based risk scenario generation algorithms to a COM-based analytics framework, allowing overnight scenario risk calculations to run in parallel on server farms.
Rolled out new interest rate curve models for 12 currencies across two business areas. A highly complex project, requiring very close co-operation with the quant group, trading, product control and risk control, and other IT groups.
Created a complete set of new trading tools for Inflation trading portfolio; including risk and position tools; P&L decomposition tools, market data publication tools; risk scenario design.

Technologies: Shell Scripting, Excel VBA, Visual Basic, Libraries, Analytics, Algorithms, Options Trading, Financial APIs, Trading, Financial Markets, Excel 2016, Data Engineering, Relational Databases, SQL, Microsoft Excel, Databases, Data Reporting, Jira, Finance, Arbitrage, Forex, Trading Systems, Financial Market Data, Fixed Income, FX Risk Analysis, Computational Finance, Quantitative Finance, Data Analysis, Time Series, Time Series Analysis, Linear Optimization, Power Query, Excel Reporting, Exchanges, Stock Exchange, Assets, Investments, Banking & Finance, Mathematical Finance, Mathematics, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, FIX Protocol, Predictive Modeling, Predictive Analytics, Entity Relationships, ETL, Regression Modeling, Financial Modeling, Fintech, Currency Exchange, XLSX File Processing

Experience

Algo Trading Platform for Machine Learning Trading Strategies

The project involved creating an algorithmic trading platform expressly designed to handle machine learning-based trading strategies. The platform incorporates multi-threading, multi-processing and asynchronous architecture, and is capable of running large numbers of independent strategies, and handling multiple data sources and trading venues simultaneously. The platform is accessible by front-end applications via a REST API (using Flask).

Neural Network Approximation of Derivatives Pricing Models

The project involved replication of existing vanilla derivatives pricing models with densely-connected neural networks (DNNs). The machine learning stack used was Scikit-Learn and Tensorflow, with hyperparameter optimization using Scikit-Optimize.

Standardized REST API for Heterogenous Market Data Sources

The project involved designing a single standard REST API specification to cover a range of market data sources, with varying requests and return formats: Bloomberg, Reuters Eikon, IBKR, Quandl, Oanda, and FXCM. Wrappers were built around the native APIs for these data sources, allowing significant removing complexity to be removed from downstream systems.

Equity Market Beta Decomposition Model

The objective of this project was to use unsupervised learning techniques (using Scikit-Learn) to allow identification and removal of both general market beta, and automated identification of equity clusters (groups of highly correlated stocks). This work was undertaken for an equity long-short hedge fund.

Optimum Vega Hedging Tool

This project was undertaken for a swaptions trading desk at an investment bank.

The tool allowed a trading desk to identify the best maturity/expiries to trade to minimize P&L volatility, given an input vega grid, and taking into account historical correlations across the volatility surface.

Signal Monitor Tool for Real-Time Market Signal Notifications

This was created for a macro hedge fund. The SignalMonitor tool allowed realtime monitoring of market data levels (or any arbitrarily complex function of those levels) for specific thresholds e.g. for trade entry/exit signals. The tool generated email/desktop/text alerts and was integrated with a hashtag-driven knowledge base such that appropriate research would be automatically sent with the alert.

RWA Reduction Trading Platform

I was a quant trader on the new "Strategic Hedging" trading desk, whose purpose was to reduce bank-wide RWA/SVAR using vanilla options to hedge tail risk. I built the technology platform from the ground up, including designing the algorithms to solve for optimal RWA-reducing vanilla options hedges.

FX & Rates Exotic Derivatives Cross Gamma Toolkit

This project involved working with scenario generation results from multiple risk engines, delivered unreliably, and in an inconsistent format, to a risk database. The toolkit had to deal with missing or incorrect scenario results, the transformation of scenario results in a consistent format, and aggregation for display purposes. The cross-gamma coverage was 6 rate curves and SABR volatility surfaces, and 10 FX forward curves and SABR volatility surfaces.

Derivatives Risk Aggregation Toolkit

Created an Excel VBA-based risk aggregation framework, used by six trading desks across the bank, which provided PV/risk/scenario aggregation or drill down to individual trade level. It also allowed design and sharing of standardised reports, and batch delivery of reports to risk management sheets.

Skills

Languages

Excel VBA, SQL, Python, Visual Basic for Applications (VBA), VBScript, Visual Basic, XML, MQL4, MQL5, MQL, Pine Script, Java, R, GraphQL, Snowflake

Libraries/APIs

NumPy, Pandas, Scikit-learn, Bloomberg API, Interactive Brokers API, Binance API, TensorFlow, REST APIs, Python Asyncio, Asyncio, SQLAlchemy, Quandl API, Matplotlib, SciPy, Keras, Protobuf

Tools

Jupyter, Reuters Eikon, Excel 2016, Microsoft Excel, Bloomberg, TensorBoard, PyCharm, IPython, Microsoft Access, Celery, Power Query, FINCAD, Adobe, Git, GitHub, MD5, Slack, Docker Compose, Pytest, Jira, Apache Airflow, Amazon SageMaker

Paradigms

Agile, Functional Programming, Object-oriented Programming (OOP), Data Science, Agile Project Management, Quantitative Research, Microservices, Asynchronous Programming, Concurrent Programming, REST, ETL, Scrum, Test-driven Development (TDD), Management, DevOps

Platforms

Jupyter Notebook, Amazon Web Services (AWS), Docker, Blockchain, Ubuntu, Heroku, Linux, Amazon EC2, Google Cloud Platform (GCP), Ethereum, Azure, AWS Lambda

Industry Expertise

Trading Systems, Banking & Finance, Project Management, High-frequency Trading (HFT)

Storage

JSON, Databases, MySQL, Amazon S3 (AWS S3), Relational Databases, PostgreSQL, Redis, Google Cloud

Other

FX, Interest Rate Risk, Interest Rate Swaps, Fixed-income Derivatives, Derivatives, Options Trading, Trading Applications, Cross-currency Swaps, Swaps, Bonds, Futures, Options Theory, Option Pricing, Risk Models, Market Risk, Support Vector Machines (SVM), Decision Trees, Random Forests, Volatility, Portfolio Optimization, Mathematical Finance, Algorithmic Trading, Algorithmic Trading Analysis, Foreign Exchange (FX) Hedging, FX Risk Analysis, Quantitative Finance, Financial Market Data, Fixed Income, Multithreading, Artificial Intelligence (AI), Machine Learning, IT Project Management, Fintech, Algorithms, Financial APIs, Trading, Financial Markets, Stock Trading, Stock Market, Excel Expert, Bots, Back-end, APIs, Non-fungible Tokens (NFT), Arbitrage, Forex, Data Analysis, Excel Macros, Finance, Computational Finance, Hedge Funds, Data Visualization, Time Series, Time Series Analysis, Optimization, Linear Optimization, DataFrames, Excel Reporting, Exchanges, Digital Asset Management, Stock Exchange, Leadership, Architecture, Assets, Investments, Automated Trading Software, Mathematics, Monte Carlo Simulations, Exploratory Data Analysis, Data Scraping, Statistical Methods, Statistical Data Analysis, Statistical Analysis, Data Scientist, Factor Analysis, Data Extraction, Data Wrangling, API Integration, Predictive Modeling, Regression Modeling, Financial Modeling, Currency Exchange, Backtesting Trading Strategies, Regression, Technical Leadership, XLSX File Processing, xlwings, Principal Component Analysis (PCA), Neural Networks, Pricing Models, Finance APIs, Processing & Threading, Macroeconomics, Economics, RESTful Microservices, Statistics, Deep Learning, Supervised Learning, Data Engineering, Crypto, Cryptocurrency, Decentralized Finance (DeFi), Bitcoin, Team Leadership, Deep Neural Networks, Data Reporting, AWS Cloud Architecture, Cloud, RDS, Fractionalization, Asynchronous I/O, CTO, Startups, Probability Theory, Predictive Analytics, Web3, Data Build Tool (dbt), Entity Relationships, Machine Learning Operations (MLOps), Analytics, Libraries, Shell Scripting, Systematic Trading, Commodity Markets, Credit Risk, Unsupervised Learning, WebSockets, Research, Econometrics, Politics, Amazon RDS, Serverless, FIX Protocol, Generative Pre-trained Transformers (GPT)

Frameworks

Flask, Django, Django REST Framework, gRPC

Education

2006 - 2007

Master's Degree in Mathematical Finance

London School of Economics - London, England, UK

2002 - 2005

Bachelor's Degree (First Class Honors) in Economics and International Politics

University of Wales - Aberystwyth, Wales, UK

Certifications

JULY 2018 - PRESENT

Tensorflow for Deep Learning

Udemy

MARCH 2015 - PRESENT

Oracle Certified Associate, Java SE8

Oracle

FEBRUARY 2013 - PRESENT

Exchange Trader Examination

Eurex

NOVEMBER 2012 - PRESENT

CISI Level 3 Certificate in Derivatives

Chartered Institute for Securities & Investment

MAY 2012 - PRESENT

Certificate in Quantitative Finance

CQF Institute

SEPTEMBER 2001 - PRESENT

Professional Certificate in Management

Open University