Colan Walsh, Quantitative Finance Developer in London, United Kingdom
Colan Walsh

Quantitative Finance Developer in London, United Kingdom

Member since January 13, 2020
Colan is an experienced senior financial quantitative researcher and developer, with experience across a broad range of asset classes and trading venues. He has a multi-disciplinary background, having worked in quant development, quant research, and derivatives trading for various investment banks and hedge funds. His most recent project involved managing a team of Toptal quant researchers, focused on alternative data trading strategies, using credit card transactions, app data downloads, etc.
Colan is now available for hire

Portfolio

  • Tickup
    Python, Scikit-learn, Linux, Research Management
  • Achilleon Consulting
    Reuters Eikon, Bloomberg, Excel VBA, TensorFlow, Scikit-learn, xlwings...
  • Nomura
    Reuters Eikon, Bloomberg, Analytics, Excel VBA, Python

Experience

Location

London, United Kingdom

Availability

Part-time

Preferred Environment

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

The most amazing...

...quant trading project I've worked on involved using credit card transactions and app download statistics for systematic equity trading.

Employment

  • Senior Quant Researcher and Developer

    2020 - 2021
    Tickup
    • Recruited and managed a team of remote quant researchers and data scientists, working on the delivery of 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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

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, Python, VBScript, Visual Basic, XML, SQL, Java, R
  • Libraries/APIs

    NumPy, Pandas, Scikit-learn, TensorFlow, Bloomberg API, Interactive Brokers' API, REST APIs, Python Asyncio, Quandl API, Matplotlib, SciPy, Keras
  • Tools

    Jupyter, Reuters Eikon, TensorBoard, PyCharm, IPython, Microsoft Access, Bloomberg, FINCAD, Adobe, Git, GitHub, MD5, Slack
  • Paradigms

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

    Jupyter Notebook, Windows, Ubuntu, Docker, Heroku, Linux
  • Industry Expertise

    Trading Systems
  • Storage

    JSON, Relational Databases, PostgreSQL
  • 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, IT Project Management, Quant Research Management, xlwings, Principal Component Analysis (PCA), Neural Networks, Pricing Models, Finance APIs, Processing & Threading, Macroeconomics, Economics, RESTful Microservices, Statistics, Deep Learning, Supervised Learning, Artificial Intelligence (AI), Machine Learning, Data Engineering, Analytics, Libraries, Shell Scripting, Systematic Trading, Commodity Markets, Credit Risk, Django-rest-auth, Unsupervised Learning, Research Management
  • Frameworks

    Django, Flask, Django REST Framework

Education

  • Master's degree in Mathematical Finance
    2006 - 2007
    London School of Economics - London, England
  • Bachelor's degree with first class honors in Economics and International Politics
    2002 - 2005
    University of Wales - Aberystwyth, Wales

Certifications

  • Tensorflow for Deep Learning
    JULY 2018 - PRESENT
    Udemy
  • Oracle Certified Associate, Java SE8
    MARCH 2015 - PRESENT
    Oracle
  • Exchange Trader Examination
    FEBRUARY 2013 - PRESENT
    Eurex
  • CISI Level 3 Certificate in Derivatives
    NOVEMBER 2012 - PRESENT
    Chartered Institute for Securities & Investment
  • Certificate in Quantitative Finance
    MAY 2012 - PRESENT
    CQF Institute
  • Professional Certificate in Management
    SEPTEMBER 2001 - PRESENT
    Open University

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