Trading Risk Analytics
Welcome to Phi Alpha Analytics Ltd, your partner for cutting-edge risk analytics in the wholesale energy trading sector. Our expertise spans three decades, ensuring you receive top-notch financial risk models and insights to inform your decision-making.
About Me
During 30 years in the energy industry I have built and led technical teams and large programmes of work, developed global policies and frameworks for the validation of trading valuation models, and developed countless mathematical/ financial models to provide practical solutions to difficult problems and add commercial value. I am adept at explaining complex ideas & models to non‐specialists and developing positive relationships across all levels of the business.
Experience Highlights
Jan 2015 – Sep 2020
Portfolio Analytics Director – BP Supply & Trading
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BP’s expert on Credit PFE, leading in-house development of global PFE systems, developing and documenting the principles, methodologies and computational details of calibration, price simulation, MTM aggregation and reporting.
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Developed bespoke tools & analytics for credit staff to approximate PFE and Cost of Credit for deals with asset-specific characteristics and illiquid underlyings, enabling deals to go forward.
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Developed a global ‘Credit Tail Risk’ model to evaluate the Unexpected Loss aspect of our counterparty credit risk exposures.
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Reviewed and revised BP’s Probability of Default methodology and coded in python, underpinning our cost of credit numbers and bp’s credit capital.
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Helped commercial teams to understand the valuation and risk impacts of contract optionalities.
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Ran training sessions on credit risk for the broader Finance function.
Sep 2007 – Dec 2014
Global Head of Risk Quantitative Analysis – BP Supply & Trading
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Launched a new team responsible for model validation of all non-linear valuation models used by BP globally. Wrote the operating standard and hired all team members. Provided management, guidance and technical oversight of all validations. Models encompassed European & Asian options, swing, spread & spark-spread options, storage, tolling, and more.
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Worked with front office to develop an understanding of the sources of value and risk in a 15-30 year deal (worth about $1bn), and developed pre-deal economics and a MTM model.
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Developed MTM models for numerous long-term methanol, petcoke-to-methanol, oil pipeline, and structured products deals.
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Developed the LNG ‘renegotiation risk’ methodology for bp’s economic evaluation framework.
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Standing member of the Board which reviewed and defined the Accounting and MTM valuations for new complex transactions.
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Technical advisor to Market Risk, e.g. on liquidity adjusted VaR, NPV@Risk, etc.
Services
We offer expert advice, quant development and training for the energy trading industry
Advisory Services
Expert advice on valuation, risk and the use of models in the energy trading sector, based on 30+ years experience.
Analytics Development
Development of bespoke quantitative models covering economic evaluation, mark-to-market, market risk and credit risk.
Training
Tailored training for risk and middle-office staff on mark-to-market concepts, deal valuation & risk of deals with embedded optionality, market & credit risk, and model validation.
Contracts
Reviewed and validated a spreadsheet economic model covering formulas, assumptions and outcomes.
Outlined a proposal to develop a fully integrated model capable of modelling and computing a range of financial and risk outputs based on a complex set of inputs, and a range of deal structures, pricing formulas and geographical locations.
Developed an initial option valuation model to model and evaluate LNG deals with embedded optionality of specified type which can be adapted for future commercial structures.
Developed an economic & commercial decision-making model model in python code in support of pricing assessments and price structuring for LNG origination and trading deals within EU and Asia.
The code was written as a collection of functions, ensuring that every step of a computation can be audited and verified. When different scenarios are run, alternative versions of data structures are produced and are fully traceable. Excel input templates were developed for ease-of-use, scalability, and flexibility. Outputs consist of dataframes plus a number of specially designed reports which summarise results and compare results between scenarios, which allows the client to look at the portfolio effects of deals under a range of scenarios and understand the risk-reward basis for commercial decisions.
Developing python code to model the value of gas storage contracts. We will provide a suite of storage valuation methodologies, e.g. Intrinsic, Rolling Intrinsic (RI), and Least Squares Monte Carlo (LSMC); with the ability to run RI and LSMC over different simulation instances / price processes. Historical price data pulled from the client’s database will feed the calibration of price-process parameters used in the Monte Carlo simulation of prices. Delta positions will also be computed to support an understanding of exposures and potential delta-hedging. Graphical / tabular presentation of outputs and functional user documentation will be provided; along with presentations to explain the models and storage modelling principles.