On paper, a financial engineer’s job is to price derivatives using inputs and models, and use logic to help clients, usually institutional investors for hedge funds or pension funds, to assess the fair value of their derivatives holdings.
But if you ask Antoine de la Borderie, a financial engineer on the Bloomberg Valuation (BVAL) Derivatives team in London, he gives a deeper view into this role and why it requires precision and dexterity. Especially with end-of-day valuations, it demands data-based decision making, while the client consultancy side of the role relies on an attuned ability to listen.
The human side of pricing
“Pricing could be seen like a black box, which is wrong,” Antoine says. Financial engineers provide all the explanation, consultation, and support that a client might need to better understand Bloomberg’s pricing on a model. With hundreds of highly sophisticated models available to use in pricing, a financial engineer’s edge is in their human ability to rationalize and determine which model could apply best to an instrument.
“Our goal is to develop some new tools for our clients to make evaluations more transparent or easier to understand,” he says. “Or we’ll try and develop a new model with quants, or think about how to integrate our evaluation service in a synergetic way within Bloomberg’s product ecosystem (such as MARS, PORT, and AIM).”
Antoine says, “Even though financial engineering may appear technical on paper, our role has a human element to it. We’ve got the knowledge and we understand pricing. And, we regularly interact with business managers, quants, engineers, and IT specialists enabling us to serve as a go-between helping clients with their questions.”
Also, just don’t assume the answer is a one-size-fits-all – or even that there is a single right answer when it comes to pricing.
“It makes me crazy to hear: You’re doing math and you should only get one price.” Yes and no. “The pricing model is only one part of the equation,” says Antoine.
What else is in that price equation?
Pricing inputs – the curves, surfaces, cubes, and so on feeding the mathematical models are an art form requiring a great practitioner’s experience. “Each derivative exhibits a specific financial behavior, and there is always a pricing model more adapted to catch this behavior,” Antoine says.
Model calibration of ensuring the parameters are adjusted properly and consistent, is another subtle complexity that, done wrong will make a good model yield wrong prices.
Hedging market prices also comes into play, as additional trading costs should be added to reflect the final derivative price – though they may not be part of the theoretical calculation. “A good financial engineer should be aware of the pricing techniques used to produce a price more in line with the reality of trading,” Antoine says.
And of course context is everything. For example, when collateral is involved, a part of the derivative valuation will depend on the portfolio trading netted positions, so in a way the pricing of one derivative will imply the valuation of the whole portfolio.
The 30,000-foot view
Human decision-making is especially important when it comes to the most intensive part of Antoine’s day, when evaluations are produced and sent to clients, corresponding to the end of the financial day in London.
“At the end of each day, “We check our valuations to measure how close they are to market observations.
Antoine and his team use statistical measures to ensure quality control of the massive amounts of data they manage.
“Now picture the cockpit of a plane,” he says. His desk is set up with multiple terminal screens showing inputs, prices, and market data, is reminiscent of a pilot’s controls.” The idea is to check that the ‘green lights,’ so to speak, so that all systems are a “go.”
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