In his last book, Noise: a flaw in human judgmentThe Nobel Prize in Economics, Daniel Kahneman, perfectly summed up the human paradox in the face of the omnipotence of algorithms. “As human beings, we are fully aware that we make mistakes, but it is a privilege that we are not ready to share. We expect machines to be perfect. If that expectation is disappointed, we are that attitude that is ingrained and will not change until they reach near-perfect levels of prediction.”
Distinguishing between good signal and bad noise is at the heart of investment fund decision-making, be it human or algorithmic. “One of the difficulties is to extract the signal from very noisy data”describes Marie Legendre, Volatility Arbitration Portfolio Manager and Head of Volatility Arbitration Group. “It’s very tempting to extract false signals, which look like real signals but are actually statistical fluctuations.”
The scientific approach, based on empirical analysis of data and on experiments, is one of the most effective ways to distinguish between noise and signal. This is how Marie Legendre has been applying, for ten years, the scientific principles she gained during her long studies in physics to determine the best signals for making investment decisions.
The forty-year-old was still a college student when Science et Finance was created in 1994, which merged with Capital Fund Management (CFM) in 2000. Jean-Philippe Bouchaud’s approach was innovative and bold, one that consisted of trust Dozens of physicists are unfamiliar with the details of financial economics.
Intuition is in place
Mary Legendre reconverted in early 2010, when she was 32 years old. “I had been doing research in physics, including thesis, for about ten years. I felt like I had made the rounds of my major, and wanted to move on. I had previous colleagues who had already worked at CFM, and so the connection was made.”
For former physicists who had already undergone retraining, the transfer was fairly easy: “What we at CFM do is analyze a very large amount of data, from which we extract a trading signal, which will give us indications about the instruments we want to trade, our portfolio risk, and control costs. I realized that the techniques used in quantitative finance were very close to the technologies that I mastered it in basic physics. I found this very interesting, I trained myself a little. I read books and articles, then applied and the match was like that.”
Mary Legender plays a dual role as portfolio manager for volatility equilibrium and manager of volatility equilibrium group. “The two positions are closely related. I define key research strategies and manage the team of researchers working on the portfolio, while being responsible for the portfolio’s safety, risk, control, and evolution in production.”
This role is to know how to continually reconcile the short run with the long run: “You have to manage this duplication, and be very strict while figuring out the portfolio down to the smallest detail. What I learned in Physics Studies is useful to me on a daily basis. The scope of application is different but the methods are completely identical. From the researcher consists in the constant attempt to question what seems obvious. We rely on Science, on the cutting edge of technology, but we also try to suggest original alternatives, to test ideas, perhaps rejecting them if they prove irrelevant, or to validate them with scientific rigor.Our approach clearly does not exclude intuition and experience.To make a strategy, it must be You have intuitions, ideas, etc… But we assume that we need scientific evidence, simulations, and absolutely specific and objective elements to validate this intuition.
The scientific approach is also a questionable, even modest, apprenticeship in a financial sector that is often very well versed in irrational intuition and confidence.
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