While I have an engineering background, having studied at École Centrale Paris, I have spent my entire professional life working in finance. Upon graduation, in the late 1980s, I saw an opportunity in finance for people with a mathematical background because of the developments on the markets triggered by deregulation and technical progress. While papers on option pricing theory by Black, Scholes and Merton were becoming widely publicised, it struck me at that time that the financial world was slow to adapt to those technical advances and that someone who combined a strong interest in financial economics with solid quantitative skills would have a competitive advantage in this industry.
Looking back, I cannot comment on whether that was a good or bad choice, but, for sure, I went through very exciting times, accompanying the development of derivatives trading, high frequency trading and quantitative risk management altogether spending close to twenty years on the sell-side. From a professional and practical business standpoint, it was exciting to be associated with the opening of new derivative markets and the emergence of new businesses, like structured products. From an intellectual stand point, new exotic derivative products created new challenges. The generalisation of electronic trading also became a game changer. In the wake of the institutional and market failure that we experienced with the global financial crisis, I realised that the financial world would change dramatically with regulation becoming a prominent factor shaping the industry. I also realised that, while there had been a lot of advanced academic work modelling risks or exploring the links between the real economy and financial markets, most financial institutions were lagging behind. While sitting back and reflecting, a third realisation came: that the time had come to refresh and strengthen my theoretical knowledge in quantitative finance. I started with the basics, enrolling in a Master’s in Statistics at Hong Kong University. Statistics is a key ingredient for financial modelling and with the advent of high frequency and big data, you need to master statistics to make sense of the observations and extract the signal from the noise. The programme was an eye opener: so much progress had been made in only twenty years. Along the way, I developed a keen interest in extreme value theory and advanced risk management. About the same time, I became aware of the EDHEC-Risk Institute PhD in Finance; the programme strongly appealed to me because its curriculum and format promised to allow me to meet my needs to further my knowledge of quantitative finance and acquire research skills without leaving my career.
Right now I am the risk manager for multi-strategy hedge fund. In 2008, as I expected the banking industry to enter a long period of restructuring, I took the deliberate step to cross over to the buy-side, expecting that perspectives would be more interesting in asset management. I also made the decision to switch from risk taking risk to risk management. Traditionally, risk managers, whether they came from an accounting and finance or a more quantitative background had limited understanding of markets and little or no decision making experience, which was consistent with a job definition that was focused on reporting and compliance. I think modern finance requires the risk manager to be forward looking and assist the investment manager in seeking excess returns and understanding the risk-returns trade-offs. This calls for professionals who combine practical market experience – the experience of making decisions in an incomplete information framework – with a sound theoretical knowledge of markets that draws on the academic advances engineered over the last twenty years.
I am convinced that advancing knowledge requires it to be formalised, and that research is the best process to do so. I am on this programme because I want to be able to produce research work in an area of interest to me. This requires intensive and extensive training and accepting that time will need to be spent to acquire the knowledge and master the techniques that will be essential in producing work that will add value from both an academic and a professional standpoint. So I looked forward to the programme to bring me up to speed in econometrics and financial economics… and it has delivered well beyond expectations, even though it has only been a year so far. The programme is very ambitious but not over-ambitious where it could become intractable by trying to cover too much ground. There is a good balance between imparting the theoretical knowledge that is fundamental if you want to explore the frontiers of research in finance and requiring participants to be practical through assignments which force them to confront with the data, make hypotheses, develop models and testing strategies, and interpret results to generate practical insights – this combination of knowledge and research skills will be essential at the dissertation stage. I have learnt a lot over the last thirteen months and enjoyed rewarding “Aha!” moments. I particularly enjoyed discovering the progress made in the modelling of preferences and the understanding of interactions between financial markets and the real economy. I was also expecting the programme to be demanding and I have not been short changed there – the onus is on the participant to balance the demands from work, family and the programme.
I definitely see huge benefits because the school environment allows for very different interactions from those you have in corporate settings and even in personal and social relationships. In particular, the opportunity to work on projects together fosters exchanges and relationships which are very direct, very open, and very different from anywhere else. I learnt a lot from group projects and found cooperation with other participants to be very synergistic. Of course, diversity is also precious in the classroom because people from different backgrounds ask different questions and raise different issues with the professors, which not only widens the horizons for all and helps in the understanding of interrelations, but can also have relevance for people working in different fields. The programme brings together highly motivated individuals with outstanding professional achievements and a wide diversity of backgrounds; these are essential ingredients for the success of this type of adventure.
It would be incorrect to describe me as a seasoned high frequency trader: serious people have been working in this area for years dedicating 100% of their time to programming trading algorithms; I have not been that far. I started my career trading options and doing index arbitrage on the Japanese markets at a time when these were already accepting electronic orders. I did a fair amount of work on electronic options markets in Asia, mostly on the Japanese and the Korean markets, but this was mostly work of a practical nature. This is because the importance of modelling the market was second to getting your information technology (IT) right; hence a significant part of my experience revolved around working with the IT engineers to solve issues of connectivity and latency. For very long, having the right technology and connectivity were far more important than having the best model for the order book or the bid-ask spread. Now, the understanding of how markets work has evolved a lot thanks to academic work and this has fuelled progress towards efficient and orderly markets. Having academics research the price discovery process has been of great significance to the financial community and has informed the regulatory debate.
I have not been involved in high-frequency trading or microstructure issues for a few years, so I am very interested to learn about the latest research results and the pending questions in an area which asset managers should strive to understand and closely follow.
I have submitted ideas to the committee and I am looking forward to their feedback, but I would like to work on the interaction between the variance premium – the high cost associated with carrying a long volatility position – and credit markets. This is something I have observed as a practitioner for a long time and I definitely want to take a research stab at it. Some work has been done already, but I hope I can produce something innovative. Another area which of interest to me is performance and risk measurement because, it is an integral part of my job in a multi-strategy fund to evaluate strategies’ alpha and understand potential adverse correlation events. There has been a lot of work in the area and I need to become more familiar with it to determine how I could try and make an original contribution to the field.