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While the availability of new trading destinations since MiFID came into effect on 1 November 2007 has improved the liquidity offer and the available information on the price formation process, it also simultaneously increases, exponentially, the complexity of intra-day trading.
While the search for a counterpart and the price discovery take place on their own time scale, the fair value of the exchanged assets and its level of uncertainty evolve on another time scale. One of the difficult tasks for investors is to find a balance between those two time scales.
Once the fair price of an asset is known with a good level of certainty, trading too fast might cause a loss on the microstructure scale, such as paying a large price impact or missing the adequate counterpart. Taking these two time scales into account requires finding a subtle balance between trading fast, to minimise the market risk, and trading slowly, to be sure of having enough information on the price formation process and finding a counterpart large enough to avoid market impact. Moreover, the appropriate combination is unique for each investor; it has to take into account his or her own risk aversion.
"That's why investors are well advised to utilise SORs (Smart Order Routers) and trading algorithms that are best adapted to this new context," says Lehalle.
New destinations have a strong incentive to innovate in terms of trading rules, thus trading algorithms must continuously evolve as new destinations become available. Tick size also has a clear impact on trading efficiency and must thus be taken into account by SORs to efficiently route orders. To be efficient, SORs must for example be adapted to the fact that the sensitivity of some stocks to NY opening on Chi-X is really different from those on their primary markets.
Moreover, the optimal way to trade a stock on a given trading destination depends on a subtle mix between the trading rules of the destination, the type of investor populating it, and the specific properties of the stock and its underlying asset. Embedding quantitative methods in algorithmic trading and SOR strategy is a good answer to the continuously changing mix of investors.
"Navigating Liquidity," CA Cheuvreux's analysis of the issues surrounding liquidity access, concludes that the well known strategy of using trading algorithms to optimise the execution of large orders by slicing them in volume-indexed intervals, now has a cross-exchange equivalent: optimal slicing across trading destinations, taking into account investors' risk aversion.
"This trading approach will have to be adapted to the rate of change in the European landscape which, to-date, has developed later than in the US and is likely to have fewer ultimate destinations," concludes Lehalle.
About the Author Charles-Albert Lehalle is Head of Quantitative Research at CA Cheuvreux. He also lectures at the "Paris 6 (Elkaroui) Master of Finance" (Ecole Polytechnique, ESSEC, Ecole Normale Suprieure) and gives master classes in the Certificate in Quantitative Finance in London. He has also given lectures at numerous seminars and international conferences at MIT and the University of Edinburgh.
With a Ph.D. in applied mathematics, Charles is an expert in stochastic processes, information theory and nonlinear control. He has published international papers in quantitative finance, real time optimisation of high dimensional processes (with applications to Formula One, high mix fabs, large plants, aerospace), and learning theory.
