Research axes

Amongst the research areas of most interest to the QMI are:

Statistical Signal Processing

Application of signal treatment to the estimation of factorial models, the detection of outliers, the filtering of trends and the robust estimation of Kalman models is an active research field of the IdR QMI. 

A «Quantitative asset management » session leaded by Serge Darolles, Member of the QMI has been organised by the QMI for the Computational Financial Econometrics (CFE) conference in Sevilla on the 12-14 December 2016. 

Listed market liquidity

Measure of the market liquidity of different assets.

Serge Darolles, Gaëlle Le Fol and Gulten Mero are working on dynamics measures of short-term and long-term liquidity measures based on the autocorrelation of return, volume and volatility. This research has been presented several times in international conferences and is conditionally accepted in Journal of Econometrics.
Taking another look at serial correlations, Adrien Becam, Serge Darolles and Gaelle Le Fol are working on hedge funds liquidity and managers’ skills.
Serge Darolles, Gaëlle Le Fol and Jean Michel Zakoian work, with another co-author, on liquidity adjusted conditional risk measure. This research was presented in Stockholm in June 2016 and has been published in Annals of Economics and Statistics in December. Fabrice Riva is for his part, with two co-authors, working on ETF liquidity.
A « Managing Liquidity » session leaded by Gaëlle Le Fol, Member of the QMI has been organised by the QMI for the Computational Financial Econometrics (CFE) conference in Sevilla on the 12-14 December 2016. This also was the topic of the QMI Annual conference and particularly of the panel session. 

Algo and/or High frequency trading

Optimisation of the VWAP (Volume Weighted Average Price) price replication algorithms, link between the speed of placing orders on the market and the arrival of information, liquidity trade-offs, maximum trading capacity.

Vincent van Kervel and Albert Menkveld, from VU University of Amsterdam have received in 2013 funding of 5,000 for their project untitled Predatory trading in equity markets. This research has been presented at the second QuantValley/QMI Annual Research Conference in Paris in November 2014 and is now completed.
Algo and High frequency trading defenders say that they provide liquidity and improve price efficiency. Serge Darolles, Gaëlle Le Fol and Gulten Mero, in a new paper, show that investors are acting strategically – by slicing their orders - to avoid being picked-off by HFTs. Doing so, they slow down the propagation of information in the prices. Again, this research has been presented several times in international conferences.
Marius Zoican and his co-author Marlene D. Haas the Josseph de la Vega Prize 2016 of the The Federation of European Securities Exchanges (FESE) for their working paper "Discrete or continuous trading? HFT competition and liquidity on batch auction markets". Marius Zoican, with some co-authors, has two papers on speed he has been presenting at several seminars and international conferences. One of them, writin with Albert Menkveld is forthcoming in Review of Financial Studies.

 

Contagion and funds flows

A measure of liquidity comovements between the currencies of various emerging economies, link between currency liquidity and liquidity of dollar debt markets, impact of hedge fund flows on contagion phenomena between countries.

Mardi Dungey and Eric Renault have also received funding of 10,000 euros by the QMI for their project on contagion modelling. This project is now completed and this research has been presented at the QMI annual conference.

Risk disaggregation and portfolio allocation

Decomposition of a portofolio’s asset’s risk contribution into systematic risk contribution and idiosyncratic risk contribution, method of allocation controlling the relative proportion of either contribution. Application to index and market-neutral portfolio creation.

Until recently the liquidity of financial assets has typically been viewed as a second-order consideration. Liquidity was frequently associated with simple transaction costs that impose effect on asset prices, and whose shocks could be easily diversified away. Yet the evidence suggests that liquidity is now a primary concern. Serge Darolles, Gaëlle Le Fol and Jean-Michel Zakoïan in their research aim at disentangling market risk and liquidity risk in the context of conditional volatility models. Their approach allows the isolation of the intrinsic liquidity of any asset, and thus makes it possible to deduce a liquidity risk even when volumes are not observed. This research was presented in Stockholm in June 2016 and has been published in Annals of Economics and Statistics in December. Fabrice Riva is for his part, with two co-authors, working on ETF liquidity.
Related to this subject, Dong Lou and Christopher Polk, from London School of Economics have presented their work on the booms and busts of beta arbitrage: measuring the extent of the low-beta crowd during the QMI Annual Conference in March. 

Trend Following Strategies

Nick Baltas from Imperial College have presented their work on Momentum strategies in futures markets and trend-following funds during the QMI Annual Conference in November 2014. The corresponding paper has been published in the BMI Hedge Funds Special issue co-edited by Serge Darolles.

Big data, machine learning and the new sources of information (Google, Twitter, ...)

The University of Rotterdam’s project  also relates to this theme. A paper on the statistical analysis of big data has been presented at several international conferences by Christian Gouriéroux. This research will be published soon in Journal of Econometrics. QMI organized a workshop on “New challenges for Big Data in Economics and Finance” together with the University of Toronto and the Fileds Institue in Toronto in November and a Conference "Big Data: A revolution for financial markets and the asset management industry?" in Paris in March.