Hedge funds: what are the main issues?

The health and dynamism of modern financial markets strongly depend on the existence of innovative and risk taking investors and institutions. Hedge funds play an important role in fostering market efficiency and stability. The theoretical value added brought by hedge funds may, however, not fully materialize in practice, looking at their performances, but hedge funds investors should be able to make informed judgments. The specific role and market impact of hedge funds may increase the potential for market manipulation and market abuse. However, hedge funds are not fundamentally different, in this regard, from other investors: strong and efficient implementation of existing rules and procedures should be adequate and sufficient to preserve market integrity. It is an open question whether stronger “governance” requirements should be introduced for those hedge funds indirectly collecting retail investors’ money, either through professional codes of conducts, market mechanisms reinforced by a “rating” process or more compulsory and binding regulations. One of the issues that could be considered is whether and how to eventually encourage hedge funds to apply the set of best practices for asset valuation proposed by the International Organization of Securities Commissions. Hedge funds’ activities may have implications for systemic risk, both through potential losses to their bank creditors and through adverse market dynamics that might in turn affect banks. Potential mitigating actions should take into account these two aspects. First, appropriate intervention by the supervisors on the prime brokers to make sure that they ask and get broad information from hedge funds and that they put in place a comprehensive risk management of all hedge funds related exposures is essential. Second, there might be scope for policy makers to encourage appropriate organization of infrastructure in order to improve the information available on the markets in which hedge funds operate. Finally, authorities may explore how to devise processes giving them, on a case by case basis, access to relevant information about hedge fund exposures and positions.

Global imbalances and financial stability

Much of the policy debate in coming years will hinge on two questions: have global imbalances contributed to the financial crisis? Is a reduction in global imbalances a prerequisite to ensuring global financial stability? In light of available research and analysis, it is reasonable to argue that common causes likely lay behind both the crisis and global imbalances. They include heterogeneous saving preferences, asymmetric financial development across countries engaged in global financial markets, and the undersupply of liquid and safe assets at the aggregate level. Looking ahead, the international community has to strike the right balance between, on the one hand, countries’ legitimate sovereignty over monetary, capital account, and exchange rate policies and, on the other hand, intensified interdependencies, the global system’s increased complexity, and diverging economic prospects across countries. Rebalancing world demand will no doubt be a gradual, long-run process. To help foster an orderly unwinding, all countries need to ensure that their policies do not create further distortions in the global economy. Several improvements to the international monetary system could be considered to help reduce incentives for distortive policies.

Particle filtering of RADAR video signals for pointwise targets

We show here the benefits on radar signal processing, of a general non-linear filtering technique, with ; 9 non-cooperative manoeuvering targets . weak signal/noise ratios. These results follow those published in [12] concerning post-processing of classical radar outputs. The common resolution tool is a particle representation of the probability space via random Dirac measures, whose weight and position are signal-conditioned . Although this approach is developed here for a coherent tracking radar, there are no limitations on the type of radar. Simulation results on particle method's performances are discussed (with weak signal/noise ratio around -10dß) .Il s'agit de montrer les bénéfices obtenus en traitement de base des signaux radar, par une approche globale des problèmes non-linéaires que pose l'extraction optimale de l'information en présence de : . cibles non-coopératives fortement manœuvrantes . faibles rapports signal/bruit. Ces résultats font suite à ceux consignés dans [12] concernant le post-traitement à la sortie d'un radar classique. L'outil de résolution commun est une représentation particulaire de l'espace de probabilité par mesures ponctuelles aléatoires, dont la masse et le support sont conditionnés par le signal. Cette approche est ici développée pour l'extracteur d'un radar de poursuite cohérent, bien qu'elle soit reproductible pour d'autres capteurs. Quelques résultats de simulation illustrent les performances obtenues à l'aide de cette technique (poursuite précise d'une cible manoeuvrante autour de -10dB)

Particle resolution and non-linear signal : processing with RADAR/SONAR applications

This paper introduces a general method for a particle solution to optimal nonlinear estimation in signal processing . We deal here with the class of discrete time Markov processes, to which the estimation problems of RADAR/SONAR signal processing belong. The main feature of particle resolution is that it generates a global picture of the probability space and therefore provides all desirable estimators (maximum likelyhood, minimum variance, etc . . . ). Its algorithmic principle relies on a dynamic version of Monte-Carlo principles and is independant of dynamic complexity (in particular the nature of non-linearities) . It is on the number of noise variables that the size of the number of particles depends, according to resolution accuracy. Convergence is inconditionaly stable under simple hypotheses. As an example, two important non-linear problems which arise in RADAR/SONAR signal processing are dealt with, using this method.Cet article présente une méthode générale de résolution particulaire pour l'estimation optimale non-linéaire en traitement du signal. Les processus considérés sont de la classe markovienne à temps discret, dont les problèmes d'estimation en traitement du signal RADAR/SONAR, pris pour illustration, sont des exemples particuliers. Le propre de la résolution particulaire est d'engendrer une exploration naturelle de l'espace de probabilité et de fournir en conséquence tous les estimateurs désirables (maxima de vraisemblance, minimum de variance,...) constituant une adaptation dynamique de la loi des grands nombres, son principe algorithmique est indépendant de la complexité dynamique (nature des non-linéarités notamment). C'est du nombre de variables "bruit" pilotant le système que dépend le plus ou moins grand nombre de particules suivant la finesse de résolution. La convergence est inconditionnellement stable sous des hypothèses simples que l'on explicite. A titre d'exemple, deux problèmes non-linéaires d'importance rencontrés en traitement du signal RADAR/SONAR sont traités par cette méthode