|
on Market Microstructure |
| By: | Christophe Chorro (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Florian Ielpo (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Unigestion SA - UNIGESTION , IPAG Business School); Benoît Sévi (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - UN - Université de Nantes) |
| Abstract: | The extraction of the jump component in dynamics of asset prices haw witnessed a considerably growing body of literature. Of particular interest is the decomposition of returns' quadratic variation between their continuous and jump components. Recent contributions highlight the importance of this component in forecasting volatility at different horizons. In this article, we extend a methodology developed in Maheu and McCurdy (2011) to exploit the information content of intraday data in forecasting the density of returns at horizons up to sixty days. We follow Boudt et al. (2011) to detect intraday returns that should be considered as jumps. The methodology is robust to intra-week periodicity and further delivers estimates of signed jumps in contrast to the rest of the literature where only the squared jump component can be estimated. Then, we estimate a bivariate model of returns and volatilities where the jump component is independently modeled using a jump distribution that fits the stylized facts of the estimated jumps. Our empirical results for S&P 500 futures, U.S. 10-year Treasury futures, USD/CAD exchange rate and WTI crude oil futures highlight the importance of considering the continuous/jump decomposition for density forecasting while this is not the case for volatility point forecast. In particular, we show that the model considering jumps apart from the continuous component consistenly deliver better density forecasts for forecasting horizons ranging from 1 to 30 days. |
| Keywords: | leverage effect,density forecasting,jumps,realized volatility,bipower variation,median realized volatility |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-01442618&r=mst |
| By: | Hacène Djellout (LMBP - Laboratoire de Mathématiques Blaise Pascal - UBP - Université Blaise Pascal - Clermont-Ferrand 2 - CNRS - Centre National de la Recherche Scientifique); Hui Jiang (Nanjing University of Aeronautics and Astronautics - Department of Mathematics) |
| Abstract: | Recently a considerable interest has been paid on the estimation problem of the realized volatility and covolatility by using high-frequency data of financial price processes in financial econometrics. Threshold estimation is one of the useful techniques in the inference for jump-type stochastic processes from discrete observations. In this paper, we adopt the threshold estimator introduced by Mancini where only the variations under a given threshold function are taken into account. The purpose of this work is to investigate large and moderate deviations for the threshold estimator of the integrated variance-covariance vector. This paper is an extension of the previous work in Djellout Guillin and Samoura where the problem has been studied in absence of the jump component. We will use the approximation lemma to prove the LDP. As the reader can expect we obtain the same results as in the case without jump. |
| Keywords: | Jump Poisson,Large deviation principle,Quadratic variation,Threshold estimator |
| Date: | 2017–03–19 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01147189&r=mst |
| By: | Andreas Karpf (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Antoine Mandel (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics); Stefano Battiston (Department of Banking and Finance - UZH - University of Zürich [Zürich]) |
| Abstract: | This paper presents an analysis of the European Emission Trading System as a transaction network. It is shown that, given the lack of a centralized market place, industrial actors had to resort to local connections and financial intermediaries to participate in the market. This gave rise to a hierarchical structure in the transaction network. To empirically relate networks statistics to market outcomes a PLS-PM modeling technique is introduced. It is shown that the asymmetries in the network induced market inefficiencies (e.g. increased bid-ask spread). Albeit the efficiency of the market has improved from the beginning of Phase II, the asymmetry persists, imposing unnecessary additional costs on agents and reducing the effectiveness of the market as a mitigation instrument. |
| Abstract: | Cet article présente une analyse du système européen de négociation d'émissions comme un réseau de transactions. Il est démontré que, compte tenu de l'absence d'un marché centralisé, les acteurs industriels ont dû recourir à des structures locales des intermédiaires financiers pour participer au marché. Cela a donné lieu à une structure hiérarchique dans le réseau de transactions. Pour relier de manière empirique les statistiques de réseaux aux résultats du marché, une technique de modélisation PLS-PM est introduite. Il est démontré que les asymétries du réseau induisent des inefficiences du marché (bid-ask spread). Bien que l'efficacité du marché se soit améliorée depuis le début de la Phase II, l'asymétrie persiste, imposant des coûts supplémentaires inutiles aux agents et réduisant l'efficacité du marché en tant qu'instrument d'atténuation. |
| Keywords: | Carbon market,network,climate economics,réseaux,Marché du carbone,économie du climat |
| Date: | 2017–02 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-01484117&r=mst |
| By: | Nathan Swem |
| Abstract: | I compare the timing of information acquisition among institutional investors and sell-side analysts, and I show that hedge fund trades predict the direction of subsequent analyst ratings change reports while other investors' trades do not. In addition, hedge funds reverse trades after analyst reports, while other investors follow the analysts. Finally, I show that hedge funds perform best among stocks with high analyst coverage. These results suggest that hedge funds have superior information acquisition skills, and that analysts assist hedge funds in exploiting information acquisition advantages. These dynamics illustrate how hedge funds play an important role in information generation. |
| Keywords: | Analysts ; Hedge Funds ; Information ; Mutual Funds |
| JEL: | G10 G11 G12 G14 G20 G24 |
| Date: | 2017–02 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2017-23&r=mst |
| By: | Nick Taylor |
| Abstract: | The rewards to speculative trading in the crude oil futures market are assessed. For investors who adopt timing strategies that maximise their (iso-elastic) utility during each trading session, the rewards can be economically significant providing that transaction costs are small. Moreover, we are able to show via a decomposition of performance that the bulk of this benefit is due to their ability to predict realised volatility (that is, the second realised moment). The benefits derived from predicting other realised moments either require unrealistic levels of skill(all odd moments) or an infeasible degree of risk aversion (the fourth moment and higher even moments). |
| Keywords: | Crude oil futures, timing strategies, realised moments, volatility. |
| JEL: | C22 C53 C58 G11 G17 |
| Date: | 2017–03–02 |
| URL: | http://d.repec.org/n?u=RePEc:bri:accfin:17/7&r=mst |