1,720,976 research outputs found
Trend detection under erroneous observations: application to quantitative financial strategies
No full textIn this paper, we show how to handle the problem of trend detection, in the context of financial strategies, when the data is potentially erroneous. We focus on the case of a filtering method based on wavelets. This is used, for instance, to build an estimator of a given security at a future time horizon, or to construct trading signals based on extreme variations from the trend. We study how the erroneous observation of past data is incorporated into the filter method and, therefore, into the estimator built with it. The techniques of error calculus with Dirichlet forms are applied to see how the errors affect the estimation: they define an expansion of the estimator in terms of its first- and second-order moments, interpreted as statistical variance/covariance and bias
Alternative to beta coefficients in the context of diffusions
No full textWe develop an alternative to the beta coefficient of the CAPM theory. We show the link between this notion and the Wiener chaos expansion of the underlying processes. In the setting of Markov diffusions, we define the drift-neutral beta, which is the quantity of benchmark such that the resulting portfolio is immune to an infinitesimal change of drift on the Brownian motion driving the benchmark. Our approach yields a coefficient which in many practical cases depends on the initial values of both the portfolio and its benchmark. It can also be used to take into account extreme risks and not only the variance. We study several classical diffusion processes and give a full analysis in the case of Jacobi processes. Examples with credit indices show the efficiency of the method in hedging a portfolio
A Gamma Ornstein–Uhlenbeck model driven by a Hawkes process
Full text linkWe propose an extension of the Γ -OU Barndorff-Nielsen and Shephard model taking into account jump clustering phenomena. We assume that the intensity process of the Hawkes driver coincides, up to a constant, with the variance process. By applying the theory of continuous-state branching processes with immigration, we prove existence and uniqueness of strong solutions of the SDE governing the asset price dynamics. We propose a measure change of self-exciting Esscher type in order to describe the relation between the risk-neutral and the historical dynamics, showing that the Γ -OU Hawkes framework is stable under this probability change. By exploiting the affine features of the model we provide an explicit form for the Laplace transform of the asset log-return, for its quadratic variation and for the ergodic distribution of the variance process. We show that the proposed model exhibits a larger flexibility in comparison with the Γ -OU model, in spite of the same number of parameters required. We calibrate the model on market vanilla option prices via characteristic function inversion techniques, we study the price sensitivities and propose an exact simulation scheme. The main financial achievement is that implied volatility of options written on VIX is upward shaped due to the self-exciting property of Hawkes processes, in contrast with the usual downward slope exhibited by the Γ -OU Barndorff-Nielsen and Shephard model
De Bernis (G.), De Montvalon (R.) Propositions pour une politique de prévention. Une politique de prévention pour les travailleurs immigrés
No full textCharbit Yves. De Bernis (G.), De Montvalon (R.) Propositions pour une politique de prévention. Une politique de prévention pour les travailleurs immigrés. In: Revue européenne des migrations internationales, vol. 6, n°3,1990. p. 173
Interest Rates Term Structure Models Driven by Hawkes Processes
Full text linkThis paper includes a marked Hawkes process in the original Heath--Jarrow--Morton (HJM) setup
and investigates the impact of this assumption on the pricing of the popular vanilla fixed-income
derivatives. Our model exhibits a smile that can fit the implied volatility of swaptions for a given
key rate (tenor). We harness the log-normality of the model, conditionally with respect to jumps,
and derive formulae to evaluate both caplets/floorlets and swaptions. Our model exhibits negative
jumps on the zero-coupon (hence positive on the rates). Therefore, its behavior is compatible with
the situation where globally low interest rates can suddenly show a cluster of positive jumps in case
of tensions on the market. One of the main difficulties when dealing with the HJM model is to keep
a framework that is Markovian. In this paper we show how to preserve the relevant features of the
Hull and White version, especially the reconstruction formula that provides the zero-coupon bonds
in terms of the underlying model factors
Optimal credit allocation under regime uncertainty with sensitivity analysis
No full textWe consider the problem of credit allocation in a regime-switching model. The global evolution of the credit market is driven by a benchmark, the drift of which is given by a two-state continuous-time hidden Markov chain. We apply filtering techniques to obtain the diffusion of the credit assets under partial observation and show that they have a specific excess return with respect to the benchmark. The investor performs a simple mean–variance allocation on credit assets. However, returns and variance matrix have to be computed by a numerical method such as Monte Carlo, because of the dynamics of the system and the non-linearity of the asset prices. We use the theory of Dirichlet forms to deal with the uncertainty on the excess returns. This approach provides an estimation of the bias and the variance of the optimal allocation, and return. We propose an application in the case of a sectorial allocation with Credit Default Swaps (CDS), fully calibrated with observable data or direct input given by the portfolio manager
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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