Parameter sensitivity of CIR process
|
|
- Phyllis Jefferson
- 5 years ago
- Views:
Transcription
1 Parameter sensitivity of CIR process Sidi Mohamed Ould Aly To cite this version: Sidi Mohamed Ould Aly. Parameter sensitivity of CIR process. Electronic Communications in Probability, Institute of Mathematical Statistics IMS, 13, 18 34, pp.1-6. <1.114/ECP.v18-35>. <hal-69856v> HAL Id: hal Submitted on 7 May 13 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.
2 Parameter sensitivity of CIR process S. M. OULD ALY Université Paris-Est, Laboratoire d Analyse et de Mathématiques Appliquées 5, boulevard Descartes, Marne-la-Vallée cedex, France sidi-mohamed.ouldali@univ-paris-est.fr May 7, 13 Abstract We study the differentiability of the CIR process with respect to its parameters. We give a stochastic representation for these derivatives in terms of the paths of V. 1 Introduction The CIR process is defined as the unique solution of the following stochastic differential equation: dv t = a bv t dt + σ V t dw t, V = v, 1.1 where a, σ, v and b R see [8] for the existence and uniqueness of the solution of the SDE. This process is widely used in finance to model short term interest rate see [3] but also used to model stochastic volatility in the Heston stochastic volatility model. The option prices in these models depend in the values of the parameters of CIR process. On the other hand, these parameters are often calibrated to market prices of derivatives, so they tend to change their values regularly. The knowledge of the derivatives of the CIR process with respect to its parameters is therefore crucial for the study the sensitivities of prices in these models. The most common approach to study the sensitivity of stochastic differential equation with respect to its parameters is to use the Malliavin calculus, especially for the sensitivity 1
3 with respect to the initial value. The Malliavin derivative gives a stochastic representation of the sensitivity of process with respect to its initial value. We note that the coefficients of 1.1 are neither differentiable in nor globally Lipschitz, so the standard results see e.g [9],[5] cannot be used here. Nevertheless, for the special case of CIR process, Alòs and Ewald [1] show the existence of Malliavin derivative of the CIR process under assumption a > σ. In mathematical finance, the sensitivities of option prices with respect to not only the initial point, but also other parameters, need to be studied very carefully. In this article, we study the differentiability of the solution of 1.1 with respect to the parameters a, b and σ in L p sense see next section. We show that, under some assumptions, this process is differentiable with respect to these parameters and give a stochastic representation of its derivatives. Differentiability For technical reasons, we will rather consider the square root of V v, denoted X v. Throughout this paper, we assume that a σ.1 Under this assumption, we have for any T, v >, P t [, T ] : V v t > = 1. The process X v is the unique solution of the following stochastic differential equation dx v t = a σ 1 8 Xt v b Xv t dt + σ dw t, X v = v.. We start by studying the differentiability of X with respect to the parameter a. We consider here the L p -differentiability of the function a X v a, i.e the existence of a process Ẋa so that We have the following result lim sup Xs v a + Xs v a s t Ẋas p =.3 Proposition.1. Let b R and σ, x. For every a ]σ, + [, let X a be the unique
4 solution of the SDE : dx t = a σ 1 b 8 X t X t dt + σ dw t, X = x and let a > σ. Then the function a X a is L p -differentiable at a, for any 1 p a σ 1 and its derivative Ẋa is given by Ẋ a t = 1 b t σ exp t u a X s 8 s du X u ds..4 Proof: Let X be the unique solution of the stochastic differential equation a + dxt = σ 1 8 Xt b X t dt + σ dw t, X = v. For >, define R t := X t X t. We can easily see that R is given by R t = U t U s 1 1 X s ds, where U = exp a + αsds, with αt = σ 1 + b 8 XsX s. We have, using the fact that for any s t, e s α u du e bt/ 1 a.s, R t tebt/ 1 sup s t 1 X v s. On the other hand, we have, using Lemma.3. of [4], [ a p < σ 1, E sup s t In particular, we have for any p [ 1, a σ 1 [, R p C. 1 X p s ] <
5 Let s now set R Ẋ a t := lim t = U t U s 1 1 X s ds. We have Ẋa C. Furthermore, Ẋ a is solution of the stochastic differential equation: p a dẋat = σ 1 8 Xt + b Ẋ a tdt + 1 X t dt. Let R 1t = X t X t Ẋat. The process R 1 is a solution of the stochastic differential equation dr 1t = αtr 1t Ẋat αt a σ [ 8 1 Xt + b ] dt. On the other hand, we have α t a σ 8 1 Xt + b α = t X t b X t R t + X t. It follows that R 1 can be written as R 1t = U t α Us Ẋ 1 a t t X t b X t R t X t ds, Using.5 and the fact that for any s t, we have e s αudu 1 e bt/ and α s e s αudu ds = 1 e α u du, we get 1 p < a σ 1, R 1 p C. The differentiability with respect to b is obtained in the same. The proof of the next Proposition is almost identical to Proposition.1. Proposition.. Let x, a, σ so that 4a > 3σ. For every b R, let X b be the unique a solution of the SDE : dx t = σ 1 8 X t b X t dt+ σdw t, X = x and let b R. The function b X b is L p -differentiable at b, for any 1 p < a 1 and its derivative σ Ẋ b is given by X s Ẋ b t = exp b t σ t u a 8 s 4 du X u ds.6
6 We now consider the differentiability of X with respect to the parameter σ. propose an extension of the result of Benhamou et al cf. [] who show that σ X is C in neighborhood of. We will show that this function is C 1 in [, a[ and C around. Proposition.3. For any σ [, a[, the function σ X is C 1 at σ in L p -sense, for every p [1, a σ 1[ and its derivative is the unique solution of the SDE : dẋσt = σ 4X t We a σ Ẋσ t b 8 X t Ẋσt dt + 1 dw t..7 Proof: Let X be the unique solution of the SDE : dx t = a σ Xt b X t dt + σ + dw t, X = v. Let set R t = X t X t. In particular, R solves the stochastic differential equation: dr t = = a σ + 1 b a 8 Xt X t σ 1 + b 8 X t X t dt + dw t [ a σ b ] R t σ + dt + 8 XsX s 8X t dw t. It follows that R can be written as where U is given by and R t = U t α s = Us 1 σ + ds + 8X s dw s, Ut = exp αsds Applying the Itô formula to the product U t 1 W t, we have R t = σ + Ut 8.8 a σ b 8 XsX s..9 Us 1 ds + X s W t + Ut 5 W s du 1 s.
7 On the other hand, using the fact that α t b/, a.s, we know that for any s t, we have U t U s 1 1 e bt/, a.s. It follows that Rt ct ct sup s t ds + X s 1 + sup X s s t sup s t Using.5, we have, for any 1 p < a σ 1, W s + sup W s 1 Ut Ut s t W s 1 + U t U t. R p C..1 Let s now set Ẋ σ t := Ut Us 1 σ ds + 1 4X s dw s. We have Ẋσ C. Furthermore, we can easily see that Ẋσ is solution to the stochastic p differential equation: a dẋσt = σ 1 8 Xt + b Ẋ σ tdt σ dt + 1 4X t dw t. Set R 1t = X t X t Ẋσt. The process R 1 solves the stochastic differential equation: dr 1t = αtr 1t Ẋσt αt a σ [ 8 1 Xt On the other hand, we can easily see that α t a σ 8 1 Xt + b It follows that R 1 can be written as R 1t = U t α = t X t b X t Us 1 α ds + Ẋσs s 8X s X s + b R t b X s ] R s + 8X t σ +. 8Xt dt. σ + ds. 8Xs 6
8 We have R1t U t U s 1 U t U s 1 α ds + Ẋσs t 8X s 8X s ds + Ẋσt + b R σ + X s X s + s 8Xs σ + ds + 8Xs b X s R s + Ut Us 1 α t Ẋσs R X s ds s b ct ds + Ẋσt R 8X s X s + s Ẋσs R +c t sup s. s t X s σ + ds 8Xs ds Finally, using.5, we have, for any 1 p < a σ 1, R 1 p C. Proposition.4. Under the assumptions of Propositions.3,.1,., the solution of the SDE 1.1 is differentiable with respect to the parameters a, b and σ. Its derivatives, denoted by V a, Vb and V σ respectively, are given as V a t = V t V b t = V t V σ t = σ V t σ 1 b σ exp t u a V s 8 b σ V s exp t u a 8 Vt ve b t a σ 8 dr Vr + a du s V u s du V u ds, ds, e b tu a σ 8 dr u Vr Vu du..11 Proof: As V t = X t, V is differentiable with respect to the parameters a, b and σ under the assumptions of Propositions.3,.1,.. The derivatives V σ is given as solution of the SDE : d V σ t = b V σ tdt + V t dw t + σ V σ t V t dw t, Vσ =. 7
9 One can see that the process Z t := V σ t σ V t is solution of the SDE : dz t = a σ bz t dt + σ Z t dwt, Z = V t σ x. On the other hand, applying Itô formula to the process ZV α, for α R, we have dzv α t = a σ V t α b1 + αz t Vt α + αa + α σ Z t V α1 dt + α α ZV dw t. It follows that, for α = 1, the process Y = ZV 1, Y has finite variation and is given as solution of dy t = a σ V t We can easily solve this equation, we get 1 b Y t a σ 8 Y t dt, Y = v. V t η Y t := V σt σ V t Vt = σ ve γ t a σ e γtγu Vu du, a.s, where Thus V σ t = σ V t σ γ t := b t + a σ 8 dr..1 V r Vt ve b t a σ 8 dr Vr + a e b tu a σ 8 dr u Vr Vu du, a.s. References [1] Alòs, E. and Ewald, C.-O.: Malliavin differentiability of the Heston volatility and applications to option pricing. Advances in Applied Probability, 4 1. pp , 8. [] Benhamou, E., Gobet, E. and Miri, M.: Times dependent Heston model, SIAM Journal on Financial Mathematics, Vol.1, pp.89-35, 1 [3] Cox, J, Ingersoll, J, and Ross, J. A.: Theory of the Term structure of Interest Rates. Econometrica, 53:385 47,
10 [4] De Marco, S.: On Probability Distributions of Diffusions and Financial Models with non-globally smooth coefficients, PhD dissertation, Université Paris Est et Scuola Normale Superiore di Pisa, 1. [5] Detemple, J., Garcia, R. and Rindisbacher, M.: Representation formulas for Malliavin derivatives of diffusion processes, Finance and Stochastics 9 3, 5. [6] Dufresne, D.: The integrated square-root process. Research Paper no. 9, Centre for Actuarial Studies, University of Melbourne, 1. [7] Heston, S.: A closed-form solution for options with stochastic volatility with applications to bond and currency options, Review of Financial Studies 1993 [8] Ikeda, N. and Watanabe, S.: Stochastic Differential Equations and Diffusion Processes. North-Holland/Kodansha, [9] Nualart, D.: The Malliavin Calculus and Related Topics, Probability and Its Applications Springer, New York
Photovoltaic deployment: from subsidies to a market-driven growth: A panel econometrics approach
Photovoltaic deployment: from subsidies to a market-driven growth: A panel econometrics approach Anna Créti, Léonide Michael Sinsin To cite this version: Anna Créti, Léonide Michael Sinsin. Photovoltaic
More informationEquilibrium payoffs in finite games
Equilibrium payoffs in finite games Ehud Lehrer, Eilon Solan, Yannick Viossat To cite this version: Ehud Lehrer, Eilon Solan, Yannick Viossat. Equilibrium payoffs in finite games. Journal of Mathematical
More informationThe National Minimum Wage in France
The National Minimum Wage in France Timothy Whitton To cite this version: Timothy Whitton. The National Minimum Wage in France. Low pay review, 1989, pp.21-22. HAL Id: hal-01017386 https://hal-clermont-univ.archives-ouvertes.fr/hal-01017386
More informationMoney in the Production Function : A New Keynesian DSGE Perspective
Money in the Production Function : A New Keynesian DSGE Perspective Jonathan Benchimol To cite this version: Jonathan Benchimol. Money in the Production Function : A New Keynesian DSGE Perspective. ESSEC
More informationControl-theoretic framework for a quasi-newton local volatility surface inversion
Control-theoretic framework for a quasi-newton local volatility surface inversion Gabriel Turinici To cite this version: Gabriel Turinici. Control-theoretic framework for a quasi-newton local volatility
More informationYield to maturity modelling and a Monte Carlo Technique for pricing Derivatives on Constant Maturity Treasury (CMT) and Derivatives on forward Bonds
Yield to maturity modelling and a Monte Carlo echnique for pricing Derivatives on Constant Maturity reasury (CM) and Derivatives on forward Bonds Didier Kouokap Youmbi o cite this version: Didier Kouokap
More informationEquivalence in the internal and external public debt burden
Equivalence in the internal and external public debt burden Philippe Darreau, François Pigalle To cite this version: Philippe Darreau, François Pigalle. Equivalence in the internal and external public
More informationStrategic complementarity of information acquisition in a financial market with discrete demand shocks
Strategic complementarity of information acquisition in a financial market with discrete demand shocks Christophe Chamley To cite this version: Christophe Chamley. Strategic complementarity of information
More informationRôle de la protéine Gas6 et des cellules précurseurs dans la stéatohépatite et la fibrose hépatique
Rôle de la protéine Gas6 et des cellules précurseurs dans la stéatohépatite et la fibrose hépatique Agnès Fourcot To cite this version: Agnès Fourcot. Rôle de la protéine Gas6 et des cellules précurseurs
More informationA note on health insurance under ex post moral hazard
A note on health insurance under ex post moral hazard Pierre Picard To cite this version: Pierre Picard. A note on health insurance under ex post moral hazard. 2016. HAL Id: hal-01353597
More informationNetworks Performance and Contractual Design: Empirical Evidence from Franchising
Networks Performance and Contractual Design: Empirical Evidence from Franchising Magali Chaudey, Muriel Fadairo To cite this version: Magali Chaudey, Muriel Fadairo. Networks Performance and Contractual
More informationInequalities in Life Expectancy and the Global Welfare Convergence
Inequalities in Life Expectancy and the Global Welfare Convergence Hippolyte D Albis, Florian Bonnet To cite this version: Hippolyte D Albis, Florian Bonnet. Inequalities in Life Expectancy and the Global
More informationRicardian equivalence and the intertemporal Keynesian multiplier
Ricardian equivalence and the intertemporal Keynesian multiplier Jean-Pascal Bénassy To cite this version: Jean-Pascal Bénassy. Ricardian equivalence and the intertemporal Keynesian multiplier. PSE Working
More informationMotivations and Performance of Public to Private operations : an international study
Motivations and Performance of Public to Private operations : an international study Aurelie Sannajust To cite this version: Aurelie Sannajust. Motivations and Performance of Public to Private operations
More informationAnalytical formulas for local volatility model with stochastic. Mohammed Miri
Analytical formulas for local volatility model with stochastic rates Mohammed Miri Joint work with Eric Benhamou (Pricing Partners) and Emmanuel Gobet (Ecole Polytechnique Modeling and Managing Financial
More informationAbout the reinterpretation of the Ghosh model as a price model
About the reinterpretation of the Ghosh model as a price model Louis De Mesnard To cite this version: Louis De Mesnard. About the reinterpretation of the Ghosh model as a price model. [Research Report]
More informationThe stochastic calculus
Gdansk A schedule of the lecture Stochastic differential equations Ito calculus, Ito process Ornstein - Uhlenbeck (OU) process Heston model Stopping time for OU process Stochastic differential equations
More informationIS-LM and the multiplier: A dynamic general equilibrium model
IS-LM and the multiplier: A dynamic general equilibrium model Jean-Pascal Bénassy To cite this version: Jean-Pascal Bénassy. IS-LM and the multiplier: A dynamic general equilibrium model. PSE Working Papers
More informationThe Hierarchical Agglomerative Clustering with Gower index: a methodology for automatic design of OLAP cube in ecological data processing context
The Hierarchical Agglomerative Clustering with Gower index: a methodology for automatic design of OLAP cube in ecological data processing context Lucile Sautot, Bruno Faivre, Ludovic Journaux, Paul Molin
More informationModèles DSGE Nouveaux Keynésiens, Monnaie et Aversion au Risque.
Modèles DSGE Nouveaux Keynésiens, Monnaie et Aversion au Risque. Jonathan Benchimol To cite this version: Jonathan Benchimol. Modèles DSGE Nouveaux Keynésiens, Monnaie et Aversion au Risque.. Economies
More informationA revisit of the Borch rule for the Principal-Agent Risk-Sharing problem
A revisit of the Borch rule for the Principal-Agent Risk-Sharing problem Jessica Martin, Anthony Réveillac To cite this version: Jessica Martin, Anthony Réveillac. A revisit of the Borch rule for the Principal-Agent
More informationWeierstrass Institute for Applied Analysis and Stochastics Maximum likelihood estimation for jump diffusions
Weierstrass Institute for Applied Analysis and Stochastics Maximum likelihood estimation for jump diffusions Hilmar Mai Mohrenstrasse 39 1117 Berlin Germany Tel. +49 3 2372 www.wias-berlin.de Haindorf
More informationThe Riskiness of Risk Models
The Riskiness of Risk Models Christophe Boucher, Bertrand Maillet To cite this version: Christophe Boucher, Bertrand Maillet. The Riskiness of Risk Models. Documents de travail du Centre d Economie de
More informationRohini Kumar. Statistics and Applied Probability, UCSB (Joint work with J. Feng and J.-P. Fouque)
Small time asymptotics for fast mean-reverting stochastic volatility models Statistics and Applied Probability, UCSB (Joint work with J. Feng and J.-P. Fouque) March 11, 2011 Frontier Probability Days,
More informationA note on the existence of unique equivalent martingale measures in a Markovian setting
Finance Stochast. 1, 251 257 1997 c Springer-Verlag 1997 A note on the existence of unique equivalent martingale measures in a Markovian setting Tina Hviid Rydberg University of Aarhus, Department of Theoretical
More informationBDHI: a French national database on historical floods
BDHI: a French national database on historical floods M. Lang, D. Coeur, A. Audouard, M. Villanova Oliver, J.P. Pene To cite this version: M. Lang, D. Coeur, A. Audouard, M. Villanova Oliver, J.P. Pene.
More informationFunctional vs Banach space stochastic calculus & strong-viscosity solutions to semilinear parabolic path-dependent PDEs.
Functional vs Banach space stochastic calculus & strong-viscosity solutions to semilinear parabolic path-dependent PDEs Andrea Cosso LPMA, Université Paris Diderot joint work with Francesco Russo ENSTA,
More informationConvergence Analysis of Monte Carlo Calibration of Financial Market Models
Analysis of Monte Carlo Calibration of Financial Market Models Christoph Käbe Universität Trier Workshop on PDE Constrained Optimization of Certain and Uncertain Processes June 03, 2009 Monte Carlo Calibration
More informationThe German unemployment since the Hartz reforms: Permanent or transitory fall?
The German unemployment since the Hartz reforms: Permanent or transitory fall? Gaëtan Stephan, Julien Lecumberry To cite this version: Gaëtan Stephan, Julien Lecumberry. The German unemployment since the
More informationAMH4 - ADVANCED OPTION PRICING. Contents
AMH4 - ADVANCED OPTION PRICING ANDREW TULLOCH Contents 1. Theory of Option Pricing 2 2. Black-Scholes PDE Method 4 3. Martingale method 4 4. Monte Carlo methods 5 4.1. Method of antithetic variances 5
More informationContinuous Time Finance. Tomas Björk
Continuous Time Finance Tomas Björk 1 II Stochastic Calculus Tomas Björk 2 Typical Setup Take as given the market price process, S(t), of some underlying asset. S(t) = price, at t, per unit of underlying
More informationNumerical schemes for SDEs
Lecture 5 Numerical schemes for SDEs Lecture Notes by Jan Palczewski Computational Finance p. 1 A Stochastic Differential Equation (SDE) is an object of the following type dx t = a(t,x t )dt + b(t,x t
More informationSTOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL
STOCHASTIC CALCULUS AND BLACK-SCHOLES MODEL YOUNGGEUN YOO Abstract. Ito s lemma is often used in Ito calculus to find the differentials of a stochastic process that depends on time. This paper will introduce
More informationDr. Maddah ENMG 625 Financial Eng g II 10/16/06
Dr. Maddah ENMG 65 Financial Eng g II 10/16/06 Chapter 11 Models of Asset Dynamics () Random Walk A random process, z, is an additive process defined over times t 0, t 1,, t k, t k+1,, such that z( t )
More informationMonte Carlo Simulations
Monte Carlo Simulations Lecture 1 December 7, 2014 Outline Monte Carlo Methods Monte Carlo methods simulate the random behavior underlying the financial models Remember: When pricing you must simulate
More informationOptimal Tax Base with Administrative fixed Costs
Optimal Tax Base with Administrative fixed osts Stéphane Gauthier To cite this version: Stéphane Gauthier. Optimal Tax Base with Administrative fixed osts. Documents de travail du entre d Economie de la
More informationRôle de la régulation génique dans l adaptation : approche par analyse comparative du transcriptome de drosophile
Rôle de la régulation génique dans l adaptation : approche par analyse comparative du transcriptome de drosophile François Wurmser To cite this version: François Wurmser. Rôle de la régulation génique
More informationOrdinary Mixed Life Insurance and Mortality-Linked Insurance Contracts
Ordinary Mixed Life Insurance and Mortality-Linked Insurance Contracts M.Sghairi M.Kouki February 16, 2007 Abstract Ordinary mixed life insurance is a mix between temporary deathinsurance and pure endowment.
More informationAn Introduction to Point Processes. from a. Martingale Point of View
An Introduction to Point Processes from a Martingale Point of View Tomas Björk KTH, 211 Preliminary, incomplete, and probably with lots of typos 2 Contents I The Mathematics of Counting Processes 5 1 Counting
More informationConditional Markov regime switching model applied to economic modelling.
Conditional Markov regime switching model applied to economic modelling. Stéphane Goutte To cite this version: Stéphane Goutte. Conditional Markov regime switching model applied to economic modelling..
More informationSPDE and portfolio choice (joint work with M. Musiela) Princeton University. Thaleia Zariphopoulou The University of Texas at Austin
SPDE and portfolio choice (joint work with M. Musiela) Princeton University November 2007 Thaleia Zariphopoulou The University of Texas at Austin 1 Performance measurement of investment strategies 2 Market
More informationFrench German flood risk geohistory in the Rhine Graben
French German flood risk geohistory in the Rhine Graben Brice Martin, Iso Himmelsbach, Rüdiger Glaser, Lauriane With, Ouarda Guerrouah, Marie - Claire Vitoux, Axel Drescher, Romain Ansel, Karin Dietrich
More informationLarge Deviations and Stochastic Volatility with Jumps: Asymptotic Implied Volatility for Affine Models
Large Deviations and Stochastic Volatility with Jumps: TU Berlin with A. Jaquier and A. Mijatović (Imperial College London) SIAM conference on Financial Mathematics, Minneapolis, MN July 10, 2012 Implied
More informationThe Sustainability and Outreach of Microfinance Institutions
The Sustainability and Outreach of Microfinance Institutions Jaehun Sim, Vittaldas Prabhu To cite this version: Jaehun Sim, Vittaldas Prabhu. The Sustainability and Outreach of Microfinance Institutions.
More informationIntroduction to Affine Processes. Applications to Mathematical Finance
and Its Applications to Mathematical Finance Department of Mathematical Science, KAIST Workshop for Young Mathematicians in Korea, 2010 Outline Motivation 1 Motivation 2 Preliminary : Stochastic Calculus
More informationLocal vs Non-local Forward Equations for Option Pricing
Local vs Non-local Forward Equations for Option Pricing Rama Cont Yu Gu Abstract When the underlying asset is a continuous martingale, call option prices solve the Dupire equation, a forward parabolic
More informationEquivalence between Semimartingales and Itô Processes
International Journal of Mathematical Analysis Vol. 9, 215, no. 16, 787-791 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/1.12988/ijma.215.411358 Equivalence between Semimartingales and Itô Processes
More informationForward Dynamic Utility
Forward Dynamic Utility El Karoui Nicole & M RAD Mohamed UnivParis VI / École Polytechnique,CMAP elkaroui@cmapx.polytechnique.fr with the financial support of the "Fondation du Risque" and the Fédération
More informationConstructing Markov models for barrier options
Constructing Markov models for barrier options Gerard Brunick joint work with Steven Shreve Department of Mathematics University of Texas at Austin Nov. 14 th, 2009 3 rd Western Conference on Mathematical
More informationTheoretical considerations on the retirement consumption puzzle and the optimal age of retirement
Theoretical considerations on the retirement consumption puzzle and the optimal age of retirement Nicolas Drouhin To cite this version: Nicolas Drouhin. Theoretical considerations on the retirement consumption
More informationThe Quantity Theory of Money Revisited: The Improved Short-Term Predictive Power of of Household Money Holdings with Regard to prices
The Quantity Theory of Money Revisited: The Improved Short-Term Predictive Power of of Household Money Holdings with Regard to prices Jean-Charles Bricongne To cite this version: Jean-Charles Bricongne.
More informationAmerican Option Pricing Formula for Uncertain Financial Market
American Option Pricing Formula for Uncertain Financial Market Xiaowei Chen Uncertainty Theory Laboratory, Department of Mathematical Sciences Tsinghua University, Beijing 184, China chenxw7@mailstsinghuaeducn
More informationWhy ruin theory should be of interest for insurance practitioners and risk managers nowadays
Why ruin theory should be of interest for insurance practitioners and risk managers nowadays Stéphane Loisel, Hans-U. Gerber To cite this version: Stéphane Loisel, Hans-U. Gerber. Why ruin theory should
More informationarxiv: v2 [q-fin.pr] 23 Nov 2017
VALUATION OF EQUITY WARRANTS FOR UNCERTAIN FINANCIAL MARKET FOAD SHOKROLLAHI arxiv:17118356v2 [q-finpr] 23 Nov 217 Department of Mathematics and Statistics, University of Vaasa, PO Box 7, FIN-6511 Vaasa,
More informationInterest rate models in continuous time
slides for the course Interest rate theory, University of Ljubljana, 2012-13/I, part IV József Gáll University of Debrecen Nov. 2012 Jan. 2013, Ljubljana Continuous time markets General assumptions, notations
More informationAn Efficient Numerical Scheme for Simulation of Mean-reverting Square-root Diffusions
Journal of Numerical Mathematics and Stochastics,1 (1) : 45-55, 2009 http://www.jnmas.org/jnmas1-5.pdf JNM@S Euclidean Press, LLC Online: ISSN 2151-2302 An Efficient Numerical Scheme for Simulation of
More informationAdvanced Topics in Derivative Pricing Models. Topic 4 - Variance products and volatility derivatives
Advanced Topics in Derivative Pricing Models Topic 4 - Variance products and volatility derivatives 4.1 Volatility trading and replication of variance swaps 4.2 Volatility swaps 4.3 Pricing of discrete
More informationCarbon Prices during the EU ETS Phase II: Dynamics and Volume Analysis
Carbon Prices during the EU ETS Phase II: Dynamics and Volume Analysis Julien Chevallier To cite this version: Julien Chevallier. Carbon Prices during the EU ETS Phase II: Dynamics and Volume Analysis.
More informationA Fast Algorithm for Computing Binomial Coefficients Modulo Powers of Two
A Fast Algorithm for Computing Binomial Coefficients Modulo Powers of Two Mugurel Ionut Andreica To cite this version: Mugurel Ionut Andreica. A Fast Algorithm for Computing Binomial Coefficients Modulo
More informationOn some key research issues in Enterprise Risk Management related to economic capital and diversification effect at group level
On some key research issues in Enterprise Risk Management related to economic capital and diversification effect at group level Wayne Fisher, Stéphane Loisel, Shaun Wang To cite this version: Wayne Fisher,
More informationTwo dimensional Hotelling model : analytical results and numerical simulations
Two dimensional Hotelling model : analytical results and numerical simulations Hernán Larralde, Pablo Jensen, Margaret Edwards To cite this version: Hernán Larralde, Pablo Jensen, Margaret Edwards. Two
More informationBarrier Options Pricing in Uncertain Financial Market
Barrier Options Pricing in Uncertain Financial Market Jianqiang Xu, Jin Peng Institute of Uncertain Systems, Huanggang Normal University, Hubei 438, China College of Mathematics and Science, Shanghai Normal
More informationM5MF6. Advanced Methods in Derivatives Pricing
Course: Setter: M5MF6 Dr Antoine Jacquier MSc EXAMINATIONS IN MATHEMATICS AND FINANCE DEPARTMENT OF MATHEMATICS April 2016 M5MF6 Advanced Methods in Derivatives Pricing Setter s signature...........................................
More informationHedging under Arbitrage
Hedging under Arbitrage Johannes Ruf Columbia University, Department of Statistics Modeling and Managing Financial Risks January 12, 2011 Motivation Given: a frictionless market of stocks with continuous
More informationOPTIMAL PORTFOLIO CONTROL WITH TRADING STRATEGIES OF FINITE
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 005 Seville, Spain, December 1-15, 005 WeA11.6 OPTIMAL PORTFOLIO CONTROL WITH TRADING STRATEGIES OF
More informationUsing of stochastic Ito and Stratonovich integrals derived security pricing
Using of stochastic Ito and Stratonovich integrals derived security pricing Laura Pânzar and Elena Corina Cipu Abstract We seek for good numerical approximations of solutions for stochastic differential
More informationAn Equilibrium Model of the Term Structure of Interest Rates
Finance 400 A. Penati - G. Pennacchi An Equilibrium Model of the Term Structure of Interest Rates When bond prices are assumed to be driven by continuous-time stochastic processes, noarbitrage restrictions
More informationConditional Density Method in the Computation of the Delta with Application to Power Market
Conditional Density Method in the Computation of the Delta with Application to Power Market Asma Khedher Centre of Mathematics for Applications Department of Mathematics University of Oslo A joint work
More information(1) Consider a European call option and a European put option on a nondividend-paying stock. You are given:
(1) Consider a European call option and a European put option on a nondividend-paying stock. You are given: (i) The current price of the stock is $60. (ii) The call option currently sells for $0.15 more
More informationDynamics of the exchange rate in Tunisia
Dynamics of the exchange rate in Tunisia Ammar Samout, Nejia Nekâa To cite this version: Ammar Samout, Nejia Nekâa. Dynamics of the exchange rate in Tunisia. International Journal of Academic Research
More informationA THREE-FACTOR CONVERGENCE MODEL OF INTEREST RATES
Proceedings of ALGORITMY 01 pp. 95 104 A THREE-FACTOR CONVERGENCE MODEL OF INTEREST RATES BEÁTA STEHLÍKOVÁ AND ZUZANA ZÍKOVÁ Abstract. A convergence model of interest rates explains the evolution of the
More information1.1 Basic Financial Derivatives: Forward Contracts and Options
Chapter 1 Preliminaries 1.1 Basic Financial Derivatives: Forward Contracts and Options A derivative is a financial instrument whose value depends on the values of other, more basic underlying variables
More informationParameters Estimation in Stochastic Process Model
Parameters Estimation in Stochastic Process Model A Quasi-Likelihood Approach Ziliang Li University of Maryland, College Park GEE RIT, Spring 28 Outline 1 Model Review The Big Model in Mind: Signal + Noise
More informationON AN IMPLEMENTATION OF BLACK SCHOLES MODEL FOR ESTIMATION OF CALL- AND PUT-OPTION VIA PROGRAMMING ENVIRONMENT MATHEMATICA
Доклади на Българската академия на науките Comptes rendus de l Académie bulgare des Sciences Tome 66, No 5, 2013 MATHEMATIQUES Mathématiques appliquées ON AN IMPLEMENTATION OF BLACK SCHOLES MODEL FOR ESTIMATION
More informationOn Leland s strategy of option pricing with transactions costs
Finance Stochast., 239 25 997 c Springer-Verlag 997 On Leland s strategy of option pricing with transactions costs Yuri M. Kabanov,, Mher M. Safarian 2 Central Economics and Mathematics Institute of the
More informationApplication of Stochastic Calculus to Price a Quanto Spread
Application of Stochastic Calculus to Price a Quanto Spread Christopher Ting http://www.mysmu.edu/faculty/christophert/ Algorithmic Quantitative Finance July 15, 2017 Christopher Ting July 15, 2017 1/33
More informationFINANCIAL PRICING MODELS
Page 1-22 like equions FINANCIAL PRICING MODELS 20 de Setembro de 2013 PhD Page 1- Student 22 Contents Page 2-22 1 2 3 4 5 PhD Page 2- Student 22 Page 3-22 In 1973, Fischer Black and Myron Scholes presented
More informationConstructive martingale representation using Functional Itô Calculus: a local martingale extension
Mathematical Statistics Stockholm University Constructive martingale representation using Functional Itô Calculus: a local martingale extension Kristoffer Lindensjö Research Report 216:21 ISSN 165-377
More informationKØBENHAVNS UNIVERSITET (Blok 2, 2011/2012) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours
This question paper consists of 3 printed pages FinKont KØBENHAVNS UNIVERSITET (Blok 2, 211/212) Naturvidenskabelig kandidateksamen Continuous time finance (FinKont) TIME ALLOWED : 3 hours This exam paper
More information"Pricing Exotic Options using Strong Convergence Properties
Fourth Oxford / Princeton Workshop on Financial Mathematics "Pricing Exotic Options using Strong Convergence Properties Klaus E. Schmitz Abe schmitz@maths.ox.ac.uk www.maths.ox.ac.uk/~schmitz Prof. Mike
More informationINTERTEMPORAL SUBSTITUTION IN CONSUMPTION, LABOR SUPPLY ELASTICITY AND SUNSPOT FLUCTUATIONS IN CONTINUOUS-TIME MODELS
INTERTEMPORAL SUBSTITUTION IN CONSUMPTION, LABOR SUPPLY ELASTICITY AND SUNSPOT FLUCTUATIONS IN CONTINUOUS-TIME MODELS Jean-Philippe Garnier, Kazuo Nishimura, Alain Venditti To cite this version: Jean-Philippe
More informationStochastic Calculus, Application of Real Analysis in Finance
, Application of Real Analysis in Finance Workshop for Young Mathematicians in Korea Seungkyu Lee Pohang University of Science and Technology August 4th, 2010 Contents 1 BINOMIAL ASSET PRICING MODEL Contents
More informationEconomathematics. Problem Sheet 1. Zbigniew Palmowski. Ws 2 dw s = 1 t
Economathematics Problem Sheet 1 Zbigniew Palmowski 1. Calculate Ee X where X is a gaussian random variable with mean µ and volatility σ >.. Verify that where W is a Wiener process. Ws dw s = 1 3 W t 3
More informationA No-Arbitrage Theorem for Uncertain Stock Model
Fuzzy Optim Decis Making manuscript No (will be inserted by the editor) A No-Arbitrage Theorem for Uncertain Stock Model Kai Yao Received: date / Accepted: date Abstract Stock model is used to describe
More informationThe binomial interpolated lattice method fro step double barrier options
The binomial interpolated lattice method fro step double barrier options Elisa Appolloni, Gaudenzi Marcellino, Antonino Zanette To cite this version: Elisa Appolloni, Gaudenzi Marcellino, Antonino Zanette.
More informationThe Whys of the LOIS: Credit Skew and Funding Spread Volatility
The Whys of the LOIS: Credit Skew and Funding Spread Volatility Stéphane Crépey, Raphaël Douady To cite this version: Stéphane Crépey, Raphaël Douady. The Whys of the LOIS: Credit Skew and Funding Spread
More informationSensitivity of American Option Prices with Different Strikes, Maturities and Volatilities
Applied Mathematical Sciences, Vol. 6, 2012, no. 112, 5597-5602 Sensitivity of American Option Prices with Different Strikes, Maturities and Volatilities Nasir Rehman Department of Mathematics and Statistics
More informationEnlargement of filtration
Enlargement of filtration Bernardo D Auria email: bernardo.dauria@uc3m.es web: www.est.uc3m.es/bdauria July 6, 2017 ICMAT / UC3M Enlargement of Filtration Enlargement of Filtration ([1] 5.9) If G is a
More informationCharacterization of bijective discretized rotations by Gaussian integers
Characterization of bijective discretized rotations by Gaussian integers Tristan Roussillon, David Coeurjolly To cite this version: Tristan Roussillon, David Coeurjolly. Characterization of bijective discretized
More informationMath 416/516: Stochastic Simulation
Math 416/516: Stochastic Simulation Haijun Li lih@math.wsu.edu Department of Mathematics Washington State University Week 13 Haijun Li Math 416/516: Stochastic Simulation Week 13 1 / 28 Outline 1 Simulation
More informationLecture 18. More on option pricing. Lecture 18 1 / 21
Lecture 18 More on option pricing Lecture 18 1 / 21 Introduction In this lecture we will see more applications of option pricing theory. Lecture 18 2 / 21 Greeks (1) The price f of a derivative depends
More information5. Itô Calculus. Partial derivative are abstractions. Usually they are called multipliers or marginal effects (cf. the Greeks in option theory).
5. Itô Calculus Types of derivatives Consider a function F (S t,t) depending on two variables S t (say, price) time t, where variable S t itself varies with time t. In stard calculus there are three types
More informationInvestigation of Dependency between Short Rate and Transition Rate on Pension Buy-outs. Arık, A. 1 Yolcu-Okur, Y. 2 Uğur Ö. 2
Investigation of Dependency between Short Rate and Transition Rate on Pension Buy-outs Arık, A. 1 Yolcu-Okur, Y. 2 Uğur Ö. 2 1 Hacettepe University Department of Actuarial Sciences 06800, TURKEY 2 Middle
More informationRisk Neutral Valuation
copyright 2012 Christian Fries 1 / 51 Risk Neutral Valuation Christian Fries Version 2.2 http://www.christian-fries.de/finmath April 19-20, 2012 copyright 2012 Christian Fries 2 / 51 Outline Notation Differential
More informationArbitrage free cointegrated models in gas and oil future markets
Arbitrage free cointegrated models in gas and oil future markets Grégory Benmenzer, Emmanuel Gobet, Céline Jérusalem To cite this version: Grégory Benmenzer, Emmanuel Gobet, Céline Jérusalem. Arbitrage
More informationStochastic Integral Representation of One Stochastically Non-smooth Wiener Functional
Bulletin of TICMI Vol. 2, No. 2, 26, 24 36 Stochastic Integral Representation of One Stochastically Non-smooth Wiener Functional Hanna Livinska a and Omar Purtukhia b a Taras Shevchenko National University
More information( ) since this is the benefit of buying the asset at the strike price rather
Review of some financial models for MAT 483 Parity and Other Option Relationships The basic parity relationship for European options with the same strike price and the same time to expiration is: C( KT
More informationA VALUATION MODEL FOR INDETERMINATE CONVERTIBLES by Jayanth Rama Varma
A VALUATION MODEL FOR INDETERMINATE CONVERTIBLES by Jayanth Rama Varma Abstract Many issues of convertible debentures in India in recent years provide for a mandatory conversion of the debentures into
More informationPractical example of an Economic Scenario Generator
Practical example of an Economic Scenario Generator Martin Schenk Actuarial & Insurance Solutions SAV 7 March 2014 Agenda Introduction Deterministic vs. stochastic approach Mathematical model Application
More informationGreek parameters of nonlinear Black-Scholes equation
International Journal of Mathematics and Soft Computing Vol.5, No.2 (2015), 69-74. ISSN Print : 2249-3328 ISSN Online: 2319-5215 Greek parameters of nonlinear Black-Scholes equation Purity J. Kiptum 1,
More information