Marshall And Olkins Method
We present a simulation algorithm proposed by Marshall and Olkin (1988) for the compound construction of copulas. This is a construction method of copulas involving the Laplace transform and its inverse function. Recall that the Laplace transform of a positive random variable y is defined by t(s) EY(e-SY) e-st dFY (t) (6.21) where FY is the distribution function of y . This is also the moment generating function evaluated at s thus, knowledge of t(s) determines the distribution. Laplace...
N 012
Notice that in particular such a function is non-negative h gt 0 and non-increasing h' lt 0 . Given the notion of complete monotonocity, we have the following Theorem 3.13 If the inverse of a strict generator is completely monotone, then the corresponding copula entails PQD Among Archimedean copulas, we are going to consider in particular the one-parameter ones, which are constructed using a generator ya t , indexed by the real parameter a. By choosing the generator, one obtains a subclass or...
T 3t2 Ps T 3 T
For r.v.s belonging to L2, concordance - in its loose significance - should be captured also by covariance. Since covariance is not a normalized or relative measure, however, the so-called Pearson product-moment or linear correlation coefficient has been introduced. We define it, show that it satisfies some of the axioms for a measure of concordance, and list five of its properties, which entail that it does not satisfy the remaining axioms. Last, we mention the estimation procedure and give an...
Survival Copula And Joint Survival Function
This section introduces the notion of survival copula and recalls the joint survival function for standard uniform r.v.s copula given above. It discusses the relationships between them and applies them to the evaluation of the distribution functions of maxima and minima of n gt 2 r.v.s. Let us consider the probability F x Pr Xi gt X1, X2 gt X2, ,Xn gt Xn 4.8 As in the bi-dimensional case, this probability is called the joint survival probability or survival function of the n agents or...
Copula Methods In Finance A Primer
Up to this point, we have seen that the three main frontier problems in derivative pricing are the departure from normality, emerging from the smile effect, market incompleteness, corresponding to hedging error, and credit risk, linked to the bivariate relationship in OTC transactions. Copula functions may be of great help to address these problems. As we will see, the main advantage of copula functions is that they enable us to tackle the problem of specification of marginal univariate...
N i Tf ji
Where t-1 v , q2 t-l z , and the copula itself is absolutely continuous. Since, as recalled by Roncalli 2002 , given a couple of r.v.s X, Y , jointly distributed as a Student's t, the conditional distribution of given X x, is a Student's t with u 1 degrees of freedom, the conditional distribution via copula C ,1u v, z is It follows that an equivalent expression for the bivariate Student's copula is If u gt 2, each margin admits a finite variance, u u - 2 , and pXY can be interpreted as a linear...
Contents
List of Common Symbols and Notations xv 1 Derivatives Pricing, Hedging and Risk Management The State of the Art 1 1.2 Derivative pricing basics the binomial model 2 1.2.1 Replicating portfolios 3 1.2.2 No-arbitrage and the risk-neutral probability measure 3 1.2.3 No-arbitrage and the objective probability measure 4 1.2.4 Discounting under different probability measures 5 1.2.5 Multiple states of the world 6 1.3 The Black-Scholes model 7 1.3.3 The martingale property 11 1.4 Interest rate...
Incomplete Markets
The most recent challenge to the standard derivative pricing model, and to its basic structure, is represented by the incomplete market problem. A brief look over the strategy used to recover the fair price of a derivative contract shows that a crucial role is played by the assumption that the future value of each financial product can be exactly replicated by some trading strategy. Technically, we say that each product is attainable and the market is complete. In other words, every contingent...
Derivative Pricing Basics The Binomial Model
Here we give a brief description of the basic pillar behind pricing techniques, that is the use of risk-neutral probability measures to evaluate contingent claims, versus the objective measure observed from the time series of market data. We will see that the existence of such risk measures is directly linked to the basic pricing principle used in modern finance to evaluate financial products. This requirement imposes that prices must ensure that arbitrage gains, also called free lunches,...
