Stochastic Processes: From Physics to Finance by Wolfgang Paul

By Wolfgang Paul

This e-book introduces the speculation of stochastic tactics with purposes taken from physics and finance. basic options just like the random stroll or Brownian movement but additionally Levy-stable distributions are mentioned. functions are chosen to teach the interdisciplinary personality of the options and strategies. within the moment version of the booklet a dialogue of utmost occasions starting from their mathematical definition to their value for monetary crashes used to be integrated. The exposition of uncomplicated notions of likelihood conception and the Brownian movement challenge in addition to the relation among conservative diffusion techniques and quantum mechanics is improved. the second one version additionally enlarges the remedy of economic markets. past a presentation of geometric Brownian movement and the Black-Scholes method of choice pricing in addition to the econophysics research of the stylized evidence of monetary markets, an creation to agent dependent modeling techniques is given.

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Extra resources for Stochastic Processes: From Physics to Finance

Example text

A measure space (Ω, F, μ), given through a set Ω, a σ -algebra F of subsets of Ω and a measure μ on F . An event is a set A ∈ F and the probability for this event is the measure μ(A). The measure has the property: μ(Ω) = 1. A σ -algebra has the following properties that correspond to the intuitively required properties of events, as discussed for the rolling of a die: • • • • Ω ∈ F and ∅ ∈ F . A ∈ F ⇒ A = Ω\A ∈ F . A, B ∈ F ⇒ A ∩ B ∈ F . Ai ∈ F, i = 1, 2, . . ⇒ ∞ i=1 Ai ∈ F ; if furthermore Ai ∩ Aj = ∅ for i = j then ∞ A ) = μ(A μ( ∞ i ).

Consider a system of N indistinguishable particles (of mass m) in a volume V ⊆ R3 , interacting through a pair potential U . 3) i=1 j >i where x = (r 1 , . . , r N , p 1 , . . , p N ) stands for the collection of 3N spatial coordinates and 3N momenta specifying the state of the system. Furthermore, let the system be in contact with a heat bath of temperature T . In statistical physics this system in its specific state is said to be in the canonical ensemble, specified by prescribing the values of the macroscopic variables (N, V , T ).

Yn ] = Yn . 71) E[Yn+1 |Y1 , . . 72) E[Yn+1 |Y1 , . . , Yn ] ≤ Yn . 73) It is a submartingale iff and a supermartingale iff This means that for a martingale the best estimator for the next value, given all the information obtained through the past values, is the actual value. If the process is a martingale, its changes (increment process) are a fair game, meaning that the expectation value of the increments is zero. We have also already seen such a behavior in our discussion of the random walk on a line in the first chapter.

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