• Aucun résultat trouvé

Stochastic Modeling: Exercise Class 7.

N/A
N/A
Protected

Academic year: 2022

Partager "Stochastic Modeling: Exercise Class 7."

Copied!
1
0
0

Texte intégral

(1)

Stochastic Modeling: Exercise Class 7.

Olivier Wintenberger: olivier.wintenberger@upmc.fr

Exercise 1. Consider a game of coin tossing between two playersAandB. If the toss results a head, then player B gives 1 euro to A, else player A gives 1 euro to B. Assume that the initial capital ofA is a euros, B is beuros. We denotep=P(”Head”).

• Model the gains of player A during the game as a discrete random walk (Xt) starting fromX0 = 0.

• Show that{0}is an atom for (Xt) and computeP0(Xk= 0) fork≥1.

• Show that η0(n) the number of passages at the atom Pn

t=11I{Xt=0} is uniformly inte- grable if and only if p6= 1/2.

• Consider the case p > 1/2. Show that uk = Pk0 = +∞) satisfies the recursive equation uk=puk+1+ (1−p)uk−1 fork≥2,u1 =pu2 and limk→∞uk= 1.

• Deduce thatP00=∞) = 2p−1 and discuss this unfair game.

• Consider the casep= 1/2. Show that

P(X2t= 0|X0 = 0) = (2t)!

(t!)2 1

4 t

, t≥1.

• We recall Stirling’s formula, valid fornlarge, n! =√

2πn n

e n

. Show thatE[η0(n)]∼p

2n/π and deduce that the Markov chain is null-recurrent.

• Show that ν the counting measure on Z is invariant. Explain why the distribution of (Xt) cannot converge toν.

1

Références

Documents relatifs

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

Data analysis and stochastic modeling – Introduction to probability.. What are we

Data analysis and stochastic modeling – Descriptive and Exploratory Statistics.. What are we

Computational multiscale frameworks based on a microscale description were further proposed in [3,4] and rely on the combination between interpolation schemes (in the space

Based on these experimental measurements, a complete parametrization of the track geometry and of its variability would be of great concern in spec- ification, security

…rst stochastic process, S (1) , represents the price of the riskless asset while the two others.. If you solve the linear system by hand, it is preferable to use a backward

Unité de recherche INRIA Rennes, Irisa, Campus universitaire de Beaulieu, 35042 RENNES Cedex Unité de recherche INRIA Rhône-Alpes, 655, avenue de l’Europe, 38330 MONTBONNOT ST

Consider an M -layer network whose layers are sub-networks of G obtained by randomly re- moving links (called link thinning) and deactivating nodes. When a node is deactivated on