Home Game Theory • Archil Gulisashvili's Analytically Tractable Stochastic Stock Price Models PDF

Archil Gulisashvili's Analytically Tractable Stochastic Stock Price Models PDF

By Archil Gulisashvili

Asymptotic research of stochastic inventory expense versions is the vital subject of the current quantity. certain examples of such versions are stochastic volatility versions, which were constructed as a solution to convinced imperfections in a celebrated Black-Scholes version of alternative pricing. In a inventory expense version with stochastic volatility, the random habit of the volatility is defined by way of a stochastic procedure. for example, within the Hull-White version the volatility method is a geometrical Brownian movement, the Stein-Stein version makes use of an Ornstein-Uhlenbeck approach because the stochastic volatility, and within the Heston version a Cox-Ingersoll-Ross approach governs the habit of the volatility. one of many author's major pursuits is to supply sharp asymptotic formulation with errors estimates for distribution densities of inventory costs, choice pricing services, and implied volatilities in a number of stochastic volatility versions. the writer additionally establishes sharp asymptotic formulation for the implied volatility at severe moves generally stochastic inventory rate versions. the current quantity is addressed to researchers and graduate scholars operating within the zone of economic arithmetic, research, or likelihood thought. The reader is predicted to be accustomed to parts of classical research, stochastic research and chance conception.

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40. 44. More details can be found in [KS91], Sect. 4. Let (Ω, F) be a measurable space and let Xt , t ≥ 0, be an Rd -valued stochastic process on Ω. For a topological space H denote by B(H ) the Borel σ -algebra of subsets of H . 42 The stochastic process X is called measurable if the mapping (t, ω) → Xt (ω) from [0, ∞) × Ω into Rd is B ⊗ F/B(R d )-measurable. 43 Let (Ω, F, {Ft }) be a measure space equipped with the filtration {Ft }, and let Xt , t ≥ 0, be an Rd -valued stochastic process on Ω.

N. Thiele. 36 1 Volatility Processes • A rigorous mathematical theory of Brownian motion was constructed by N. Wiener in [Wie23] and [Wie24]. Wiener’s fundamental work laid the foundation of stochastic analysis and stochastic modeling. • Brownian motion with drift is not a reasonable stochastic model for the stock price because the price process in this model takes negative values. M. A. Samuelson [Sam65], see also [Sam02]. Note that early empirical observations of the behavior of stock returns in [Ken53] and [Rob59] led the authors to the conclusion that stock returns are normally distributed.

B In addition, it is not hard to see that lim m(Yt ) = t→∞ a b and lim v(Yt ) = t→∞ ac2 . 40 imply the following assertion that describes the marginal distributions of CIR processes. 45 (a) Let a > 0 and b > 0. Then the marginal distribution μt of the CIR process Y admits a density ρt given by 2b y ν t 2 bt ρt (y) = exp b 1 + 2 c (e − 1) y0 × exp − where ν = 2a c2 − 1. 15 Marginal Distributions of CIR Processes 33 (b) Let a > 0 and b = 0. Then the marginal distribution μt of the CIR process Y admits a density ρt given by 2 ρt (y) = 2 c t y y0 ν 2 √ 4 y0 y 2(y0 + y) exp − Iν , c2 t c2 t y > 0, − 1.

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