الانتقال إلى المحتوى
The Lumenary
السنة الأولى من الدراسات العلياProbability & Statisticsمُخطَّط له

Stochastic processes

Continuous-time processes: Poisson processes, continuous-time Markov chains, Brownian motion and its path properties, continuous-time martingales, and an introduction to Itô calculus and stochastic differential equations.

math.prob.stochastic-processes

لم يُكتب درس هذا الموضوع بعد. المخطط أدناه جزء من خريطة المنهج ولم تجرِ مراجعته.

يعتمد على

عدد المتطلبات السابقة الإلزامية (حتى الأساس): 48

ستتعلّم

  • Construct the Poisson process and derive its basic properties.
  • State the defining properties of Brownian motion and use its basic path properties.
  • Apply Itô's formula and solve simple stochastic differential equations such as that of geometric Brownian motion.

تعريف

  • Standard Brownian motion is a process B with B₀ = 0, continuous paths, and independent increments with B_t − B_s normally distributed with mean 0 and variance t − s for s < t.
  • The Itô integral ∫ H dB is defined as a limit in L² of sums in which the integrand is evaluated at the left endpoint of each interval.

مبرهنة

  • Brownian paths are almost surely continuous and nowhere differentiable.
  • Itô's formula: for twice continuously differentiable f, df(B_t) = f′(B_t) dB_t + ½ f″(B_t) dt.
  • The equation dS = μS dt + σS dB has the solution S_t = S₀ exp((μ − σ²/2)t + σB_t).

مفاهيم خاطئة شائعة

  • Applying the ordinary chain rule to Itô integrals.
  • Thinking Brownian paths are differentiable because they are continuous.

اكتشافات اختيارية

قراءات إضافية

  • Ioannis Karatzas and Steven E. Shreve, Brownian Motion and Stochastic Calculus (1988)
  • Bernt Øksendal, Stochastic Differential Equations