jagomart
digital resources
picture1_Calculus Pdf 169529 | Math6203 Syllabi


 137x       Filetype PDF       File size 0.06 MB       Source: math.charlotte.edu


File: Calculus Pdf 169529 | Math6203 Syllabi
math6203 8203 stochastic calculus for finance i syllabus spring 2019 text stochastic calculus for finance i the binomial asset pricing model by steve shreve stochastic calculus for finance ii continuous ...

icon picture PDF Filetype PDF | Posted on 25 Jan 2023 | 2 years ago
Partial capture of text on file.
                  MATH6203-8203: Stochastic Calculus for Finance I
                          Syllabus: Spring 2019
        Text:
         • Stochastic Calculus for Finance I(The Binomial Asset Pricing Model) by Steve Shreve.
         • Stochastic Calculus for Finance II (Continuous-Time Models) by Steve Shreve.
        Binomial asset pricing model: one-period two state model, actual probability, risk neutral probability,
        arbitrage, arbitrage free or risk-neutral pricing formula, delta-hedging formula.
        Review of General Probability Theory: Sigma-algebra( or sigma field), Axioms of probability measure,
        Properties of probability measures, Discrete probability space, Uncountable sample space, Borel sets, Borel
        sigma algebra.
        Random Variables and Distribution: Random variables, Distribution measure of a random variable,
        Cumulative distribution function, Properties of cumulative distribution function, Discrete random variable,
        Probability mass function, Some examples of discrete random variables, Continuous random variables, Proba-
        bility density function, Some properties of probability density function, Some examples of continuous random
        variables with their probability density function and cumulative distribution function.
        Expectations: Expected value for when the sample space is finite or countably infinite. Expected value of
        a discrete random variable. Expected value of a continuous random variable. Computation of Expectation.
        Moment Generating Function. Convergence of random Variables: Almost Sure Equal. Almost Sure Conver-
        gence and Point-wise Convergence, Convergence in distribution and Mean-square convergence. Monotone
        Convergence and Dominated Convergence.
        Change of Measure: Change of measure and Radon-Nikodym derivative process for finite sample space.
        Change of Measure for uncountable infinite sample space. Equivalent probability measure, Radon-Nikodym
        derivative of one measure with respect to another measure, Change of measure for a normal random variable,
        Radon-Nikodym Thoerem.
        Information and Conditioning: Filtration, Sigma algebra generated by collection of sets, Sigma algebra
        generated by a random variable, Independence of events, Independence of sigma algebras. Independence of
        random variables. Simple way of verifying random variables are independent. Covariance and Correlation.
        Conditional probability. Radon-Nikodym Theorem. General conditional expectation: Expectation condi-
        tioned on a sigma algebra, Properties of Conditional expectation, Martingale property for discrete processes,
        Martingale Property for Continuous process, Sub-martingale, Super-martingale, Markov processes.
        Random walk: Symmetric random walk , Increments of symmetric random walk, martingale property of
        symmetric random walk. Quadratic Variation of symmetric random walk. Limiting distribution of the scaled
        random walk.
        Brownian motion: Definition of Brownian motion. Filtration for Brownian motion. Martingale property
        of Brownian motion, Exponential martingale, Markov property of Brownian motion, Quadratic variation:
        First order variation, Quadratic variation of Brownian motion. Volatility of Geometric Brownian motion.
        Stochastic Calculus: Itˆo Integral for simple integrands, Itˆo Integral for general integrands, Some prop-
        erties of Itˆo integrals, Riemann Integral of Brownian motion, Itˆo-Doeblin Formula for Brownian motion.
        Solved some examples. Itˆo process, Quadratic variation of Itˆo processes, Integration with respect to Itˆo
        processes. Itˆo-Doeblin formula for Itˆo processes. Integration by part formula, Solved examples. Itˆo Inte-
        gral of deterministic integrand, Generalize Geometric Brownian motion.Some applications to mean-reverting
        models: Vasicek model and CIR model. 2-Dimensional Itˆo-Doeblin formula, Product rule and quotient rule
        formula.
                               1
        Black-Sholes-Merton Model: Risk-free asset process, Evolution of portfolio value process, Discounted
        stock price, Discounted portfolio value, Evolution of option value, Derivation of the celebrated Black-Scholes-
        Merton partial differential equation. Second-oder partial differential equation: Homogeneous heat equation,
        Derivation of the solution of the Black-Scholes-Merton partial differential equation, The Greeks, Put-Call
        parity.
        Risk-Neutral Pricing: Review of change of measure. Risk-neutral measure: Girsanovs Theorem for a
        single Brownian motion, Recognizing Brownian motion, Risky asset price process with stochastic mean rate
        of return and volatility, Risk-free interest rate, Discount process with adapted interest rate process, Risk-
        neutral measure, Discounted risky asset price process under risk-neutral measure, Portfolio value process,
        Discounted portfolio value process under Risk-Neutral Measure. Pricing under the risk-neutral measure.
        Deriving the Black-Scholes-Merton formula.
                               2
The words contained in this file might help you see if this file matches what you are looking for:

...Math stochastic calculus for finance i syllabus spring text the binomial asset pricing model by steve shreve ii continuous time models one period two state actual probability risk neutral arbitrage free or formula delta hedging review of general theory sigma algebra eld axioms measure properties measures discrete space uncountable sample borel sets random variables and distribution a variable cumulative function mass some examples proba bility density with their expectations expected value when is nite countably innite computation expectation moment generating convergence almost sure equal conver gence point wise in mean square monotone dominated change radon nikodym derivative process equivalent respect to another normal thoerem information conditioning filtration generated collection independence events algebras simple way verifying are independent covariance correlation conditional theorem condi tioned on martingale property processes sub super markov walk symmetric increments quadr...

no reviews yet
Please Login to review.