Refik Güllü

IE 592 Special Topics: Stochastic Models in Finance

Credit Information: 
3
Description: 
An introduction to stochastic models in financial decision making. Discrete time models: Martingales, risk-neutral probability measure and Radon-Nikodym derivative in discrete time. Brownian motion, Ito’s formula and change of measure in continuous time, along with the Black-Scholes model. Discussion on stopping times and their application to American options. Stochastic models for interest rates and fixed income derivatives.

IE 360 Statistical Forecasting and Time Series

Description: 
Exploring data patterns; moving averages, simple and double exponential smoothing, smoothing methods with seasonal data, Holt-Winter method; simple and multiple regression; regression with time series data; ARIMA models; Box-Jenkins method for forecasting; demand management and applications.

IE 621 Inventory Control Theory

Credit Information: 
(3+0+0) 3
Description: 
Description and characteristics of inventory models; economic order quantity and economic lot size models; multiple product and multiple location models under deterministic demand; stochastic single-item models with capacity constraints and lead-times; structure of dynamic inventory policies; multi-item stochastic demand inventory models; supply chain models and current issues in inventory planning.
Prerequisite: 
IE 505 or instructor's consent.

IE 255 Probability for Industrial Engineers

Credit Information: 
(3+0+0) 3
Description: 
Basic topics in probability theory; sample space, probability, and conditional probability; random variables, marginal, joint and conditional distributions; expectations and conditional expectations; hypergeometric, binomial, geometric distributions and their implications in IE/OR; Poisson, exponential, Erlang, gamma distributions and the Poisson arrival model; moment generating functions and Laplace transforms; law of large numbers, central limit theorem, and the Normal distribution; numerical and computational aspects of random variable generation.
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