Business Analytic Tools
University of Memphis
Popular in Business Analytic Tools
Popular in Finance
This 2 page Class Notes was uploaded by Precious Notetaker on Thursday April 14, 2016. The Class Notes belongs to at University of Memphis taught by Dr. Amini in Spring 2016. Since its upload, it has received 21 views. For similar materials see Business Analytic Tools in Finance at University of Memphis.
Reviews for Business Analytic Tools
Same time next week teach? Can't wait for next weeks notes!
Report this Material
What is Karma?
Karma is the currency of StudySoup.
You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!
Date Created: 04/14/16
Business Analytic Tools Dr. MehdaAmini (University of Memphis) written by Precious Fox Simulation Models and DecisionAnalysis What is a Monte Carlo Simulation? It is a model that uses repeated random sampling to represent uncertainty in a model representing a real system and that computes the calues of model outputs. Values for the probabilistic inputs to a simulation are randomly generated based on historical info. Simulations: Do not guarantee optimality Are flexible and do not require assumptions of theoretical models Allow testing of the system without affecting the real system Provide a convenient experimental laboratory for the real system What is a decision analysis? It is an approach that is systematic, logical, factual, and data-driven and helps in decision making. There is a five step process for a decision analysis. 1.) Clearly define the problem 2.) List all possible alternatives 3.) Identify all possible outcomes for each alternatives 4.) Identify the payoff for each alternative and outcome combination 5.) Use a decision modeling technique to choose as an alternative When talking about these simulations, there are three terms that are very important to know: certainty, uncertainty, and risk. Certainty is where the decision criteria, alternatives, outcomes, and all other relevant information are known. Uncertainty and risk may sound the same, but they are not. Uncertainty is when relevant information is known, but the chances of its outcomes are not. Risk is when relevant information is known as well as the probability of outcomes, you just don't know all of what is going to happen. Adecision tree model is designed specifically to help decipher this. It is the graphical representation of a decision problem. The five distinct components of a decision tree model are: 1.) Decision Node- (square) denotes when a choice must be made 2.) Chance Node- (circle) an event or state of nature 3.) Branch- (line) decision alternatives 4.) Outcome/Payoff- quantitative measurement indicating result 5.) State of Nature Probability- shows likelihood, value between 0 and 1
Are you sure you want to buy this material for
You're already Subscribed!
Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'