Simulation modeling using @Risk - Info and Reading Options

"Simulation modeling using @Risk" Table Of Contents:

• 1- Machine generated contents note: Chapter 1: What Is Simulation? 1
• 2- 1.1 Actual Applications of Simulation 2
• 3- 1.2 What's Ahead? 4
• 4- 1.3 Simulation Models Versus Analytic Models 6
• 5- Chapter 2: Random Numbers-The Building Blocks of Simulation 9
• 6- Problems 11
• 7- Chapter 3: Using Spreadsheets to Perform Simulations 13
• 8- Example 3.1: The Newsvendor Problem 13
• 9- 3.1 Finding a Confidence Interval for Expected Profit 18
• 10- 3.2 How Many Trials Do We Need? 18
• 11- 3.3 Determination of the Optimal Order Quantity 19
• 12- 3.4 Using Excel Data Tables to Repeat a Simulation 24
• 13- 3.5 Performing the Newsvendor Simulation with the Excel
• 14- Random Number Generator 28
• 15- Problems 30
• 16- Chapter 4: An Introduction to @RISK 33
• 17- 4.1 Simulating the Newsvendor Example with @RISK 33
• 18- 4.2 Explanation of Statistical Results 40
• 19- 4.3 Conclusions 41
• 20- Chapter 5: Generating Normal Random Variables 43
• 21- 5.1 Simulating Normal Demand with @RISK 43
• 22- 5.2 Using the Graph Type Icons 45
• 23- 5.3 Placing Target Values in the Statistics Output 46
• 24- 5.4 Estimating the Mean and Standard Deviation of a Normal Distribution 46
• 25- Problems 47
• 26- Chapter 6: Applications of Simulation to Corporate Financial Planning 49
• 27- 6.1 Using the Triangular Distribution to Model Sales 57
• 28- 6.2 Sensitivity Analysis with Tornado Graphs 59
• 29- 6.3 Sensitivity Analysis with Scenarios 61
• 30- 6.4 Alternative Modeling Strategies 62
• 31- Problems 63
• 32- Chapter 7: Simulating a Cash Budget 69
• 33- Example 7.1: Cash Budgeting 69
• 34- Problems 75
• 35- Chapter 8: A Simulation Approach to Capacity Planning 83
• 36- Example 8.1: Wozac Capacity Example 83
• 37- Problems 89
• 38- Chapter 9: Simulation and Bidding 93
• 39- 9.1 Uniform Random Variables 93
• 40- 9.2 A Bidding Example 93
• 41- Problems 95
• 42- Chapter 10: Deming's Funnel Experiment 97
• 43- 10.1 Simulating Rule 1 (Don't Touch That Funnel!) 98
• 44- 10.2 Simulating Rule 2 100
• 45- 10.3 Comparison of Rules 1-4 102
• 46- 10.4 Lesson of the Funnel Experiment 102
• 47- 10.5 Mathematical Explanation of the Funnel Experiment 102
• 48- Problems 104
• 49- Chapter 11: The Taguchi Loss Function 105
• 50- 11.1 Using @RISK to Quantify Quality Loss 106
• 51- Problems 108
• 52- Chapter 12: The Use of Simulation in Project Management 111
• 53- Example 12.1: The Widgetco Example 111
• 54- 12.1 Estimating Probability Distribution of Project Completion Time 113
• 55- 12.2 Determining the Probability That an Activity Is Critical 117
• 56- 12.3 The Beta Distribution and Project Management 118
• 57- Problems 120
• 58- Chapter 13: Simulating Craps (and Other Games) 123
• 59- Example 13.1: Simulating Craps 123
• 60- 13.1 Confidence Interval for Winning at Craps 125
• 61- problems 126
• 62- Chapter 14: Using Simulation to Determine Optimal Maintenance Policies 129
• 63- Example 14.1 129
• 64- Problems 133
• 65- Chapter 15: Using the Weibull Distribution to Model Machine Life 135
• 66- Example 15.1: Simulating Equipment Replacement Decisions 136
• 67- Problems 139
• 68- Chapter 16: Simulating Stock Prices and Options 141
• 69- 16.1 Modeling the Price of a Stock 141
• 70- 16.2 Estimating the Mean and Standard Deviation of Stock Returns
• 71- from Historical Data 142
• 72- 16.3 What Is an Option? 144
• 73- 16.4 Pricing a Call Option 145
• 74- Example 16.1a: Pricing a European Call Option with @RISK 145
• 75- 16.5 Analyzing a Portfolio of Investments 148
• 76- Example 16.1b: Simulating Portfolio Return 149
• 77- Problems 153
• 78- Chapter 17: Pricing Path-Dependent and Exotic Options 157
• 79- Example 17.1: Pricing a Path-Dependent Option 158
• 80- Problems 160
• 81- Chapter 18: Using Immunization to Manage Interest Rate Risk 161
• 82- 18.1 Duration 164
• 83- 18.2 Convexity 165
• 84- 18.3 Immunization Against Interest Rate Risk 165
• 85- Example 18.1: Immunization Using Solver 165
• 86- 18.4 Better Models'for Interest Rate Risk 172
• 87- Problems 172
• 88- Chapter 19: Hedging with Futures 175
• 89- 19.1 Hedging with Futures: The Basics 175
• 90- 19.2 Modeling Futures Risk with @RISK 176
• 91- Problems 179
• 92- Chapter 20: Modeling Market Share 183
• 93- Example 20.1a: Market Share Simulation 183
• 94- 20.1 Is Advertising Worthwhile? 185
• 95- Example 20. b: Advertising Effectiveness 185
• 96- 20.2 To Coupon or Not to Coupon? 187
• 97- Example 20.1c: Should Coke Give Out Coupons? 187
• 98- Problems 189
• 99- Chapter 21: Generating Correlated Variables: Designing a New Product 193
• 100- Example 21.1 193
• 101- Problems 200
• 102- Chapter 22: Simulating Sampling Plans with the Hypergeometric
• 103- Distribution 205
• 104- Example 22.1: Simulating a Sampling Plan 206
• 105- Problems 207
• 106- Chapter 23: Simulating Inventory Models 209
• 107- Example 23.1: Simulating a Periodic Review Inventory System 210
• 108- Problems 214
• 109- Chapter 24: Simulating a Single-Server Queuing System 217
• 110- Example 24.1: Queuing Simulation in RISK 217
• 111- 24.1 Estimating the Operating Characteristics of a Queuing System 223
• 112- Problems 224
• 113- Index 225.

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