...Abstract Using the internet and all that’s available on the web today, an eight week stock simulation was conducted to investigate the effects of different trading strategies on outcome of investments in the stock market. The knowledge and experience received from this project would be helpful for people to become better investors in future real-life investments. 5 Chapter 1: Introduction 1.1 Goals of the Project: The main goal of this project is to learn about the stock market through practice with a short-term and long-term stock market simulation. I will start short-term trading with 10 stocks that I selected over the first few weeks. I have also selected 2 stocks which will I will trade in a long-term method over the next 8-week period. After investing in the selected stocks, I will be able to analyze the simulation and make conclusions based on my performance. I am beginning with $200,000, and then will scope over my profits and losses to understand which methods work best. Starting in Chapter 1, I will explain the history of the stock market and who is involved with it. In the following chapters I will show my results of the simulation and discuss them. I will conclude the simulation in the final chapter, which will cover all results and what I learned during the 8-week period. 1.2 History of the Stock Market: The stock market is a trading place where bonds and stocks can be traded, usually to gain some type of income. Basically, a stock is a piece of...
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...Software Requirements Specification for Stock Market Simulator Version 1.0 approved Prepared by Divesh Mirchandani, Abhishek Oturkar, Sumit Kriplani, Kedar Nadkarni 30-01-2015 Table of Contents Table of Contents ii Revision History ii 1. Introduction 1 1.1 Purpose 1 1.2 Document Conventions 1 1.3 Intended Audience and Reading Suggestions 1 1.4 Product Scope 1 1.5 References 2 2. Overall Description 2 2.1 Background 2 2.2 System Context 2 2.3 System Capabilities 3 3. Behavioural Requirements 4 3.1 System Inputs & Outputs 4 3.2 Detailed Output Behaviour 4 3.3 Software Interfaces 4 3.4 Communications Interfaces 4 4. Quality Requirements 12 5. Fundamental Assumptions 12 6. Expected Changes 12 7. Appendices 13 Introduction 1 Purpose To fully document the expected functionality and requirements for our Stock Market Simulation Game. 2 Document Conventions • Concept of Operations gives a user-oriented, high-level overview of our Stock Market Simulator. • Behavioral Requirements gives a more-detailed vision of the simulator's operations, which is better suited to developers and those interested in the technology. 3 Intended Audience and Reading Suggestions The set of stakeholders includes the team members, the project and overseeing managers, and potential users of our stock market simulation. • Team Members - can use this document to gain a detailed understanding...
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...analysis and Monte Carlo simulation in order to identify and prioritize the target market selection criteria (Case study: Food distribution companies of Mashhad-Iran) Amir kariznoee Ph.D. student of Industrial Management,University of Mazandaran ,Iran (Corresponding Author's E-mail: Amir.kariznoee@yahoo.com) Monireh Bijandi Graduate of Accounting in Ferdowsi University of Mashhad,Iran Mahdi Ghayur Maddah Student of Public Management in Ferdowsi University of Mashhad,Iran Vajihe Mogharabi M.A. Student of Information Technology Management, Shahid beheshti University,Tehran,Iran Abstract The aim of this study is to identify and prioritize the key factors in selecting a target market in the food industry. In order to determine the components and subcomponents of this study, we have used previous researches in this area. In order to match these factors with the food industry situation and create a hierarchical structure, we have obtained the opinions of 323 experts about affecting factors on choosing a market in this industry with the use of questionnaire. Then, using a combination of hierarchal analysis process and Monte Carlo simulation and cooperation with 10 senior executives of distribution companies, the weight of each component and sub-component was determined. In general, four components and ten sub-components were examined in this study. After determining the weight of these components, the importance of each component in choosing a market has been prioritized...
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...The simulation positioned users of the software as a CEO of East-West Transportation a freight transportation company. The simulation took users through each division of the company, that if which being Consumer Goods, Coal, Chemical, and Forest Products. The simulation aided in the differentiation between the four market structures. It also taught students to identify and interpret cost and revenue curves for each market. The Consumer Good’s Division of East-West Transportation Inc operates as a perfect competitive market. A perfect competitive market structure has “a large number of buyers and sellers” (Colander, 2004). With this type of market structure, no company controls the market price. The CEO develops the market price to determine the output of production to maximize profits. The CEO, implements the output where MR equals MC. Therefore, the profit maximizes at a point where P equals MR equals MC. The CEO evaluates the study and determines at this point, East-West Transportation Inc will continue to operate. Even with losses at every level of production, the continuation of production allows the company to recover the variable costs but not fixed costs. Shutting down the operations the company would incur losses equal to the fixed costs, which is higher than the continuation of production. The Coal Division of East-West Transportation Inc is a “regional monopoly” (University of Phoenix, 2009). A monopoly structure firm has control over setting prices and therefore...
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...Monte Carlo Statistical Analysis Name Course Instructor Date The Monte Carlo method is a mathematical method used for problem solving through the generation of random numbers and then observing a fraction of these numbers and the properties they obey. It is useful in obtaining numerical solutions to problems that are too complicated for analytical solutions. It is a form of probability used to understand the impact of risk and uncertainty in various areas such as financial and cost forecasting. It involves computation of the likelihood of given events occurring or not occurring, without taking into account the interaction of the elements involved in influencing the occurrence. The mathematical method was invented by Stanislaw Ulam in 1946 and named by Nicholas Metropolis after a classy gambling resort in Monaco, where a relative of Ulam frequently gambled [ (Fishman, 1996) ]. Concepts of the Monte Carlo method Uncertainty Being a forecasting model, there are assumptions that need to be made due to the uncertainty of various factors. One therefore needs to be able to make estimations of the expected results as they cannot predict with certainty what the end value will be. Important factors such as historical data and past experiences in the field can be helpful in making an accurate estimate. Estimation In some cases, estimation may be possible but in others it is not. In situations where estimation is possible, it is wise to use a wide range of possible values instead...
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...materials such as Ultra/Advanced High Strength Steels (U/AHSS), aluminum alloys, magnesium alloys and boron steels in automotive industry is increasing to reduce vehicle weight and increase crash performance. The use of these relatively new materials requires advanced and reliable techniques to a) obtain data on material properties and flow stress, b) predicting springback and fracture in bending and flanging, c) selecting lubricants and die materials/coatings for stamping and forging and d) designing tools for blanking and shearing. In addition, designing the process and tooling for a) hot stamping of boron steels, b) warm forming of Al and Mg alloys, and c) optimizing the use of servo-drive presses require advanced Finite Element based simulation methods. CPF is conducting R&D in most of these topics and also in many hot and cold forging related topics. This paper gives an overview of this research and discusses how the research results are applied in cooperation with industry. Keywords: Metal Forming, Sheet metal, Forging, FEM 1 INTRODUCTION The Center for Precision Forming (CPF) has been established with funding from the National Science Foundation (NSF) and a number of companies (www.cpforming.org). CPF is an outgrowth of the Engineering Research Center for Net Shape Manufacturing (ERC/NSM – www.ercnsm.org) and conducts research in sheet metal forming while ERC/NSM focuses on cold and hot forging related R&D projects. Both Centers work closely with industry under contract....
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...is considered formal as they are structured and planned to facilitate the job description. As for the manager’s training in particular, formal settings, such as classroom lectures at the tertiary level or the organization’s own training institution providing coaching by outsourced professionals or the company’s own executives, seminars, workshops and meetings of company’s executives fostering networking and management development are recommended. Whatever the setting are the methodologies applied therein are conceptually the same as they are essentially structured to improve skills and knowledge. The contents of management training normally target issues facing the company as well as bench marking or leaning “best practice”/scenario simulation that...
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...Modeling Order Book Fluctuation by Monte Carlo Technique CONTENTS Page no. 1) Certificate 2 2) Acknowledgement 3 3) Abstract 5 4) Introduction 6 5) Simulation code 8 ➢ Order Book 8 ➢ Diffusion 9 ➢ Price and Annihilation 11 ➢ One Trade return 14 ➢ Waiting time between consecutive trades 16 ➢ Conditional return 19 ➢ Hurst curve 20 6) Results and Discussion 22 7) Summary 28 8) Future Prospects 29 9) References ...
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...JET Copies Case Problem In analyzing the case, JET Copies Case Problem, the following categories will be addressed: Model number of days to repair 1. In Excel, use a suitable method for generating the number of days needed to repair the copier, when it is out of service, according to the discrete distribution shown. JET copies needs to know the number of days they need to repair, when the copy machine is out of service. Using the given table, there are three columns of probability, repair time and cumulative. I used the figures given in case problem for probability and repair time days but for the cumulative column we started at 0.00 cumulative, then added the 0.20 to that to get the cumulative for day 2. For each probability subsequent to the previous we added, so for the 0.45 probability we added the 0.20 to get 0.65. Then repeating the same for the rest of probabilities, after 0.65 the cumulative resulted in 0.90. Then we used the table with ten columns. In the first column starting at A5, the formula entered was the =RAND() function to create random number for the first cell. That function formula was then dragged down to the below cells and locked to have the values be fixed. In the next column, I use the numbers copied from my first column. Then in the G5 column, we entered the function VLOOKUP to find the number of days needed to repair =VLOOKUP(F5,Lookup,2) and dragged the cell to have the same formula for the below cells in the column. Look up, in the...
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...This report provides an in-depth analysis of the two Everest Simulations conducted by Group 10 of MGMT1001 Thursday Tutorial. This task required students to form teams consisting of five to six members whose goals were to summit Mount Everest. While it provided us with a rich experience in team dynamics and collaboration, it also enabled us to explore key managerial concepts taught in the course, consisting of: • Communication • Groups and Teams • Leadership In this report, we examine the effectiveness of Face to Face Communication (FTFC) versus Computer Mediated Communication (CMC), and the problems encountered through the utilisation of the virtual medium including efficiency of the feedback system, loss of personal focus and other emergent issues. It includes personal reflections on attitudes and perceptions, as well as group performance and strategies adopted in the second Simulation in order to create a more positive team experience. Theories which relate to interpersonal communication have also been integrated in the report to illustrate its relation to certain situations encountered during the Simulation. Additionally, we provide a multifaceted analysis on the notion of team cohesiveness and how it attributes to better performance outcomes. An overview on the different intragroup conflicts encountered in the Simulation has been included, examining the positive and negative impact that conflict had on team experience and performance, and how mutual agreements were reached...
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...is a computer necessary in conducting a realworld simulation? Answer It is important because there are many different types of outcomes that comes in with simulation. Computers are used in daily life activities and it is necessary. 14-11 What is operational gaming? What is systems simulation? Give examples of how each may be applied. Answer Operational gaming is the use of simulation in competitive situations such as military games and business or management. System simulation ls that deal with the dynamics of large organizational or governmental systems. Validation The process of comparing a model to the real system that it represents to make sure that it is accurate. 14-17 (a) Resimulate the number of stockouts incurred over a 20-week period (assuming Higgins maintains a constant supply of 8 heaters). (b) Conduct this 20-week simulation two more times and compare your answers with those in part (a). Did they change significantly? Why or why not? (c) What is the new expected number of sales per week? Answer A. The number of stockouts incurred over a 20 week period is HOT WATER NUMBER OF HEATER SALES WEEKS THIS PER WEEK NUMBER WAS SOLD 3 2 4 9 5 10 6 15 7 25 8 12 9 12 10 10 B, Two more times would give us the value of a multiplied by 2. c. 25 14-18 A. 15 days of barge uploadings and average number of barges delayed B, They both are probabilistic simulations. Chapter 5 HW 5-14 Using MAD, determine whether...
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...A SYSTEM SIMULATION STUDY ON THE THREE FAST MOVING PRODUCTS (MARLBORO, C2, VIVA) OF THE COLLEGE VARIETY SHOPPE USING THE MONTE CARLO SIMULATION IN INVENTORY MANAGEMENT EXECUTIVE SUMMARY This study shows how the selected three fast moving products (Marlboro cigarettes, C2, Viva mineral water) move from the current Inventory Management technique of the College Variety Shoppe from its distributors to its warehouse storage to the end user or customer. An excel program and a simulation model was made to observed its current performance. After the observation, the group performs an experimentation that will improve the current technique of the College Variety Shoppe. After simulating the experimentation, the group then give conclusions and recommendations on how to improve the College Variety Shoppe’s current Inventory Management. TABLE OF CONTENTS Title Page ........................................................ 1 Executive Summary ........................................................ 2 Table of Contents ........................................................ 3 Introduction ........................................................ 4 Methodology ........................................................ 6 Model Development ........................................................ 7 Model Validation ........................................................ 11 Experimentation, Results .......
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...Initial operations strategy Prior to the commencement of the simulation, we examined the 50 days of historical data to glean as much information as we could about the operations. We performed some analysis in Excel and created a dashboard to illustrate various data. Specifically, we regressed the prior 50 days of jobs accepted to forecast demand over the next 2 - 3 months within a 95% confidence interval. The yellow and grey lines represent the maximum and minimum variability, respectively, based on two standard deviations (95%). Exhibit 1: Forecasted and actual demand by Day 50 and Day 270 Our two primary goals at the beginning of the simulation were as follows: 1) Eliminate bottlenecks and increase capacity in order to meet forecasted demand 2) Decrease lead time to 0.25 days in order to satisfy Contract 2 and maximize revenue In order to achieve these goals, we would need to know the capacity and throughput time of the entire system. We used the time required by each machine to process a lot to calculate capacity per station and then capacity of the entire production line (380 kits/day or 6 orders/day). In Exhibit 2 we can observe that the capacity of the production line is given by the station that produces the least number of units per day. Exhibit 2: Capacity of the production line The Decisions We decided to work with the maximum variability of demand because there was a penalty for late jobs and because there was no revenue for orders that took more than “x”...
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...Introduction This chapter describes our work in evolution of buildable designs using miniature plastic bricks as modular components. Lego 1 bricks are well known for their flexibility when it comes to creating low cost, handy designs of vehicles and structures. Their simple modular concept make toy bricks a good ground for doing evolution of computer simulated structures which can be built and deployed. Instead of incorporating an expert system of engineering knowledge into the program, which would result in more familiar structures, we combined an evolutionary algorithm with a model of the physical reality and a purely utilitarian fitness function, providing measures of feasibility and functionality. Our algorithms integrate a model of the physical properties of Lego structures with an evolutionary process that freely combines bricks of different shape and size into structures that are evaluated by how well they perform a desired function. The evolutionary process runs in an environment that has not been unnecessarily constrained by our own preconceptions on how to solve the problem. The results are encouraging. The evolved structures have a surprisingly alien look: they are not based in common knowledge on how to build with brick toys; instead, the computer found ways of its own through the evolutionary search process. We were able to assemble the final designs manually and confirm that they accomplish the objectives introduced with our fitness functions. This chapter...
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...developed, operated and maintained the Concept Simulator since 1998. The Concept Simulator models the functional operation and inter-operation of key components of train control system architecture and the external systems to which the system interfaces. The simulator is valuable in the development and analysis of operational principles, and in assessing design trade-offs. The SEA-designed facility simulates operation at ERTMS Levels 1, 2, and 3. Components include a Communications Network, a Network Management Centre, a generic Interlocking, a Radio Block Centre, a Track Simulator including both conventional and TCS equipment, a Driver Desk, a European Vital Computer and a Driver MMI. The components are modelled using software-based simulations hosted on networked PCs. The simulator has been valuable in the engineering evaluation and validation of emergent system architectures, and enables system constraints to be explored and defined. ERTMS operational modes and the transitions between them are simulated and ERTMS principles and procedures are followed. Innovative Customer Information System (ICIS) SEA's Innovative Customer Information System (ICIS) is capable of managing and displaying customer information, including real time information, in a visually dynamic manner. The system utilises intelligent screens and wireless technology to distribute data, thus minimising installation and commissioning efforts. The system will be suitable for any transport environment, mobile...
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