...Time series analysis We are pleased to submit the following report on the “Time Series Analysis”. By completing the report, we have got acquainted importance and relevance of time series on business application. We also perceived idea on the whole process of Time Series Analysis. We acquired knowledge about the method of measuring trend, growth rate, acceleration rate etc. In spite of limitation of time & opportunity we have tried our level best to complete the report. We are pleased to provide you with this report with necessary analysis, references and we shall be available for any clarification, if required. Thank you for assigning us in this study. On behalf of the group Md. Arif Hasan ID: 12-150 Table of Contents Serial No Topic Page No 1 Letter of Transmittal 1 2 Rationale of the study 2 3 Objectives of the report 3 4 Methodology of the report 3 5 What is Time Series 4 6 Uses of Time Series in Business 5 7 Components of a Time Series 5 8 Classical Time Series Model 9 9 Methods of trend measurement 9 10 Least squares method 10 11 The Growth Rate 14 12 The Acceleration Rate 15 13 Rule of 72 16 14 Bibliography 17 Rationale of the study Having been assigned to prepare a report on Time Series Analysis we are submitting the term paper based on our findings and understandings. Time series analysis has vast application and is of huge importance in the field of Business and Economics as well as in decision making thereof. Calculating secular trend we can...
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...ON TIME SERIES ANALYSIS PLANNING AND CONTROL OF OPERATONS FAWAZ MOHAMED KUTTY 215112035 MBA Ist YEAR TIME SERIES ANALYSIS A time series may be defined as a set of values of a variable collected and recorded in a chronological order of the time intervals. Time series is used by statisticians to describe the flow of economic activity. In short time series refers to the data depending on time. It refers to a set of observations concerning any activity against different periods of time. The duration of the time period may be hourly, daily, weekly, monthly or yearly. According to Morris Hamburg “A time series is a set of statistical observations arranged in chronological order”. Therefore time series is also called historical data or historical series. The study of movement of quantitative data through time is referred to as ‘time series analysis’. Time series is of great importance to the planners of economic development and economists. The success of planning depends upon making accurate forecasts of future conditions of economy. It enables the economists to foresee what is likely to come and to analyze the repercussions of past behavior. The analysis of time series enables us to understand the past behavior or performance. Time series analysis can be used to know how the data changes over time and find out probable reasons for such change. UTILITY OF TIME SERIES ANALYSIS Analysis of time series is of relevance whenever a variable is found to vary over time. Variable...
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...Time Series Analysis Yt=observed value of the time series in time period t TRt=the trend component or factorin time period t SNt=the seasonal componentor factorin time period t CLt=the cyclical componentor factorin time period t IRt=the irregular componentor factorin time period t 7.1) CL*IRCL=IR a) SN1=1.191 TR1=240.5 CL1=null IRt=null SN2=1.521 TR2=260.4 CL2=0.998 IR2=0.990 SN3=0.804 TR3=280.4 CL3=0.994 IR3=0.986 SN4=0.484 TR4=300.3 CL4=1.003 IR4=1.008 b) It presents a multiplicative decomposition model Yt=TRt*SNt*CLt*IRt SNt*IRt=YtTRt CLt snt*irt=YtCMAt =YtCMAt Equation of the estimated trend: TRt=Bo+B1t dt=B0+B1t+εt TRt=220.53+19.94(t) c) Yt=trt*snt Y17=220.53+19.9417*1.191=666.6 Y18=220.53+19.9418*1.521=881.6 Y19=220.53+19.9419*0.804=482.1 Y20=220.53+19.9420*0.484=299.9 d) Yt=trt*snt*cl We cannot see a definitive cycle and because the values of cl are close to 1. We do not take it into account. Y21=220.53+19.9421*0.191=761.6 e) Since there are just four years of data and most values are near 1 we cannot discern a well-defined cycle. f) Y21=220.53+19.9421*0.191=761.6 It agrees with the values computed in part c g) Excel Spreadsheet h) Prediction intervals for the next 4 quarters t=17,18,19,20 t=17:654.094,679.542 t=18:869.038,894.542 t=19:469.107,494.556 t=20:286.977,312.426 8.1) Smoothing equation l0=t=1nYtn Which is the average of the first series values lT=αyT+(1-α)lT-1 α:smoothing constant ...
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...REPORT ON TIME SERIES ANALYSIS REPORT ON TIME SERIES ANALYSIS SUBMITTED TO M. KHAIRUL HOSSAIN PROFESSOR Department Of Finance University Of Dhaka SUBMITTED BY Group – 17 Section-A BBA 12th Batch Department Of Finance WE ARE... |Sl. No |Name |Roll No | |1. |Dulal Paul |12-143 | |2. |Rahat Hussain Md. Zaidy |12-149 | |3. |MD. Arif Hasan |12-150 | |4. |MD. Khurshid Alam |12-170 | |5. |MD. Saiful Islam |12-254 | Letter of Transmittal Date: 16th September, 2008 M. Khairul Hossain Professor Department Of Finance Faculty of Business Studies University of Dhaka Subject: Submission of report We are pleased to submit the following report on the “Time Series Analysis”. By completing the report, we have got acquainted importance and relevance of time series on business application. We also perceived idea on the whole process of Time Series Analysis. We acquired knowledge about the method...
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...Time Series Analysis Summary Tokelo Khalema 2008060978 BSc. Actuarial Science University of the Free State Bloemfontein November 1, 2012 Time Series Analysis A time-series is a stochastic process {Xt : t = 1, . . . , T } with a continous state space and discrete time domain. It arises naturally as an ordered series of values observed over time. Examples include daily closing prices of a stock index recorded over several years, say, the flow rate of the River Nile, road casualties in Great Britain over the years 1969-84, etc. Stationary time-series are particularly easy to analyse. A series is stationary if its mean and variance are constant over time. Special aids are available to help determine whether or not a series is stationary. Particularly notable in this regard are the autocorrelation function (ACF) and the partial autocorrelation function (PACF). These are plots of the sample autocorrelation and partial autocorrelation coefficients at various time lags, respectively. If the ACF decays gradually to zero, then the series is non-stationary. If on the other hand the ACF and PACF decay rapidly to zero, then the series is stationary. A series being non-stationary can be brought about by, among others, a trend, irregular fluctuations, or seasonal variation. Non-constant variance, or as commonly called, heteroscedasticity can be eliminated by using a variance-stabilising transformation. A number of ways exist that eliminate a trend. Two of which are, to subtract a regression line...
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...A Time Series Forecasting Analysis on the Monthly Stocks of Rice in the Philippines A Research Paper Presented To Dr. Cesar Rufino Of the Department of Economics School of Economics De La Salle University, Manila In Partial Fulfillment of the Course Requirements in Economic Forecasting (ECOFORE) Term 3 AY 2014-2015 Submitted by: Jayme, Kevin Matthew D. April 24 2015 0 I. Introduction The Philippines has been the accredited as an agricultural nation that provides different types of agricultural related goods, both for the domestic and international market. Rice has been the staple food in the Philippine to 80% of the population as it is customary diet that has been in beaded in the Philippine culture (Drilon Jr., 2012). Despite the strong history of agriculture and the skills and weather condition perfect for growth of rice, decrease of land and increase of total population around the Philippines decrease the opportunity for the population to have access to rice. In addition, neighboring countries, such as Thailand and Vietnam, had been on the rise of rice exportation. Not to mention the implementation of the ASEAN integration is happening in 2015. This means that the Philippines is lagging behind as it is the 8th largest exporters of rice in the world (Tiongco & Francisco, 2011). Institution, such as International Rice Research Institute (IRRI), has gone into research and development of rice growth in different conditions and situation...
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...I. Goal The aim of this project is to analyze the output of the Transit Time System and recommend changes to improve the reliability of its estimates. II. Background By the current definition, Transit Time (TT) is the number of hours it takes for a package to get delivered to the customer from the moment it was tendered at the FC. It excludes the non-processing time (e.g. weekends) of the carriers. (Refer Appendix IIA for an example of UPS transit times from LEX1) Transit Times are used to predict whether a given ship method can meet a given promise to the customer. Also, inconsistencies in measured/estimated transit times may expose issues or opportunities in the shipping processes. Transit Time is a function of a 3-tuple: (source, ship method,...
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...Part I Task 1 Type of Property: Bungalow Location: Taman Tun Dr. Ismail, Kuala Lumpur |Number |Square Feet |Price (RM'000) | |1 |4500 |3280 | |2 |4800 |4180 | |3 |4500 |3300 | |4 |4500 |3300 | |5 |5000 |4100 | |6 |5000 |4700 | |7 |4000 |3300 | |8 |5000 |5000 | |9 |4352 |4000 | |10 |4000 |3300 | |11 |4000 |4000 | |12 |7000 |7800 | |13 |4352 |4000 | |14 |4300 |3280 | |15 |4000 |4300 | |16 |3800 |4500 | |17 |7000 |7800 | |18 |5000 |4700 | |19 |5650 |2600 | |20 |5000 |3880 | |21 |6000 |4180 | |22 |5200...
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...“The Time Machine” is a science fiction novel by H. G. Wells, published in 1895. This novel has revolutionized the concept of using a vehicle to time travel. It was written in a time where industrialization was booming, new technological advances were being discovered, people constantly debated about capitalism and communism, and the theory of “Social Darwinism” was being viciously applied. To summarize the novel, a Victorian scientist is determined to prove his theory that there is a fourth dimension, which is time. And like the other three dimensions (space), you can move forward and backward. To demonstrate this, he builds a time machine and travels to the future, where he encounters the Eloi, and describes them as pale and weak physically...
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...CHAPTER 5. EMPIRICAL RESULTS, FINDINGS AND ANALYSIS 1. Over all graphical analysis For any index the best way to gauge its long term movement is to plot its movement over a period of time. So here to start with the analysis part , first the overall movement of the daily “close” data for S&P CNX NIFTY FIFTY is examined for the period starting from 2nd May 2002 till 3rd Feb 2012. There are in total 2347 observations and the econometric package EViews 7 has been used to track the movement. The plot is shown in Fig No 5.1. [pic] Fig No 5.1. Daily movement of Nifty Fifty “close” during 02/05/2002 – 03/02/2012 From the graph it is clear that Nifty has shown an upward trend over the period of time. While the upward trend is pretty evident from 2002 to 2007 however since 2007 Nifty movement has been somewhat unstable due to frequent market fluctuation and thus the market seems to be more volatile during this period. In terms of volatility another aspect is visible from the graph that is an upward trend is being followed by further upward trend while a downward trend is being followed by further downward trend and this feature is known as “volatility clustering” and this volatility clustering seems to be present in the index. More about the volatility and the movement of the index will be explored in the further subsections where the task of comparing Nifty movement at times is being taken. 2. Over all statistics The performance of Nifty over the years is tabulated...
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...slump, government excise taxes and other factors such as decreased numbers in both tourist arrivals to the Caribbean island and beer exports to the U.S. As purchasing manager, Benson’s prime responsibility was maintaining adequate inventory levels for all goods and materials used in the company’s production processes, including the purchase of new bottles and the scheduling of deliveries (Erskine, 2004). State the Assignment Question As purchasing manager, Benson was responsible for all goods and materials used in the company’s production process, inclusive of new bottles purchase. Benson had to be cognizant of the fact that orders for new bottles had to be ordered four months in advance to allow for supplier transportation and lead times....
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...Forecasting Project House Sales in USA Presented by: Michelle Deets Ravin Seju Ankan Sinha March 7, 2016 Professor Dawit Zerom ISDS 526 Executive Summary The data in the report “Monthly total houses sold in the United States for the period January 1978 through July 2007” is time series data representing sales in thousands of units. The data has not been seasonally adjusted. Our project was to produce forecasts of housing sales by creating a model using Forecast Pro’s Expert Selection Method. The model was generated by withholding 2 years of data and creating a forecast based upon the data from January 1978 to July 2005. We provided fit measures based upon MAPE and RMSE and evaluated the model’s accuracy MAPE, RMSE, and GMRAE from Forecast Pro’s out-of-sample statistic evaluation table. The MAPE numbers show that the forecast expands from a 7.95% error at the beginning of the holdout period and quickly grows to 32% error within 24 months. The acceptability of this error depends upon which managers are using it. The housing industry touches many fields, from moving to painting to construction to land purchases. This large of an error might could be unacceptable given the amount of risk and resources involved in construction of new single family homes; a manager might prefer to only use the first 6 months of forecasted data to stay within a 10% error range. Looking at the results of the forecast’s graph, the actual data (Exhibit A, represented by the...
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...c t Behavioral economics tells us that emotions can profoundly affect individual behavior and decisionmaking. Does this also apply to societies at large, i.e. can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from largescale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time. We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs. negative mood and Google-Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). We cross-validate the resulting mood time series by comparing their ability to detect the public’s response to the presidential election and Thanksgiving day in 2008. A Granger causality analysis and a Self-Organizing Fuzzy Neural Network are then used to investigate the hypothesis that public mood states, as measured...
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...ISCOM 471 December 24, 2012 Planning and Controlling the Supply Chain Within the many different organizations in todays business world there are some key factors that will establish the profitability, growth, and longevity of a company. Some of the things we will discuss will be that of how my chosen corporation American Express applies some of the forecasting techniques to better develop the company. There will also be the analysis of production plans, master production schedules, and carrying inventory and how it relates to the overall American Express budget. Along with all the above we will also compare and contrast how planning usage differentiates between a service organization such as American Express and a manufacturing organization. Lastly we will also compare and contrast the use of material requirements planning system concepts. When it comes to forecasting it is first important to determine the different types of forecasting and how they are classified. In forecasting there are four basic types which are qualitative, time series analysis, casual relationship, and simulation. The first forecasting type qualitative is "subjective or judgmental and are based on estimates and opinions", (Chase, Jacobs, & Aquilano, 2006). Some of the main characteristics of qualitative forecasting are market research which is encompassed by collecting data by surveys and interviews which help determine market hypothesis. This research is most commonly used for long range and new...
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...students of Bachelor of Sciences (Hons) (Statistics), Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) are required to undergo the industrial training. The students will be placed in the government or private organizations of their choice for a period of three months, during which they are also required to design a research project. The following one month will be allocated for data analysis, report writing and oral presentation. This training is very beneficial and important to expose students to the various aspects of industrial practices and ethics. The students are also able to apply the theories and knowledge that they have learned to the projects assigned to them. 1.2 OBJECTIVES OF INDUSTRIAL TRAINING The objectives of the industrial training are: ❖ To expose students to the real working environment ❖ To train students being familiar with the organization structure, operations, and administration. ❖ To acquire real experience in solving research problems and apply appropriate statistical data analysis. ❖ To enable students to integrate the theory learned at UiTM with practice. ❖ To cultivate cooperative networking between industries and UiTM 1.3 INDUSTRIAL TRAINING ATTACHMENT I had undergone my industrial training at Socio Economic and Environmental Research Institute (SERI) at Penang from 3rd January 2011 until 31st March 2011. I was directly supervised by Dr Chan Huang Chian and Ms Ong Wooi...
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