• Title/Summary/Keyword: Sales Forecast

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The Accuracy of Various Value Drivers of Price Multiple Method in Determining Equity Price

  • YOOYANYONG, Pisal;SUWANRAGSA, Issara;TANGJITPROM, Nopphon
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.1
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    • pp.29-36
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    • 2020
  • Stock price multiple is one of the most well-known equity valuation technique used to forecast equity price. It measures by multiplying "the ratio of stock price to a value driver" by a value driver. The value driver can be earning per share (EPS), sales or other financial measurements. The objective of price multiple technique is to evaluate the value of assets and compare how similar assets are priced in the market. Although stock price multiple technique is common in financial filed, studies on the application of the technique in Thailand is still limited. The present study is conducted to serve three major objectives. The first objective is to apply the technique to measure value of firms in banking sector in the Stock Exchange of Thailand. The second objective is to develop composite price multiple index to forecast equity prices. The third objective is to compare valuation accuracy of different value drivers of price multiple (i.e. EPS, Earnings Growth, Earnings Before Interest Taxes Depreciation and Amortization, Sales, Book Value and Composite Index) in forecasting equity prices. Results indicated that EPS is the most accurate value drivers of price multiple used to forecast equity price of firms in baking sector.

Economic Value Analysis of Asian Dust Forecasts Using Decision Tree-Focused on Medicine Inventory Management (의사결정트리를 활용한 황사예보의 경제적 가치 분석-의약품 재고관리문제를 중심으로)

  • Yoon, Seung-Chul;Lee, Ki-Kwang
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.1
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    • pp.120-126
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    • 2014
  • This paper deals with the economic value analysis of meteorological forecasts for a hypothetical inventory decision-making situation in the pharmaceutical industry. The value of Asian dust (AD) forecasts is assessed in terms of the expected value of profits by using a decision tree, which is transformed from the specific payoff structure. The forecast user is assumed to determine the inventory level by considering base profit, inventory cost, and lost sales cost. We estimate the information value of AD forecasts by comparing the two cases of decision-making with or without the AD forecast. The proposed method is verified for the real data of AD forecasts and events in Seoul during the period 2004~2008. The results indicate that AD forecasts can provide the forecast users with benefits, which have various ranges of values according to the relative rate of inventory and lost sales cost.

Movie attendance and sales forecast model through big data analysis (빅데이터 분석을 통한 영화 관객수, 매출액 예측 모델)

  • Lee, Eung-hwan;Yu, Jong-Pil
    • The Journal of Bigdata
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    • v.4 no.2
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    • pp.185-194
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    • 2019
  • In the 100-year history of Korean films, Korean films have grown to more than 100 million viewers every year since 2012, and their total sales are estimated at 1 trillion. It is assumed that the influence on the popularity of Korean movies is related to 2012, when 60% of smartphone penetration rate and 30 million subscribers exceeded. As a result, before and after 2012, changes in movie boxing factor variables were needed, and the prediction model trained as a new independent variable was applied to actual data.

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An Empirical Study of Financial Analyst's Forecasting Activities on the Firm's Operating Performances (기업실적에 대한 재무분석가의 예측활동에 관한 실증연구)

  • Kwak, Jae-Seok
    • The Korean Journal of Financial Management
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    • v.20 no.1
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    • pp.93-124
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    • 2003
  • This paper studies the financial analyst's forecasting activities on the firm's operating performance during the period from 1999 to 2003. In this study, financial analyst's forecasting activities are focused on the sales, operating income and net income and financial analyst's forecasting accuracy, forecasting revising patterns and forecasting activities to the unexpected firm's operating performance are studied. Some empirical findings in this study are as follows. First, standard estimate error on the sales, operating income and net income are all significantly negative value and so financial analyst's forecast on the firm's operating performance are upwardly biased. Second, domestic financial analyst's forecasting activities is relatively more accuracy than foreign financial analyst's forecasting activities. Third, forecasting time is more close to the end of the operating performance announcement day, forecasting activities are more accuracy. Fourth, comparing with individual financial analyst's forecast, consensus forecast is more accuracy. Fifth, in the comparative forecasting activities study according to the prior firm's operating performance, financial analyst's forecasting revision activities are found to be upward or downward. Sixth, financial analysts overreact in the sales forecast and underreact in the operating income and net income forecast. Seventh, in the empirical analysis on the Easterwood-Nutt's test model(1999) which the firm's performance change are divided into the expected performance change and the unexpected performance change, it is found that financial analyst's forecasting activities on the firm's operating performance are systematically optimistic.

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Accuracy Improvement in Demand Forecast of District Heating by Accounting for Heat Sales Information (열판매 정보를 고려한 지역난방 수요 예측의 정확도 향상)

  • Shin, Yong-Gyun;Yoo, Hoseon
    • Plant Journal
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    • v.15 no.1
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    • pp.31-37
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    • 2019
  • In this study, to improve the accuracy of forecast of heat demand in the district heating system, this study applied heat demand performance among the main factors of district heating demand forecast in Pankyo area as the heat sales information of the user facility instead of existing heat source facility heat supply information, and compared the existing method with the accuracy based on the actual value. As a result of comparing the difference of the forecasts values of the existing and changed methods based on the performance values over the one week (2018.01.08 ~ 01.14) during the hot water peak, the relative error decreased from 7% to 3% The relative error between the existing and revised forecasts was 9% and 4%, respectively, for the five-month cumulative heat demand from February to February 2018, Also, in case of the weekend where the demand of heat is differentiated, the relative error of the forecasts value is consistently reduced from 10% to 5%.

Data Science and Machine Learning Approach to Improve E-Commerce Sales Performance on Social Web

  • Hussain Saleem;Khalid Bin Muhammad;Altaf H. Nizamani;Samina Saleem;M. Khawaja Shaiq Uddin;Syed Habib-ur-Rehman;Amin Lalani;Ali Muhammad Aslam
    • International Journal of Computer Science & Network Security
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    • v.23 no.8
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    • pp.137-145
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    • 2023
  • E-Commerce is a buzzword well known for electronic commerce activities including but not limited to the online shopping, digital payment transactions, and B2B online trading. In today's digital age, e-commerce has been playing a very important and vital role in areas such as retail shopping, sales automation, supply chain management, marketing and advertisement, and payment services. With a huge amount of data been collected from various e-commerce services available, there are multiple opportunities to use that data to analyze graphs and trends. Strategize profitable activities, and forecast future trade. This paper explains a contemporary approach for collecting key data metrics and implementing cost-effective automation that will support in improving conversion rates and sales performance of the e-commerce websites resulting in increased profitability.

Design and Implementation of Marketing and Sales Information System for Automotive Part Company Using Object-Oriented Methodology (객체지향 방법론을 이용한 자동차부품기업의 영업관리시스템 설계 및 구현)

  • Kang Sung-bae;Moon Tae-Soo
    • The Journal of Information Systems
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    • v.13 no.1
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    • pp.77-95
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    • 2004
  • According to the increase of organizational complexity and the change of rapid information technology environment, many firms have shifted their information technology(IT) strategy from developing information systems in-house to purchasing application software such as Enterprise Resource Planning(ERP) Systems. Marketing and Sales functions within a Korean automotive part company include developing new assembly products, determining pricing, taking customer's orders, and shipping assembly products to customers. Marketing and Sales Information System(MSIS) in ERP system plays an important role in next Production Planning process. MSIS also makes management reporting and decision making faster and more uniform throughout an organization. MSIS promotes thinking about corporate goals, as opposed to thinking only about the goals of a single department or functional area. This paper intends to design and implement a MSIS in ERP systems for Korean automotive part company using object-oriented methodology In order to accomplish the implementation of MSIS in ERP system, we employed UML as its standard modeling language. In this study, four diagramming techniques such as use case diagram, sequence diagram, class diagram, component diagram among eight modeling techniques are used for analyzing hierarchical business process. In traditional marketing and sales function, a company with an unintegrated information system can have marketing and sales data that is data redundant or inaccurate. MSIS integrated in ERP system can solve the sales forecast problem, which minimizes the total costs of production, inventory, and transportation under constraints of production capacity. Also, the use of UML methodology makes S/W programmers shorten the phase of analysis and design in the implementation of MSIS system, and increase the reuse of software and the interoperability with corporate internal Information system.

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Analysis of Automobile Industry Trends and Demand Forecasting of Monthly Automobile Sales in Chin (중국 내 자동차 산업 동향과 월별 판매량 시계열분석)

  • Chenyang, Wang;Se Won, Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.1
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    • pp.35-48
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    • 2023
  • In this study, we introduced the development status and the government policy of the Chinese automobile industry under the rapidly changing global economic environment. We conducted a consumer trend survey on automobile purchases by consumers in China. Despite the Chinese government's strong national emission control policy and stricter standards for manufacturing and selling internal combustion engine vehicles, 59.6% of respondents saying they would choose an internal combustion engine vehicle when purchasing a vehicle in the future for various reasons. It was confirmed that there is a significant gap between government policies and consumer perceptions. In addition, we have discovered the recent declining trend of automobile sales in China, and used the monthly sales volume from January 2010 to December 2020 as training set, and the sales volume from January 2021 to November 2022 as a test set. We proposed and evaluated a time-series model for predicting future automobile demand in China. Then, we showed the monthly sales forecast for 2023 when each model was applied.

Forecasting the Evolution of Innovation Considering Consumers' Choice : An Application of Home-Networking Market in Korea (소비자 선택을 고려한 신기술 혁신의 확산 예측: 한국의 홈네트워킹 시장을 대상으로)

  • Lee, Cheol-Yong;Lee, Jeong-Dong;Kim, Yeon-Bae
    • Journal of Technology Innovation
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    • v.13 no.1
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    • pp.1-24
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    • 2005
  • This paper applies a prelaunch forecasting model to the Home-Networking (HN) market of South Korea. The HN market of Korea is categorized into two distinctive markets. One HN market consists of new apartments in which builders install HN and the other HN market consists of existing houses in which residents purchase HN Among these markets, this paper focuses on existing houses as capturing consumers' choice. To forecast sales of HN for existing houses, we use a conjoint model based on our survey data of consumer preferences. By incorporating various indicators of HN technologies into our conjoint model, we also forecast diffusion of HN system embodied in PLC or Wireless Lan. We call this model Choice-Based Diffusion Model. In addition, based on the simulation experiments, we also identify important factors that affect the demands of HN system.

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