• Title/Summary/Keyword: Revenue Forecast Uncertainty

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The Matching Principle, Earnings Persistence and Information Asymmetry (수익비용대응, 이익지속성 및 정보비대칭)

  • Lee, Kyu-Jin
    • The Journal of the Korea Contents Association
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    • v.19 no.5
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    • pp.280-286
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    • 2019
  • This study first examines whether the matching principle reduces information asymmetry and verifies the effect on earnings sustainability and information asymmetry. In the presence of information asymmetry between managers and information users, managers can reduce information asymmetry by increasing the quality of earnings. Information asymmetry is measured by the financial analysts' earnings forecast variance. When we look at the results of previous studies, verify whether information asymmetry decreases as the response to the revenue cost increases and whether negative relationship between profit persistence and information asymmetry appears when the response to the revenue cost is high. As a result, firms with high revenue cost response showed a decrease in information asymmetry. The persistence of the earningss from the high earnings-cost response shows that the analysts' earnings forecast dispersion decreases. This means that the better the response to the revenue cost, the better the quality of the earnings and the less the information risk about the uncertainty of the enterprise. This study is different from the previous studies in that it analyzed whether the persistence of the earnings that responded to the high revenue cost reduces the information asymmetry. The results of this study suggest that managers can reduce the information asymmetry by carrying out appropriate revenue - cost responses, which provides important implications for stakeholders who use accounting earnings information.

A Study on Early Termination Payment Option of BTO PPI Projects (BTO 민간투자사업 해지시지급금 매수청구권 가치에 관한 연구)

  • Shin, Sung-Hwan
    • Korean Journal of Construction Engineering and Management
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    • v.12 no.3
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    • pp.121-130
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    • 2011
  • Real option values of early termination payment for selected BTO PPI projects are studied using binomial models. Two cases of early termination payments are considered; an option with the condition of private participants' default, and an option without the condition. Values vary depending upon parameter values such as revenues, costs, discount rates, debt ratio, and volatility of revenues. For selected projects, the option values without the default condition are estimated as 1%~7% of total project costs, whereas the option values with the default condition are estimated as 0%~1.89% of total project cost. When actual revenues differ from the forecasted revenues, apparently the option values deviate from the values based upon the forecasted revenues. When actual revenues fall short of the forecasted revenues, the option values increase by a large amount whereas the option values decrease by a small amount in the opposite case. This implies that the option values can be quite bigger than the values based upon the forecasted revenue especially when the revenue forecast uncertainty is large. This study is expected to play an important role in improving the early termination payment option policy of the government in PPI projects in Korea.

Development of Model for Optimal Concession Period in PPPs Considering Traffic Risk (교통량 위험을 고려한 도로 민간투자사업 적정 관리운영기간 산정 모형 개발)

  • KU, Sukmo;LEE, Seungjae
    • Journal of Korean Society of Transportation
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    • v.34 no.5
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    • pp.421-436
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    • 2016
  • Public-Private-Partnerships tend to be committed high project development cost and recover the cost through future revenue during the operation period. In general, long-term concession can bring on more revenue to private investors, but short-term concession less revenue due to the short recovering opportunities. The concession period is usually determined by government in advance or by the private sectors's proposal although it is a very crucial factor for the PPPs. Accurate traffic forecasting should be most important in planing and evaluating the operation period in that the forecasted traffic determines the project revenue with user fees in PPPs. In this regards, governments and the private investors are required to consider the traffic forecast risk when determining concession period. This study proposed a model for the optimal concession period in the PPPs transportation projects. Monte Carlo simulation was performed to find out the optimal concession period while traffic forecast uncertainty is considered as a project risk under the expected return of the private sector. The simulation results showed that the optimal concession periods are 17 years and 21 years at 5.5% and 7% discount level, respectively. This study result can be applied for the private investors and/or any other concerned decision makers for PPPs projects to set up a more resonable concession period.

Application of Risk Management to Forecasting Transportation Demand by Delphi Technique (Delphi기법을 통한 교통수요예측 Risk Management 적용 방안)

  • Chung, Sung-Bong;Yi, Su-Ho;Namkung, Baek-Kyu
    • Proceedings of the KSR Conference
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    • 2011.05a
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    • pp.1572-1581
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    • 2011
  • Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment has been active on transport infrastructure. But investment of transport infrastructure has more risks than others due to overforecast of transport demand for ensuring project validity, and cost uncertainty arising from financial crisis, commodity prices and so on. In the case of Incheon international airport express, after 2 years and 6 months, Incheon international airport express is opened, Korail take over equity stake in private investor due to the problems of MRG(Minimum Revenue Guarantee) be contracted with private investor. Not only that, in other case of Yong-in light rail, it is ongoing for legal disputes between Yong-in local government and private investor on account of opening delaying. On current Investment Assessment System of Transport Infrastructure, Risk Management system on investment of transport infrastructure is inadequate because Sensitivity Analysis in economic efficiency have been performed on the simple method which only changes benefits, expense and social discount rate. For this reason, this study analyze risks for investment of transport infrastructure demand forecast, and rise to the management practice for every particular item.

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Valuing the Risks Created by Road Transport Demand Forecasting in PPP Projects (민간투자 도로사업의 교통수요 예측위험의 경제적 가치)

  • Kim, Kangsoo;Cho, Sungbin;Yang, Inseok
    • KDI Journal of Economic Policy
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    • v.35 no.4
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    • pp.31-61
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    • 2013
  • The purpose of this study is to calculate the economic value of transport demand forecasting risks in the road PPP project. Under the assumption that volatility of the road PPP project value occurs only in regard with uncertainty of traffic volume forecasting, this study calculates the economic value of the traffic forecasting risks in the case of the road PPP project. To that end, forecasted traffic volume is assumed to be a stochastic variable and to follow the Geometric Brownian motion as time passes. In particular, this study attempts to differentiate itself from existing studies that simply use an arbitrary assumption by presenting the application of different traffic volume growth volatility and the rates before and after the ramp-up period. Analysis of the case projects reveals that the risk premium related to traffic volume forecast of the project turns out as 7.39~8.30%, without considering option value-such as minimum revenue guarantee-while the project value volatility caused by transport demand forecasting risks is 17.11%. As the discount rate grows higher, the project value volatility tends to decrease and volatility in project value is always suggested to be larger than that in transport volume influenced by leverage effect due to fixed expenditure. The market value of transport demand forecasting risk-calculated using the project value volatility and risk premium-is analyzed to be between 0.42~0.50, implying that a 1% increase or decrease in the transport amount volatility would lead to a 0.42~0.50% increase or decrease in risk premium of the project.

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Prediction of a hit drama with a pattern analysis on early viewing ratings (초기 시청시간 패턴 분석을 통한 대흥행 드라마 예측)

  • Nam, Kihwan;Seong, Nohyoon
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.33-49
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    • 2018
  • The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.