• Title/Summary/Keyword: Price Control

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The Role of Accounting Professionals and Stock Price Delay

  • RYU, Haeyoung;CHAE, Soo-Joon
    • The Journal of Industrial Distribution & Business
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    • v.11 no.12
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    • pp.39-45
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    • 2020
  • Purpose: The stock price delay phenomenon refers to a phenomenon in which stock prices do not immediately reflect corporate information and the reflection is delayed. A prior study reported that the stock price delay phenomenon appears strongly when the quality of corporate information is low (Callen, Khan, & Lu, 2013). The purpose of the internal accounting control system is to improve the reliability of accounting information. Specifically, the more professionals such as certified public accountants are placed in the internal accounting control system, the more information is prevented from being distorted, so the occurrence of stock price delay will decrease. Research design, data and methodology: In this study, companies listed on the securities market from 2012 to 2016 were selected as a sample to analyze whether the stock price delay phenomenon is alleviated as accounting experts are assigned to the internal accounting control system. The internal control personnel data were collected in the "Internal Accounting Control System Operation Report" attached to the business report of each company of the Financial Supervisory Service's Electronic Disclosure System(DART). The measurement method of the stock price delay phenomenon was referred to the study of Hou and Moskowitz (2005). The final sample used in the study is 2,641 firm-years. Results: It was found that companies with certified accountants in the internal accounting control system alleviate the stock price delay phenomenon. This result can be interpreted as increasing the speed at which corporate information is reflected in the stock price by improving the reliability of information disclosed in the market by the placement of experts in the system. Conclusions: The results of this study suggest that accounting professionals assigned to the internal accounting control system are playing a positive role in providing high-quality information to the market. In this study, focusing on the fact that the speed at which corporate information is reflected in the stock price is very important for the stakeholders in the capital market, we find that having a certified public accountant in the internal accounting control system alleviates the stock price delay phenomenon.

An Experimental Study on the Price Discrimination on the Internet: The Effect of Illusion of Control and Lateral Customer Relationship on Price Fairness (인터넷의 다이나믹 프라이싱 구매방식에서의 가격차별화에 대한 구매자의 가격공정성 인지에 관한 연구)

  • Lee, Zoon-Ky;Lee, Ji-Hae
    • Journal of Information Technology Services
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    • v.6 no.2
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    • pp.19-33
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    • 2007
  • The current advance of IT and the e-commerce triggers the wide practice of dynamic pricing in all industries although the price discrimination has been very cautiously applied in the limited areas in the past. The price discrimination which offers different prices for each customer depending on their preference and buying behaviors has recently gained attention as it could provide superior benefits to sellers. The wide adoption of price discrimination, on the other hand, is reported to face buyer resistances and complaints. Our limited understanding on the perception of price fairness, which we think is key concept in the price discrimination on the Internet-enabled transactions, motives us to investigate factors that affect the perception of price fairness. This study focuses on illusion of control and lateral customer relationship to investigate their effects on price fairness in online auction and group purchase context. By conducting laboratory experiments, our study demonstrates that customers' perception on illusion of control in price determination and advantageous lateral customer relationship significantly affect price fairness perception in both online auction and group purchase environment. The findings are expected to provide researchers and managers with useful insights to develop better pricing strategies and design effective dynamic pricing mechanisms.

House Rent Control System and Its Implementation in France (프랑스 주택 임대료 규제 및 관련 제도 연구)

  • Lee, Seong-Keun;Choi, Min-Ah
    • Land and Housing Review
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    • v.9 no.4
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    • pp.1-9
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    • 2018
  • Since year 2000, French housing and rent prices rose at a rapid rate and the housing market has been overheated. Face to this phenomena, the French government enacted a new law Alur which is a legislatif tool to control the private housing rent price for the cities, where the tension of the housing market is very high. This new law has impacted the housing market in two major ways. First, for the 38 cities designated by this law, the rent price's increase rate can not rise above the IRL, which is the rent reference index. Secondly, this law also permits local authorities to control the housing rent's price following the concrete price guidance. Especially in Paris, the city applicated this method for private rental housing since 2015. This city classified its own area by 14 zones. Based on the market surveys of each sector, local authority made a guidance for private housing rent's price. The guideline is consisted of average prices, maxima and minima price by types, which is classified by the construction year, number of rooms and furnished or not. Therefore, this study aims to understand french housing rent's price control system and draw implementation for korean housing rent policies. This research is meaningful for it introduces recent foreign regislations which could be helpful to control the housing market in Korea.

Demand Control Application Strategies for Saving Electric Power Price of Central Cooling System (중앙 냉방시스템의 전력량 요금절감을 위한 디맨드제어 적용방안 연구)

  • Hwang, Jin-Won;Song, Jae-Yeob;Ahn, Byung-Cheon
    • Journal of the Korean Society for Geothermal and Hydrothermal Energy
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    • v.8 no.4
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    • pp.1-7
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    • 2012
  • In this study, computer simulation for demand control strategies to save the electric energy and power price in the building central cooling system is done. The demand control and outdoor reset control algorithms are applied by consideration the electric energy and power price according to the energy consumption characteristics. The suggested control methods show better responses in the power price and energy consumption in comparison with the conventional one.

The working experience of internal control personnel and crash risk

  • RYU, Hae-Young;CHAE, Soo-Joon
    • The Journal of Industrial Distribution & Business
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    • v.10 no.12
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    • pp.35-42
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    • 2019
  • Purpose : This study examines The impact of human resource investment in internal control on stock price crash risk. Effective internal control ensures that information provided is complete and accurate, financial statements are reliable. By overseeing management, internal control systems can reduce agency costs between management and outside parties. In Korea, firms have to disclose information about internal control systems. The working experience of human resources in internal control systems is also provided for interested parties. If a firm hires more experienced internal control personnel, it can better facilitate the disclosure of information. Prior studies reported that information asymmetry between managers and investors increases future stock price crash risk. Therefore, the longer working experience internal control personnel have, the lower probability stock crashes have. Research design, data and methodology : This study analyzed the association between the working experience of internal control personnel and crash risk using regression analysis on KOSPI listed companies for fiscal years 2016 through 2017. The sample consists of 1,034 firm-years of non-financial firms whose fiscal year end on December 31. Career spanning data of internal control personnel was collected from internal control reports. The professionalism(IC_EXP) was measured as the logarithm of the average working experience of internal control personnel in months. Negative conditional skewness(NSKEW) and down-to-up volatility (DUVOL) are used to measure firm-specific crash risk. Both measures are based on firm-specific weekly returns derived from the expanded market model. Results : We find that work experience in internal control environment is negatively related to stock price crashes. Specifically, skewness(NSKEW) and volatility (DUVOL) are reduced when firms have longer tenure of human resources in internal control division. The results imply that firms with experienced internal control personnel are less likely to experience stock price crashes. Conclusions : Stock price crashes occur when investors realize that stock prices have been inflated due to information asymmetry. There is a learning effect when internal control processes are done repetitively. Thus, firms with more experienced internal control personnel could manage their internal control more effectively. The results of this study suggest that firms could decrease information asymmetry by investing in human resources for their internal control system.

Using Neural Networks to Forecast Price in Competitive Power Markets

  • Sedaghati, Alireza
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.271-274
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    • 2005
  • Under competitive power markets, various long-term and short-term contracts based on spot price are used by producers and consumers. So an accurate forecasting for spot price allow market participants to develop bidding strategies in order to maximize their benefit. Artificial Neural Network is a powerful method in forecasting problem. In this paper we used Radial Basis Function(RBF) network to forecast spot price. To learn ANN, in addition to price history, we used some other effective inputs such as load level, fuel price, generation and transmission facilities situation. Results indicate that this forecasting method is accurate and useful.

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The Effect of Control-Ownership Wedge on Stock Price Crash Risk (소유지배 괴리도가 주가급락위험에 미치는 영향)

  • Chae, Soo-Joon;Ryu, Hae-Young
    • The Journal of Industrial Distribution & Business
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    • v.9 no.7
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    • pp.53-59
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    • 2018
  • Purpose - This study examines the effect of control-ownership wedge on stock crash risk. In Korea, controlling shareholders have exclusive control rights compared to their cash flow rights. With increasing disparity, controlling shareholders abuse their power and extract private benefits at the expense of the minority shareholders. Managers who are controlling shareholders of the companies tend not to disclose critical information that would prevent them from pursuing private interests. They accumulate negative information in the firm. When the accumulated bad news crosses a tipping point, it will be suddenly released to the market at once, resulting in an abrupt decline in stock prices. We predict that stock price crash likelihood due to information opaqueness increases as the wedge increases. Research design, data, and methodology - 831 KOSPI-listed firm-year observations are from KisValue database from 2005 to 2011. Control-ownership wedge is measured as the ratio (UCO -UCF)/UCO where UCF(UCO) is the ultimate cash-flow(control) rights of the largest controlling shareholder. Dependent variable CRASH is a dummy variable that equals one if the firm has at least 1 crash week during a year, and zero otherwise. Logistic regression is used to examine the relationship between control-ownership wedge and stock price crash risk. Results - Using a sample of KOSPI-listed firms in KisValue database for the period 2005-2011, we find that stock price crash risk increases as the disparity increases. Specifically, we find that the coefficient of WEDGE is significantly positive, supporting our prediction. The result implies that as controlling shareholders' ownership increases, controlling shareholders tend to withhold bad news. Conclusions - Our results show that agency problems arising from the divergence between control rights and cash flow rights increase the opaqueness of accounting information. Eventually, the accumulated bad news is released all at once, leading to stock price crashes. It could be seen that companies with high control-ownership wedge are likely to experience future stock price crashes. Our study is related to a broader literature that examined the effect of the control-ownership wedge on stock markets. Our findings suggest that the disparity is a meaningful predictor for future stock price crash risk. The results are expected to provide useful implications for firms, regulators, and investors.

The Effect of Corporate Integrity on Stock Price Crash Risk

  • YIN, Hong;ZHANG, Ruonan
    • Asian Journal of Business Environment
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    • v.10 no.1
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    • pp.19-28
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    • 2020
  • Purpose: This research aims to investigate the impact of corporate integrity on stock price crash risk. Research design, data, and methodology: Taking 1419 firms listed in Shenzhen Stock Exchange in China as a sample, this paper empirically analyzed the relationship between corporate integrity and stock price crash risk. The main integrity data was hand-collected from Shenzhen Stock Exchange Website. Other financial data was collected from CSMAR Database. Results: Findings show that corporate integrity can significantly decrease stock price crash risk. After changing the selection of samples, model estimation methods and the proxy variable of stock price crash risk, the conclusion is still valid. Further research shows that the relationship between corporate integrity and stock price crash risk is only found in firms with weak internal control and firms in poor legal system areas. Conclusions: Results of the study suggest that corporate integrity has a significant influence on behaviors of managers. Business ethics reduces the likelihood of managers to overstate financial performance and hide bad news, which leads to the low likelihood of future stock price crashes. Meanwhile, corporate integrity can supplement internal control and legal system in decreasing stock price crash risks.

Call Admission Control Algorithm Based on Dynamic-Price in Communication Networks (통신망에서의 동적 과금 기반의 호수락 제어 알고리즘)

  • Gong, Seong-Lyong;Lee, Jang-Won
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.163-164
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    • 2008
  • In this paper, we study a dynamic price-based call admission control algorithm for communication networks. When a call arrives at the network, the network calculates the price for the call such that its expected revenue is maximized. The optimal price is dynamically adjusted based on some information of the call, and the congestion level of the network. If the call accept the price, it is admitted. Otherwise, it is rejected. Simulation results show that our dynamic pricing algorithm provides higher call admission ratio and lower price than the static algorithm [1][2], even though they provide almost the same revenue.

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Electricity Price Forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural Network Based Model

  • Aggarwal, Sanjeev Kumar;Saini, Lalit Mohan;Kumar, Ashwani
    • International Journal of Control, Automation, and Systems
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    • v.6 no.5
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    • pp.639-650
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    • 2008
  • Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.