Tracks

2002 ◽  
Vol 17 (3) ◽  
pp. 258-272 ◽  
Author(s):  
Laurence Blose ◽  
Marinus DeBruine ◽  
Parvez Sopariwala
Keyword(s):  
Stock Market ◽  
Market Price ◽  
Estimation Method ◽  
Economic Loss ◽  
General Motors ◽  
Management Literature ◽  
Recent Developments ◽  
Unused Capacity ◽  
June July ◽  
The Cost

The General Motors/UAW strike in June-July 1998 involved a 54-day work stoppage. General Motors and automobile analysts have attempted to quantify the loss from this strike and have come up with varied numbers. The stock market analysts' reactions to the strike, and consequently, the stock market price reaction, vary depending on which estimation method is employed. There is no real consensus among these various sources because their “economic loss” estimates rely on predictions of how many of the vehicles could not be produced and sold as a result of the strike (or recovered in future quarters). Using recent developments in the cost management literature, we determine the cost of unused capacity or the “accounting loss” suffered by General Motors during the second and third quarters of 1998. We show that General Motors may have lost about $2,332.7 million after taxes (excluding Delphi) due to the strike and an additional $1,313.8 million after taxes (excluding Delphi) due to capacity unused for other reasons. More importantly, such “accounting losses,” to the extent they are not strike-related, are expected to continue each year unless market conditions improve or the company takes action to reduce its capacity.

Stock Market Bellwether—General Motors

1962 ◽  
Vol 18 (6) ◽  
pp. 94-95
Author(s):  
B. Barret Griffith
Keyword(s):  
Stock Market ◽  
General Motors

Wage disparities between high and low wage cities with and without the cost of living within Punjab and Sindh: An application of Oaxaca-Blinder using PSLM with HIES

2020 ◽  
Vol 4 (4) ◽  
pp. 1-14
Author(s):  
Farrukh Mahmood ◽  
Shumaila Hashim ◽  
Uzma Iram ◽  
Muhammad Zubair Chishti
Keyword(s):  
Estimation Method ◽  
Living Standards ◽  
Wage Dispersion ◽  
Cost Of Living ◽  
Wage Policy ◽  
Essential Component ◽  
Sindh Province ◽  
Economic Survey ◽  
The Cost ◽  
Wage Disparities

Wage disparities research hardly incorporate for the cost of living differences due to data restriction, while the wage disparity issue is the crucial area of economist interest. The study aims to examine the wage disparities between high and low wage cities for Punjab and Sindh province of Pakistan with and without the cost of living, deploying the data of Pakistan Social and Living Standards Measurement Survey (PSLM) with Household Integrated Economic Survey (HIES) for 2005, 2007, 2010, and 2013. Applying the Oaxaca-Blinder estimation method, the findings infer that wage dispersion is high without the cost of living model for both provinces (Punjab and Sindh) as compared to with cost of the living model. Moreover, the results reveal that the wage dispersion is greater in Punjab province than Sindh province. For policymakers, our study suggests that the cost of living is an essential component of the wage dispersion in Pakistan’s cities; it should be considered while formulating for wage policy.

Share Market Data Prediction Strategies using Deep Learning Algorithm

2019 ◽  
Vol 13 ◽  
Author(s):  
A John. ◽  
D. Praveen Dominic ◽  
M. Adimoolam ◽  
N. M. Balamurugan
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Stock Market ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Market Price ◽  
Stochastic Gradient ◽  
Stochastic Gradient Descent ◽  
Mining Machine ◽  
Gradient Descent Algorithm

Background:: Predictive analytics has a multiplicity of statistical schemes from predictive modelling, data mining, machine learning. It scrutinizes present and chronological data to make predictions about expectations or if not unexplained measures. Most predictive models are used for business analytics to overcome loses and profit gaining. Predictive analytics is used to exploit the pattern in old and historical data. Objective: People used to follow some strategies for predicting stock value to invest in the more profit-gaining stocks and those strategies to search the stock market prices which are incorporated in some intelligent methods and tools. Such strategies will increase the investor’s profits and also minimize their risks. So prediction plays a vital role in stock market gaining and is also a very intricate and challenging process. Method: The proposed optimized strategies are the Deep Neural Network with Stochastic Gradient for stock prediction. The Neural Network is trained using Back-propagation neural networks algorithm and stochastic gradient descent algorithm as optimal strategies. Results: The experiment is conducted for stock market price prediction using python language with the visual package. In this experiment RELIANCE.NS, TATAMOTORS.NS, and TATAGLOBAL.NS dataset are taken as input dataset and it is downloaded from National Stock Exchange site. The artificial neural network component including Deep Learning model is most effective for more than 100,000 data points to train this model. This proposed model is developed on daily prices of stock market price to understand how to build model with better performance than existing national exchange method.

PP581 Catastrophic Costs Of Multidrug-Resistant Tuberculosis: Estimation Based On The Cost Of Treatment In China

2020 ◽  
Vol 36 (S1) ◽  
pp. 43-43
Author(s):  
Lijun Shen ◽  
Shangshang Gu ◽  
Fan Zhang ◽  
Zhao Liu ◽  
Yuehua Liu
Keyword(s):  
Market Price ◽  
Multidrug Resistant ◽  
Policy Support ◽  
World Health ◽  
Chinese Patients ◽  
Resistant Tuberculosis ◽  
Multidrug Resistant Tuberculosis ◽  
Mdr Tb ◽  
Drug Affordability ◽  
The Cost

IntroductionChina bears a considerably high burden of multidrug-resistant tuberculosis (MDR-TB). Second-line anti-TB drugs are urgently needed yet domestic MDR-TB drugs are expensive and lack policy support. Patients’ living conditions are closely related to the drug affordability. The national TB prevention programs should play a critical role. The purpose of this study is to measure the cost of treating MDR-TB patients under different treatment schemes and price sources. The results of this study are expected to inform the relevant drug protection policies and provide inputs for further cost-effectiveness analyses.MethodsBased on the treatment plan of China's Multidrug-Resistant Pulmonary Tuberculosis Clinical Path (2012 edition) and the World Health Organization (WHO) Drug-Resistant Tuberculosis Treatment Guide (2018 edition), the treatment costs of MDR-TB were measured under different scenarios. Catastrophic health expenditure was then calculated if the treatment cost exceeds 40 percent of the household's non-subsistence income. National, rural and disposable income per capita in 2018, were used to represent Chinese patients’ affordability.ResultsUnder varied treatment schemes and market price sources in China, the total costs for MDR-TB patients range from 19,401 to 126,703 CNY [2,853 to 18,633 USD] per person. Under current prices, all treatment schemes recommended by the WHO will incur catastrophic costs for Chinese MDR-TB patients. Significant differences were found between rural and urban areas as 52.8 percent of the treatment listed in the 2012 China Guideline would lead to catastrophic cost for rural patients but not urban ones.ConclusionsOur study concludes that the domestic drugs are more expensive than the international purchase price and the treatment of MDR-TB imposes substantial economic burden on patients, especially in the rural areas. The results of the study also indicate that it is urgent for the state to emphasize government responsibility and initiate centralized procurement for price negotiations to reduce the market price of MDR-TB drugs. The urban-rural gap should also be addressed in the design of future policies to ensure the drug affordability for all patients in need.

scholarly journals Backward-forward linear-quadratic mean-field Stackelberg games

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Kehan Si ◽  
Zhen Wu
Keyword(s):  
Large Population ◽  
Consistency Condition ◽  
Market Price ◽  
Mean Field ◽  
Mapping Method ◽  
Open Loop ◽  
Stackelberg Games ◽  
Linear Quadratic ◽  
Population System ◽  
The Cost

AbstractThis paper studies a controlled backward-forward linear-quadratic-Gaussian (LQG) large population system in Stackelberg games. The leader agent is of backward state and follower agents are of forward state. The leader agent is dominating as its state enters those of follower agents. On the other hand, the state-average of all follower agents affects the cost functional of the leader agent. In reality, the leader and the followers may represent two typical types of participants involved in market price formation: the supplier and producers. This differs from standard MFG literature and is mainly due to the Stackelberg structure here. By variational analysis, the consistency condition system can be represented by some fully-coupled backward-forward stochastic differential equations (BFSDEs) with high dimensional block structure in an open-loop sense. Next, we discuss the well-posedness of such a BFSDE system by virtue of the contraction mapping method. Consequently, we obtain the decentralized strategies for the leader and follower agents which are proved to satisfy the ε-Nash equilibrium property.

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