Volatility Modelling Using Hybrid Autoregressive Conditional Heteroskedasticity (ARCH) - Support Vector Regression (SVR)

High fluctuations in stock returns is one problem that is considered by the investors. Therefore we need a model that is able to predict accurately the volatility of stock returns. One model that can be used is a model Autoregressive Conditional Heteroskedasticity (ARCH). This model can serve as a model input in the Support Vector Regression (SVR) model, known as Hybrid ARCH-SVR. This modeling is one of the alternatives in modeling the volatility of stock returns. This method is able to show a good performance in modeling the volatility of stock returns. The purpose of this study was to determine the stock return volatility models using a Hybrid ARCH-SVR model on stock price data of PT. Indofood Sukses Makmur Tbk. The result shows that the determination of the input variables based on the ARIMA (3,0,3)-ARCH (5), so that the SVR model consists of 5 lags as input vector. Using a this model was obtained that the Mean Absolute Percentage Error (MAPE) of 1,98% and R2 =99,99%

The Economic Pay-Offs To On-The-Job Training In Routine Service Work

This study examines the relationship between on-the-job training and job performance among 3,408 telephone operators in a large unionized telecommunications company. We utilize individual data on monthly training hours and job performance over a five-month period as provided by the company’s electronic monitoring system. Results indicate that the receipt of on-the-job training is associated with significantly higher productivity over time, when unobserved individual heterogeneity is taken into account. Moreover, workers with lower pre-training proficiency show greater improvements over time than those with higher pre-training proficiency. Finally, whether the training is provided by a supervisor or a peer also matters. Workers with lower proficiency achieve greater productivity gains through supervisor training, while workers with higher proficiency achieve greater productivity gains through peer training

Volatility Modelling Using Hybrid Autoregressive Conditional Heteroskedasticity (ARCH) - Support Vector Regression (SVR)

High fluctuations in stock returns is one problem that is considered by the investors. Therefore we need a model that is able to predict accurately the volatility of stock returns. One model that can be used is a model Autoregressive Conditional Heteroskedasticity (ARCH). This model can serve as a model input in the Support Vector Regression (SVR) model, known as Hybrid ARCH-SVR. This modeling is one of the alternatives in modeling the volatility of stock returns. This method is able to show a good performance in modeling the volatility of stock returns. The purpose of this study was to determine the stock return volatility models using a Hybrid ARCH-SVR model on stock price data of PT. Indofood Sukses Makmur Tbk. The result shows that the determination of the input variables based on the ARIMA (3,0,3)-ARCH (5), so that the SVR model consists of 5 lags as input vector. Using a this model was obtained that the Mean Absolute Percentage Error (MAPE) of 1,98% and R2 = 99.99%. Keywords: ARCH; ARIMA; SVR; Volatilit

Accounting for Health and Safety costs: Review and comparison of selected methods

A part of the emerging sustainability management accounting is corporate health and safety performance. One performance dimension is the costs of occupational accidents in companies. The underlying logic for calculating these costs is that if occupational accidents are prevented then these costs could be avoided. This chapter presents and discusses selected methods for calculating the costs of occupational accidents. The focus is on presenting the characteristics of each method and disclosing the benefits and drawbacks of each methodNo keywords;

User's Guide to the ROI Forecasting Calculator: Estimating ROI for Medicaid Quality Improvement Programs

Explains the online tool for state Medicaid agencies, health plans, and stakeholders to assess the cost-savings potential of quality improvement measures. Outlines analytical issues and best practices for each component and how to interpret the results

Welfare-to-Work Program Benefits and Costs: A Synthesis of Research

Most welfare programs seek to ensure that poor families have adequate income while at the same time encouraging self-sufficiency. Based on studies of 28 programs involving more than 100,000 sample members, this synthesis compares the costs, benefits, and returns on investment of six welfare program strategies -- from the perspectives of participants, government budgets, and society as a whole

Estimating the potential impacts of open access to research findings

Advances in information and communication technologies are disrupting traditional models of scholarly publishing, radically changing our capacity to reproduce, distribute, control, and publish information. The key question is whether there are new opportunities and new models for scholarly publishing that would better serve researchers and better communicate and disseminate research findings. Identifying access and efficiency limitations under the subscription publishing model, this paper explores the potential impacts of enhanced access to research outputs using a modified Solow-Swan model, which introduces ‘accessibility’ and ‘efficiency’ parameters into calculating returns to R&D. Indicative impact ranges are presented for Government, Higher Education and Australian Research Council R&D expenditures. We conclude that there may be substantial benefits to be gained from more open access to research findings

Tax incentives for R&D

A long-standing concern surrounding the performance of the UK economy is its perceived failure to maintain the same technological pace as its competitors. Industrial research and development (R&D) expenditure as a proportion of GDP fell during the 1980s at a time when all other G7 countries increased the proportion of their output given over to R&D. This ratio is now lower in the UK than in most other G7 countries. If this world-wide trend toward more R&D indicates that industrial production is becoming increasingly science-based, then the UK may be in danger of becoming a relatively low-tech economy. One purpose of this article is to examine whether there is a rational basis for these fears.