Multiplicative Regression Models of the Relationship between Accounting Numbers and Market Value

2011 ◽  
Author(s):  
Michael Falta ◽  
Roger J. Willett
Keyword(s):  
Regression Models ◽  
Market Value ◽  
Accounting Numbers ◽  
The Relationship

scholarly journals Mathematical Approach for Predicting the Gross Domestic Product of Malaysia

2020 ◽  
Vol 5 (10) ◽  
pp. 247-257
Author(s):  
Maryam Rukayyah Al-Munirah Ayob ◽  
Azizah Mohd Rohni
Keyword(s):  
Gross Domestic Product ◽  
Regression Model ◽  
Regression Models ◽  
Market Value ◽  
Domestic Product ◽  
Main Subject ◽  
Exponential Regression ◽  
Goods And Services ◽  
Future Developments ◽  
The Relationship

Gross domestic product (GDP) is a monetary measure of the market value of overall final goods and services produced in a given year, and serves as a gauge of the economy’s overall health and size. The GDP prediction is significant, as it can capture and understand the future developments of a country’s economy. In this paper, three different mathematical models have been used to predict Malaysia’s gross domestic product using regressions. The models discussed in this paper are linear, exponential and parabolic regressions. In developing the models, data from year 1970 to 2014 has been employed and data from year 2015 to 2019 has been used to examine the models' accuracy. The models are then observed to identify the most appropriate to express the relationship between the years and Malaysia’s gross domestic product. In this study, it is found that the parabolic regression model is more accurate compared to the linear and exponential regression models. The parabolic regression model is also the most appropriate since it is adjusted to the real conditions of Malaysia's gross domestic product which is the main subject of this paper. Finally, it is obtained that the prediction values of GDP in Malaysia will increase for the next ten years (2020 - 2029).   Keywords: Gross domestic product, Linear regression, Exponential regression, Parabolic regression

scholarly journals Exploring the Relationship between Market Value and Accounting Numbers of Firms in Pakistan

2015 ◽  
Vol 7 (1) ◽  
pp. 230
Author(s):  
Salman Riaz ◽  
Yangping Liu ◽  
Sajjad Hussain Khan
Keyword(s):  
Market Price ◽  
Market Value ◽  
Time Span ◽  
Cement Industry ◽  
Market Prices ◽  
Book Value ◽  
Earnings Per Share ◽  
Accounting Numbers ◽  
Equity Ratio ◽  
The Relationship

<p>This study examines the relationship between accounting numbers and market prices for the Pakistani cement industry. The study covers a time span of nine years from 2005-2014. We study the influence of book value of share, breakup value of share, earning per share, gearing ratio and dividend to equity ratio on market value of share. After applying different econometric techniques we found that book value of share and earnings per share have statistically significant influence on the market price of share.  </p>

Is Voluntary Disclosure Value Relevant? Evidence from Top Listed Firms in India

2021 ◽  
pp. 097226292098629
Author(s):  
Rupjyoti Saha ◽  
Kailash Chandra Kabra
Keyword(s):  
Voluntary Disclosure ◽  
Value Relevance ◽  
Stock Exchange ◽  
Market Value ◽  
Policy Implications ◽  
Positive Contribution ◽  
Listed Firms ◽  
Strategic Disclosure ◽  
Relevant Evidence ◽  
The Relationship

In view of ongoing reforms in India with emphasis on improving transparency of corporate, the present study aims to examine the influence of voluntary disclosure on the market value of India’s top-listed firms. To this end, the study uses a sample of top 100 non-financial and non-utility firms listed at Bombay Stock Exchange based on market capitalization over a 5-year period (2014–2018). To control potential endogeneity in the relationship between voluntary disclosure and firms’ market valuation, fixed effect panel data model and two-stage least squares model of estimation have been employed. The result obtained from the analysis suggests that enhanced level of voluntary disclosure significantly improves the market value of sample firms. The study further undertakes additional analysis by categorizing voluntary disclosure into its sub-components wherein the findings reveal that three components of voluntary disclosure such as corporate and strategic disclosure, forward looking disclosure and corporate governance disclosure make positive contribution towards market value of firms, while the remaining components of voluntary disclosure such as human and intellectual capital disclosure and financial and capital market disclosure do not appear to have any significant influence on the same. Overall, the finding suggests that voluntary disclosure made by sample firms is considered relevant by investors. However, value relevance of different components of voluntary disclosure varies with the nature and extent of information disclosed. The study offers some important policy implications.

785 Reported Restful Sleep Predicting Emotional Distress: Does Exercise (and its modalities) moderate?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A305-A306
Author(s):  
Jesse Moore ◽  
Ellita Williams ◽  
Collin Popp ◽  
Anthony Briggs ◽  
Judite Blanc ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aerobic Exercise ◽  
Regression Models ◽  
Regression Analyses ◽  
Logistic Regression Models ◽  
The Past ◽  
Strengthening Exercise ◽  
Waking Up ◽  
The Relationship ◽  
Age And Sex

Abstract Introduction Literature shows that exercise moderates the relationship between sleep and emotional distress (ED.) However, it is unclear whether different types of exercise, such as aerobic and strengthening, affect this relationship differently. We investigated the moderating role of two types of exercise (aerobic and strengthening) regarding the relationship between ED and sleep. Methods Our analysis was based on data from 2018 National Health Interview Survey (NHIS), a nationally representative study in which 2,814 participants provided all data. Participants were asked 1) “how many days they woke up feeling rested over the past week”, 2) the Kessler 6 scale to determine ED (a score &gt;13 indicates ED), and 3) the average frequency of strengthening or aerobic exercise per week. Logistic regression analyses were performed to determine if the reported days of waking up rested predicted level of ED. We then investigated whether strengthening or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Logistic regression analyses were performed to determine if subjective reporting of restful sleep predicted level of ED. We investigated whether strengthening exercise or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Results On average, participants reported 4.41 restful nights of sleep (SD =2.41), 3.43 strengthening activities (SD = 3.19,) and 8.47 aerobic activities a week (SD=5.91.) We found a significant association between days over the past week reporting waking up feeling rested and ED outcome according to K6, Χ2(1) = -741, p= &lt;.001. The odds ratio signified a decrease of 52% in ED scores for each unit of restful sleep (OR = .48, (95% CI = .33, .65) p=&lt;.001.) In the logistic regression model with moderation, aerobic exercise had a significant moderation effect, Χ2(1) = .03, p=.04, but strengthening exercise did not. Conclusion We found that restful sleep predicted reduction in ED scores. Aerobic exercise moderated this relationship, while strengthening exercise did not. Further research should investigate the longitudinal effects of exercise type on the relationship between restful sleep and ED. Support (if any) NIH (K07AG052685, R01MD007716, K01HL135452, R01HL152453)

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

scholarly journals The Impact of Weather and Seasons on Falls and Physical Activity among Older Adults with Glaucoma: A Longitudinal Prospective Cohort Study

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3415
Author(s):  
Hursuong Vongsachang ◽  
Aleksandra Mihailovic ◽  
Jian-Yu E ◽  
David S. Friedman ◽  
Sheila K. West ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Fall Prevention ◽  
Regression Models ◽  
Activity Promotion ◽  
Injurious Fall ◽  
Multivariable Regression ◽  
Multivariable Regression Models ◽  
The Impact ◽  
The Relationship

Understanding periods of the year associated with higher risk for falling and less physical activity may guide fall prevention and activity promotion for older adults. We examined the relationship between weather and seasons on falls and physical activity in a three-year cohort of older adults with glaucoma. Participants recorded falls information via monthly calendars and participated in four one-week accelerometer trials (baseline and per study year). Across 240 participants, there were 406 falls recorded over 7569 person-months, of which 163 were injurious (40%). In separate multivariable regression models incorporating generalized estimating equations, temperature, precipitation, and seasons were not significantly associated with the odds of falling, average daily steps, or average daily active minutes. However, every 10 °C increase in average daily temperature was associated with 24% higher odds of a fall being injurious, as opposed to non-injurious (p = 0.04). The odds of an injurious fall occurring outdoors, as opposed to indoors, were greater with higher average temperatures (OR per 10 °C = 1.46, p = 0.03) and with the summer season (OR = 2.69 vs. winter, p = 0.03). Falls and physical activity should be understood as year-round issues for older adults, although the likelihood of injury and the location of fall-related injuries may change with warmer season and temperatures.

scholarly journals Online News and Protest Participation in a Political Context: Evidence from Self-Reported Cross-Sectional Data

2021 ◽  
Vol 7 (1) ◽  
pp. 205630512098445
Author(s):  
Nora Kirkizh ◽  
Olessia Koltsova
Keyword(s):  
Digital Media ◽  
Regression Models ◽  
Online News ◽  
Political Context ◽  
Government Control ◽  
Multilevel Regression ◽  
Traditional Media ◽  
Cross Sectional ◽  
Internet Media ◽  
The Relationship

Availability of alternative information through social media, in particular, and digital media, in general, is often said to induce social discontent, especially in states where traditional media are under government control. But does this relation really exist, and is it generalizable? This article explores the relationship between self-reported online news consumption and protest participation across 48 nations in 2010–2014. Based on multilevel regression models and simulations, the analysis provides evidence that those respondents who reported that they had attended a protest at least once read news online daily or weekly. The study also shows that the magnitude of the effect varies depending on the political context: surprisingly, despite supposedly unlimited control of offline and online media, autocratic countries demonstrated higher effects of online news than transitional regimes, where the Internet media are relatively uninhibited.

scholarly journals Investigating the Relationship Between Emotion Recognition Software and Usability Metrics

i-com ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 139-151
Author(s):  
Thomas Schmidt ◽  
Miriam Schlindwein ◽  
Katharina Lichtner ◽  
Christian Wolff
Keyword(s):  
Emotion Recognition ◽  
Regression Models ◽  
Affective Computing ◽  
Large Scale ◽  
General Purpose ◽  
Thinking Aloud ◽  
Continue Research ◽  
Usability Metrics ◽  
Recognition Software ◽  
The Relationship

AbstractDue to progress in affective computing, various forms of general purpose sentiment/emotion recognition software have become available. However, the application of such tools in usability engineering (UE) for measuring the emotional state of participants is rarely employed. We investigate if the application of sentiment/emotion recognition software is beneficial for gathering objective and intuitive data that can predict usability similar to traditional usability metrics. We present the results of a UE project examining this question for the three modalities text, speech and face. We perform a large scale usability test (N = 125) with a counterbalanced within-subject design with two websites of varying usability. We have identified a weak but significant correlation between text-based sentiment analysis on the text acquired via thinking aloud and SUS scores as well as a weak positive correlation between the proportion of neutrality in users’ voice and SUS scores. However, for the majority of the output of emotion recognition software, we could not find any significant results. Emotion metrics could not be used to successfully differentiate between two websites of varying usability. Regression models, either unimodal or multimodal could not predict usability metrics. We discuss reasons for these results and how to continue research with more sophisticated methods.

scholarly journals An analysis of Italian university students’ performance through segmented regression models: gender differences in STEM courses

Genus ◽  
2021 ◽  
Vol 77 (1) ◽  
Author(s):  
Andrea Priulla ◽  
Nicoletta D’Angelo ◽  
Massimo Attanasio
Keyword(s):  
Gender Differences ◽  
Regression Models ◽  
First Year ◽  
Strongly Correlated ◽  
Segmented Regression ◽  
Freshmen Students ◽  
Female Performance ◽  
And Mathematics ◽  
The Relationship ◽  
Better Than

AbstractThis paper investigates gender differences in university performances in Science, Technology, Engineering and Mathematics (STEM) courses in Italy, proposing a novel application through the segmented regression models. The analysis concerns freshmen students enrolled at a 3-year STEM degree in Italian universities in the last decade, with a focus on the relationship between the number of university credits earned during the first year (a good predictor of the regularity of the career) and the probability of getting the bachelor degree within 4 years. Data is provided by the Italian Ministry of University and Research (MIUR). Our analysis confirms that first-year performance is strongly correlated to obtaining a degree within 4 years. Furthermore, our findings show that gender differences vary among STEM courses, in accordance with the care-oriented and technical-oriented dichotomy. Males outperform females in mathematics, physics, chemistry and computer science, while females are slightly better than males in biology. In engineering, female performance seems to follow the male stream. Finally, accounting for other important covariates regarding students, we point out the importance of high school background and students’ demographic characteristics.

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