presentation on effects of dividends on common stock prices in the nepelese evidence paper was was published by prof. rade shyam pradhan in the the excellence
The theory of marginal analysis states that whenever marginal benefit exceeds marginal cost, a manager should increase activity to reach the highest net benefit. ... Sunk costs, fixed costs, and average costs do not affect marginal analysis. They are irrelevant to future optimal decision-making
The theory of marginal analysis states that whenever marginal benefit exceeds marginal cost, a manager should increase activity to reach the highest net benefit. ... Sunk costs, fixed costs, and average costs do not affect marginal analysis. They are irrelevant to future optimal decision-making
Linear Programming Problems {Operation Research}FellowBuddy.com
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This presentation is trying to explain the Linear Programming in operations research. There is a software called "Gipels" available on the internet which easily solves the LPP Problems along with the transportation problems. This presentation is co-developed with Sankeerth P & Aakansha Bajpai.
By:-
Aniruddh Tiwari
Linkedin :- http://in.linkedin.com/in/aniruddhtiwari
Short Version: A Simple Economics of InequalityYosuke YASUDA
The presentation slides for the following paper (very preliminary):
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2755893
Full version is available on the link below:
http://www.slideshare.net/YosukeYasuda1/equal-market-design
My research discovers a potential weakness or limitation of market economy, showing that perfectly competitive market tends to realize fewer trades than other allocation mechanisms do. In this sense, market economy achieves the greatest happiness of the MINIMUM number.
LINEAR PROGRAMMING Assignment help services at Globalwebtutors are available 24/ by online LINEAR PROGRAMMING experts , LINEAR PROGRAMMING tutors are available for instant LINEAR PROGRAMMING questions help , LINEAR PROGRAMMING writers can help you with complex LINEAR PROGRAMMING dissertation requirements.
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Linear Programming Problems {Operation Research}FellowBuddy.com
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
This presentation is trying to explain the Linear Programming in operations research. There is a software called "Gipels" available on the internet which easily solves the LPP Problems along with the transportation problems. This presentation is co-developed with Sankeerth P & Aakansha Bajpai.
By:-
Aniruddh Tiwari
Linkedin :- http://in.linkedin.com/in/aniruddhtiwari
Short Version: A Simple Economics of InequalityYosuke YASUDA
The presentation slides for the following paper (very preliminary):
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2755893
Full version is available on the link below:
http://www.slideshare.net/YosukeYasuda1/equal-market-design
My research discovers a potential weakness or limitation of market economy, showing that perfectly competitive market tends to realize fewer trades than other allocation mechanisms do. In this sense, market economy achieves the greatest happiness of the MINIMUM number.
LINEAR PROGRAMMING Assignment help services at Globalwebtutors are available 24/ by online LINEAR PROGRAMMING experts , LINEAR PROGRAMMING tutors are available for instant LINEAR PROGRAMMING questions help , LINEAR PROGRAMMING writers can help you with complex LINEAR PROGRAMMING dissertation requirements.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
AN ANALYSIS OF THE FINANCIAL PERFORMANCE EFFECT OF SHARIA COMPANIES ON STOCK ...Saputra Ayudi
This study entitled " An Analysis of the Financial Performance Effect of Sharia Companies on Stock Price Changes ( a Case Study of Companies Listed on the Sharia Stock Listing) ". This study uses eight (8) the financial ratios are debt to equity ratio, current ratio, inventory turnover ratio, total asset turnover, net profit margin, return on equity, price earning ratio, and dividend yield. The above financial ratios have been considered representative of the five types of financial ratios, which are 5 types of financial ratios in question are leverage ratios, liquidity ratios, efficiency ratios, profitability ratios, and market value ratios.
Predicting future sales is intended to control the number of existing stock, so the lack or excess stock can be minimized. When the number of sales can be accurately predicted, then the fulfillment of consumer demand can be prepared in a timely and cooperation with the supplier company can be maintained properly so that the company can avoid losing sales and customers. This study aims to propose a model to predict the sales quantity (multi-products) by adopting the Recency-Frequency-Monetary (RFM) concept and Fuzzy Analytic Hierarchy Process (FAHP) method. The measurement of sales prediction accuracy in this study using a standard measurement of Mean Absolute Percentage Error (MAPE), which is the most important criteria in analyzing the accuracy of the prediction. The results indicate that the average MAPE value of the model was high (3.22%), so this model can be referred to as a sales prediction model.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
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A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
The affect of service quality and online reviews on customer loyalty in the E...
Effects of dividends on common stock prices the nepalese evidence
1. Effects of Dividends on Common
Stock Prices : The Nepalese
Evidence*
Author : Radheshyam Pradhan
The Excellence – The Journal For Management And IT Professionals
Vol.2, No.1 (Balasore: Academy of Business Administration, Orissa, India, July
,2003),pp.18-25
2. Group - 4
Group members
Nirmala Baniya
Sangita Giri
Subas B.k
Meera Thapa
Neetu Yadav
Pankaj Kunwar
3. Introduction
Effect of dividend payment and retained earnings
Dividend policy decision
Association between Stock return and dividend yields
Dividend policy has been a subject of Considerable study
Shareholder in perfect capital market are indifferent
5. Study of resolving issue in the Nepal
Dividends or retained earnings are more attractive
Elasticity of dividends or retained earnings with respect to the
market price per share
Fact of economies of scale in dividend supply functions
Relationship between dividend or retained earning and market
price per share
Whether the speed of adjustment through dividend payment or
retained earnings between desired and actual shares prices is slow
or fast ?
6. Literature Review
Those who believe dividend affects the share price based their argument on the
hypothesis ( Chawla and Shrinivasan, 1987)
- Shareholders prefer current to future income
- Dividend has information content and its payment indicates company’s good
earning capacity.
7. Contd.
The argument that the dividend policy may affect the values can be viewed in
two categories (Van Horne and McDonald, 1971):
1. investor may have a net preference for dividends relative to capital gains or vice
versa owing to uncertainty resolution, transaction and inconvenience costs, and
differential tax rates.
2. Costs associated with the sale of issues of new issues of equity securities may
make these issues more costly source of equity financing than retained earnings.
8. Contd.
Some argue that required rate of return used by investors to discount dividends
expected in future period increases with time . (Gordon ,1963)
Another evidence is that the firms with higher dividend yields sell for lower prices . (
Litzenberger and Ramaswami, 1982 )
A study conducted in 1971 using time series data concluded that the retained earnings
had no effect on share price (Sarkar ,1971 )
Another study carries out in 1975 by using cross section data revealed impact of
retained earnings in cotton textiles industry and the impacts of dividends in electrical
industries ( Kumar and Man Mohan, 1975)
9. The Basic Model
As suggested by Friend and puckett in 1964, this model is the one of the most
commonly applied to cross - section data as follows:
MPSit = a + b DPSit + c REit + eit . . . (1)
Where,
MPSit = Market price per share
DPSit = Dividend per share
REit = Retained earning per share
The above model assumes the following reasonable a priori hypothesis:
DPSit > 0
REit > 0
10. Contd.
The subscript i denotes the ith company is a sample of n companies selected from
a particular industry.
All variables are measured in the ith time period.
Market price per share is the average of high, low and closing prices of the year.
11. Contd.
If the companies in a sample tend, on the average, to pay out less than the
optimum, b should be greater than c.
if they pay out more than the optimum, b should be less than c
if they pay just the optimum, regardless of what that optimum is, or if the payout is
matter of indifference, b should equal c.
12. The problem of least square bias
The problem of least squares bias can be handled by specifying a dividend supply
function such as the following:
MPSit = a + b DPSit + c REit + (PE)t-1 + eit . . . (2)
Lagged price also hold constant any firm effects that exist.
MPSit = a + b DPSit + c REit + MPSit-1 + eit . . . (3)
13. Nature and Sources of Data
The models are estimated by using secondary data for the listed companies of
Nepal.
The data for the study purpose is based pooled and cross-section data of 29
companies from 1994 to1999 which results total of 93 observations.
Not all the 110 listed companies in Nepal Stock Exchange provide scope of the
study.
There is absence of data as many of these companies are either new and have
just begun their operations and old listed companies which do not submit their
financial statements to Nepal Stock Exchange Ltd.
14. Empirical Results
The simple linear equation,
MPS = 1709.62 + 4.57 DPS – 12.54 RE . . . (4)
(2.41) (4.72*) (1.71)
R-bar square = 0.43 F = 7.60 SEE = 225.90 DW = 1.29
Coefficient of DPS is significant.
15. Linear Relationship Including Lagged Price
Earnings
MPS = 1701.37 + 4.54 DPS – 12.43 RE + 0.09 PEt-1 . . . (5)
(2.38) (4.71*) (1.69) (0.28)
R-bar square = 0.42 F = 5.04 SEE = 229.13 DW = 1.30
Coefficient of DPS is significant and coefficient of RE is negative.
16. Linear Relationship Including Lagged Price
Variable
MPS = 1666.18 – 9.31 DPS – 15.57 RE + 0.75 MPSt-1 . . . (6)
(3.07) (0.82) (2.78) (8.08)
R-bar square = 0.49 F = 30.45 SEE = 77.99 DW =1.44
Dividend receive greater relative weight and has a greater effect than retained
earnings.
17. Logarithmic Model
ln MPS = 3.62 + 0.60 ln DPS + 0.24 ln RE . . . (7)
(0.92) (5.28*) (0.29)
R-bar square = 0.63 F = 20.91 SEE = 0.86 DW = 1.44
18. Contd.
ln MPS = 3.96 + 0.63 ln DPS – 0.05 ln RE + 0.32 lnPEt-1 . . . (8)
(1.10) (5.75*) (0.06) (3.70*)
R-bar square = 0.56 F = 13.04 SEE = 0.787 DW = 1.42
Here,
Coefficient of RE is negative
Coefficient of dividend is significant.
Elasticity of dividend with respect to share price is less than unity which shows the
absence of economies of scale.
19. Contd.
ln MPS = 3.73 – 0.01 ln DPS – 0.51 ln RE + 0.77 MPSt-1 . . . (9)
(1.38) (0.07) (0.91) (8.55*)
R-bar square = 0.64 F = 39.84 SEE = 0.591 DW = 2.28
Here,
Adjustment coefficient = 0.23, this implies that the speed of adjustment between
desired and actual share prices is slow.
Only 23% of adjustment of actual to desired share price is completed within a
year.
20. Conclusion
Higher investor valuation may be placed on Dividends rather than Retained
Earnings.
Possible to increase stock price by rising dividends.
For growing companies, management might increase stock price by greater
retention of earnings, but could not be revealed by this study.
21. limitations
Tests were undertaken for few companies i.e 93 observations.
Regression model explained less than half of the total variance in linear
equations.
Ignorance of qualitative factor affecting market price of shares
22. RECOMMENDATION
Similar study can be conducted at different point of time to update finding
Industrywise analysis can give the proper result