Future Dividends Research Articles

ARIMA Model, Discounted Cash Flow Analysis, and Dividend Discount Model for Five Technology Stocks' Pricing and Trading Strategy

This study examines the ability of three widely used financial and econometric models-the Autoregressive Integrated Moving Average (ARIMA), the Discounted Cash Flow (DCF), and the Dividend Discount Model (DDM), to accurately forecast the stock prices of five well-known technological companies. Every theoretical framework offers a unique point of view. DDM places an emphasis on the value of expected future dividends. Collecting historical information on each stock and then applying that information to the relevant models in order to make projections about future stock values was an integral part of the process. In order to evaluate the accuracy, dependability, and applicability of each model in regard to the technology equity, a head-to-head comparison was carried out. Based on the preliminary findings, it appears that while ARIMA can provide valuable insights for price changes in the short term, DCF and DDM can provide a more comprehensive view of the long-term intrinsic worth of a company's stock. However, the effectiveness of each model differed among the several technological stocks that were considered, underscoring the relevance of selecting a model that is adapted to the particular qualities and dynamics of a specific stock as well as the industry in which it operates.

Maximizing Retirement Savings: Strategic Forecasting of Employees’ Provident Fund (EPF) Dividends

This study embarks on an analytical drive to project future dividends of the Employees Provident Fund (EPF) by harnessing the historical dividend data spanning from 1952 to 2023. With a comprehensive methodology that fuses both descriptive and inferential statistical approaches, the study conducts an in-depth examination of the fluctuations and trends in EPF dividend rates across seventy years. Utilizing EXCEL statistical tools, such regression models, it examines into identifying the pivotal factors that have historically influenced EPF dividends, thereby enabling the prediction of their future trajectories. This endeavor aims to refine the strategies employed in financial planning, ensuring they are more aligned with predicted outcomes. The study uncovers a pattern of volatility in EPF dividends, marked by significant highs and lows which correspond with the changing tides of the economic landscape. The development and application of a predictive model, deemed most effective through this study, shed light on potential future trends of EPF dividends. This model is instrumental in proposing a strategic approach for EPF contributors, tailored to navigate the complexities of investment planning with foresight. Moreover, the significance of this study transcends the boundaries of dividend prediction. It lays down a comprehensive framework that deepens the understanding of how retirement fund dividends are influenced by economic fluctuations. This contribution is invaluable for investors and policymakers alike, providing them with the foresight needed to make informed decisions that could preemptively address the challenges posed by future economic shifts. In essence, this paper makes a profound contribution to the domain of financial planning and analysis by advocating for a shift towards a more proactive and informed management of retirement savings.

Bankruptcy Risk in Discounted Cash Flow Equity Valuation

We investigate the importance of bankruptcy risk in discounted cash flow (DCF) equity valuation. Our analyses first show how bankruptcy risk is incorporated in DCF valuation, where investment risk is captured by cash flow certainty equivalents. Within this general setting, we find that bankruptcy risk can be captured by discounting factors incorporating period-specific bankruptcy probabilities, allowing the numerators in a DCF valuation model to follow a binary random walk. Elaborating a model of this kind, we assess the value of the equity holders’ limited liability right (the equity holders’ right to hand over the firm to its creditors if bankruptcy occurs). Two valuation models commonly used in academic research and professional practice—the Dividend Discount Model (DDM) and the Residual Income Valuation (RIV) model—are addressed specifically. Our analyses show that bankruptcy probabilities are important for the estimation of the value drivers in both models. Even if bankruptcy probabilities are as low as 0.02, equity values might be severely exaggerated if bankruptcy risk is ignored in DDM or RIV. In particular, this holds for firms expected to have high future growth (conditioned on firm survival). For the RIV model to properly capture bankruptcy risk, we identify “bankruptcy event accounting principles” and an additional term that must be included in the model. We also show that bankruptcy risk under certain conditions can be handled through a specific calibration of the discounting rate/-s in all DCF models, allowing the value drivers—i.e., future dividends or residual income—to be forecasted conditioned on firm survival.

Artificial Intelligence and Infectious Disease Imaging.

The mass production of the graphics processing unit and the coronavirus disease 2019 (COVID-19) pandemic have provided the means and the motivation, respectively, for rapid developments in artificial intelligence (AI) and medical imaging techniques. This has led to new opportunities to improve patient care but also new challenges that must be overcome before these techniques are put into practice. In particular, early AI models reported high performances but failed to perform as well on new data. However, these mistakes motivated further innovation focused on developing models that were not only accurate but also stable and generalizable to new data. The recent developments in AI in response to the COVID-19 pandemic will reap future dividends by facilitating, expediting, and informing other medical AI applications and educating the broad academic audience on the topic. Furthermore, AI research on imaging animal models of infectious diseases offers a unique problem space that can fill in evidence gaps that exist in clinical infectious disease research. Here, we aim to provide a focused assessment of the AI techniques leveraged in the infectious disease imaging research space, highlight the unique challenges, and discuss burgeoning solutions.

Determinants of the dividend payout policy of multinational companies in Bangladesh: Evidence from Dhaka stock exchange

This study tries to establish the important factors influencing the dividend payout policy of the Multinational Companies (MNCs) in Bangladesh in order to assist investors in making the best possible investment decisions. Data for this study was collected from several MNCs listed on the DSE from 2015 to 2021. The relationship between the dependent variable, Dividend Payout Ratio (DPR) and selected independent variables such as Return on Equity (ROE), Liquidity Ratio (LEQR), Leverage Ratio (LEVR), Firm Size (FS), Dividend Payout Ratio of Previous Year (PDPR), Corporate Tax Ratio (CTR) and Capital Adequacy Ratio (CAR) is evaluated using Pearson's correlation and Ordinary Least Squares (OLS) regression models for data analysis and hypothesis testing. The regression analysis results showed a mixed result. The ROE and CTR are significantly related to DPR. Higher ROE and CTR emphasis a higher dividend for stock holders. The FS is significantly negatively related to DPR. Due to the costs associated with paying for the profits of substantial assets, large firms pay lower dividends. Other variables such as LEQR, LEVR, PDPR, CTR and CAR have no significant impact on the DPR. The investors and the concerned authorities can consider ROE, CTR and FS to forecast the future dividend for the MNCs in Bangladesh.

Factors Influencing Dividend Payment Decisions: A Case of Mutual Funds in Tanzania

The study aimed at investigating the factors influencing dividend payout decisions of mutual funds in Tanzania for panel data in the time interval of 2019 to 2022. Using the modified Lintner model as a theoretical framework, explanatory research design was used. Employment of explanatory variables including past dividend, free cash flow, liquidity, sales growth, return on assets, financial leverage, firm size and market risk and using descriptive and inferential statistical tools i.e. correlation, fixed effect and random effect regression models the facts were realized. The results of analysis found that dividend payout decision is positively and significantly affected by past dividend and return on assets. Also it was revealed that free cash flows, liquidity, sales growth, financial leverage , firm size had a positive and insignificant effects on dividend payout decision. Either market risks revealed to have negative and insignificant influence on dividend payout. These results therefore recommend that mutual funds management should make much concentration on paying for floating dividend. Furthermore, the findings remind mutual funds management to ensure firm makes profit for firm realize performance, cash inflows, liquidity and growth. Satisfactory payment of dividend ensures for a firm value increase, firm growth and investors prosperous measured in terms of increase in financial leverage. Increase in financial leverage is the firms’ management performance which expects to help hedge the market risks for market efficiency hypothesis being realized important for perpetual future dividend payment.

The Ability of The Direct Method Operating Cash Flow Components in Predicting Future Cash Flows and Dividens (in Manufacturing Companies Listed on The Indonesia Stock Exchange in 2018-2021)

This research is associative research with a quantitative approach which aims to analyze the ability of the direct method operating cash flow components in predicting future cash flows and dividends in manufacturing companies listed on the Indonesia Stock Exchange in 2018-2021 period. The samples used in this study were 32 companies. Sampling used technique purposive sampling. The analytical method used is panel data regression. The data is tested using software Eviews 10. Operating cash flow proxied by cash inflows and cash outflows had a significant impact on predicting future cash flows in the first model study, as evidenced by partial testing with the t test. However, the second model study's findings demonstrate that operating cash flow, as proxied by cash inflows and cash outflows, has no significant impact on predicting future dividends.

Stable dividends under linear-quadratic optimisation

The optimisation criterion for dividends from a risky business is most often formalised in terms of the expected present value of future dividends. That criterion disregards a potential, explicit demand for the stability of dividends. In particular, within actuarial risk theory, the maximisation of future dividends has been studied as the so-called de Finetti problem. However, there the optimal strategies typically become so-called barrier strategies. These are far from stable, and suboptimal affine dividend strategies have recently received attention. In contrast, in the class of linear-quadratic problems, the demand for stability is explicitly stressed. These have often been studied in diffusion models different from the actuarial risk models. We bridge the gap between these thinking patterns by deriving optimal affine dividend strategies under a linear-quadratic criterion for an additive process. We characterise the value function by the Hamilton-Jacobi-Bellman equation, solve it, and compare the objective and the optimal controls to the classical objective of maximising the expected present value of future dividends. Thereby we provide a framework within which stability of dividends from a risky business, e.g. in classical risk theory, is explicitly demanded and obtained.

Equity market connectedness across regimes of geopolitical risks: Historical evidence and theory

We use a threshold VAR model to capture the connectedness of the equity returns of the G7 in a regime-contingent manner as defined by low- and high-geopolitical risks (GPR). We find that connectedness is statistically stronger when GPR is at its higher rather than lower regime, but more importantly, this observation can be associated with the threat of adverse geopolitical events, rather than with their actual realization. To explain our empirical observations we employ a model of international trade in assets and international relative asset prices. We introduce uncertainty in future dividend payments combined with agents' ambiguity aversion to changes in the expected dividends. This allows us to model a geopolitical threat as a shock that affects the level of ambiguity about future dividends. At the same time, a geopolitical act is defined as a shock to the current period endowment of a given country, with limited effects on asset prices and returns. Our obtained results have important portfolio allocation implications for investors.

An Evaluation of the Dividend Discount Model and its Extensions

The valuation of the stock is one of the most fundamental financial concepts, whereas the Dividend Discount Model is the basis of the stock valuation. The model state that the value of the stock is the sum of the present value of the infinite future dividend. It is, however, impossible for Humans to forecast future dividend accurately. Therefore, the assumption of the future dividend and the extension of the dividend discount model are required. In this paper, the assumption, advantages, and limitations of the general Dividend discount model and its extension, including the Fix dividend discount model, Gordon growth model, Two-stage model, Three-phase model, H-model, Geometric and additive model, and the modified Geometric and additive model, are introduced in this paper, which can be used as a reference for the investors for them to make their financial decision or for the scholars for their researches.

Understanding the price reaction to large dividend increases

Recent studies report muted price reactions to large dividend increases, attributing the phenomenon to the fact that these events are part of volatile dividend streams and are followed by dividend cuts. I find that the price also reacts slower to large dividend increases, suggesting the price effects of these events are more uncertain than small dividend increases. Further analysis shows that large dividend increases display some persistence and this offsets the effects of subsequent dividend cuts on future dividends. These results are more consistent with the muted price reaction arising from market concerns about dividend volatility than subsequent dividend cuts.

Evaluation Of Stock Through Fundamental Analysis With The Dividend Discount Model (DDM) Approach

The goal of this research is to determine the fairness of stock prices by looking at the intrinsic value of shares in the healthcare industry from 2017 to 2021. Investors use this assessment of the fairness of the share price to choose whether to sell, hold, or purchase shares. The Dividend Discounted Model (DDM) with a Constant Growth Model was used for the analysis. The Dividend Discounted Model (DDM) is used to compare the stock's intrinsic value to its market value to determine the intrinsic value of shares. This value is calculated by anticipating future dividend payments. The Healthcare Sector Company on the Indonesia Stock Exchange is the subject of this kind of descriptive research. Nine companies were chosen as samples using the purposive sampling strategy. Shares of DVLA, KLBF, MERK, MIKA, PEHA, PRDA, SIDO, and TSPC were found to be undervalued in the outcomes. On the other hand, HEAL shares was found overvalued. For potential investors in DVLA, KLBF, MERK, MIKA, PEHA, PRDA, SIDO, and TSPC shares, the best investment decision is to buy shares in these companies before the market price of these shares rises. Meanwhile, investors who already own shares in these companies should hold the company's shares and increase their share ownership with the assumption that the share price will rise in the future. Furthermore, potential investors should not buy HEAL company shares and investors who already own the company shares should immediately sell the company shares in order to get capital gains.

Multiple-prior valuation of cash flows subject to capital requirements

We study market-consistent valuation of liability cash flows motivated by current regulatory frameworks for the insurance industry. The value assigned to an insurance liability is the consequence of (1) considering a hypothetical transfer of an insurance company's liabilities, and financial assets intended to hedge these liabilities, to an empty corporate entity, and (2) considering the circumstances under which a capital provider would want to achieve and maintain ownership of this corporate entity given limited liability for the owner and that capital requirements have to be met at any time for continued ownership.We focus on the consequences of the capital provider assessing the value of continued ownership in terms of a least favorable expectation of future dividends, meaning that we consider expectations with respect to probability measures in a set of equivalent martingale measures. We show that natural conditions on the set of probability measures imply that the value of a liability cash flow is given in terms of a solution to a backward recursion. Through a life and a non-life insurance example we demonstrate how to make the valuation approach operational.

Analysis of Intrinsic Stock Value Based on Discounted Cash Flow (DCF) Model -- Take China Construction Bank (601939) as an Example

The DCF model is a simple and effective way to predict the intrinsic value of a stock by discounting future dividends. In this paper, China Construction Bank is used as the research object and valued by the DCF model [1]. The research results show that the current share price of China Construction Bank is undervalued, and with a large gap between the stock price seen by the public and the true intrinsic value of China Construction Bank, there is still plenty of room to go in the decades to come. so it is recommended to increase the stock to wait for future gains [2].

Inflation and west African sectoral stock price indices: An asymmetric kernel method analysis

Our work puts into perspective the relationship between inflation and West African sectoral indices between November 2001 and January 2020 using the asymmetric kernel method. The sectoral indices considered for the analysis include retail, finance, industry, utilities, agriculture, transportation, and other sectors. Our work reveals that while all sectors are sensitive to inflation, the utilities and agriculture sectors are more sensitive to changes in inflation. Moreover, we discover that the relationship between inflation and sectoral stock market indices is rather non-linear to support the hypothesis that the relationship between inflation and stock market indices varies across different inflationary economies. These results imply that investors modify the structure of their investment portfolio according to the variation in the levels of inflation to the extent that this variation ultimately affects future dividends.

Overview of Navy Medicine's Limited Duty Patient Population.

U.S. Navy Medicine's temporary limited duty (LIMDU) program is the primary vehicle for managing the medical care and subsequent career outcomes of the ill and injured active component (AC) Sailors and Marines to ensure a medically ready force. Before the LIMDU Sailor and Marine Readiness Tracker System (SMART) came online, it was very difficult to examine LIMDU program administration metrics, patients' experiences during LIMDU, and their subsequent health and career outcomes. This study examined the LIMDU patient population's demographic, military career, and LIMDU-specific characteristics; identified characteristics that differed significantly by military service; and evaluated potentially modifiable factors associated with patient outcomes. A comprehensive SMART extract was used to identify all AC Sailors and Marines in active LIMDU status between October 1, 2016, and September 30, 2019. The SMART extract was merged with comprehensive administrative military personnel data by patient identifiers to create a longitudinal dataset and to conduct descriptive statistics, bivariate, and multivariate logistic regression analyses for this study. The sample included 26,591 AC Sailors and Marines with complete SMART and military personnel records who ended LIMDU on or before September 30, 2019. During the study's 3-year period, Navy Medicine's rate of initial LIMDU entry by AC personnel increased each year from 2,041 in FY2017 to 2,424 in FY2019 per 100,000 personnel. At the time of initial entry, most LIMDU patients were male (76%), E4-E6 paygrades (54%), and had a single diagnosis recorded in their SMART records (66%). Pain patients (23%) constituted the largest diagnostic group, followed closely by musculoskeletal patients (23%), and then mental and behavioral health patients (20%). Variables that might reflect administration practices of the program did not differ significantly by service, suggesting good internal standardization of LIMDU administration across Navy Medicine. However, bivariate and multivariate analyses identified significant differences by service for almost all personal demographic, LIMDU-specific, and post-LIMDU military career sample characteristics measured at the last LIMDU close date or later. Study results suggested that the Navy and Marine Corps referred Sailors and Marines to start LIMDU for different medical reasons; to receive care from different military treatment facilities; to close LIMDU with different final actions; and to experience different post-LIMDU career outcomes. Navy Medicine's SMART data is an important new resource for LIMDU program evaluation and population-level patient research, despite the data limitations and concerns identified and addressed by this study. The study results provide a baseline empirical understanding about the LIMDU patient population. Further research is necessary to interrogate the validity of these results over a longer period and to initiate other lines of inquiry. While the construction of the larger project's LIMDU patient population longitudinal dataset required a significant initial investment, future dividends from ongoing work are anticipated. Results derived from verified SMART data will benefit Navy Medicine, operational commands, and LIMDU patients alike by informing continuing efforts to improve patient health and career outcomes, identify and implement best clinical and administrative practices, and optimize force readiness.

Languages and dividends

We study whether languages are related to corporate dividend policies around the world. Users of languages with a weak future time reference (FTR), such as Japanese and Finnish, do not need to grammatically distinguish future and current events, while users of strong-FTR languages such as French and Italian do. Chen (2013) shows that people who use weak-FTR languages may perceive the future to be nearer and have less precise perceptions of the timing of future events than users of strong-FTR languages. We argue that these perceptions may result in a lower discount rate and a higher valuation of future dividends, leading to a weaker preference and demand for a dividend today. Using a large sample of firms from 19 markets, we find supporting evidence that firms in weak-FTR language markets pay lower dividends than firms in strong-FTR language markets. The results remain robust after a battery of robustness tests, including using a single market with multiple languages and using a difference-in-differences approach in a market with a change of official languages. Further evidence shows that weak-FTR languages are related to a lower implied cost of equity capital and stronger market reactions to dividend changes. Our results offer a new explanation for cross-country differences in dividend policies and add to the research on culture and financial markets.

Does Accounting Measurement Influence Market Efficiency? A Laboratory Market Perspective

ABSTRACTUsing laboratory markets where accounting regimes can be directly compared with equivalent economic parameters, we test whether and how two different accounting measurement bases—historical cost (HC) and mark-to-market (MTM)—influence trader perceptions and asset mispricing. Our results show that traders perceive otherwise equivalent assets differently by regime, consistent with accounting regimes imposing differential information processing costs. In the MTM regime, traders integrate market price information to a greater extent and integrate asset fundamental information to a lesser extent. We also observe that traders in the MTM regime express prospective preferences for information about future market prices, but in HC prefer information about future dividends. These individual-level effects correspond with greater market-level mispricing/bubbles under MTM. Our results suggest that accounting regimes can, on their own, contribute to price bubbles and their subsequent collapse.Data Availability: Data are available on request.

A Model-Free Term Structure of U.S. Dividend Premiums

AbstractWe estimate a model-free term structure of the ex ante dividend risk premium by combining two data sets with different information about future dividends. We aggregate survey forecasts about future dividends for single companies over multiple horizons to construct a term structure of expected S&P 500 dividend growth rates. We use European call and put option prices on the S&P 500 to estimate the term structures of options-implied dividend growth rates and risk-free rates. Applying the method to 2004–2021 data offers a new, ex ante perspective on the conditional time variation of the term structure of the dividend risk premium.

When Investors Speak, Do Firms Listen? The Role of Investors' Dividend‐related Complaints from Online Earnings Communication Conferences

We study whether investor voice affects firm policy. Using a novel dataset of the transcripts of online earnings communication conferences (OECC) of Chinese listed firms during 2006 and 2015, we show that firms do respond to investor complaints about dividend policy with increased future dividends. We find that the number of dividend‐related questions raised by investors, the number of complaints (questions with negative attitudes), firm executive responsiveness, and CEO attendance in the OECC are positively associated with future dividend payouts. Moreover, positive responses are concentrated in firms facing greater pressure from peers, the market, and the regulator. Our additional analysis shows that the increase in payouts in response to investors' voice is not at the expense of cutting value‐increasing investment. Overall, our results suggest that the online interactive platform empowers shareholders' voice and helps them to conduct a successful dialogue with firm managers in a cost‐effective way.