Capital Decisions Research Articles

Using regime-switching models in Sharia-compliant stocks: performance assessment of investors with discriminated risk-appetite

Purpose The paper aims to assess the performance of investors that are discriminated based on their risk-appetite who intend to invest in listed Sharia-compliant (SC) stocks to maximize their portfolios’ wealth through two different models (i.e. regime-switching [RS] and non-RS). Design/methodology/approach Study period (i.e. November 18, 2015–May 31, 2019), well described in two distinct volatility-related bull-regime and bear-regime, is divided into in-sample and out-sample where Rs. 1.00 is invested on the out-sample start date. Each investor’s cumulated wealth forecasted through different models is checked daily throughout the out-sample period, and then, analyzed based on investors’ cumulated ending wealth, and Sharpe ratio (SR) is obtained through different models. Findings The ending wealth of risk-averse and risk-neutral investors obtained through RS-models increased 5.27 times while that of risk-taker investors increased 5.13 times. However, ending wealth obtained through non-RS models remained far low. The SR remained unchanged among investors. However, the SR of RS models (i.e. 1.0867) is higher than that of non-RS models (i.e. 0.8681). Overall, RS model-based investments outperformed in all categories of investors. Practical implications The study helps the investor during the process of portfolio diversification in their asset(s) selection and limited capital apportionment decisions. It also helps market regulators in formulating regulations and the policymakers in articulating/implementing policies that may protect the stakeholders form consequent disasters, particularly when market switches regimes. Originality/value The uniqueness stems from its focus on risk-appetite discriminated investors’ portfolio wealth maximization issue examined through technical analysis using two completely distinct models in the emerging market’s listed SC stocks.

Predictive HR analytics and talent management: a conceptual framework

Digitisation, new technologies and artificial intelligence demand organisations for new ways of working with a different skill set to accomplish strategic objectives. HR analytics is the scientific solution enabling organisations to make significant human capital and strategic business decisions and thereby gain a competitive advantage. However, theory-based relationships in HR analytics adoption is meagre. Further, there is a paucity of HR analytics literature on the role of contextual factors that affect organisations in building predictive HR analytics (PHRA) capability. Addressing this gap, we develop a conceptual framework through the lens of the Technological-Organisational-Environmental (TOE) framework and Resource-based theory to examine the relationships among the antecedents and consequences of PHRA capability considering talent management under the moderating effect of a data-driven culture. This paper is possibly the first study to propose a theoretical model to examine the effect of PHRA capability on talent management outcomes.

Working capital management and CEO age

The existing literature provides strong evidence that working capital management affects a firm’s performance and value. In this paper, we examine how CEO age affects firms’ working capital decisions. Using a sample of 28,243 firm-year observations of U.S. firms from 1993 to 2018, we find that net operating working capital increases with CEO age, and firms with younger CEOs hold lower levels of inventory and higher levels of payables. The results are robust to various model specifications and variable definitions, providing strong and robust evidence that younger CEOs tend to implement more aggressive working capital management policies (Aggressive strategy hypothesis). The findings provide important insights to the board of directors, investors, and various monitoring groups.

Do Working Capital Decision and Efficiency of Working Capital Management Contribute to the Profitability? Evidence from Bangladesh

This study attempts to explore how working capital decision, that is, aggressive investment and finance decision and efficiency of the working capital management (WCM) contribute to the profitability operationalised by gross operating profit (GOP) and return on assets of listed manufacturing firms in Bangladesh. To investigate this relationship, the study has taken into consideration of 468 sample observations from 108 listed firms covering the year from 2013 to 2017. This study finds that aggressive investment and finance decision significantly contribute to the profitability of the firm. Besides, the efficiency of WCM has significant impact on the profitability. In addition, the constructs of efficiency of WCM—that is, days in inventory outstanding, days in sales outstanding—has significant negative impact on the profitability of the firm. Unfortunately, this study finds no significant impact of days in payables outstanding on firm’s profitability.

Can state and local government capital spending be a vehicle for countercyclical policy? Evidence from new interview and survey data

This paper investigates the extent to which state and local government capital spending in the United States can be an effective vehicle for countercyclical policy. Policy responses to recent cyclical downturns have included a variety of policies to encourage greater spending at the state and local level, including efforts to lower borrowing costs for these governments, but the effectiveness of these policies remains unclear. To examine the effectiveness of state-local capital spending as a countercyclical tool, I use a unique data set consisting of open-ended interviews with state and local budget officers and a survey of state governments. I find that at present, there are significant barriers preventing countercyclical state-local capital spending. First, interventions to stimulate capital spending via easing financing conditions are likely limited by two factors: some governments use minimal amounts of borrowing to finance capital spending, and for governments that do rely primarily on borrowing, capital spending appears insensitive to interest rates. Second, state and local capital spending decisions involve substantial lags, making it a poor vehicle for countercyclical fiscal policy even in the absence of financing constraints. Third, state-local budget officials do not view capital spending as a tool for economic stabilization.

Approach-oriented and avoidance-oriented measures under complex Pythagorean fuzzy information and an area-based model to multiple criteria decision-aiding systems

The purpose of this paper is to evolve a novel area-based Pythagorean fuzzy decision model via an approach-oriented measure and an avoidance-oriented measure in support of multiple criteria decision analysis involving intricate uncertainty of Pythagorean fuzziness. Pythagorean membership grades embedded in a Pythagorean fuzzy set is featured by tensible functions of membership, non-membership, indeterminacy, strength, and direction, which delivers flexibility and adaptability in manipulating higher-order uncertainties. However, a well-defined ordered structure is never popular in real-life issues, seldom seen in Pythagorean fuzzy circumstances. Consider that point operators can make a systematic allocation of the indeterminacy composition contained in Pythagorean fuzzy information. This paper exploits the codomains of the point operations (i.e., the quantities that express the extents of point operators) to launch new measurements of approach orientation and avoidance orientation for performance ratings. This paper employs such measurements to develop an area-based performance index and an area-based comprehensive index for conducting a decision analysis. The applications and comparative analyses of the advanced area-based approach to some decision-making problems concerning sustainable recycling partner selection, company investment decisions, stock investment decisions, and working capital financing decisions give support to methodological advantages and practical effectiveness.

Intellectual capital and firms' financing decisions in the European context: a panel data analysis

Intellectual capital and firms' financing decisions in the European context: a panel data analysis

How does capital structure affect firm’s market competitiveness?

Effective capital decisions not only increase the operational efficiency of businesses but also is strategic to bring the enterprise’s competitive advantages to the market. Using an appropriate deb...

Do Firms Consider Economic Outlook When Determining Payout Policy?

Payout policy is one of the most important policies set by firms and represents a major use of capital by publicly traded corporations. Firms should consider future economic activity and future firm performance when determining payout policy choices, given they are cash outflow commitments from the firm. We empirically examine whether firms use economic outlook when determining payout policy using publicly available data from the Chicago Federal Reserve Bank and Compustat. We find that economic outlook is positively related to firm payout policy. Specifically, we find that firms are more likely to pay out cash dividends and repurchase shares when economic outlook is positive. Furthermore, when examining only firms already paying dividends and/or repurchasing shares, firms pay greater amounts of cash dividends and repurchase more shares when economic outlook is positive. We are the first, to our knowledge, to examine whether firms use economic outlook to determine their payout policy. Our paper motivates future research in corporate finance to examine how firms use economic outlook when making capital planning decisions.

ANALYSIS OF INVESTMENT DECISIONS, FUNDING DECISIONS, FINANCIAL RISK MANAGEMENT IMPACTS ON FINANCIAL DISTRESS WITH MODERATION OF GOOD CORPORATE GOVERNANCE IN MANUFACTURING INDUSTRY SECTORS LISTED ON THE INDONESIA STOCK EXCHANGE

Globally, the development of the manufacturing industry can be used as a parameter for national industrial development in a country. Therefore, to keep manufacturing companies continuing or developing, it is necessary to have clear policies in developing this manufacturing industry. Some manufacturing companies did not develop as expected because they experienced Financial Distress (FD). The study population was conducted at several manufacturing companies that experienced financial distress with the study period from 2015-2018. The research sample was determined by non-random sampling (purposive sampling) to determine which companies are included in the Financial Distress category. Of the 163 manufacturing companies listed on the Indonesia Stock Exchange / IDX for the 2015-2018 period, 32 companies were included in the FD category. In this study, Smart PLS software is used to analyze and prove the effect of investment decisions, capital decisions, and financial risk management on financial distress by using good corporate governance / GCG as a moderating variable. The results showed that capital decisions, financial risk management, and good corporate governance had a significant effect on financial distress, except that investment decisions had no significant effect on financial distress. GCG significantly moderates the effects of investment decisions, capital decisions, and financial risk management on financial distress.

WITHDRAWN: Venture capital decision based on FPGA and machine learning

Abstract Venture capital decision based Machine Learning is the Intelligence is a way to build, economic and execute stock market that allow you to make your own decisions. Global market intelligence technology attracts a wide range of people by making it an essential adaptation of various industries internal activities. It accelerates all internal (external or internal) tasks by increasing the focus on data-based decision-making methods. The traditional sub-sectors of the financial services venture capital industry have a lot to do with human interaction. Venture capital investment is considered a high-risk, high-return asset class. In the previous method based on IOT (Internet of Thing) and data mining for Venture capital decision. The existing method gives the data security, personal security, low data monitoring. The proposed method is based on FPGA (Field Programmable Gate Arrays) and Machine learning for Venture capital decision. Venture investment decisions can use machine learning to apply pre-optimized transactions, company data, founder data, etc. Understand how venture capitalists use artificial intelligence tools and methods to improve venture capital decisions. By focusing on the following eight value chain areas involved in commercial procurement, contract selection, valuation, transaction formation, post-investment appreciation, termination, and the company's internal and external enterprise-decision-making venture capital to improve human decision-making in the venture capital industry FPGA (Field Programmable Gate Arrays) tools and machine learning techniques can be used to Determine how to use artificial intelligence in such critical scenarios and venture capital decisions and the advantages and disadvantages of using artificial intelligence systems.

Financing and Herd Behaviour in Financial Crises: Investment Decision

Purpose: The purpose of this study is to provide evidence related to the development of financing and herd behaviour in financial crisis arranging investment decision. Design/Methodology/Approach: This research is a type of literature study. The methodology used is through descriptive research with the support of theories and the findings from previous studies. Findings: Capital structure, as has been proven, affects investment decision in financial crisis period, as well as herd behaviour. The firm value can be influenced from the capital decision that gives signals to the market. However, researchers have not yet reached the optimum capital structure. In this paper, the authors find that recent literature on financing and herd behaviour provides some new insights into investment decision during financial crises. Practical Implications: Authors suggest further directions for increasing the investment strategy in stock market. Evaluating the financing and investment behaviour can lead to the expected return in terms of financial crises. Originality/Value: The authors’ approach can become the basis for investment decision in financial crises. The roles of financing and herd behaviour are really important for investment. There is still less research exploring the role of financial crises in funding decisions and herd behaviour in order to compose investment decision for investor in developed market context.

The role of heterogeneous risk preferences, discount rates, and earnings expectations in college major choice

We estimate a rich model of college major choice using a panel of experimentally-derived data. Our estimation strategy combines two types of data: data on self-reported beliefs about future earnings from potential human capital decisions and survey-based measures of risk and time preferences. We show how to use these data to identify a general life-cycle model, allowing for rich patterns of heterogeneous beliefs and preferences. Our data allow us to separate perceptions about the degree of risk or about the current versus future payoffs for a choice from the individual’s preference for risk and patience. Comparing our estimates of the general model to estimates of models which ignore heterogeneity in risk and time preferences, we find that these restricted models overstate the importance of earnings to major choice. Additionally, we show that while men are less risk averse and patient than women, gender differences in expectations about own-earnings, risk aversion, and patience cannot explain gender gaps in major choice.

THE DETERMINANTS OF BANK CAPITAL STRUCTURE IN THE WORLD

We examine the determinants of bank capital structure using a large sample of banks in the world. We find that banks determine their capital structure in much the same way as non-financial firms, except for growth opportunities. We also provide evidence that country-level factors, such as the legal system, bank-specific factors and economic conditions influence banks’ capital decisions through their impacts on bankruptcy costs, agency costs, information asymmetry and liquidity creation. The results show that, besides the direct effects, there are indirect impacts of country-level factors on the decision of bank capital. Our results have potential policy implications for the on-going regulatory reform.

Sunshine Fastech Pvt. Ltd.: working capital financing decision

Learning outcomes The learning outcomes of this paper is to understand the working capital finances offered by bank; comprehend application by the company, loan proposal and bank procedure for additional finance; compute, analyze and interpret financial statements of company and its peers; and assess various factors to be considered while taking loan sanctioning decisions. Case overview/synopsis Sunshine had expanded its business by starting in-house manufacturing of a few stages of production of fasteners. Sunshine was in urgent need of additional finance for working capital and had applied to Rajya Bank of India Ltd. (RBIL), requesting to enhance working capital finance limits and other changes. Ruchit Mehta, Relationship Manager of S.G. Highway Branch of RBIL have to assess this request and include his evaluations in the proposal, which he had to present to Assistant General Manager of RBIL. Complexity academic level MBA or related program in finance courses such as financial management, corporate finance, financial statement analysis, bank management/finance and training program on “credit management” for bank employees. Supplementary materials Teaching Notes are available for educators only. Subject code CSS 1: Accounting and Finance

A meta-analysis: capital structure and firm performance

PurposeThe paper aims at providing insights on the relationship between capital structure and performance of the firm by employing meta-analytical approach to obtain a synthesized result out of controversial studies as well as the sources for such inconsistency.Design/methodology/approachUsing secondary data, the analysis is divided into two main parts with concerns to the overall strength of the relationship, the effect size and the potential paper-specific characteristics influencing the magnitude of impacts between leverage and firm performance (moderators of the relationship). Overall, a total number of 32 journals, reviews and school presses were selected besides online libraries and publishing platforms. There were 50 papers with 340 studies chosen from 2004 to 2019, of which data range from 1998 to 2017.FindingsUsing Hedges et al. (1985,1988), descriptive and quantitative analysis have been conducted to confirm that corporate performance is negatively related to capital decisions, which inclines toward trade-off model with agency costs and pecking order theory. The estimation induces rather small effect size that implies sufficiently large sample size to be effectively investigated. In terms of moderator analysis, random-effects meta-regression models of three different techniques are used to increase the robustness in research findings, showing statistically significant elements as publication status, factor of industry and proxy of firm performance.Originality/valueThis paper is one of the first papers presenting meta-analysis in capital structure and performance for two languages, Vietnamese and English, providing a consistent result with previous worldwide papers.

Pollution, Ability, and Gender-Specific Investment Responses to Shocks

AbstractThis paper explores how labor market conditions drive gender differences in the human capital decisions of men and women. Specifically, I investigate how male and female schooling decisions respond to an exogenous change in cognitive ability. Using data from Mexico, I begin by documenting that in utero exposure to thermal inversions, which exacerbate air pollution, leads to lower cognitive ability in adulthood for both men and women. I then explore how male and female schooling decisions respond differentially to this cognitive shock: for women only, pollution exposure leads to reduced educational attainment and income. I show that this gender difference is explained by the fact that women disproportionately sort into white-collar jobs, where schooling and ability are more complementary than they are in blue-collar jobs.

Women in surgery: a capital decision.

Women in surgery: a capital decision.

Equity versus Asset Acquisitions in the REIT Industry

Real estate investment trust (REIT) acquisitions are recurrent capital allocation decisions that impact the value and operations of the firm. Although REIT equity acquisitions have received considerable attention in the literature, the effects of major asset acquisitions require further scrutiny. We examine the impact of acquisition type on REIT market returns and operating performance. The results suggest no significant differences in market reaction to the form of acquisition. We interpret this as evidence in favor of efficiency in REIT acquisition decisions. However, the results suggest a net positive effect in operating performance of asset acquisitions relative to equity acquisitions, conditioned by firm and deal characteristics. Overall, our results suggest that asset acquisitions are more efficient in the long run. We provide evidence that the type of acquisition is relevant to firm operations.

Asset Pricing Through Downside Risk Based Arbitrage Pricing Theory: Empirical Evidence from Pakistan Stock Exchange

This study extends the downside risk applications in multifactor asset pricing model by incorporating the downside risk spillovers from economic and financial factors to stock returns. We amplify the conventional APT model by replacing the variance-based betas with semivariance based downside betas that better capture the risk volatilities in varying market conditions. The inclusion of downside risk betas based on semivariance and semideviation methods in the augmented asset pricing model improves both the theoretical and methodological applications relative to the limitations and restriction of conventional APT factors model. The mean-variance hypothesis replaced by meansemivariance hypothesis and asymmetric behaviour of stock returns distribution, empirically suggest the use of an alternative factors model. The models based on downside risk premia for asset pricing in emerging markets. The study tested the downside risk-return relationship based on the excess monthly stock returns of listed PSX firms and observed economic, financial and global factors representing spillover triangulation from 1997 to 2017. The findings of the study indicate that the augmented DR-APT model with pricing restrictions of unconditional linear factors method could not be deserted over the targeted period of study. The selected observed pricing factors except exports are significant enough for pricing the security returns in the augmented DR-APT Model. Findings of the panel regression, likelihood ratio tests and F-test corroborate DR-APT as a better model to price stock returns in volatile situations compare to conventional APT model. Our findings are consistent with the downside risk-return framework based on mean semi variance hypothesis and have implications for managers and decision markets that incorporate downside risk in asset valuation, cost of capital estimations, portfolio construction and investment analysis decisions. Key Words: Downside Risk, Semi variance, Semi covariance, Downside Beta, Downside risk-based Arbitrage Pricing Theory (DR-APT).