Stock Turnover Research Articles

Capital Market Performance and Bangladesh’s Economy: An Empirical Study

This article aims to analyse the effect of capital market performance on Bangladesh’s economy using the data of market capitalization, stock turnover and gross domestic product (GDP) growth from 2001 to 2018. This study employed unit root test, Johansen cointegration test, vector error correction model, autoregressive distributed lag model, non-linear autoregressive distributed lag model, Granger causality test and Toda–Yamamato Granger non-causality test to examine this effect. The result of the vector error correction model revealed the existence of a long-run association between market capitalization and stock turnover as independent variables with GDP. Again, the results of autoregressive distributed lag model and non-linear autoregressive distributed lag model also showed that there exists a significant positive relationship between the stock market and GDP of Bangladesh. Finally, Toda–Yamamato Granger non-causality test confirms that there is a unidirectional causality running from the capital market to GDP.

The Ability of Financial Ratios to Predict the Index of Banking Sector in Amman Stock Exchange: An empirical study

The main objective of this study is to test the predictive power of the financial ratios (ownership ratio, liquidity ratio, debt ratio, stock turnover ratio, return on equity ratio, return on total assets ratio, and market to book ratio) on the performance of the banking sector in Amman Stock Exchange (ASE). The analysis relies on yearly data for the period 2000-2014. The sample consists of fourteen banks listed on Amman Stock Exchange. Using the ordinary least square method (OLS), we regress the seven selected variables against the index of the banking sector. The findings show that the financial ratios can predict the behavior of the index in the banking sector. There is a statistically significant positive relationship between the liquidity ratio, debt ratio, stock turnover ratio, return on total assets ratio, market to book ratio with the banking index. While the return on equity is negatively associated with the banking index. There is no statistically significant relationship between the ownership ratio and the index in the Amman Stock Exchange.

The Impact of Foreign Ownership on Stock Price Volatility: Evidence from Thailand

This paper examines the impact of foreign ownership on stock price volatility in an emerging market, namely, Thailand. The data were obtained from SETSMART, the database of the Stock Exchange of Thailand (SET). After removing financial firms, banks, and insurance companies as well as filtering outliers, the final sample covers 1,755 firm-year observations from 371 nonfinancial firms listed on the SET over the five-year period from 2014 to 2018. The regression model consists of stock price volatility, measured by two methods, as the dependent variable, foreign ownership as the main independent variable, and firm characteristics including firm size, leverage, market-to-book ratio, and stock turnover as the control variables. The pooled OLS, fixed effects, and random effects estimations are employed to examine the relationship between foreign ownership and stock price volatility. The results reveal that foreign ownership has a negative and significant impact on stock price volatility. The two-stage least squares (2SLS) are also performed to address potential endogeneity problem. The results still indicate a negative relationship between foreign ownership and stock price volatility. Taken together, the findings of this study suggest that foreign investors help reduce stock price volatility and thus stabilize share price in the Thai stock market.

<i>Corrigendum to:</i> Impacts of fire on soil organic carbon stocks in a grazed semi-arid tropical Australian savanna: accounting for landscape variability

Fire and grazing are commonplace in Australian tropical savannas and the effects of these management practices on soil organic carbon stocks (SOC) is not well understood. A long-term (20 years) experiment studying the effects of fire on a grazed semi-arid tropical savanna was used to increase this understanding. Treatments, including frequency of fire (every 2, 4 and 6 years), season of fire [early (June) vs late (October) dry season] and unburnt control plots, were imposed on Vertosol grassland and Calcarosol woodland sites, which were grazed. Additionally long-term enclosures [unburnt (except the Calcarosol in 2001) and ungrazed since 1973] on each soil type adjacent to each site were sampled, although not included in statistical analyses. SOC stocks were measured to a soil depth of 0.3m using a wet oxidation method (to avoid interference by carbonates) and compared on an equivalent soil mass basis. Significant treatment differences in SOC stocks were tested for, while accounting for spatial background variation within each site. SOC stocks (0–0.3m soil depth) ranged between 10.1 and 28.9tha<sup>–1</sup> (Vertosol site) and 20.7 and 54.9tha<sup>–1</sup> (Calcarosol site). There were no consistent effects of frequency or season of fire on SOC stocks, possibly reflecting the limited statistical power of the study and inherent spatial variability observed. Differences in the response to frequency and season of fire observed between these soils may have been due to differences in clay type, plant species composition and/or preferential grazing activity associated with fire management. There may also have been differences in C input between treatments and sites due to differences in the herbage mass and post-fire grazing activity on both sites and changed pasture composition, higher herbage fuel load, and a reduction in woody cover on the Vertosol site. This study demonstrated the importance of accounting for background spatial variability and treatment replication (in the absence of baseline values) when assessing SOC stocks in relation to management practices. Given the absence of baseline SOC values and the potentially long period required to obtain changes in SOC in rangelands, modelling of turnover of SOC in relation to background spatial variability would enable management scenarios to be considered in relation to landscape variation that may be unrelated to management. These considerations are important for reducing uncertainty in C-flux accounting and to provide accurate and cost-effective methods for land managers considering participation in the C economy.

Under COVID-19 Research on the Impact of Supermarket Participation in Farming‑Supermarket Docking Supply Chain

본 연구는 중국의 우한을 시작으로 지난 2020년 초부터 전 세계적으로 대유행한 코로나19와 같은 갑작스러운 외부 환경 변화요인에 의하여 농산물 공급 체인의 혼란이 야기되었을 때, 소비자들에게 신선한 농산물 공급의 안정과 품질을 담보하기 위하여 “생산자와 슈퍼마켓 유통업자 간의 공급체인 상에서 영향을 미치는 요인”을 연구하고자 하였다. 연구방법으로는 생산자와 슈퍼마켓유통 체인 간의 공급망에서 각자의 역할에 대한 참여의지에 영향을 미치는 주요 요인을 도출하여 설문하였으며, 이를 통해 공급자와의 관계, 공급자의 능력, 공급사슬 내의 환경, 슈퍼마켓운영자의 기대치와 인식된 품질에 영향을 미친다는 것을 확인할 수 있었다. 또한, 공공 비상환경에 대응하기 위하여 품질개선에 대한 공급자의 인식 전환을 통하여 슈퍼마켓 체인의 유통환경을 개선할 수 있으며, 공급관계 강화 및 공급능력 강화, 공급환경의 최적화, 슈퍼마켓 체인의 참여 의지를 더욱 강화하는데 도움이 된다는 것을 확인할 수 있었다.Purpose: The sudden outbreak of COVID-19 became a challenge to the supply chain stability of fresh agricultural products in supermarkets. When dealing with major public emergencies, the supply chain is unstable or even broken. Insufficient upstream supplier production and operation ability causes lack of timely supply. The supermarket s own scheduling, inventory capacity, and so on are insufficient to meet the needs of downstream consumers, which leads to lesser customer satisfaction and the loss of many loyal customers. Therefore, improving the supply capacity of upstream suppliers, accelerating stock turnover, and meeting the needs of downstream consumers have become pressing problems for supermarkets. Research design, data, methodology: Considering the supermarket as the research object and examining the actual situation of “Farmer-Supermarket Docking” under COVID-19, this paper summarizes the main factors influencing the willingness of supermarkets to participate in the “Farmer-Supermarket Docking” supply chain .Through a questionnaire survey to obtain data, We propose hypotheses and establish models. Results: The factors influencing supermarkets participation in the “Farmer-Supermarkets Docking” supply chain are docking advantage, docking relationship, docking ability, docking environment, through supermarket expectation lead to significant and positive effect on supermarket participation. Docking advantage and docking ability through perceived quality have significant and positive influence on supermarket participation. Conclusions: To help supermarkets in the face of major public emergencies, there is need to enhance docking advantage, consolidate docking relationship, strengthen docking ability, optimize docking environment, improve perceived quality, and meet supermarket expectations, which are all conducive to increasing the willingness of the supermarket to participate in “famer-supermarket Docking” and stabilize the supply chain.

Turnover premia in China's stock markets

This paper explores turnover premia in China's stock markets. There is a negative cross-sectional relation between turnover and average realized returns. Turnover premia, which is the return on buying low turnover stocks and shorting high turnover stocks, can reach 34% per annum. In effect, turnover in China's stock markets can be explained mainly by both liquidity risk and firm-specific uncertainty. Turnover premia are more pronounced for firms with higher cash flow risk, an indicator of firm-specific uncertainty. Cash flow risk could also amplify the turnover premia of option-like firms.

Stock Turnover Prediction Using Search Engine Data

The stock turnover values are sensitive to external factors, and remain great challenges in its prediction. The consideration is that search engine data can reflect market environment, policies and attentions on stocks. Therefore, a dual sides autoregression (DSAR) method is proposed to benefit from both observed turnover values and exogenous data. The proposed DSAR consists of linear representation stage and combination stage. In linear representation stage, the short-term patterns of turnover values and query data are represented, respectively. In combination stage, the outputs from previous stages are combined. Intensive experiments on two groups of data collections show the effectiveness of our proposed method.

Microeconomic Firm Characteristics and Long Run Returns: The Case of Firms That Issued Equity at Nairobi Securities Exchange

This study looks at micro-economic determinants of long run performance of shares issued in Nairobi Securities Exchange from 1st Jan. 2007 to 31st Dec.2013. Do these selected microeconomic determinants have statistically significant effects on long run return on equity issued in the Nairobi security exchange in Kenya? The study has a total 12 firms that issued shares in the security exchange during this period. In order to achieve the objectives of the study “a calendar study” approach on the issued shares was adopted. Monthly average returns were calculated for a period of 5 years. Nine hypotheses were deduced and executed. Three were based on benchmarks namely: Nairobi Securities Exchange Index (NSEI), Capital Asset Pricing Model (CAPM) and Matching Firms (MF). Along with the 3 mentioned measurement models, other 6 micro-economic variables were incorporated in the study; firm size, offer size, stock turnover, book/ market ratio, age and quality of underwriter. A panel data multi-regression and single regression analysis were run to examine the relationship between average return and micro-economic determinants on firm performance in the long run. The results of the study showed that the study corresponds with some of results of the previous studies with regard to the long run returns of either under or over performance. The level of under of over performance based on the benchmarks used were that NSEI and Matching firms performed better than firms that issued equity. However firms that issued equity performed better than CAPM as bench mark. The study also revealed that two explanatory variables; Age and Quality of underwriter were statistically significant as determinants of long run performance. Finally two independent variables were found to have positive influence on firms that issued equity in the NSE. In conclusion this study confirmed the results of previous studies done either supporting certain variables as determinants of long run return or do not support certain variables as determinants of long run return.

Does Partisanship Shape Investor Beliefs? Evidence from the COVID-19 Pandemic

We use party-identifying language—like “liberal media” and “MAGA”—to identify Republican users on the investor social platform StockTwits. Using a difference-in-difference design, we find that partisan Republicans remain relatively unfazed in their beliefs about equities during the COVID-19 pandemic, while other users become considerably more pessimistic. In cross-sectional tests, we find Republicans become relatively more optimistic about stocks that suffered the most during the COVID-19 crisis, but more pessimistic about Chinese stocks. Finally, stocks with the greatest partisan disagreement on StockTwits have significantly more trading in the broader market, explaining 28% of the increase in stock turnover during the pandemic.

Decarbonizing US passenger vehicle transport under electrification and automation uncertainty has a travel budget

The transportation sector is at the beginning of a transition represented by electrification, shared mobility, and automation, which could lead to either increases or decreases in total travel and energy use. Understanding the factors enabling deep decarbonization of the passenger vehicle sector is essential for planning the required infrastructure investments and technology adoption policies. We examine the requirements for meeting carbon reduction targets of 80% and higher for passenger vehicle transport in the United States (US) by midcentury under uncertainty. We model the changes needed in vehicle electrification, electricity carbon intensity, and travel demand. Since growth in fleet penetration of electric vehicles (EVs) is constrained by fleet stock turnover, we estimate the EV penetration rates needed to meet climate targets. We find for a base case level of passenger vehicle travel, midcentury deep decarbonization of US passenger transport is conditional on reducing the electricity generation carbon intensity to close to zero along with electrification of about 67% or 84% of vehicle travel to meet decarbonization targets of 80% or 90%, respectively. Higher electricity generation carbon intensity and degraded EV fuel economy due to automation would require higher levels of fleet electrification and/or further constrain the total vehicle travel allowable. Transportation deep decarbonization not only depends on electricity decarbonization, but also has a total travel budget, representing a maximum total vehicle travel threshold that still enables meeting a midcentury climate target. This makes encouraging ride sharing, reducing total vehicle travel, and increasing fuel economy in both human-driven and future automated vehicles increasingly important to deep decarbonization.

Investor Attention, Market Dynamics, and Momentum in the Korean Stock Market

This study examines the effects of investor attention on momentum in the Korean stock market. The results reveal significant negative momentum profits in stock groups with high investor attention (high turnover stocks), but insignificant results in those with low investor attention (low turnover stocks). Within high turnover stock groups, the winner portfolio has a declining price trend and insignificant performance, while the loser portfolio realizes significant positive performance through a substantial price increase in the future period. The momentum effect is highly dependent on the reversed performance of the loser portfolio. Second, the performance of the large overreaction stock group shows a more significant negative momentum effect compared to the low overreaction stock group, that is, the degree of overreaction significantly affects the momentum effect. Third, negative momentum profits are consistently observed regardless of the market dynamics. Specifically, more substantial and significant negative performance occurs in the transition market, where the market situation reverses between the past and future periods. Fourth, negative momentum profits are consistently identified even after controlling for the impact of common factors and volatility and liquidity into turnover. Our findings are qualitatively different from the characteristics of the traditional momentum effects generally reported in Western countries.

Evaluation of Senegal supply chain intervention on contraceptive stockouts using routine stock data.

BackgroundUntil 2011, stockouts of family planning commodities were common in Senegalese public health facilities. Recognizing the importance of addressing this problem, the Government of Senegal implemented the Informed Push Model (IPM) supply system, which involves logisticians to collect facility-level stock turnover data once a month and provide contraceptive supplies accordingly. The aims of this paper were to evaluate the impact of IPM on contraceptive availability and on stockout duration.Methods and findingsTo estimate the impact of the IPM on contraceptive availability, stock card data were obtained from health facilities selected through multistage sampling. A total number of 103 health facilities pertaining to 27 districts and nine regions across the country participated in this project. We compared the odds of contraceptive stockouts within the health facilities on the 23 months after the intervention with the 18 months before. The analysis was performed with a logistic model of the monthly time-series. The odds of stockout for any of the five contraceptive products decreased during the 23 months post-intervention compared to the 18 months pre-intervention (odds ratio, 95%CI: 0.34, 0.22–0.51).To evaluate the impact of the IPM on duration of stockouts, a mixed negative binomial zero-truncated regression analysis was performed. The IPM was not effective in reducing the duration of contraceptive stockouts (incidence rate ratio, 95%CI: 0.81, 0.24–2.7), except for the two long-acting contraceptives (intrauterine devices and implants). Our model predicted a decrease in stockout median duration from 23 pre- to 4 days post-intervention for intrauterine devices; and from 19 to 14 days for implants.ConclusionsWe conclude that the IPM has resulted in greater efficiency in contraceptive stock management, increasing the availability of contraceptive methods in health facilities in Senegal. The IPM also resulted in decreased duration of stockouts for intrauterine devices and implants, but not for any of the short-acting contraception (pills and injectables).

DEMAND FORECASTING FOR HIGH-TURNOVER SPARE PARTS IN AGRICULTURAL AND CONSTRUCTION MACHINES: A CASE STUDY

Conventional demand forecasting and inventory management models cannot be applied to replacement parts due to their intermittent and seasonal demand. Thus the aim of this study is to compare, in the case of the strategic stocking of high turnover replacement parts, the demand forecast model currently used by construction and agricultural machinery companies with the Box-Jenkins statistical model. The results show that it is important to use a methodology based on statistical techniques in inventory management, and that the proposed model adapts better to high turnover stock control.

Building Vulnerability Predictive Indicator for the Banking Sector

Abstract
 For risk and capital measurement, banks and other financial institutions need to meet forthcoming regulatory requirements. However, it is a serious issue to think that meeting regulatory requirements is the sole or even the most important reason for establishing a scientific, sound risk management system. To direct capital to activities with the best risk/reward ratios, managers need reliable risk measures. To stay within the limits imposed by readily available liquidity, by creditors, customers, and regulators, they need estimates of the size of potential losses. They need mechanisms to monitor positions and create incentives for prudent risk-taking by divisions and individuals. Risk measurement deals with the quantification of risk exposures, whereas risk management refers to the overall process by which managers satisfy these needs and follows to define a business strategy, to detect the risks to which are visible, quantifying those risks, and to control and understand the nature of the risks it faces. This research focuses on the economic vulnerability faced by banks in the financial sector in terms of the crises issues perspective of economic distress. Here, the methodology followed is based on the CAMELS framework variables. CAMELS is an abbreviation for: capital adequacy (C), asset (A), management (M), earnings (E), liquidity (L) and sensitivity to market risk (S). Based on these terminologies, a couple of variables should be selected, such as capital asset ratio, non-performing loan, cost income ratio, industry production index, non-interest income, reserve of gold, inflation, stock turnover ratio, real interest rate as component series and return on equity (RoE) as reference series to identify the turning points of economic vulnerability in the banking sector in Bangladesh. Thus, by forecasting the directional changes it could make policymakers aware of changes in the financial markets and banking economy and allow them to undertake preventive steps for remedial purposes. The constructed MPI should have a remarkable lead time of about not less than 6 months on average in case of prediction against the leading for reference Series.By mending the financial efficacy of investment banks. Bangladesh also should improve their corresponding banking system to implement these suggestions.

Developing a generic System Dynamics model for building stock transformation towards energy efficiency and low-carbon development

Promoting the decarbonisation of buildings requires effective policy measures. An integral part of policy design is ex-ante evaluation of possible policy options and effects. System Dynamics, one of a range of potential modelling paradigms, emphasises the dynamic complexity arising from stock-and-flow structures, feedbacks, non-linearities and time lags of the system in question. It is therefore well placed to model building stock turnover dynamics and the associated energy use and carbon emissions, in order to conduct scenario analysis for policy evaluation. Previous efforts to employ System Dynamics based models in buildings in various national contexts are found to have some common fundamental structural and behavioural limitations. We present an improved formulation that includes both building stock disaggregation and dynamics of energy-related retrofits. The model is characterised by greater transparency facilitating reproducibility and further improvements, high structural and functional flexibility for either extensions or reductions depending upon needs, and high generality and adaptability in diverse applications. It can be used as a stand-alone model or as part of a larger model for policy evaluation and scenario analysis exploring the transformation of building stock from improving energy efficiency and shifting towards low-carbon development.

Forecasting urban residential stock turnover dynamics using system dynamics and Bayesian model averaging

Knowing the size of building stock is perhaps the most basic determinant in assessing energy use in buildings. However, official statistics on urban residential stock for many countries are piecemeal at best. Previous studies estimating stock size and energy use make various debateable methodological assumptions and only produce deterministic results. This paper presents a Bayesian approach to characterise stock turnover dynamics and estimate stock size uncertainties, applied here to China. Firstly, a probabilistic dynamic building stock turnover model is developed to describe the building aging and demolition process, governed by a hazard function specified by a parametric survival model. Secondly, using five candidate parametric survival models, the building stock turnover model is simulated through Markov Chain Monte Carlo to obtain posterior distributions of model-specific parameters, estimate marginal likelihood, and make predictions of stock size. Thirdly, Bayesian Model Averaging is applied to create a model ensemble that combines model-specific posterior predictive distributions of the recent historical stock evolution pathway in proportion to posterior model probabilities. Finally, the Bayesian Model Averaging model ensemble is extended to forecast future trajectories of residential stock development through 2100. The modelling results suggest that the total stock in China will peak around 2065, at between 42.4 and 50.1 billion m2. This Bayesian modelling framework produces probability distributions of annual total stock, age-specific substocks, annual new buildings and annual demolition rates. This can support future analysis of policy trade-offs across embodied-versus-operational energy consumption, in the context of sector-wide decarbonisation.

Does Partisanship Shape Investor Beliefs? Evidence from the COVID-19 Pandemic

We use party-identifying language – like “Liberal Media” and “MAGA”– to identify Republican users on the investor social platform StockTwits. Using a difference-in-difference design, we find that the beliefs of partisan Republicans about equities remain relatively unfazed during the COVID-19 pandemic, while other users become considerably more pessimistic. In cross-sectional tests, we find Republicans become relatively more optimistic about stocks that suffered the most from COVID-19, but more pessimistic about Chinese stocks. Finally, stocks with the greatest partisan disagreement on StockTwits have significantly more trading in the broader market, explaining 28% of the increase in stock turnover during the pandemic.

The Impact of Financial Information on Noise Traders: Based on the Perspective of Behavioral Finance

<p>In China's incomplete stock market which mainly consists of retail games and short-term operations, both of the high stock turnover rate and P/E ratios reflect excessive noise trading. This article focuses on the characteristic that individual investors are susceptible to financial media information, combined with the development and characteristics of financial media. From the perspective of behavioral finance, this paper analyzes the impact of financial media on noise trading. Using behavioral finance and psychology-related knowledge, investor behavior can be better understood, so as the motivation behind noise trading. Finally, in order to promote the healthy development of the stock market, this paper makes recommendations to improve the efficiency of the capital market.</p>

The Role of Powertrain Electrification in Achieving Deep Decarbonization in Road Freight Transport

Decarbonizing road freight transport is difficult due to its reliance on fossil fuel internal combustion engine vehicles (ICEVs). The role of powertrain electrification in achieving deep decarbonization in road freight transport was studied using a vehicle stock turnover model, focusing on Japan. Twelve vehicle types were considered; combining four powertrains, ICEV, hybrid electric vehicle (HEV), battery electric vehicle (BEV) and fuel cell electric vehicle (FCEV); and three vehicle size classes, normal, compact and mini-sized vehicles. A scenario-based approach was used; considering a Base scenario, and three alternative scenarios targeting powertrain electrification. Between 2012 and 2050, tank to wheel CO2 emissions decrease 42.8% in the Base scenario, due to the reduction of vehicle stock, the improvement of vehicle fuel consumption and the adoption of HEVs. Diffusion of FCEVs in normal vehicles and BEVs in compact and mini-sized vehicles achieves the largest tank to wheel CO2 emissions reductions, up to 44.6% compared with the 2050 baseline value. The net cash flow is positive over the whole time horizon, peaking at 6.7 billion USD/year in 2049 and reaching 6.6 billion USD/year by 2050. Powertrain electrification is not enough to achieve any of the CO2 emissions reduction targets in road freight transport.

Stock market mispricing and firm innovation based on path analysis

Based on a sample of Listed Companies in China between 2007 and 2018, this paper analyzes the impact of stock market mispricing on company’s innovation. The results demonstrate that when the stock price is overvalued, a company’s innovation investment will be higher, that is, overvaluation by the stock market is significantly positively related to firm innovation. In the path analysis, this paper finds that about 10% (RII, RVI, MPI) or 20% (MFFLOW) influence of stock mispricing on enterprise innovation is from financing demand. Further, this paper finds that the level of firm growth and stock turnover play a moderating role in the relationship between them. The conclusions of this paper are robust after a series of tests, such as instrumental variable, sub-sample test, two-way fixed effect and two-way cluster analysis.