Number Of Stocks Research Articles

Research on the Regeneration Procedure for Reutilizing Vacant Housing Stock in Japan

Since the economic development period in the 1960s and ’70s, old buildings were always considered unsuitable because of the risk of earthquakes or due to new social trends. But new construction finally dropped in the ’90s, and the birth rate also declined and the aging population grew instead. The number of vacant housing stocks have been more than doubled in Japan last 20 years, with 500,000 residences increased every year, and the issue of regeneration and reutilization of old buildings has become a focus. Yet it has not been easy to achieve successful outcomes because of many and complex impediments, interfere, such as legal, social, structural, economic, or tax-related reasons. In this study, through unraveling these complex impediments, effective countermeasures are organized and case examples of regenerated buildings that have overcome these barriers are introduced to clarify how each problem can be surmounted, and these regeneration procedures will be drawn in the shape of process planning that visualizes the steps of measures against each problem. There are five main problems: old housing plans against new social needs; degradation of building structure and materials against new building standards; old technical standards against new technologies; existing legally non-conforming buildings against ever-added new building laws; and old building reliability against possible economic value estimated. These five problems are used to clarify the regeneration procedure in order to propel and increase the fruitful utilization of this stock for the future.

내부자거래와 정보비대칭의 관계에 관한 연구

This study analyzes the pre-transaction period accounting earnings-stock price relation among companies with and without insider trade(insider sell and buy) to find out whether information asymmetry increase potential insider’s profit, thereby, motivate insider to trade their own stocks.
 In order to figure out correct relationship between insider trading and information asymmetry, this study recognize succesive insider trading, and use only first trade observation of succetive insider sell and buy, respectively. Therefore the total number of stocks and the first trade of each successive insider tradings are respectively presumed as an insider trading volume and as an observation of the the succesive insider trading.
 Also, all ownership information of directors and major shareholder is cellected from DART using Python, and quarterly financial information is used for our analysis to alleviate the possible problem coming from assumption of period of insider trading.
 The analysis period is from 2012 to 2018, and non-financial companies among listed companies on the Korea Stock Exchange and KOSDAQ are targeted.
 Empirical analysis shows as follow.
 First, it was found that the greater the over-estimate of earnings-return relation incurs greater probability of occurrence of insider stock sales and greater insider sales stock volume. These relationships are larger and more significant than those between insider trading and future earnings level, future earnings growth, and future stock return, which represent insiders' information advantage on future prospects of the firm. Second, the effect of estimation bias of earnings-return relation on the probability of insider sales was stronger and more immediate than those of insider purchases. The positive relationship between future prospects and insider trading, reported in previous studies, was stronger in insiders purchases than in insider sales.
 This study directly analyzed whether information asymmetry between insiders and external stakeholders plays a major role of insider trading, comparing pre-period earning-return relation estimates of insider trading firms with those of control firms. It is also meaningful in that it shows that the information asymmetry difference between insiders and external stakeholders can have different effects on insider trading for different properties of insider sales and purchase.

Volatilitas Indeks IDXMESBUMN Sebelum Dan Setelah Invansi Militer Rusia ke Ukraina

Volatility is a response from a portfolio or securities to a phenomenon that occurs. The response can be seen from the price changes of a number of stocks. The purpose of this study is to determine and analyze the return volatility of the Jakarta Islamic Index (JII) to the phenomenon of the Russian military invasion of Ukraine. The research method used is the analysis of different returns before and after the military invasion in the form of data 5 days before and 5 days after the invasion by using data sourced from the Indonesian stock exchange in the form of data as many as 17 companies that are members of the MESBUMN index. The results showed a significant value of 0.478, so there was a significant difference in the IDXMESBUMN index returns before and after the Russian military invasion.

Risks and adaptation options for the Mediterranean fisheries in the face of multiple climate change drivers and impacts

Abstract The Mediterranean Sea is among the most vulnerable semi-enclosed seas to climate change. Multiple oceanic changes occur besides warming that can generate numerous ecological, social, and economic risks, challenging fisheries management at various spatial scales—from local to international. In this study, we applied a semi-quantitative climate risk assessment (CRA) to the Mediterranean small pelagic and demersal fisheries in relation to a diversity of climate-related drivers and impacts. We assessed the risks of climate change effects on demersal and small pelagic fisheries resources, fishing operations, livelihoods, and wider social and economic implications in seven sub-regions of the Mediterranean Sea. Ocean warming, an increase in extreme weather events, and changes in vertical stratification resulted in the most important climate drivers. Overall, climate drivers present higher risks to fishing resources and livelihoods than to fishing operations and wider social and economic impacts. The study puts into evidence geographic differences in terms of the drivers and impacts, with the south-eastern Mediterranean being the sub-region with higher risk levels for both fisheries, while the north-central Mediterranean also showed important risk levels for the demersal fisheries. The study furthermore discusses the most plausible adaptive measures in management, policy, research, and livelihoods to be potentially applied to address high priority risks, as well as various implementation concerns and technical effectiveness issues. Enhancing adaptive fisheries management needs to be the primary strategy for this region to reverse the high number of overfished stocks and build resilience to climate change.

Integrated optimization of train formation plan and rolling stock scheduling under Time-dependent demand

Both train formation plan (TFP) and rolling stock scheduling (RSS) have significant impacts on train operation. However, traditional sequential optimization could lead to infeasible RSS for the predetermined TFP, especially when the number of available rolling stocks is limited. This paper focuses on integrally optimizing TFP and RSS, where each train service can utilize different train formations and multiple turnaround operations occur in the depot. The key to solving the problem is to determine how many formations are needed for each train service and how train services are connected by rolling stocks. The multiple turnaround operations include immediate turnaround, turnaround with entering/exiting depot operations, and turnaround with coupling/decoupling operations. Considering the fixed costs and operating costs, we propose a multi-objective mixed-integer nonlinear programming (MINLP) model to minimize the number of rolling stocks (NR), the number of formations (NF), and the number of coupling/decoupling operations (NC) based on the time–space network. The model is further reformulated into a single-objective mixed-integer linear programming (MILP) model by the linearization method and fuzzy programming, and the reformulated model can be effectively solved by the MILP solver CPLEX. We test the model on realistic instances of the Batong Line in Beijing Subway Network to verify its effectiveness. The results demonstrate that the integrated model effectively solves the shortage of rolling stocks when the number of available rolling stocks is limited. Furthermore, in the integrated model, the decrease in the number of the rolling stocks and coupling/decoupling operations are at the cost of more formations used to balance the conflicts among objectives.

Do the Underlying Portfolios Matter? A Comparative Study of Equity-Linked Pay-at-Maturity Principal Protected Notes in Canada and the UK

This study examines the relationship between the return and the holding cost of equity-linked pay-at-maturity principal protected notes (EL-PAM-PPNs) and the mean return and volatility of the underlying portfolio using 1568 EL-PAM-PPNs issued in the UK and Canada between 2003 and 2015. We find that: (i) the underlying portfolio’s mean return decreases the note holding cost; (ii) the underlying portfolio’s volatility increases the note return and decreases the note holding cost; (iii) investors could maximize note return and minimize holding costs by choosing EL-PAM-PPNs prudently. Investors in both countries should purchase notes with higher participation rates, where the underlying portfolio contains a higher number of stocks and lower expected volatility. UK investors should avoid callable notes and choose notes with a longer time to maturity, where payoff is determined by a single observation of the underlying portfolio’s value at maturity. Surprisingly, Canadian investors should choose callable notes and notes with a shorter time to maturity, where payoff is determined by the average of multiple observations of the underlying portfolio’s value over the life of the note. They should also look for notes that include a guaranteed positive return, and where the underlying asset has a higher dividend yield.

Vegetative propagation of Epimedium elatum C. Morren and Decne.

Epimedium L. is a celebrated medicinal genus of Chinese pharmacopoeia comprising of sixty two species, with only one species, Epimedium elatum C. Morren and Decne., in Indian subcontinent. The species is endemic to Kashmir Himalaya and grows wild as undergrowth in forests. It is a slow-growing and slow-reproducing medicinal herb, with a huge potential for being exploited for therapeutic uses, thereby necessitating its conservation, cultivation and propagation. In this context, the present work has been undertaken to develop its propagation protocol. In spring, rhizomes were divided into different sizes on the basis of the number of buds and fresh mass; planted in 10 cm pots and then evaluated for survival, growth, production and multiplication. Similarly, the divisions were made in different seasons to study the seasonal effect. Single bud divisions, with or without roots, were also made to study the effect of IBA on rooting. Rhizome divisions of larger size produced plants with the best growth characteristics and propagation potential. Plants produced from the rhizome divisions of small size didn’t flower, but showed high bud production efficiency. Rhizome divisions of spring significantly produced plants of bigger size, with better growth characteristics, than plants produced from divisions of summer and autumn. When treated with different concentrations of IBA, single-bud divisions without roots, rooted successfully; however, rooting and survival rate was significantly higher at IBA concentration of 800 ppm as compared to other two IBA concentrations. The present study indicates that small size divisions can be used in nurseries to produce more plants from a smaller number of mother stock, while large size divisions can be used to produce and cultivate mature plants. Though division of Epimedium elatum rhizomes can be undertaken at any time of the growing season, spring is the best season.

Peramalan Penjualan Produk Sepatu dengan Menggunakan Metode Double Moving Average (DMA)

Halim Jaya Kisaran shop is one of the trading businesses that sells people's basic needs such as shoes and bags. This store requires forecasting in an effort to process data and generate accurate reports. This is done because the Halim Jaya Kisaran Store to determine the demand for shoes is unpredictable, so it often experiences a lack of shoes to be purchased in order to serve the demand for shoes needed by customers. In designing this system, the author uses the Double Moving Average (DMA) forecasting method for the decision support process in determining the number of shoe stocks to be sold for the next month, using the calculation method. This forecasting application was created using the Visual Basic Net 2010 programming language with Microsoft Access as the database. From making the system an application can be produced that can control optimal and economical demand and with a high level of accuracy and can predict the number of shoe requests at the Halim Jaya Kisaran Store so that the forecast results can help the store to avoid running out of stock of shoe requests at the Halim Jaya Kisaran Store

Unraveling feed and nutrient use efficiencies in grassland-based dairy farms

Grassland-based dairy farms are important for the provisioning of milk and ecosystem services. However, the key factors and interactions that influence the feed use efficiency of grassland-based dairy farms in practice are not well known and understood, and as a consequence no well-targeted recommendations can be provided. This paper addresses the question ‘what are the main factors that determine the variations in calculated feed efficiency and N and P use efficiencies on dairy farms subjected to agri-environmental regulations’. Monitoring and modeling data from ~12000 grassland-based dairy farms in The Netherlands over a 4 year period (2017–2020), collected through the KringloopWijzer model, were analyzed and the data from 2020 were statistically analyzed in detail. Farms greatly differed in milk production intensity (range < 10 to >25 Mg per ha per yr) and in the amount of purchased feed. The 5 and 95 percentile values of frequency distribution of the calculated annual mean feed efficiency at herd level were 0.9 and 1.3 kg milk per kg feed dry matter, respectively. Feed efficiency was statistically related to milk yield and number of young stock per cow, the share of concentrates and silage maize in the ration, and the net energy content of silage grass. At herd level, the 5 and 95 percentile values of the calculated annual mean N use efficiency increased with feed efficiency from 21 to 28%, and those of the annual mean P use efficiency from 32 to 40%. Contrary to expectations, mean surpluses of N and P at farm level remained more or less constant with feed efficiency and the intensity of milk production, but the amounts of purchased feed and manure export strongly increased with the intensity of milk production. The N and P surpluses and use efficiencies at farm level were sensitive to accounting for the externalization of feed production and manure utilization. The modeled ammonia and methane emissions per kg milk produced were relatively low on farms with high feed efficiency. In conclusion, feed use and N and P use efficiencies are key indicator for the profitability and environmental performance of dairy farms. Differences between farms in these key indicators were large, and these differences were related to a limited number of explanatory variables. Our study provides lessons for improving the profitability and environmental performance of grassland-based dairy farms.

A portfolio stock selection model based on expected utility, entropy and variance

In the context of investment decision-making, the selection of stocks is important for a successful construction of portfolios. In this paper the expected utility, entropy and variance (EU-EV) model is applied for stock selection, which can be used as preselection model for mean–variance portfolio optimization problems. Based on the EU-EV risk, stocks are ranked and the best ranked stocks with lower risk are selected in order to form subsets of stocks, which are then used to construct portfolios. The EU-EV model is applied to the PSI 20 index, to the Euro Stoxx 50 index and to the Nasdaq 100 index. Subsets of selected stocks are analysed and their portfolios’ efficiencies are compared with those of the portfolios obtained from the whole set of stocks using the mean–variance model. The results reveal that the EU-EV model is an adequate stock selection model for building up efficient portfolios with a lower number of stocks.

A Novel Weighted Hybrid Recommendation System using Sharpe Ratio for a Profitable Diversified Investment Portfolio

Identifying where to invest and how much to invest can be very challenging for common people who have limited knowledge in the domain. Portfolio managers are financial professionals who spend a lot of time and effort to help investors in investing funds and implementing investment strategies, but not all can afford to consult them. The study aims to develop a weighted hybrid recommendation system that recommends an optimized investment portfolio based on the investor’s preferences regarding risk and return. Generally, investors usually ask investment for advice from friends or relatives with similar risk preferences or if they are interested in a particular item, the investors ask for the experience of someone who already has invested in the same item. Therefore, the methodology considers the investor’s past behavior and the past behavior of the nearest neighbor investors with similar risk preferences. Using user-based collaborative filtering the number of stocks is recommended using Pearson correlation based on the investor’s income, then using another user-based collaborative filtering the number of stocks is recommended based on the investor’s age. Weights are assigned to the recommended number of stocks generated based on income and age and their weighted average is finally considered. Finally, the feasibility of the proposed system was assessed through various experiments. Based on the received results, the authors conclude that the proposed weighted hybrid approach is robust enough for implementation in the real world. The novelty of the paper lies in the fact that none of the existing approaches make use of more than one type of weighted recommendation algorithm. Additionally, the final results obtained this way have been never further fortified with the highest Sharpe ratio and minimum risk for the investor. This combination of hybrid and Sharpe ratios has never been explored before.

Does the dual-class share structure help stock markets attract issuers? Empirical lessons from global financial centres

AbstractFinancial globalisation has given issuers more freedom to carry out jurisdiction shopping. As a policy response, a growing number of stock markets have introduced the dual-class share structure to enhance global competitiveness. However, does the dual-class share structure help stock markets attract issuers? It is a question rarely examined empirically in existing scholarly work. This paper explores the practices of three jurisdictions with global financial centres, ie the US, China and Hong Kong, to narrow the research gap. Based on hand-collected data, it explains the infrequent listings with the dual-class share structure in China and Hong Kong in the post-reform era in two ways: low demand due to the use of substitutes; and limited allowance caused by the harsh ex ante regulation, and is the first comparative quantitative study in this field. Drawing on the empirical lessons, this paper recommends that China relax its ex ante regulation and suggests the wider community consider the necessity of introducing the dual-class share structure and the balance they aim to achieve between investor protection and market openness.

Analisis Peramalan Obat Menggunakan Metode Simple Moving Average, Weighted Moving Average, Dan Exponential Smoothing

Forecasting is one of the essential measures in decision making, especially for estimating the number of needs. Some large companies often hire consultants to analyze and advise on forecast product demand. Especially in the health sector, forecasting is needed to meet customer drug demand. In the last two years, the Healthy Prayer Clinic experienced problems in planning the procurement of non-generic drugs due to the COVID-19 pandemic, where the number of drug requests was greater than the number of available drug stocks. This happened because the Healthy Prayer Clinic ordered non-generic drugs without planning. This study aims to determine the demand for non-generic medications in the next period and provide recommendations for the best forecasting method to meet customer needs. The methods used in this research are Simple Moving Average (SMA), Weighted Moving Average (WMA), and Exponential Smoothing (ES). Then test the accuracy of forecasting using Mean Square Error (MSE), Mean Absolute Deviation (MAD), and Mean Absolute Percentage Error (MAPE). The results of the overall forecasting calculation using the Simple Moving Average method of 19.774, then the Weighted Moving Average method of 19.573, and the Exponential Smoothing method of 20.851. The results of the calculation of the best demand forecasting using the Exponential Smoothing (ES) method for 3 months carried out from April 2021 to April 2022 obtained results of 20.851 with forecasting error accuracy using Mean Square Error (MSE), Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE) is 1.341.137, respectively; 883; and 0.90%. The best method with the smallest accuracy rate for forecasting errors is the Exponential Smoothing method with forecasting values for the next month, April 2022, amounting to 20.851

Estimating and accounting for fish losses under the footrope of a survey trawl: The case of northern shelf anglerfish

Anglerfish, or, monkfish, (Lophius piscatorius and L. budegassa) are two of the most valuable commercial fish species in northern Europe. The stock which occupies the northern European shelf is monitored by an annual bottom trawl survey which aims to estimate absolute abundance. This estimation includes corrections for herding by the trawl gear but also requires an estimate of the capture efficiency of the net. To determine the latter, losses of fish under the footrope were quantified by 1 cm length class using trawls fitted with sub-footrope collection bags. The results demonstrate clear length dependency with the smallest fish being the most likely to escape under the gear. Overall, approximately 27 % of the anglerfish were lost under the footrope, with approximately 77 % of those below 30 cm being found in the ground gear collection bags. A length-based retention model for the gear was fitted here with a day-night effect, following appropriate model selection. This estimated higher proportions of fish escapes at night than during the day. The model was then used to estimate total stock numbers at length using data from the 2006 monkfish survey data to examine their impact on the stock estimates. As expected, this demonstrated a significant increase in the abundance of smaller recruiting fish when escapement under the footrope is accounted for. The estimates at length and age will provide better inputs for future developments of an age- or length-based analytical stock assessment which in turn will contribute to better stock management.

UKRAINIAN SIMMENTAL BEEF CATTlE BREED: CREATION IDEA AND ANALYSIS OF FORMATION

UKRAINIAN SIMMENTAL BEEF CATTlE BREED: CREATION IDEA AND ANALYSIS OF FORMATION

The increasing number of subsidiaries and stock price crash risk: evidence from the Chinese stock market

PurposeWith the development of the economy, an increasing number of listed companies form subsidiaries in China. Though the increase in the number of subsidiaries affects the hierarchical structure and risk of conglomerates, few studies relate the hierarchical relationship between the parent company and its subsidiaries to its capital market performance at the conglomerate level. Therefore, this study aims to investigate the relationship between the number of subsidiaries and crash risk.Design/methodology/approachUsing a sample of all the A-share companies in the Shanghai and Shenzhen stock markets from 2007 to 2015, this study conducts multivariate regression analyses between the number of subsidiaries and the stock price crash risk.FindingsThis study finds an inversed U relationship between the number of subsidiaries and the stock price crash risk, and the above inversed U relationship is steeper in conglomerates with stronger managerial power and less finance distress.Originality/valueThis research has an incremental contribution to the agency problem and governance effect of the parent–subsidiary system in conglomerates. To the best of the authors’ knowledge, this is the first study to show a significant quadratic relationship between the future crash risk and the number of subsidiaries. This paper provides new evidence that the number of subsidiaries has an incremental ability to predict future firm-specific crash risk above other predictors identified by previous research.

Past Asbestos Exposure in Rolling Stock Manufacturing in the Absence of Environmental Monitoring: An Original Method.

The aim of this study is the reconstruction of asbestos exposure in absence of environmental monitoring data, to use the results in a cohort study of railway rolling stock workers. To reconstruct past exposures, the production data (number of rolling stock and asbestos content) and working methods were reconstructed with former employees and company documentation, literature data, and author expertise. The result of the work is a job/exposure matrix from 1956 to 1979, when sprayed asbestos was used as insulator of the metal bodies. Annual exposure estimate varies from 0.08 to 4.9 fb/mL depending on the specific jobs. Thirty-one mesotheliomas with occupational exposure, one with environmental and one with family exposures, were identified. The originality of the study consists on the use of company production data to establish frequency duration of asbestos exposure.

The Aegean Sea demersal fishery under four climatic and socio-political futures

The future of the Aegean Sea demersal fishery is projected under four climatic and socio-political scenarios, namely: “World Markets“, “Global Sustainability”, “National Enterprise” and “Local Stewardship”. The scenarios combine two IPCC climatic futures (RCP4.5 and RCP8.5) with four socio-political systems that foresee changes in economic, technological as well as management aspects of the fishery corresponding to four contrasting futures. The future projection of a large number of physico-chemical variables per climatic scenario, made available through CERES project (http://ceresproject.eu/), gave the opportunity to model the effects of Climate Change (CC) on the productivity of demersal stocks. The projections foresee an increase in primary productivity in the Aegean Sea waters, which is projected to become mesotrophic from currently oligotrophic, while statistical analysis suggests that mullet stocks might be favored, while the European hake stock is more likely to be in decline. The combined, as well as the individual, effects of the different components of change on the fishery are explored. With respect to management, the results demonstrate the key role of technical interactions in the attempt to achieve sustainable and optimally harvested fisheries. It is found that a minor reduction of effort can achieve sustainability and good yield (PGY) from key stocks. A main source of uncertainty stems from the large number of stocks that remain unassessed. The ongoing tropicalization of the Aegean Sea and the response of these other stocks to CC increases the uncertainty and creates new challenges but also new opportunities for the Aegean Sea demersal fishery.

Portfolio optimization with tri-objective for index fund management

Using an index fund is a popular strategy that is designed to simulate the behavior of a market index and obtain the excess return that is more stable than other mutual funds. In setting up an index fund, investors must first choose a small number of stocks and then assign a weight to each selected stock. However, with traditional methods, investors hardly determine how well the designed index fund can mimic the market index. The main objective of this paper is to demonstrate the improvement of index fund performance by using a multi-objective optimization algorithm that can assign weights automatically.

Optimisation Models for Inventory Management with Limited Number of Stock Items

Background: Stocks of raw materials and finished products are found in all units of logistics systems and require significant financial means of management. For this reason, scientifically justified approaches to stock management and cost minimisation must be explored. Despite the existence of many such approaches in literature and practice, each case has its own specificities and specificities to which stock management models should be adapted. In this article, the aim of the authors is to propose an approach to determine optimal supply sizes from different types of stocks (more than one is known in the literature as multi-nomenclature) that minimises only the cost of inventory management. The cost of inventory is not included. Methods: The article used the methods of mathematical optimisation, the method of least squares, and regression analysis. The scope of the models in the article is inventory management, with a limited number of stock keeping units. Time series data for the delivered quantities and time series data for the costs of stock management are used. Both time series use the same time period. Results: The constructed specific nonlinear mathematical models for optimising the total cost of stock management are approbated based on sample data and the results obtained are analysed. Conclusions: The created mathematical models and methods for optimising the total cost of stock management may be used by logistics managers to minimise the total costs of inventory management.