Maximum Rate Of Return Research Articles

Application of mean-variance modal in four industries

Portfolio optimization is highly valued and used by many people in the financial field. This paper analyzes the asset portfolio allocation of different industries, namely, transportation industry, software industry, semiconductor industry, and insurance industry. This paper selected four representative assets from these four industries, and then used the mean-variance combination model to analyze asset allocation and forecast the return on investment. In order to find the optimal proportion of investment portfolio in these four industries. The results show that "MMC" has the largest weight proportion in the combination of least squares and the maximum Sharpe ratio combination's "MSFT" weight percentage is the highest, while "UPS" has the smallest weight proportion in the combination of least squares and maximum Sharpe ratio. Therefore, in these four industries, the mean-variance model predicts that the insurance industry and software industry can get the maximum rate of return, while the cosmetics and nursing industry cannot get the maximum rate of return.

Megahertz repetition rate satellite laser ranging demonstration at Graz observatory.

Using ultra-high repetition rate lasers (≥100kHz) is one of the most promising strategies for the next generation of satellite laser ranging (SLR) systems. We present successful 1 MHz repetition rate SLR to targets up to inclined geosynchronous orbits at nighttime. Among those, a maximum return rate of up to 53% was achieved, equivalent to 265 k returns per second for the satellite Swarm-B. In addition, daytime megahertz (MHz) SLR was realized by utilizing a propagated MHz range gate to reduce the massive background noise. In the future, MHz SLR will greatly improve current technology with respect to data amount and data precision, shorter acquisition time, target signature detection, and attitude determination.

3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model

This study presents an agent-based model of capital markets by adopting simple trading rules for bounded rational agents who maintain different expectations regarding a tipping point at which price starts to change its direction from rising (falling) to falling (rising). The effect of herding behavior on the volatility of stock market prices and the rate of return to the herding group are investigated by dividing agents into one or more groups. Herding behavior by a group of agents leads to high market volatility and high return for the agents in the group. Maximum rate of return is reached when the group size is approximately 3% of the total number of agents. This finding is consistent with the actual degree of herding behavior in markets found by empirical studies. However, the rates of return decrease when the group size exceeds 3%, and the premium of the herding group tends to disappear when the group size reaches a certain level (20%) compared with that of non-herding groups. Reducing the number of groups (or increasing the average size of the herding groups) leads to high price volatility.

Closed-loop supply chains with complementary products

In this paper, we search for the best configuration for a closed-loop supply chain (CLSC) dealing with complementary goods. In our model, a manufacturer sells two complementary goods to a retailer, which sells both products in the market. When the products reach their end-of-use stage, the manufacturer has several options for the CLSC: (i) Collect both products (exclusive collection), (ii) collect only one product while outsourcing the other product collection to the retailer (partial outsourcing), and (iii) fully outsource the collection process to the retailer (full outsourcing). Our findings demonstrate that the presence of complementary products makes the CLSC selection extremely difficult. For instance, we demonstrate that the CLSC structure with maximum returns does not necessarily possess the minimum or the maximum wholesale price. Analogously, the minimum retail price (i.e., maximum sales) and maximum return rate often occur in different collection options. We also show that the best collection option for the manufacturer seldom leads to the maximum profit for the retailer. Moreover, often the CLSC option that maximizes the manufacturer’s profit leads to lower returns. Therefore, the presence of complementary products entails several trade-offs among collection performance, prices, and profits.

Pengaruh Likuiditas dan Profitabilitas terhadap Return Saham pada Perusahaan Manufaktur yang Terdaftar di Bursa Efek Indonesia

To invest in the capital market, investors must know that in addition to receiving profits, they will also suffer losses. One of the motives of inventors to invest is to get a maximum rate of return with certain risk or obtain a certain rate of return on minimal risk. This study aims to examine the effect of liquidity and profitability on stock returns. The population is a manufacturing company which are listed in Indonesia Stock Exchange in 2013-2017 periods. The sampling technique uses a purposive sampling method with predetermined criteria and obtained a sample of 34 companies with 170 observations. The data of the financial statement of the companies has been obtained from the official website of IDX. The analytical method used is regression analysis of panel data with the help of application E-Views 8. Panel data regression can be estimated using three models, namely Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). To get the best model, a further test was used, namely the Chow Test and Hausman Test. From the results of the estimation model, it is found that REM is the best model in this study. Furthermore, the results of the study show that liquidity has a positive and not significant effect on stock returns, while profitability has a positive and significant effect on stock returns.

Impact of dewatering technologies on specific methanogenic activity

Dewatering methods for recuperative thickening and final dewatering can potentially impact methanogenic activity and microbial community. This influences both the feasibility of recuperative thickening to increase solids residence time within a digester, and the utilisation of dewatered digestate as inoculum for new digesters. Thickening technology can reduce methanogenic activity through either air contact (rotary drum, DAF, or belt filter press), or by lysing cells through shear (centrifuge). To assess this, two plants with recuperative thickening (rotary drum) in their anaerobic digester, and five without recuperative thickening, had specific methanogenic activity tested in all related streams, including dewatering feed, thickened return, final cake, and centrate. All plants had high speed centrifuges for final dewatering. The digester microbial community was also assessed through 16s pyrotag sequencing and subsequent principal component analysis (PCA). The specific methanogenic activity of all samples was in the expected range of 0.2–0.4 gCOD gVS−1d−1. Plants with recuperative thickening did not have lower digester activity. Centrifuge based dewatering had a significant and variable impact on methanogenic activity in all samples, ranging between 20% and 90% decrease but averaging 54%. Rotary drum based recuperative thickening had a far smaller impact on activity, with a 0% per-pass drop in activity in one plant, and a 20% drop in another. However, the presence of recuperative thickening was a major predictor of overall microbial community (PC1, p = 0.0024). Microbial community PC3 (mainly driven by a shift in methanogens) was a strong predictor for sensitivity in activity to shear (p = 0.0005, p = 0.00001 without outlier). The one outlier was related to a plant producing the wettest cake (17% solids). This indicates that high solids is a potential driver of sensitivity to shear, but that a resilient microbial community can also bestow resilience. Sensitivity of methanogens to centrifuging does not rule out centrifuges for recuperative thickening (particularly where hydrolysis is rate-limiting), but may impose a maximum return rate to avoid digester failure.

Market Value of the Firm, Market Value of Equity, Return Rate on Capital and the Optimal Capital Structure

The firm should pursue both maximum return rate on capital and maximum return rate on equity simultaneously. Maximum return rate on capital is the primary goal for firms because maximum return rate on capital guarantees efficiency. Therefore, maximum profit, maximum market value of the firm, maximum value of equity and maximum return rate on equity are inappropriate to be the primary goal. Since gross profit is independent of capital structure, capital structure just distributes return on capital into equity and debt (i.e., maximum return rate on equity determines capital structure). The maximum return rate on equity is the secondary goal that the firm pursues. Leverage makes the return rate on equity be higher than interest rate. Leverage explains the puzzle of equity premium.

Context-Sensitive Solutions versus Practical Solutions

In recent years, the concept of the context-sensitive solution (CSSs) has been promoted by both AASHTO and FHWA as a best practice for project development. A CSS provides a systematic and comprehensive approach to project development from inception and planning through operations and maintenance. Recently, the economic constraints facing several state departments of transportation have created a new emphasis on financial issues as they relate to project development. Practical design and practical solutions are a process emphasizing design solutions that aim to achieve the maximum rate of return for the individual project and to maximize system returns. As a result, the concepts of practical design and practical solutions have seemingly clashed with CSS. In contrast, these concepts address and emphasize the systemwide optimization that was not addressed by CSS. Moreover, they improve CSS applications and principles by further refining them, and potentially they could add the need to consider systemwide improvements. The main conclusion from the work presented here is that a systematic, principle-driven, benefit-justified project development process is necessary to deliver the appropriate project. This paper presents the concepts and issues for each and compares their approaches, aiming to initiate a dialogue for understanding these approaches and improving the project development process so that it is more comprehensively performance oriented.

The optimal number of machines to be operated by a single worker. (1st report. The condition for the existence of the optimal number).

This paper considers a man-machine system consisting of some numerically -controlled (NC) machines and a single worker. This system processed many kinds of items. The role of worker is loading the workpieces on and unloading the workpieces from machines. In such a system design, it is an important problem to determine the number of machine5 to be operated by the worker. First. we formulate the system as a stochastic model to analyze the above optimal problem. The desicion variable is the number of machines and the optimal criteria are 'the maximum production rate', 'the minimum total cost', 'the maximum profit rate' and 'the maximum return's rate of operating cost'. It is shown that the optimal numbers under these criteria depend on only the utilization of the worker. and hence the minimum total cost, and the maximum return's rate criteria are the same. It is proved that there exist the optimal numbers under these criteria if the worker's utilization is a concave function of the number of machines used. Furthermore, an ordering between the optimal numbers under the minimum total cost and the maximum profit rate criteria is suggested theoretically. The validity of the concavity and the ordering is established by many numerical experiments. The applicability of the results to practical problem is discussed via a case study.

Optimizing Batch Manufacture for Multiple Products and Irregular Demand

A previous paper 1 presented a relatively straightforward method of maximising the rate of return on investment in batch manufacture, a more important criterion, it was argued, than that of solely minimising costs. The present paper presents two further extensions to the practical optimisation of batch manufacture. Firstly, concepts of a particular economic quantity hold only if the demand is constant. Therefore a method is given which deals with randomly varying demand, utilising a variable reorder quantity, variable reorder point system, which also maintains stock control and the “maximum rate of return” criterion. Secondly, the capacity matching and schedule requirements for multi-product batch manufacturing are considered. Again maximum rate of return is used as the objective function, in relation to the optimisation of the total composite schedule.

A Test of 17α-Methyltestosterone as a Growth Promoter in a Coho Salmon Hatchery

Abstract Coho salmon (Oncorhynchus kisutch) fry reared at densities of 87–92 fish/m3 in hatchery ponds were fed a moist diet supplemented with 1 mg/kg 17α-methyltestosterone during a 7-month period. Hormone-treated fish grew faster and utilized food more efficiently than controls receiving the same diet without hormone. At the time of release from the hatchery, muscle of hormone-treated fish had slightly lower protein content than that of controls. Weight-to-length ratios and gonad development were not altered. Hormone treatment did not affect the rate of return of precocious males. Hormone-treated fish returned as 3-year-old adults to the hatchery almost as abundantly as control fish, but numbers caught in the fishery were reduced. Recent information indicates that the size of the released hormone-treated fish exceeded the most favorable size for maximum rate of return of adults. Both treated and control fish returned at higher rates than hatchery-production fish raised at higher densities. Egg viability...

Portfolio analysis of asset and liability management in small-, medium- and large-sized banks

The paper presents an analysis of the commercial banking firm based on Markowitz portfolio analysis. A bank is treated as a portfolio of five banking assets and three banking liabilities. The average rate of return and risk of each asset and liability is estimated empirically for groups of banks categorized by size — small, medium and large. Banks' rates return on equity are defined as the weighted average of the assets' rates of return less the liabilities' rates of return. Quadratic programming is used to delineate the set of banking portfolios which have the maximum rate of return on equity at each level of risk.