An Improved BPNN Algorithm Based on Deep Learning Technology to analyze the Market Risks of A+H Shares

The backpropagation neural network (BPNN) algorithm of artificial intelligence (AI) is utilized to predict A+H shares price for helping investors reduce the risk of stock investment. First, the genetic algorithm (GA) is used to optimize BPNN, and a model that can predict multi-day stock prices is established. Then, the Principal Component Analysis (PCA) algorithm is introduced to improve the GA-BP model, aiming to provide a practical approach for analyzing the market risks of the A+H shares. The experimental results show that for A shares, the model has the best prediction effect on the price of Bank of China (BC), and the average prediction errors of opening price, maximum price, minimum price, as well as closing price are 0.0236, 0.0262, 0.0294 and 0.0339, respectively. For H shares, the model constructed has the best effect on the price prediction of China Merchants Bank (CMB). The average prediction errors of opening price, maximum price, minimum price and closing price are 0.0276, 0.0422, 0.0194 and 0.0619, respectively.

Accounting of goods in pharmacies

Pharmacies belong to the category of wholesale and retail trade, but their goods are of high importance for the population, since they allow you to maintain or correct an important quality of a person — health. The implementation of operations for the movement of a wide range of medicines and medical products from suppliers through pharmacies to end-users at the same time differs in its similarity when reflected in the accounting process. Differences are observed in the approaches to setting a trade mark-up for each category of goods, depending on the frequency of purchases, or assigning them to a price segment. The exception to the rules for setting the price is vital medicines, for which the maximum price is set by the state. But the accounting of these pharmacy products also has the same mechanism as the goods without restrictions in the margin. In this case, the object of VAT taxation appears, the accounting of which has its own specifics, depending on the applicable tax regime.

An Optimal Inventory Pricing and Ordering Strategy Subject to Stock and Price Dependent Demand

This article considers the deterministic optimal control problem of profit maximization for inventory replenished at a variable rate and depleted by demand which is assumed to vary with price and stock availability. Optimal policies for the inventor, product order rate and price are derived using the maximum principle. Bounds on the maximum price possible are also derived.

A QPTAS for ɛ-Envy-Free Profit-Maximizing Pricing on Line Graphs

We consider the problem of pricing edges of a line graph so as to maximize the profit made from selling intervals to single-minded customers. An instance is given by a set E of n edges with a limited supply for each edge, and a set of m clients, where each client specifies one interval of E she is interested in and a budget B j which is the maximum price she is willing to pay for that interval. An envy-free pricing is one in which every customer is allocated an (possibly empty) interval maximizing her utility. Grandoni and Rothvoss (SIAM J. Comput. 2016) proposed a polynomial-time approximation scheme ( PTAS ) for the unlimited supply case with running time ( nm ) O ((1/ɛ) 1/ɛ ) , which was extended to the limited supply case by Grandoni and Wiese (ESA 2019). By utilizing the known hierarchical decomposition of doubling metrics , we give a PTAS with running time ( nm ) O (1/ ɛ 2 ) for the unlimited supply case. We then consider the limited supply case, and the notion of ɛ-envy-free pricing in which a customer gets an allocation maximizing her utility within an additive error of ɛ. For this case, we develop an approximation scheme with running time ( nm ) O (log 5/2 max e H e /ɛ 3 ) , where H e = B max ( e )/ B min ( e ) is the maximum ratio of the budgets of any two customers demanding edge e . This yields a PTAS in the uniform budget case, and a quasi-PTAS for the general case. The best approximation known, in both cases, for the exact envy-free pricing version is O (log c max ), where c max is the maximum item supply. Our method is based on the known hierarchical decomposition of doubling metrics, and can be applied to other problems, such as the maximum feasible subsystem problem with interval matrices.

Estimating the global demand curve for a leishmaniasis vaccine: a generalisable approach based on global burden of disease estimates

BackgroundA pressing need exists to develop vaccines for neglected diseases, including leishmaniasis. However, the development of new vaccines is dependent on their value to two key players – vaccine developers and manufacturers who need to have confidence in the global demand in order to commit to research and production; and governments (or other international funders) who need to signal demand based on the potential public health benefits of the vaccine in their local context, as well as its affordability. A detailed global epidemiological analysis is rarely available before a vaccine enters a market due to lack of resources as well as insufficient global data necessary for such an analysis. Our study seeks to bridge this information gap by providing a generalisable approach to estimating the commercial and public health value of a vaccine in development relying primarily on publicly available Global Burden of Disease (GBD) data. This simplified approach is easily replicable and can be used to guide discussions and investments into vaccines and other health technologies where evidence constraints exist. The approach is demonstrated through the estimation of the demand curve for a future leishmaniasis vaccine.Methodology/Principal findingsWe project the ability to pay over the period 2030-2040 for a vaccine preventing cutaneous and visceral leishmaniasis (CL / VL), using an illustrative set of countries which account for most of the global disease burden. First, based on previous work on vaccine demand projections in these countries and CL / VL GBD-reported incidence rates, we project the potential long-term impact of the vaccine on disability-adjusted life years (DALYs) averted as a result of reduced incidence. Then, we apply an economic framework to our estimates to determine vaccine affordability based on the abilities to pay of governments and global funders, leading to estimates of the demand and market size. Based on our estimates, the maximum ability-to-pay of a leishmaniasis vaccine (per course, including delivery costs), given the current estimates of incidence and population at risk, is higher than $5 for nearly half of the 24 countries considered, with a median value-based maximum price of $4.4-$5.3, and total demand of over 560 million courses.Conclusion/SignificanceOur results demonstrate that both the quantity of vaccines estimated to be required by the countries considered as well as their ability-to-pay could make a vaccine for leishmaniasis commercially attractive to potential manufacturers. The methodology used can be equally applied to other technology developments targeting health in developing countries.Author summaryAs of 2019, between 498,000 and 862,000 new cases of all forms of leishmaniasis were estimated to occur each year resulting in up to 18,700 deaths and up to 1.6 million DALYs lost. Given low treatment coverage, poor compliance and the emergence of drug resistance, challenges in sustaining vector control strategies and the ability of parasites to persist in animal reservoirs independent of human infection, an effective vaccine could significantly reduce the health and economic burden of these diseases. However, commitment to the development of a new vaccine requires a market signal from governments and global funders who in turn require better estimates of the potential public health value of the vaccine. This study uses the development of a leishmaniasis vaccine as a case study to illustrate a generalizable approach to estimating the commercial and public health value of a technology relying primarily on publicly available GBD data. More specifically, by projecting the potential public health impact of the rollout of a leishmaniasis vaccine and translating this into monetary values based on the concept of health opportunity cost, we estimate the demand curve for such a vaccine for an 11-year period between 2030 and 2040. At an estimated global demand of over 560 million courses and a median value-based maximum price of $4.4-$5.3, our results demonstrate that both the quantity of vaccines estimated to be required by the countries considered as well as their ability-to-pay make the vaccine commercially attractive to potential manufacturers.

IDENTIFICATION OF SIGNIFICANT RISK FACTORS OF GUARANTEED MAXIMUM PRICE (GMP) CONTRACTS

The construction industry is a risk-prone industry where projects are implemented in a dynamic environment with frequent exposure to various uncertainties. A construction contract is a document that allocates the risks associated with a construction project among the project stakeholders. Guaranteed Maximum Price (GMP) contracts have become popular as a project delivery method because they provide the client with a high degree of cost certainty through a fixed price cap that the contractor cannot exceed. However, most of the GMP projects are risky. Thus, the significant risk factors of GMP projects have to be identified to ensure their successful completion. This study, therefore, aimed to identify and rank the most significant risk factors present in GMP contracts. The study adopted a quantitative approach, which included a Delphi survey conducted in two rounds and a statistical analysis of the survey data. The most significant risk factors associated with GMP contracts were ranked according to their impact on the projects and their probability of occurrence (severity). Poorly defined scope of work and design changes were found to be the most significant risk factors associated with GMP contracts. The other significant risk factors of the projects are related to the scope of work, design, documentation, unfamiliarity with the GMP concept, agreed GMP value, and financial failures of the client and contractor.

Cost variation analysis of oral anti-diabetic agents available in Indian market

Background: The objective of this study was to analyze cost variations of oral antidiabetic drugs available in Indian market.Methods: An observational study was carried out using CIMS (current index of medical specialities), (July 2020 to October 2020) and 1 mg.com, where difference in the maximum and minimum price of a particular drug, manufactured by different pharmaceutical companies, in the same strength, number and dosage form was compared and the percentage variation in price was calculated. Data was analyzed using descriptive statistical analysis.Results: The minimum and maximum percentage price variation for different classes of drugs respectively is as follows- in single drug therapy, the price variation between a sulfonylurea group of drugs glibenclamide (5 mg) shows maximum price variation of 400%, while glipizide (2.5 mg) shows variation of 81.8%. In biguanides, thizolidinediones and DPP4 inhibitor groups of drugs, metformin (500 mg), pioglitazone (30 mg) and vildagliptin show maximum price variation of 334.78%, 307 % and 264.6% respectively. In α- glucosidases inhibitor group of drugs voglibose (0.2 mg) shows maximum price variation of 284%. In meglitinides group of drugs, nateglinide (60 mg) shows maximum price variation of 284.6 %. In combination drug therapy, glimepiride and metformin combination (2+500 mg SR) shows the maximum variation up to 352.8%.Conclusions: The percentage cost variation of different brands of the same drug manufactured in India is very wide and the reason behind marketing a drug should be directed towards maximizing the benefit of therapy and minimizing negative personal and economic consequences.

Approaches and methods for calculating the initial (maximum) price of contracts for the supply of goods, performance of work, provision of services for state and municipal needs

В соответствии с законодательством Российской Федерации заказчики для осуществления закупки необходимо обосновать объект закупки, необходимость его закупки, план-график осуществления закупки, начальную (максимальную) цену контракта, а так же способ ее определения, что является актуальным вопросом, в контексте которого в статье изложены подходы и методы для обоснования (расчета) начальной (максимальной) цены контрактов на выполнение работ, оказание услуг и поставок товара, реализуемых в рамках федеральных и национальных проектов, государственных и целевых программ в сфере образования и науки. Практическая значимость материалов статьи заключается в том, что в них представлены классификация существующих подходов и методов, а также рекомендации по их применению для определения цены контракта в зависимости от предмета контракта. In accordance with the legislation of the Russian Federation, customers need to justify the object of purchase, the need for its purchase, the procurement schedule, the initial The (maximum) price of the contract, as well as the method of determining it, which is a relevant issue in the context of which the article sets out the approaches and methods to justify (calculating) the initial (maximum) price of contracts for the performance of work, the provision of services and supplies of goods implemented within the framework of federal and national projects, state and target programs in the field of education and science. The practical significance of the article is that it presents a classification of existing approaches and methods, as well as recommendations on their use to determine the price of a contract depending on the object of the contract.

Kesediaan Membayar (Willingness To Pay) Beras Organik di Kabupaten Banyumas dan Faktor Yang Mempengaruhinya

The objectives of this study are: (1) to identify the characteristics of organic rice consumers in Banyumas Regency, (2) to determine the maximum average price for organic rice that consumers in Banyumas Regency are willing to pay, and (3) to analyze and find out factors underlying the consumers’ willingness to pay for organic rice. This research was conducted in Banyumas Regency by interviewing 68 respondents who were selected using the snowball sampling method. Data is analyzed using descriptive analysis, contingent valuation method (CVM), and logistic regression analysis. The study indicates that the characteristics of organic rice consumers who are willing to pay more for organic rice in Banyumas Regency are mostly aged 36 to 55 years, having an undergraduate degree, working as civil servants, and having an income level of Rp 3.000.001 to Rp 6.000.000 with 1-4 family members. The maximum price for organic rice that consumers in Banyumas Regency are willing to pay is Rp18.346 per kilogram. Factors underlying the willingness to pay for organic rice are income, length of consumption, and consumers’ perception of organic rice quality.

Bitcoin and the South Sea Company: A comparative analysis

This paper examines historical Bitcoin price data together with the price data of a well-known and generally accepted historical asset price bubble (the 1720 South Sea Bubble) with the aim of identifying possible similarities. In order to find empirical evidence of speculative bubble tendencies, the article analyses distribution moments and autoregressive models of time series of both assets. Results show that historical daily prices of both assets—taking into account one year before and one year after the maximum price level—clearly show the two phases of bubble expansion and subsequent crash. Furthermore, various similarities between the South Sea Bubble and Bitcoin can be found in descriptive statistics, such as mean of return, standard deviation, and skewness. Statistical tests also show several explosive moments in the time series of the South Sea Company and Bitcoin returns, which implies that both assets exhibit more than one financial bubble.