Net Price Research Articles

Cost-effectiveness analysis of once-daily insulin glargine 300 U/mL versus insulin degludec 100 U/mL using the BRAVO diabetes model.

A cost-effectiveness analysis was conducted to compare insulin glargine 300 U/mL (Gla-300) versus insulin degludec 100 U/mL (IDeg-100) in insulin-naïve adults with type 2 diabetes (T2D) sub-optimally controlled with oral anti-diabetic drugs (OADs). The BRAVO diabetes model was used to assess costs and outcomes for once-daily Gla-300 versus once-daily IDeg-100 from a US healthcare sector perspective. Baseline clinical data were based on BRIGHT, a 24-week, non-inferiority, randomised control trial comparing Gla-300 and IDeg-100 in adults with T2D sub-optimally controlled with OADs (with or without glucagon-like peptide-1 receptor agonists). Treatment costs were based on doses observed in BRIGHT as well as net prices. Costs associated with complications were based on published literature. Lifetime costs (US$) and quality-adjusted life-years (QALYs) were predicted and used to calculate incremental cost-effectiveness ratio estimates; extensive scenario and sensitivity analyses were conducted. Overall lifetime medical costs were estimated to be $327,904 and $330,154 for people receiving Gla-300 and IDeg-100, respectively; insulin costs were $43,477 and $44,367, respectively. People receiving Gla-300 gained 8.024 QALYs and 18.55 life-years, while people receiving IDeg-100 gained 7.997 QALYs and 18.52 life-years. Because Gla-300 was associated with a cost-saving of $2250 and 0.027 additional QALYs, it was considered to be dominant compared with IDeg-100. Results of the scenario and sensitivity analyses confirmed the robustness of the base case results. Gla-300 was the dominant treatment option compared with IDeg-100 based on the willingness-to-pay threshold of $50,000/QALY. Results remained robust against a wide range of alternative assumptions on key parameters.

Matching Pell Grants: Implications for College Debt and Parental Transfers

We study the causal effect of the net price of college on student debt, schooling investment, and parental transfers by exploiting a natural experiment. A large public US university introduced a program to match Pell Grants in academic year 2019-2020. We use a difference-in-difference approach to measure the impact of this policy on the variables of interest and interpret our findings using a simple structural model of human capital investment under credit constraints.

METHODS OF VALUATION OF ITEMS OF FINANCIAL REPORTING OF UKRAINIAN ENTERPRISES: UNIFICATION OF NATIONAL AND INTERNATIONAL STANDARDS

The purpose of the paper is to unify the methods of valuation of items of financial reporting of Ukrainian enterprises on the basis of national and international standards. Methodology. The theoretical aspects of the study are based on international accounting and financial reporting standards, as well as national accounting regulations (standards). The applied aspects consist in specifying the methods of valuation of certain objects of accounting (assets, liabilities, income, expenses) and their reflection in the financial statements. The results of the paper made it possible to determine the conditions for the implementation of international accounting and financial reporting standards in Ukraine. It was shown that their implementation began in 2007 and was completed in 2012 by public joint stock companies due to the requirements for placement of securities on stock markets. The impact on the implementation of international accounting and financial reporting standards by Ukrainian enterprises in connection with the signing by Ukraine of the Association Agreement with the European Union was determined. The characteristics of the Anglo-American and continental accounting models, their regulatory standards, existing differences between US GAAP and IFRS/IAS, work on their harmonization with a view to creating an international accounting model were presented. The methods of valuation of items of financial reporting were systematized: historical cost, present value, net selling price, fair value or amount of expected compensation. Their advantages, disadvantages and scope of application were determined. The cost approach to the valuation of financial reporting items and the prospects for its use were examined in more detail. It was shown that enterprise value is characterized by indicators reflected in balance sheet, off-balance sheet and financial statements. The information model for determining the value of an enterprise on the basis of financial statements was proposed. The methods of value determination depending on the organizational and legal form of an enterprise were differentiated. The sources of formation of its market and fundamental value have been clarified. The informational capacity of the items of the financial statements of an enterprise was estimated. The practical implications include the creation of an information model for determining the value of the company according to financial reporting, the substantiation of recommendations for regrouping its items for the needs of management accounting, and the creation of additional reporting forms – a value statement and a value-added statement. Value/originality. The methodological recommendations for the harmonization of the systems of financial and management accounting of added value were substantiated in terms of: recognition of income generated by fully depreciated assets; capitalization of financial costs; use of 8-class accounts; off-balance sheet accounting to reflect non-financial information about capital and integrated added value of a company; simplification of the tax system by introducing a single value added tax, which will absorb income tax and lead to further harmonization of financial and tax accounting.

Quantitative analysis and co-optimization of cathode catalyst layer compositions and operating conditions on cost and performance of PEM fuel cell

ABSTRACT Increasing the net power density of proton exchange membrane fuel cell without extra cost is beneficial to its commercialization. To this end, a one-dimensional, two-phase, non-isothermal model was developed in this work. The influences of cathode catalyst layer compositions including the mass ratio of ionomer to carbon (Ri/c) and mass ratio of platinum to carbon (Rpt/c) and operating conditions including temperature, cathode relative humidity (RHc), anode relative humidity (RHa), and operating voltage (V) on the cost and performance of fuel cell were quantitatively investigated by range and variance analyses based on an orthogonal test. The results indicate that Ri/c is the most significant factor affecting net power and unit power price. In addition, the RHc and V are also sensitive parameters to the net power, while Rpt/c affects the unit power price. Finally, with the consideration of the interaction between the operating conditions and the cathode catalyst layer compositions, a multi-objective optimization was conducted to improve the aforementioned two indicators. Compared to the base case, the optimized fuel cell achieves a net power increase of 50.8% and a 24.7% reduction in unit power price, which allows the realization of a high-performance, low-cost fuel cell.

PENGARUH PBV DAN NPM TERHADAP HARGA SAHAM PERUSAHAAN DEPARTMENT STORE DI BEI

This study's benefits include examining the effects of Net Profit Margin (NPM) and Price to Book Value (PBV) on Stock Price in Department Store companies listed on the Indonesia Stock Exchange between 2012 until 2021. Three Department Store companies that were listed on the Indonesia Stock Exchange between 2012 until 2021 comprise the sample for this quantitative study. The Classic Assumption Test, Multiple Linear Regression Analysis, Correlation Coefficient, Determination Coefficient, and t-Test and F-Test are the data analysis techniques utilized. The t-Test Research's findings had a significance of 0.216 or greater, indicating that the Price Book Value has no bearing on the stock price of the business. The T-Test Research Results revealed a significance level of 0.016 < 0.05, indicating that the company's stock price is influenced by Net Profit Margin. While the F-Test Research Results, which were obtained with a significance of 0.012 < 0.05, demonstrate that the Net Profit Margin and Price to Book Value both have an effect on the stock price of the company simultaneously.

Optimal sizing of residential photovoltaic and battery system connected to the power grid based on the cost of energy and peak load

The use of renewable energy is necessary to achieve the goals of sustainable development, and sooner or later all countries are forced to plan and make policies for the use of this equipment. Considering the growing trend of smart systems and the ability of these systems to control and use renewable resources, it is necessary to investigate how to control and optimally use these resources in smart systems. Considering the geographical conditions and significant solar energy radiation in Iran, the most suitable option for using renewable energy in residential buildings is solar energy. Among the types of solar energy used around the world, photovoltaic panels are used more due to their wide range, being cheaper than other sources of electric power from solar energy and more durable than other sources. In order to reduce widespread losses and reduce the cost of transmission and distribution, increase efficiency, the possibility of the presence of private sector investors and increase the security and stability of the power grid, distributed production of electrical energy at consumption locations using small-scale units is the most cost-effective way to use home solar panels. Also, the production of energy from wind turbines can be done in the areas where anemometer data determine it to be suitable. The combination of solar energy and wind energy can effectively reduce the need for batteries, but studies show that this combination is only economically viable when it is used on a large scale and with high powers, which requires a lot of investment. Large initial capital is one of the biggest problems of distributed production systems, so the use of artificial intelligence methods for accurate capacity determination of renewable energy production systems becomes doubly important. The economic results show that the least cost of electricity and net price cost are 0.44 $ per kWh and 15.0 million $ respectively, when the converter size was gradually changed, with a renewable fraction of 46.7%.

Sales-Based Rebate Design

In this paper, we study a family of sales-based rebate mechanisms as an effective tool to implement price discrimination across a population of buyers with correlated heterogeneous valuations on indivisible goods and services. In order to implement such sales-based rebate mechanisms, the seller charges each buyer a fixed price at the time of purchase contingent on a rebate that is a function of the ex post sales volume to be realized at the end of the sales period. The seller declares both a price and a menu of rebates as a function of sales. We show that, when there is a common component of uncertainty in consumers’ valuations (to which we refer as the quality of the product), such rebates enable a seller to effectively induce different expected net prices at different valuations. Importantly, this effective price discrimination over valuations is achieved keeping both the base price and the rebate uniform across all buyers. This uniformity of price and rebate across buyers is a key advantage of our proposed rebate mechanism, thereby providing a new mechanism for price discrimination in crowd-based markets. We use tools and techniques from game theory and variational optimization to provide insight into the economics of such mechanisms. In particular, we identify two mechanisms that are monotone functions of the sales volume that are easy to implement in practice and perform well when compared with the much more complex optimal mechanism. We provide a rigorous analysis of the optimal mechanism and discuss practical limitations in implementing the globally optimal design, further demonstrating the efficacy of our proposed monotone mechanisms. This paper was accepted by Gabriel Weintraub, revenue management and market analytics. Funding: This research was supported by a Vannevar Bush Fellowship from the Office of Secretary of State and Army Research Office [MURI Project W911NF-19-1-0217]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4691 .

The influence of Medicare Part D on the list pricing of brand drugs.

To compare the Medicare Part D market share of brand drugs with their net-to-list price ratio. SSR Health Brand Net Price Tool and Medical Expenditure Panel Survey, 2007-2019. For each drug, we calculated the ratio of net to list price and the percent of users that were Medicare-eligible. We compared these cross-sectionally in each year and estimated a difference-in-differences model comparing drugs with high or low Medicare market shares (MMS) after following changes to program incentives in 2010. The sample included brand drugs without generic competitors appearing in both datasets. Net-to-list price ratios were negatively correlated with MMS in the later years of our sample. In 2019, a 10% increase in MMS was associated with a significant 4.6% [95% CI: 2.1%, 7.1%] decrease in net-to-list ratio. Difference-in-differences showed net-to-list price ratios of drugs with above median MMS fell relative to those with below median MMS. By 2019, we observe an absolute reduction of -0.2 [95% CI: -0.29, -0.11], representing 28% reduction relative to the average ratio in 2010. Greater exposure to the Medicare Part D market was associated with larger differences between net and list prices of drugs.

Budget impact analysis of anakinra in the treatment of familial Mediterranean fever in Italy

ABSTRACT Introduction: Familial Mediterranean Fever (FMF) is a hereditary autoinflammatory disease that significantly reduces occupational productivity and quality-of-life in affected patients. Italy has an estimated FMF prevalence of 1 in 60,000 people. While colchicine is the primary treatment for FMF, biologics are administered to intolerant and non-responder patients. Anakinra and canakinumab are the only biologics approved and reimbursed for FMF in Italy. Both medicines have demonstrated efficacy in FMF patients yet differ in treatment costs. This study aimed to perform a budget impact analysis (BIA) following anakinra’s reimbursement for FMF treatment, considering pharmaceutical costs from the Italian National Healthcare Service (NHS) perspective. Methods: A ‘Reference scenario’ (all patients treated with canakinumab) was compared to an ‘Alternative scenario’, with increased anakinra market shares. The target population was estimated based on the Italian population, epidemiological and market research data. Drugs costs were estimated based on Summary of Product Characteristics and net ex-factory prices. Sensitivity analyses were implemented to test results’ robustness. Results:The base case analysis showed an overall cumulative expenditure of €30,586,628 for ‘Reference scenario’ and € 16,465,548 for ‘Alternative scenario’. A cumulative savings of €14,121,080 (46.2%) was calculated over 3 years as a result of the reimbursement and increasing uptake of anakinra. The sensitivity analyses, even considering a discount of 50% for canakinumab, confirmed the base case results. Conclusions: Anakinra’s introduction, in FMF treatment, provides a financially sustainable option for Italian patients, with savings increasing according to greater use of anakinra.

Simulated Medicare Drug Price Negotiation Under the Inflation Reduction Act of 2022

The Inflation Reduction Act of 2022 gives Medicare the authority to negotiate prices for certain prescription drugs. Which drugs will be selected and how prices will be negotiated remain unclear. To simulate drug selection and the minimum savings that would have been achieved at statutory ceiling prices if Medicare drug price negotiation had been implemented from 2018 to 2020. In this cross-sectional study, a policy simulation analysis of high-spending prescription drugs in Medicare Part B and Part D that were eligible for negotiation from January 2018 to December 2020 was performed from August 5 to November 20, 2022. Eligibility criteria for selection and discounts afforded by the statutory ceiling prices for negotiation. The main outcomes were characteristics of drugs subject to negotiation and estimated Medicare savings from 2018 to 2020 that would have been achieved through spending at ceiling prices compared with existing net prices accounting for price concessions. Among the 40 selected drugs, 35 were primarily reimbursed through Medicare Part D and 5 through Part B and 10 were biologics. The most common therapeutic classes were endocrine (11), neurologic or psychiatric (5), pulmonary (4), rheumatologic or immunologic (4), and cardiovascular (4). Median time from US Food and Drug Administration approval to selection was 12 years (IQR, 10-14 years). Three drugs faced generic competition in the 2 years between selection and price negotiation. For the remaining 37 drugs, estimated net Medicare spending from 2018 to 2020 was $55.3 billion; spending at ceiling prices would have been reduced by an estimated $26.5 billion, which represented 5% of estimated net Medicare drug spending during those 3 years. In this cross-sectional study, simulating the drug price negotiation provisions in the Inflation Reduction Act of 2022 revealed important limitations, including strict selection criteria and the potential for drugs to become ineligible for negotiation during the 2 years between selection and prices taking effect. Despite these limitations, the policy still delivered substantial savings because ceiling prices offered steep discounts, in part, by erasing excess spending from price increases faster than inflation.

Impact of list price changes on out-of-pocket costs and adherence in four high-rebate specialty drugs.

Insurers manage the cost of specialty medicines via rebates, however it is unclear if the savings are passed on to patients, and whether reducing rebates may lead to changes in patient out-of-pocket (OOP) costs and medication adherence. This study examined two drug classes to understand the impact of reducing list prices to net prices, via lower-priced national drug codes (NDCs) or authorized generics, on patient OOP costs and adherence. This retrospective analysis assessed IQVIA PharMetrics ® Plus adjudicated medical and pharmacy claims for commercially insured patients. Patient OOP costs per prescription and payer drug costs were assessed for evolocumab or alirocumab (proprotein convertase subtilisin/kexin type 9 inhibitors [PCSK9is]) or velpatasvir/sofosbuvir or ledipasvir/sofosbuvir (hepatitis C virus [HCV] medications). For PCSK9is and HCV medications, the original and lower-priced versions were compared. Adherence was estimated based on proportion of days covered (PDC) (PCSK9is) and receipt of full treatment regimen (HCV medications). In total, 10,640 patients were included (evolocumab, 5,042; alirocumab, 1,438; velpatasvir/sofosbuvir, 2,952; ledipasvir/sofosbuvir,1,208). After list price reductions, mean payer drug costs decreased by over 60%, while patient OOP cost reductions ranged from 14% to 55% (evolocumab: 55%, p < 0.01; alirocumab: 51%, p < 0.01; velpatasvir/sofosbuvir: 30%, p < 0.01; ledipasvir/sofosbuvir: 14%, p = 0.03). Patients with coinsurance as the largest contributor to their OOP costs had the largest reductions in OOP costs, ranging from adjusted, mean values of US$135 to US$379 (>60% reductions). Six-month PDC for PCSK9is and proportion receiving full HCV treatment regimen were high with the original versions and did not substantially differ with the new, lower-priced versions. Reducing list prices to approximate net prices (as a proxy for reducing rebates) resulted in lower patient OOP costs, particularly for those with coinsurance. Our findings suggest that future reduction of rebates may assist in patient affordability, although additional transparency is needed.

A Comparison of Artificial Neural Network and Time Series Models for Timber Price Forecasting

The majority of the existing studies on timber price forecasting are based on ARIMA/SARIMA autoregressive moving average models, while vector autoregressive (VAR) and exponential smoothing (ETS) models have been employed less often. To date, timber prices in primary timber markets have not been forecasted with ANN methodology. This methodology was used only for forecasting lumber futures. Low-labor-intensive and relatively simple solutions that can be used in practice as a tool supporting decisions of timber market participants were sought. The present work sets out to compare RBF and MLP artificial neural networks with the Prophet procedure and with classical models (i.e., ARIMA, ETS, BATS, and TBATS) in terms of their suitability for forecasting timber prices in Poland. The study material consisted of quarterly time series of net nominal prices of roundwood (W0) for the years 2005–2021. MLP was found to be far superior to other models in terms of forecasting price changes and levels. ANN models exhibited a better fit to minimum and maximum values as compared to the classical models, which had a tendency to smooth price trends and produce forecasts biased toward average values. The Prophet procedure led to the lowest quality of projections. Ex-post error-based measures of prediction accuracy revealed a complex picture. The best forecasts for alder wood were obtained using the ETS model (with RMSE and MAE values of approx. 0.38 € m−3). ETS also performed well with respect to beech timber, although in this case BATS was just as good in terms of RMSE, while the difference between ETS and neural models amounted to as little as 0.64 € m−3. Birch timber prices were most accurately predicted with BATS and TBATS models (MAE 0.86 € m−3, RMSE 1.04 € m−3). The prices of the most popular roundwood types in Poland, i.e., Scots pine, Norway spruce, and oaks, were best forecasted using ANNs, and especially MLP models. Among the neural models for oak (MAE 4.74 € m−3, RMSE 8.09 € m−3), pine (MAE 2.21 € m−3, RMSE 2.83 € m−3), beech (MAE 2.31 € m−3, RMSE 2.70 € m−3), alder (MAE 1.88 € m−3, RMSE 2.40 € m−3), and spruce (MAE 2.44 € m−3, RMSE 2.58 € m−3), the MLP model was the best (the RBF model for birch). Of the seven models used to forecast the prices of six types of wood, the worst results were obtained for oak wood, while the best results were obtained for alder.

Estimates of Medicaid and Non-Medicaid Net Prices of Top-Selling Brand-name Drugs Incorporating Best Price Rebates, 2015 to 2019

The US spends far more on brand-name prescription drugs than other comparable countries. However, studies of prescription drug spending in the US are often limited because there can be substantial differences in the confidential rebates that drug manufacturers pay to Medicaid vs other payers. To demonstrate an approach for improved estimation of Medicaid rebates through case studies of 18 top-selling drugs to better understand trends in net Medicaid and non-Medicaid spending and prices for brand-name drugs. This was a cross-sectional study of US pricing data from 2015 to 2019 derived from Medicaid State Drug Utilization data SSR Health, Medi-Span, the Federal Supply Schedule, and IQVIA. Pricing data for 18 top-selling brand-name drugs measured consistently in both SSR Health, which captures US sales reported by publicly traded companies, and IQVIA's top US prescription drugs by nondiscounted spending in 2015 to 2019. Data were accessed and analyzed from January 2019 to June 2021. Gross and net Medicaid and non-Medicaid drug spending for the sample of 18 drugs and prices corresponding to a 30-day supply of medication. Medicaid aggregate gross spending for the 18 drugs in the sample increased 173%, from $3.6 billion in 2015 to $9.9 billion in 2019, and estimated net spending after discounts increased by 119%, from $1.4 billion to $3.0 billion. Medicaid inflation-linked rebates reduced average gross price per 30-day supply by an estimated 43% in 2019, and up to 67% for individual drugs. In addition to the basic rebate, the best price provision reduced the average gross price per 30-day supply by an estimated 3% in 2019 and up to 54% for individual drugs. Between 2015 and 2019 across all study drugs, estimated average non-Medicaid net 30-day prices were between 1.9 and 2.6 times higher than Medicaid net prices. Excluding adalimumab-a spending anomaly because of the entry of a new high-cost formulation-net prices weighted by average gross spending decreased annually by 1% from 2015 through 2019 for Medicaid, while increasing by 2% for non-Medicaid payers. In this cross-sectional study of 18 top-selling brand-name drugs, excluding 1 anomaly, Medicaid average net prices declined from 2015 to 2019. Simultaneously, for non-Medicaid payers, net price increased more than previously published marketwide growth rates, raising the importance of restraining drug price growth in non-Medicaid markets. Rigorous and transparent methods to estimate Medicaid discounts are imperative to understand patterns in Medicaid and non-Medicaid prices and develop policies that better align drug prices with clinical benefits.

Residential rooftop solar demand in the U.S. and the impact of net energy metering and electricity prices

We use a panel dataset of residential rooftop solar adoption for 27 states from 2008 to 2018 to estimate demand for rooftop solar and the impact of net energy metering compensation. We find demand is highly price elastic and that income is elastic as well. We find a large cross-price effect with respect to residential electricity price indicating that rooftop solar is a strong substitute for utility-provided electricity driven, in part, by poor residential rate design that primarily recovers fixed system costs through volumetric charges. We find that net energy metering has a large positive impact on the demand for residential rooftop solar, resulting in at least a doubling of demand and in uneconomic customer bypass of utility-supplied electricity, as net energy metering is not a market-based compensation rate. Our analysis lends support to ongoing state policy efforts to reform net energy metering and to improve electricity rate design.

Yes or Not in My Backyard (YIMBY vs. NIMBY)? The Impact of New Social Housing Construction on Single-Family House Prices in Quebec City (Canada)

The development of new social housing faces important resistance by local population, a phenomenon knows as the “not in my backyard” movement. One argument from residents to oppose such project is the idea that new construction will negatively impact property values. This is what this paper aims to investigate. The analysis is based on a complete recension of the new social housing projects built between 2000 and 2020 and on single-family house transactions that occurred between 2004 and 2020 in Quebec City (Canada). A repeated sales model integrating a difference-in-differences estimator is developed to isolate the net price premium related to the emergence of a new social housing building while accounting for the possible heterogeneity impact related to characteristics of the building, including the number of apartments and the type of clientele hosted as well as the local characteristics, such as the spatial concentration of social housing buildings and distance to the city center. The results show a complex net price premium rent function that leads to mixed conclusions and has important implications for the development of new social housing projects.

Urban Crime and Its Net Implicit Price to North Carolina Households

This study investigates the impact of urban crime rates—property and violent—on wages and rents and estimates the net implicit monetary value of crime rates for living in metropolitan areas, using the American Community Survey 2019 data for cities in North Carolina. A seemingly unrelated regression estimation finds that the crime rates are capitalized into both wages and rents, and suggests crime rates affect wages positively and rents negatively. This investigation estimates a negative value of $51.80 per month—the average net marginal implicit price—for living in cities with high city crime rates. This negative value suggests that households are being compensated for living in cities with high crime rates.

Pharmacy Benefit Management: The Cost of Drug Price Rebates.

Pharmacy Benefit Managers (PBM) induce drug manufacturers to offer rebates to insurers and employers by denying coverage through formulary exclusions, impeding physician prescription through prior authorization, and reducing patient drug use through cost sharing. As they tighten these access obstacles, PBMs reduce the net prices received by the manufacturers.

Resetting Prices: Estimating the Effect of Tuition Reset Policies on Institutional Finances and Enrollment

Private nonprofit colleges are increasingly using tuition resets, or a decrease in sticker price by at least 5%, to attract new students and counter declining demand. While discounting tuition with institutional aid is a common practice to get accepted students to matriculate and to increase affordability, a tuition reset is a more transparent approach that moves colleges away from a high aid/high tuition model. The authors find minimal evidence that these policies increase student enrollment in the long run, but that there may be short-term impacts. As expected, institutional aid decreases and varies directly with the size of the sticker price reduction. The average net price students pay decreases, but this effect may be driven by changes in the estimated non-tuition elements of the total cost of attendance. Finally, net tuition revenue appears unrelated to tuition resets. These findings call into question the efficacy of this practice.

A Study of Liquidity Analysis of Ambuja Cement for Last Ten Years

This research is carried out to examine the financial structure in terms of liquidity analysis of Ambuja Cement. Objective: To evaluate financial performance analysis of Ambuja cement for liquidity analysis. It assumed that there is no significant difference in liquidity ratio of Ambuja cement for financial year 2013 to 2022. Time Taken for Study: Normally it is not possible for the researcher to study the financial performance of any cement company for longer period because there is constrain of the time, money and efforts. So, the present study is done for ten years of period because of convenience for proper data collection and analysis for the period of ten years for the study. The present study is made for a period of last ten years i.e. accounting years 2013 to 2022. Parameters of the Study: Liquidity Ratios. Tools Used for Study: Descriptive Statistics and Analysis of Variance (ANOVA) Findings of the Study: The firm has failed to balance the current ratio for financial year 2021 only. Similarly, the quick ratio values can be good for firm if it has measured one or more than one. The ideal quick ratio is not found good for the financial year 2017, 2021 and 2022. It shows that the firm is failed to balance liquidity during the said years. It is observed that for each financial year the firm has least value of inventory turnover ratio of 8.89 for financial year 2019 and highest is measured for the year 2022. It is indicating that the firm has balanced inventory for each year. The ideal dividend pay-out ratio on net and current price is tends to the financial circumstances of the firm. It is observed that the firm has paid least dividend during financial year 2019 and 2020. It may be due to the Covid-19 pandemic.

Refusing the best price?

The Regulation National Market System (Reg NMS) links fragmented stock exchanges by routing orders to the National Best Bid and Offer (NBBO). As the NBBO ignores exchange fees, 62% of routings lead to worse net prices. An increase in fee differences increases the market share captured by orders that refuse Reg NMS routings, particularly for stocks whose fees account for a large portion of transaction costs. Heterogeneous opportunity costs rationalize routing choices: non-routable orders entail lower non-execution costs than routable orders. Our results indicate that fees and clientele segmentation drive the proliferation of order types in the Reg NMS era.