Low Price Research Articles

The bright side of analyst coverage: Evidence from stock price resilience during COVID-19

Understanding a firm's stock price resilience is crucial in an increasingly uncertain environment. We investigate the impact of financial analysts on a firm's stock price resilience. We find that firms in the Chinese stock market with higher analyst coverage were more resilient during the COVID-19 crisis and had lower pandemic-induced stock price declines, shorter decline and recovery periods, and higher recovery probability. This positive relationship is more prominent for firms with strong star analyst coverage and does not depend on ownership type or firm size. Moreover, analysts help firms attract attention from media and institutional investors, improve corporate governance by improving information disclosure quality (especially for private information), and reduce financial constraints, in turn, firms’ ability to absorb pandemic shocks improves. Overall, we demonstrate that financial analysts play a crucial role in shaping a firm's stock price resilience during crises, particularly for firms with strong star analyst coverage.

Geospatial Analysis of the Socioeconomic and Demographic Effects of Historic Coal Mining in the Greater Pittsburgh Region, Pennsylvania, USA

A geospatial model was developed to statistically assess the socioeconomic effects of coal mining in the greater Pittsburgh, Pennsylvania area by integrating home sale data, abandoned mine lands (AML) inventory “problem area” sites, and census demographic information. Results indicated that homes located within problem areas sold for an average of 28% ($58,600) less than homes outside of these regions. Demographic data revealed a notable disparity in the population distribution within Allegheny County mining problem areas as having a statistically significant larger Black population. This same trend was even more pronounced in urban areas. The study also established that areas influenced by past mining activities had a higher proportion of individuals without formal postsecondary education. Logistic regression models were created to analytically evaluate the relationship between predictor variables, specifically home sale price and Community Needs Index, to the probability of being situated within mining problem areas. The home sale analysis indicated a negative correlation between sale prices and the likelihood of residing in a mining-affected zone, implying that properties with lower prices are more commonly situated in these impacted areas. The CNI logistic regression model revealed a correlation between the probability of living in a mining problem area and overall higher community needs.

Socio-Demographic Profile, Farming Challenges and Local Government Unit (LGU) Support to Rubber Farmers in Tampilisan, Zamboanga Del Norte: A Pre and Actual Pandemic Analysis

This study investigates the socio-demographic profile, farming challenges, and the Local Government Unit (LGU) support to rubber farmers in Tampilisan, Zamboanga del Norte, Philippines. The research employed a pre and actual-pandemic analysis to assess the effectiveness of LGU extension services in empowering rubber farmers. Data from 50 rubber farmers across 15 barangays were analyzed using a descriptive-correlation method. Findings reveal that rubber farmers in Tampilisan are predominantly middle-aged, have a high school education level, and have low monthly incomes. Farmers engage in diverse farming practices, including intercropping and integrated farming systems, demonstrating adaptive strategies for income diversification. While participation in LGU extension services was high before the pandemic, it significantly declined during the pandemic due to restrictions and limitations. Farmers identified several key challenges, including low rubber prices, capital constraints, and lack of skilled labor, which persisted before and during the pandemic. Despite these challenges, farmers reported moderate agreement on the benefits derived from LGU extension services, particularly regarding education for their children and food security for their families. Findings also suggest that farmers' income correlates with the types of crops planted, indicating that diversifying crops like coconut, banana, and fruit trees can lead to increased income. More so, the correlation between farmer participation and the acquisition of farming tools and planting materials underscores the positive impact of active engagement on resource access. Analyzing the above results, the study revealed the importance of sustained farmer engagement in extension services for enhancing agricultural resilience and livelihood sustainability. The insights elicited from this study include strengthening technical training and infrastructure, promoting farmer group participation, and fostering collaboration between the Local Government Unit (LGU), educational institutions, and government agencies to ensure the effectiveness of extension programs and support sustainable rubber farming practices in Tampilisan.

Conditions for economic efficiency of latent heat thermal energy storage systems at nuclear power plants

In conditions of uneven schedules of electricity consumption and construction of power plants using renewable energy sources, nuclear power plants will participate in regulating the unevenness of daily energy consumption. At the same time, nuclear power plants have high economic feasibility of operating with a maximum installed capacity utilization factor due to significant capital investments at a relatively low fuel price. The use of nuclear power plants to cover uneven energy consumption will reduce the possibility of a return on investment, which will only be realized with greatly inflated capacity charges. At the same time, the annual operating costs will increase significantly. A possible decrease in the economic efficiency of a nuclear power plant is due to the fact that, at the request of the system operator of the energy system, the NPP will be to reduce electricity generation during off-peak hours or sell electricity on the market at significantly lower prices. In this regard, the problem of increasing economic efficiency of nuclear power plants under conditions of uneven daily energy consumption becomes particularly relevant. The solution to the problem could be the accumulation of excess energy and its subsequent use. Previously, the authors developed a method of additional redundancy of auxiliary needs of nuclear power plants based on the use of low-power steam turbines. In the present paper, schemes for increasing efficiency of using low-power steam turbines at nuclear power plants when regulating the load unevenness in the power system using thermal energy storage systems based on the latent heat thermal energy storage are developed. The design characteristics of the accumulator as part of a nuclear power plant are determined to ensure operation of the heat storage system throughout the entire period of energy consumption. In this research, the lithium nitrate was considered as a phase change material. The technical and system conditions under which the maximum economic effect is achieved have been determined. The boundary conditions under which a return on investment is achieved are shown.

Kepercayaan di Internet: Studi Kasus pada Korban Layanan Top Up Game Online di Media Sosial

This study aims to understand the characteristics of online game top-up fraud victims on social media, especially teenagers. Advances in technology and internet access have changed the way people seek entertainment, including online games, but have also triggered fraud in top-up transactions. This research identifies factors that make teenagers vulnerable to becoming victims, such as attractive promotions, many account followers, and low prices. Data was collected through observations and interviews with teenagers who have been victims of online game top-up scams. The results show that victims are generally teenagers aged 21 and under who are easily trusting, often find out about top-up services through social media such as Instagram, and tend to trust accounts recommended by friends or family. Promotional factors, number of followers, and low prices are the main drivers of transactions that lead to fraud. This research is expected to raise public awareness about the importance of vigilance in online transactions and provide insights for the development of fraud prevention strategies among teenagers.

Impacts of CEO-employee pay disparity on investor behavior and market dynamics: Evidence from laboratory asset markets

This study explores the impacts of CEO-to-employee pay disparity on investor behavior and market dynamics using an experimental methodology. We employed two laboratory asset markets with identical company valuations but differing CEO-employee pay ratios. Our findings reveal that a higher pay ratio leads investors to quote higher prices for the company's stock. This effect is driven by two conflicting mechanisms of social preference: inequality aversion, which motivates investors who value fairness to quote lower prices for stocks of companies with high pay ratios, and social comparison, where the high pay ratio prompts investors to compare their wealth with that of CEOs, thus becoming more risk-seeking and quoting higher prices. Moreover, higher pay ratios contribute to increased stock prices, fostering larger market bubbles, enhancing the dispersion of investor opinions, boosting trading volumes, and escalating market volatility. This study enriches our understanding of how asset markets react to CEO-to-employee pay disparities, providing valuable insights for policymakers and market participants.

Structural Modification Effect of Se-doped Porous Carbon for Hydrogen Evolution Coupled Selective Electrooxidation of Ethylene Glycol to Value-added Glycolic Acid.

The ethylene glycol oxidation reaction (EGOR) has attracted attention because ethylene glycol (EG), which exhibits large-scale production and a low market price, can be reformed into valuable glycolic acid (GCA) with the cogeneration of high-purity hydrogen gas during the reaction. In this study, a noble catalyst material of Pt nanoparticles supported on Se-doped porous carbon (Pt/SePC) is prepared and investigated for the selective electrochemical oxidation of EG to GCA. Pt/SePC achieved a maximum EG conversion of 94.6% and GCA selectivity of 84.4% and maintained this high performance with negligible degradation during durability tests. Furthermore, the EGOR required lower overpotential rather than the oxygen evolution reaction, thus the EGOR coupled with the hydrogen evolution reaction can reduce the cell overpotential to 0.60 V, which is much lower than that of water electrolysis (1.58 V). The effect of Se doping is investigated through experimental analyses and density functional theory (DFT) calculations, and they shows that Se modified the binding energy of Pt nanoparticles and the adsorption energy of reactants by lattice deformation and charge density modification. This study provides scientific insights and strategies for electrocatalyst design for the selective oxidation of polyols to value-added chemicals via the cogeneration of hydrogen gas.

Under the context of competition between platform sales and live streaming sales, who has the pricing power of products?

The rapid rise of live-streaming selling and the increasing diversity of e-commerce channels have sparked ongoing debates regarding product pricing power. This price competition behaviour of online dual channels triggered by the supply-side pricing dilemma is a topic of significant research interest and forms the focal point of this paper. Therefore, we leverage the principles of game theory to construct a three-party evolutionary game model consisting of a brand, a steamer, and a traditional e-commerce platform. Within this framework, the brand holds the primary pricing authority. Our analysis examines the equilibrium strategies adopted by the various players under diverse scenarios and explores how the evolving behaviours of these parties impact the overall game system. Additionally, we employ the “people-goods-scene” perspective to deconstruct the intricate dynamics within this complex supply chain ecosystem. Our findings reveal two distinct evolutionary stable strategies: one in which brands maintain a stance against low-price negotiation, streamers avoid bargaining, and platforms avoid providing subsidies; the other in which brands are open to negotiating low prices, streamers engage in bargaining, and platforms provide subsidies. Notably, in most cases, brands tend to avoid explicitly stating their opposition to low-price negotiation. However, if a brand’s strategy shifts towards rejecting such negotiation, the negative implications of price wars across channels become a critical consideration. Conversely, when a brand opts for a more concessive pricing strategy, we need to consider the potential positive impacts of low-price competition.

Determinants of Intra-City Residential Migration Patterns of Older Adults: A GIS and Decision Tree Analysis of Yancheng City, China

This study investigates the spatial patterns of residential migration among older adults in the city center of Yancheng and the influencing factors using data on the home purchases of individuals aged 65 and older from 2016 to 2018, along with peripheral point of interest (POI) data, analyzed with ArcGIS and a decision tree model. The results indicated that persons aged 60–65 accounted for 42.8% of the total sample and primarily chose to migrate in the early stages of retirement. The intra-city migration of older adults exhibits both centripetal and centrifugal patterns, with a greater tendency toward the city center. House prices, floor levels, and commercial facilities significantly impact their choice of migration destinations. Among these, house prices were the most critical determinant, with the majority of older adults migrating to neighborhoods with lower house prices. This study contributes by integrating residential migration and location choice research and constructing an analytical framework based on facility accessibility. The findings provide insights into the key determinants of location choice for intra-city residential migration among older adults and the construction of livable neighborhoods for them.

Cannabis consumers’ preferences for legal and illegal cannabis: evidence from a discrete choice experiment

BackgroundIn U.S. states that legalized and commercialized recreational cannabis, cannabis sales in illegal markets are still sizable or even larger than those in legal markets. This study aimed to assess cannabis consumers’ preferences for purchasing cannabis from legal and illegal markets and estimate the trade-offs under various policy scenarios.Methods963 adults were recruited, who used cannabis in the past year and lived in a state with recreational cannabis legalization. In a discrete choice experiment, participants chose purchasing cannabis from a legal dispensary or an illegal dealer with varying levels in product attributes including quality, safety, accessibility, potency, and price. Mixed logit models were used to analyze preferences.ResultsThe likelihood of choosing legal cannabis increased with a higher quality, the presence of lab test, a shorter distance to seller, a higher tetrahydrocannabinol level, and a lower price. The likelihood of choosing illegal cannabis increased with a higher quality, a shorter distance to seller, and a lower price. Among product attributes, quality and accessibility were perceived to be the most important for legal cannabis and price was perceived to be the most important for illegal cannabis. Policy simulations predicted that improving quality, ensuring safety, allowing delivery services, increasing dispensary density, and lowering prices/taxes of legal cannabis may reduce illegal cannabis market share.ConclusionsIn the U.S., cannabis consumers’ preferences for illegal cannabis were associated with both legal and illegal cannabis product attributes. Policies regulating legal cannabis markets should consider potential spillover effects to illegal markets.

Operation of coupled power-gas networks with hydrogen refueling stations, responsive demands and storage systems: A novel stochastic framework

Because of factors such as low natural gas prices, low greenhouse gas emission and high efficiency has increased the penetration of natural gas-fired generators in electric power systems. Large gas consumption of gas-fired generators has caused intense interdependence of electricity and gas systems. Most often, the operational planning of power and gas systems is conducted through a co-optimisation model in which the total cost of electricity and gas systems is minimised and the constraints of both systems are considered. On the other hand, due to environmental concerns, the usage of fuel cell vehicles (FCVs) is increasing. Hydrogen refueling stations (HRSs) are needed for refueling FCVs. This paper puts forward a stochastic model for co-optimisation of wind-integrated power and gas systems, hosting HRSs, electric storage systems (ESS's) and responsive electricity and gas demands. The effect of ESS's, responsive demands, contingencies, wind uncertainties and demand response on operation of power-gas nexus is scrutinized. An incentive-based demand response program has been used for both electricity and gas demands. The case study is the Belgian gas network connected to the a 24-bus power system. The findings indicate that responsive electric demands reduce electric system cost by 9.4 %, while responsive gas demands reduce the gas network cost and total operation cost by 1 %. The contingency analysis on the power-gas nexus shows that single line outage contingencies in power system does not result in any demand shed and does not increase the operation cost of either electricity network or gas network.

Study on the Stability of Fe/Al2O3 Interface in Metal-Based Cermets Using Thermodynamic Modeling

Iron-based cermet has the advantages of high-temperature resistance, low price, good performance, and so on. At present, most of the studies on cermets are focused on the measurement of macroscopic properties and optical microscopic characterization, while there are few microscopic studies on the interface structure. In this paper, based on density functional theory (DFT), the stability of the Fe/Al2O3 interface is studied, and the stability difference and interface formation mechanism of different end combinations are investigated. By calculating the surface energy, adhesion work, interface energy, density of states, charge density, differential charge density, and so on, it was concluded that the stability of the O-terminal interface was greater than that of the Al interface. It has a certain guiding role in the preparation of Fe/Al2O3 cermet materials.

Efficiency Unveiled: Comparative Analysis of Load Balancing Algorithms in Cloud Environments

Load Balancing is fundamental for reliable activities in presented problems. As Cloud Registering is just one of the most effective stages, which provides a capability of data at a lower price as well as is accessible for good over the internet, payload balancing for the Cloud has come to be an extremely amazing and also notable exploration location. Load harmonizing assists with achieving superior client fulfillment and also asset utilization percentage by promising every resource's efficient and fair portion. Numerous summations were suggested to give effective parts to update the Cloud's standard discussion and also give the customer very serious meeting and efficient company.

Simulation of extractive distillation of C6 components from Fischer‐Tropsch Synthesis oil

AbstractExtractive distillation is used for separating oxygenates from other components in the C6 cut oil from Fischer‐Tropsch Synthesis followed by separating 1‐hexene from N‐hexane using the same solvent as the extractant. Furfural (FUR) is identified as an excellent solvent for extractive distillation of the C6 cut from FTS oil for separating oxygenates from other components as well as for separating 1‐hexene from N‐hexane via searching from more than 100 solvents by simulation using Aspen Plus. The behavior of the newly found solvent FUR is compared with that of the reported best solvent N‐methyl‐2‐pyrrolidone (NMP) and the results show that FUR scheme has the advantages of lower market price, lower dosage needed, less reboiler duty required and higher overall tray efficiency for fulfilling the same separation task.

Antitumor properties of griseofulvin and its toxicity.

Griseofulvin (GF), which is mainly extracted from Penicillium griseofulvum, is a heat-resistant, chlorine-containing non-polyene antifungal antibiotic. Previous research shows that GF has a variety of pharmacological effects, such as anti-inflammatory, antifungal, antiviral, and antitumor effects. In recent years, GF has received extensive attention for its antitumor effects as a natural compound, offering a low price, a wide range of uses, and other beneficial characteristics. However, no comprehensive review of GF pharmacological activity in tumors has been published so far. In order to fully elucidate the antitumor activities of GF, this review focuses on the antitumor potential and toxicity of GF and its derivatives, based on a literature search using PubMed, Web of Science, and other databases, to lay a good foundation for further research of GF and the development of new drugs for antitumor activities.

Design: UI/UX Penjualan Telur Ayam di Cilacap dengan Metode R&D

Nowadays, more and more e-commerce platforms are emerging, creating a highly competitive environment for both individuals and groups. User experience and interface are key factors in attracting users' attention and fulfilling various needs to survive in a crowded market. In this context, the author proposes the prototyping of a chicken egg sales application named EiTech Supply in Cilacap Regency. This application is designed to overcome the problems that chicken egg farmers often face, such as competition between regions and the entry of new farmers with very low prices to attract customers. With the EiTech Supply application, it is expected to reduce these problems and increase the competitiveness of chicken egg farmers both inside and outside the region.

Lenacapavir to prevent HIV infection: current prices versus estimated costs of production.

Despite improvements in treatment and oral pre-exposure prophylaxis (PrEP) access, 1.3 million people acquired HIV in 2022. Six-monthly lenacapavir PrEP could benefit tens of millions of people at high risk of infection. However, prices are currently up to $44 819 per person per year (pppy). We projected minimum lenacapavir pricing based on generic mass production and a Cost-Plus (Cost+) model. Current active pharmaceutical ingredient (API) and key starting materials (KSMs) costs were obtained from export databases. The routes of synthesis (ROS) were analysed to project a cost of goods (COGs). Formulation, vials and profit margin costs were included using standardized algorithms and Cost+ pricing. We estimated prices with scale-up to supply 1 million then 10 million treatment-years, comparing this with national list prices. The lenacapavir API is currently exported from India for $64 480/kg on 1 kg scale. Based on the ROS and KSMs, API COGs of $25 000/kg and $10 000/kg are achievable for a committed demand of 1 million (2 million tonnes/annum of API) and 10 million treatment-years, respectively. Including formulation steps, injectable lenacapavir could be mass produced for approximately $94 pppy for 1 million and $41 for 10 million treatment-years, if voluntary licences are in place and competition between generic suppliers substantially improves. Greater scale-up with improvements in manufacturers' ROS could reduce prices further. Currently lenacapavir costs $25 395-44 819 pppy. Lenacapavir could be mass produced for <$100 pppy at launch. Voluntary licensing and multiple suppliers are required to achieve these low prices. This mechanism is already in place for other antiretrovirals. To date, Gilead has not agreed lenacapavir voluntary licences with the Medicines Patent Pool.

Stock Market Prediction in Nepali Stock Market using Machine Learning Model

The stock market, a key driver of the global economy, presents a formidable challenge for accurate prediction due to its intricate, chaotic, and dynamic nature. This study explores machine learning approaches, specifically comparing three prediction models—Back Propagation Neural Network (BPNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The analysis incorporates historical stock trading data, including open, high, low, and close prices, and technical analysis indicators such as moving average, Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Commodity Channel Index (CCI) so on. The evaluation focuses on the performance of these models in predicting future trends in stock prices, utilizing data from the Nepal Stock market spanning from 2013 to 2023. The selected stocks for analysis include two stock NIC Asia Bank Limited and, NMB Bank Limited, two index NEPSE and Hydropower index. Through rigorous assessment, it is determined that LSTM demonstrates superior overall performance compared to GRU and BPNN. This research contributes valuable insights into the effectiveness of machine learning models in forecasting stock market trends, with implications for investors and financial practitioners.

Enhancing bargaining power for energy communities in renewable power purchase agreements using Gaussian learning and fixed price bargaining

Power purchase agreements aim to secure long-term contracts between sellers and buyers, particularly in renewable energy transactions. However, successful negotiations for a fixed long-term price and energy volume while ensuring maximum utility for stakeholders remains a significant challenge. This paper introduces a comprehensive model for negotiating 24/7 power purchase agreements, focusing on hourly pricing to address deficits and surpluses throughout each day of the contract timeline. The model incorporates demand flexibility through battery storage, settling on the strike price using Nash Bargaining theory and optimal management of energy consumption relative to market price fluctuations. A soft margin support vector machine classification model determines the buyer’s maximum acceptable price. Moreover, Gaussian process classification is employed to calculate a probabilistic, risk-adjusted strike price, enabling a data-driven approach to power purchase negotiations. The proposed model’s performance is demonstrated through a detailed case study of Norway, illustrating how demand flexibility can significantly lower long-term power purchase agreement contract prices. The analysis of yearly price trends indicates that incorporating flexibility resources in long-term energy contracts may lead to a reduction in strike prices by around 25%. Moreover, such flexibility enhances demand-generation matching, thereby increasing renewable energy transactions within such agreements.

Equilibrium vertical structure with a common supplier

AbstractWe consider a vertically related market, in which each downstream firm produces a differentiated product by assembling a key input produced by a common supplier and another input produced by a dedicated upstream firm. On the one hand, vertical integration has the advantage of inducing the common supplier to set a lower input price, but the disadvantage of reducing downstream firms' competitiveness in the downstream market. On the other hand, vertical separation has the advantage of increasing downstream firms' competitiveness in the downstream market but the disadvantage of inducing the common supplier to set a higher input price. Contrary to results of previous studies, we find that the existence of a common supplier can lead to vertical integration under Cournot competition, which emerges as a unique equilibrium when a common supplier adopts input discrimination. Although vertical integration is better for the individual firms, it reduces the total welfare. Even when the common supplier uses uniform input pricing, vertical integration also emerges in equilibrium.