Market Profitability Research Articles

Financial Indicators and Stock Market Performance in Nigeria

This study examined financial indicators and stock market performance in Nigeria. The low performance of the stock market has been attributed to so many factors, ranging from financial, macroeconomic to political and institutional. Hence, the study examined the relationship between financial indicators and stock market performance, using the econometric analytical technique. Annual time series data sourced from the Central Bank of Nigeria and Nigerian Stock Exchange were employed. Stock market performance was measured by all-share index while financial indicators were represented by stock market profitability, liquidity and efficiency. The bound testing and Autoregressive Distributed Lag model estimation techniques were employed for the analysis. It was revealed that a long run relationship exists among the variables in the estimated model. A positive relationship exists between market profitability, liquidity, efficiency and stock market performance in Nigeria with coefficients of 58.98, 879.58 and5152.51, respectively. The implication of the findings is that market profitability, market liquidity and market efficiency have positive impact on stock market performance in Nigeria. Hence, the study recommends that; there is need for implementing policy such as good corporate governance that will maximize profit for investors in the market, make it attractive and hence deepen the Nigerian stock exchange market; the provision of windows for firms to raise cash through issuance of new shares, debentures, loans and deposits, when needed and enhance the ability of the firms to convert assets to cash to pay its current liabilities and its debt capacity;while a high trading volume should be maintained to enhance efficiency of the Nigerian capital market.

Multi-criteria Agriculture Recommendation System using Machine Learning for Crop and Fertilizesrs Prediction.

Agriculture plays an essential role in the economies of developing countries such as India and contributes significantly to the gross domestic product (GDP). The escalation in population has led to an upsurge in food demand. Numerous challenges such as the selection of crops, fertilizers, and pesticides without considering the various parameters like types of soil, water requirement, temperature conditions, and profitability analysis of crops for a particular region may lead to degradation in the quality of crop, yield and profitability. With the advancement of Computational technologies, researchers are working on recommending crops according to soil condition, water requirement, and market profitability along with fertilizers recommendation, disease identification, and pesticide recommendation. Through this research, we propose a machine learning-based crop and fertilizer recommendation algorithm called AgriRec. We have utilized soil properties, water level, farm size, and minimum support price of crop and design a machine learning model which predicts crops for different seasons. Further, we propose another mechanism that processes the properties/details of soil, crop, and fertilizer to envisage a combination of fertilizer(s) for a given pair of soil and crop. Our algorithm is tested for 5000 land samples of Gujarat region with 24 different crop and it successfully recommends crops with 95.85% accuracy and fertilizer with 92.11% accuracy with 4 times better performance as compared to existing benchmark recommendation approaches.

Margin Analysis and Efficiency of the Day Old Duck (DOD) Marketing Channel (Case Study on Adam Gobek Lareh Sago Halaban)

Through creating and exchanging products and value with others, marketing is a social and management activity that enables individuals and groups to fulfill their needs and desires. This study analyzes DOD's channels, margins, profits, and marketing efficiency in Adam Gobek Lareh Sago Halaban hatchery. This research was conducted from March 2021 to May 2021. The data collection method used was a survey method. This research is a case study on Adam Gobek Lareh Sago Halaban to determine the sample in the marketing channel used snowball sampling. The results showed five marketing channels for DOD in Adam Gobek's hatchery business. The highest marketing margin is in marketing channel IV, amounting to IDR2,000.00/tail. In contrast, the marketing channel with the lowest Margin is marketing channel II of IDR940/tail. The highest marketing profit is marketing channel I of IDR861/director, while the marketing channel with the lowest profit is marketing channel II of IDR292/tail. A very efficient marketing channel is marketing channel I, with a percentage of 1.7%, while inefficient marketing is visible on marketing channel IV, with a percentage of 5.6%.

Determinants of Investor Awareness in Nepalese Capital Market

Background: Capital market investors have propelled the industry, and the stock market has worked as a facilitator; hence, in order to develop a successful market system, all information must be acknowledged and delivered to the acquisition and offering sectors. It is obvious that educating investment communities or stakeholders about their possible return on Investment, investment objectives, alternatives, decision-making processes, and so on might aid in the acceleration of capital market expansion. As a result, the research aims to increase investor awareness and stock trading in the capital market. Objectives: The main purpose of the study is to explore the extent of awareness of common stock investors and analyze the determinants of investors' awareness in the Nepalese capital market. Methods: The research design for the study is a survey research design, and convenience sampling was used to collect 250 samples from various brokerage houses within Pokhara valley. Data was collected with a structured questionnaire. Various analysis tools like Confirmatory Factor analysis and Path analysis were used to examine the relationship between Investor's awareness and its determinants. Results: The result of CFA with fit indices of GFI=0.938, AGFI=0.913, χ2/df=1.233, RMSEA=0.031, CFI=0.896 and TLI=0.881 advocate that the measurement model has an excellent fit. Furthermore, path analysis results show that the majority of independent factors, including social learning and motivation, fundamental and technical analysis, and evaluation of investment alternatives, have a significant and positive impact on the dependent variable investor awareness. Conclusion: The study highlights the importance of investor awareness for effective investment decisions and the growth of the capital market in underdeveloped economies like Nepal. Investors' understanding is essential for investment decisions and the long-term growth of the capital market. So, there should be a proper understanding of various determinants of investors' awareness and work accordingly. Recommendation: Marketing campaigns, seminars, publications, and FM/TV shows, among many other means, should be used by regulatory agencies such as SEBON to inform the general public about the dynamics of risk and profit in the capital market.

A bi-level framework for interactive competition and CPPs-based demand response

This paper proposes a multi-leader–follower framework for interactive competition among participants. To do so, a Stackelberg game model is formulated to take into account the price competition between leaders and captive power plants (CPPs). The retailer and the distribution company (DISCO) adopt a rival strategy to determine sale prices, aiming to maximize respective profit in a competitive market. DISCO pricing bound is set during the interaction process. The response at the lower level also affects hierarchical prices and CPP revenue. CPPs enact demand response viable through load shifting and peer-to-peer (P2P) energy trading. A quadratic penalty function is employed in the model to reduce the peak load demand and reshape the load profile, which brings the load consumption curve close to the forecast value. A general Nash bargaining game is utilized to incentivize P2P energy sharing with neighbors. To solve the multi-leader–follower model, a fixed-point iteration algorithm is proposed, which enables the model to reach convergence. Simulations are conducted to demonstrate the price–demand relationship and hierarchical interaction.

Conflicting Interests of Trading Companies and Causes of the South African War, 1899-1902

The author examines the economic aspects of the South African colonial exploration by the Europeans in the representation of accumulated contradictions between business organizations, which ultimately became a cause of the 1899-1902 conflict. Based on the study of Dutch East India Company’s activities in this region, as well as the specifics of the settlement establishment by the British and Boers, attention is paid to the root causes of the disharmonious economic situation of the rivalling parties, taking place before the discovery of gold deposits in the Witwatersrand (1886). The changing regional supremacy of the Cape colony and the other British possessions, as well as Boer States (the Republic of South Africa – Transvaal and the Orange Free State) has been periodized. The factors of the 1899 armed conflict have been structured to reveal the conflicting interests of trading companies which had sought to monopolize the business for extraction of valuable mineral raw materials. The author concludes that the main reason for the South African War was the desire of British trading companies to gain access to rich gold deposits in the Boer-populated Transvaal and form a single English-based state in South Africa. In order to achieve such goal, the British tried their best at delaying peace initiatives of the Boers, putting forward various contradictory demands to them, using the armies of private companies to conduct raids and sabotaging the formation of a federal state in the region. We have discovered the preposterous look of the British pretext for the outbreak of war, based on the protection of the Boer states English-speaking population interests, which had been supposed to initiate an uprising. The South African War became not only a place, where new methods of warfare were applied, and a “black hole” for the UK budgetary expenditures, but also a profitable market for new types of weapons and military equipment, which allowed their manufacturers to make considerable profits.

The Problem with Capitalism in the Trichological Sciences.

Karl Marx and Friedrich Engels exposed a pattern of societal conduct they chose to name capitalistic bourgeoisie. The bourgeoisie created a common language of communication through collaboration, gathered in circles such as free academies, scientific academies, literary circles, and the media, that provided forums for the emerging bourgeoisie to conceive of new social orders. One aspect of bourgeoisie culture is conspicuous consumption, central to which, is a culture of prestige through material consumption. Capitalism is an economic system based on private ownership and the operation for profit. Characteristic features of capitalism include competitive market, commercialism, property rights recognition, capital accumulation, material consumption, culture of prestige, sycophancy, and coterie. Critiques of capitalism allege that it is exploitative, alienating, unstable, unsustainable, and inefficient. In turn, critical theory inspired philosophers such as Michel Foucault to conceptualize how we form identities through social interaction. When the patient's body entered the field of medicine, it also entered the field of power where the patient can be manipulated by professional authority. Without forcibly being a proponent of political theory, as an academic, one is inevitably confronted with Marxism in terms of philosophy. As a discipline at the interface of medicine, lifestyle, and cosmetics, trichology is particularly susceptible to the primary aims of profit, consumption, and prestige that characterize the capitalistic bourgeoisie. The trichological sciences, particularly trichoscopy, have discovered a profitable market for itself. The practice of trichology is not immune to malpractice. It has created an industry that dwells on the autistic thinking of patients and doctors, and because it is prosperous, makes propaganda among lay people and doctors that necessarily leads to abuses.

Analisis Pendapatan Agroindustri Ubi Kayu Di Kabupaten Deli Serdang, Indonesia

One of the empowerment of micro small businesses carried out by the Regional Government of Deli Serdang is the utilization of cassava as a raw material for agroindustry which has the potential to be developed and has a profitable market potential for MSMEs. Even cassava agroindustry commodities can be a source of income for farmers/entrepreneurs who support the movement of the regional economy. Therefore this study aims to analyze the income of MSMEs in Deli Serdang Regency. The population of this study were all cassava-based micro, small and medium agroindustry entrepreneurs in Pancur Batu District, Deli Serdang Regency. The sample was selected as many as 35 MSMEs that process cassava into opaque. Data collection techniques using questionnaires, field observations and literature study. The data analysis technique used is the cost, revenue, income and R/C analysis model. The results of the research show that variable costs are the biggest costs compared to other costs. The average cost of production incurred by MSMEs is Rp. 293,071,511 per month, the average income is Rp. 318,000,000 per month and the average income is Rp. 24,928,489 per month, with an R/C ratio of 1.08 which means that the cassava agroindustry is profitable or feasible to develop in the research area.

Does financial education help to improve the return on stock investment? Evidence from China

Individual investors are important capital market participants, and improving their financial welfare has been a long-standing objective for policymakers and researchers. Using the data from a national survey on individual investor behavior in China, we explore the relationship between individual investors' financial education attainment and the performance of their stock portfolios. The results show that individual investors who receive financial education are more likely to increase their profits in the stock market because they have good investment habits and elevate theirare more risk tolerant. Further, financial education demonstrates a greater effect on stock market profit making among investors with less experienced and from areas with lower levels of investor protection.

The Value of Craft Beer Styles: Evidence from the Italian Market.

This study aims to estimate the market value, or implicit prices, associated with the main craft beer attributes (e.g., beer style, organic, gluten-free, and package-related features) and support producers in detecting the more profitable marketing strategies. For this purpose, we conducted an empirical analysis employing sales data of craft beers from the Italian online market, and we estimated a hedonic price model via ordinary least squares. Results show that the type of package and cup only has moderate effects on price. Furthermore, a moderate premium price is found for gluten-free craft beers, while craft beers with organic labels and Italian origin do not benefit from the higher price. Instead, the beer style adopted strongly affected the product price: the highest premium prices were detected for Barleywine (+49.9%) and Italian Grape Ale (+39.6%) beer styles. Furthermore, relevant premium prices, higher than +25%, were estimated for other beer styles such as Sour, Fruit Beer, and Stout. Results suggest that artisanal breweries can effectively differentiate their product according to the beer style. To the best of our knowledge, the current study offers the first empirical evidence on how beer styles as well as other product characteristics affect the market price of craft beer by using secondary data.

Price Competition with Differentiated Products on a Two-Dimensional Plane: The Impact of Partial Cartel on Firms’ Profits and Behavior

A numerical procedure capable of obtaining the equilibrium states of oligopoly markets under several assumptions is presented. Horizontal and vertical product differentiation were included by taking into account Euclidean distance in a two-dimensional space and quality characteristics of the product. Different quality preferences of consumers were included in the model. Firms implement two strategies in the market: profit maximization and market share maximization. Numerical discretization of a two-dimensional area was performed for computing the equilibrium prices which allows one to consider any market area and any location of the firms. Four scenarios of oligopoly markets were developed by combining both strategies from one side and competitive behavior and a partial cartel agreement from another side. The main differences between the scenarios are outlined. Profits, market shares and equilibrium prices are presented and compared. The influence of collusion, the existence of participants with a market share maximization strategy and consumer preferences on the firm’s profits and equilibrium prices were examined. Cases whereby firms prefer to leave the cartel were investigated. Best locations for the setting of a new store for profit maximization are shown and discussed.

Joint pricing and inventory management in a competitive market using reinforcement learning: a combination of the agent-based and simulation-optimization approaches

ABSTRACT One of the most important tools is an appropriate pricing mechanism to attract more customers and increase profits. The retailers’ main question is how to set the prices and inventory policies to maximize profit in a competitive heterogeneous market in presence of non-zero lead time and lost sales. A reinforcement learning algorithm is proposed to create appropriate decision-making mechanisms for pricing. A coordinated inventory policy in a competitive environment reduces logistic costs and leads to a higher profit. We use a reinforcement learning algorithm to investigate the performance of a retailer in a competitive environment. An agent-based modeling experimental environment combined with a simulation-optimization method in which a virtual market has been reproduced is used. The market is not homogeneous with respect to customer behavior. It is assumed that the retailer uses (R, Q) policy where the lead time is a fixed amount (L), and the shortage is permissible. The quality, distance, service level, and price are factors that influence customers’ choices. The simulation results for some randomly generated examples show that the algorithm in the competitive environment can make more profit than other available methods and the combined utilization of simulation-optimization methods has been able to find better solutions for the hybrid model of pricing and inventory management considering customer behavior. The results of simulation for three different categories of customers (more sensitive to price, equally sensitive to price, quality and service level, and more sensitive to quality (indicate that the average profit for the proposed algorithm is higher than that of other examined algorithms.

Earning Power Modelling for Manufacturing Operation

One of the most important criteria to consider while analysing the MTO company’s ability to make a profit in a competitive market is earning power. Specifically, this is defined by the Earning Power criterion. This means that the Earning Power modelling is a solid strategy for selecting and assessing which orders will bring profit to companies. As a result, a company manager must provide a model that can interact with the economic environment to make an offer and a price quotation to ensure the competitiveness of the company. In this article, we analyse this criterion for the processing operation.

Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm

Coordinated energy scheduling and management strategies in the energy hub plan are essential to achieve optimal economic performance. In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. The conventional FLA is inspired by the concept of Fick’s diffusion law, and, in this study, its performance against premature convergence is improved by using Rosenbrock’s direct rotational method. The performance of the IFLA when applied to EH coordinated scheduling and management problems with the aim of profit maximization is compared with the conventional FLA, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO) methods. The results show that the proposed scheduling and multi-energy management framework achieves more energy profit in the day-ahead electricity, gas, and heating markets by satisfying the operation and EH constraints compared to other methods. Furthermore, according to the findings, the increased (decreased) demand and the forced outage rate caused a decrease (increase) in the EH profit. The results show the effectiveness of the proposed framework to obtain the EH maximum energy profit in the day-ahead market.

The Dual Effects of Team Contest Design on On-Demand Service Work Schedules

Emerging on-demand service platforms (OSPs) have recently embraced teamwork as a strategy for stimulating workers’ productivity and mediating temporal supply and demand imbalances. This research investigates the team contest scheme design problem considering work schedules. Introducing teams on OSPs creates a hierarchical single-leader multi-follower game. The leader (platform) establishes rewards and intrateam revenue-sharing rules for distributing workers’ payoffs. Each follower (team) competes with others by coordinating the schedules of its team members to maximize the total expected utility. The concurrence of interteam competition and intrateam coordination causes dual effects, which are captured by an equilibrium analysis of the followers’ game. To align the platform’s interest with workers’ heterogeneous working-time preferences, we propose a profit-maximizing contest scheme consisting of a winner’s reward and time-varying payments. A novel algorithm that combines Bayesian optimization, duality, and a penalty method solves the optimal scheme in the nonconvex equilibrium-constrained problem. Our results indicate that teamwork is a useful strategy with limitations. Under the proposed scheme, team contest always benefits workers. Intrateam coordination helps teams strategically mitigate the negative externalities caused by overcompetition among workers. For the platform, the optimal scheme can direct teams’ schedules toward more profitable market equilibria when workers have inaccurate perceptions of the market. History: This paper has been accepted for the Service Science Special Issue on Innovation in Transportation-Enabled Urban Services. Funding: This work was supported by the National Science Foundation [Grant FW-HTF-P 2222806]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/serv.2023.0320 .

Nested Bilevel Energy Hub Bidding and Pricing With Price-Responsive Demand

The increasing interdependence among different energy systems has led to the development of the integrated energy system (IES), where the energy hub (EH) is a primary market player in the distribution-level energy market. In an EH, subsystems such as electric, natural gas, and heating systems coexist and are interdependent. This paper proposes an innovative bilevel strategic decision-making framework of an EH that maximizes profit in the energy market and simultaneously reallocates profit among EH subsystems through a dynamic pricing mechanism. In the upper level, the EH acts as a price maker in the day-ahead distribution electricity market for profit maximization. In the lower level, Nash-Bargaining-based profit redistribution is realized through bilateral pricing between energy subsystems in the EH, where the fairness and interests of individual subsystems are respected. The price-responsive load couples the profit maximization and profit reallocation problems. Case studies demonstrate that the proposed framework can effectively solve the bidding and pricing problem of an EH in a day-ahead market, and the cooperation within energy subsystems contributes to higher overall profit and better fairness for the EH subsystems.

The international regime of drug control may violate the human right to life and security.

Critics of the international regime of drug control have often pointed to its criminogenic effects, maintaining that drug criminalization gives rise to a profitable illicit drugs market which in turn sustains organized crime networks. Here I will expand upon this critique to argue that the violent crime resulting from the drug criminalization regime may constitute a violation of the human right to life and security. To support this argument, I will discuss the extent to which policy makers and the citizens who empower them may stand morally responsible for unintended but foreseeable consequences of the policies they implement. I will note that a north-south imbalance is at play: while the Global North has been the driving force behind the criminalization regime, the violent criminality entailed by the regime of drug control has impacted the Global South most strongly.

Looking for ‘Uncle Johnnie’: The extraordinary success of Johnnie Walker Scotch Whisky in India

This case study examines the factors underlying the success of Johnnie Walker Scotch whisky in India. India provides a quixotic case in that it is the world’s largest whisky market, despite having a long tradition of abstinence and social stigma towards alcohol-drinking. The paper traces the history of Johnnie Walker and how it metamorphosed from a tradition-bound Scottish company into a global brand with its footprint in more than 180 countries. India has emerged as a very profitable market for Diageo, the parent company of Johnnie Walker. Detailed here are the distinctive characteristics of the Indian alcohol market as well as the novel tactics Diageo has implemented towards Johnnie Walker’s goal of capturing 56 per cent of the Scotch market in the country. The paper ends with managerial implications that are relevant for marketing professionals and brand practitioners even in disparate industries looking to penetrate and develop overseas markets.

System and Market-Wide Impact Analysis of Coordinated Demand Response and Battery Storage Operation by a Load-Serving Entity

Because of electricity markets, environmental concerns, transmission constraints, and variable renewable energy sources (VRES), coordinated operation of demand response (DR) and battery energy storage systems (BESS) has become critical. In turn, the optimal coordinated operation of DR and BESS by an entity can affect overall electricity market outcomes and transmission network conditions. The coordinated operation is desirable for the profit-seeking entity, but it may adversely affect the cost and revenues of other market participants or cause system congestion. Though few coordinated operation models already exist, our aim in this research is to provide a novel multi-objective optimization-based methodology for the coordinated operation of DR and BESS to boost market profit. Moreover, another goal is to simultaneously study the combined effects of such coordinated models on transmission networks and electricity markets for the first time. This paper has proposed a new method for coordinated DR and BESS utilization by a load-serving entity (LSE) to increase its profit. Moreover, it has employed agent-based modeling of the electricity systems (AMES) for testing our coordinated DR and BESS method under day-ahead market and transmission system conditions. Simulation results of case studies indicate that the operating costs of all LSEs decreased, and there was as much as 98,260 $/day in cost savings for BESS deploying LSE1. Although revenues of cheaper generation companies (GenCos) decreased, those of expensive GenCos increased or showed mixed trends. For example, GenCo 3 exhibits an 8765 $/day decrease in revenue for 25% BESS capacity, whereas a 6328 $/day increase in revenue for 37.5% BESS capacity. The variance of LMPs, widely used as a risk index, greatly decreased for the LSE utilizing the coordinated methodology, somewhat decreased for other LSEs but increased for cheaper GenCos with no LSE at the local node. Since BESS deployment decisions of an LSE can have system-wide or market-wide consequences, simulation analysis before deployment can help reduce market distortions or system congestions.

Research on prediction method of financial stock curve based on BP neural network

In the development of social and economic construction, the stock as an important financial instrument, after the recent decades of regional pilot and nationwide expansion, the stock market supervision mechanism and trading principles have become more and more perfect, the level of our capital market has become more and more rich, the overall scale has expanded rapidly. In order to make investors understand the changes of macro market environment faster and reduce the threshold of investors' investment and trading, stock exchanges and some financial service institutions put forward to use artificial intelligence algorithm to build a prediction system on the basis of integrating the accumulated experience in the past. Based on the research of financial stock curve prediction in recent years, this paper proposes a neural network system for stock market prediction. The final experimental results show that BP neural network can make short-term prediction of the stock market. As long as the appropriate prediction model is selected, it can get more than the average market profit level.