Excess Stock Research Articles

Penyelesaian Permasalahan Pengadaan Stok di Toko Grosir Naek Menggunakan Logika Fuzzy dengan Metode Tsukamoto

Stock management is an important aspect in the operations of a grocery store. By knowing when to add stock, shop owners can optimize the availability of goods without excess stock. In this research, the fuzzy logic method is applied to determine stock procurement decisions based on sales data and remaining stock. The results of the research show that fuzzy logic can be used to assist in making stock procurement decisions with a fairly high level of accuracy.

Revolutionising Skincare Through Airtificial Intelligence

Abstract: Background: Over the last 10years there has been a drastic shift in the development of computer-based systems, artificial intelligence, algorithms and technology in the world of dermatology be it cosmetic or even retail production of products sold to customers with high-tech technology and innovative means to build their client base through customer delight. Artificial Intelligence is particularly helpful in recognizing the type of skin customers have and suggesting solutions which help customers pick from the range of options given to them. Most e-commerce platforms have begun using such AI driven soft wear to help customers while they are in the comfort of their homes to choose from a range of cosmetic options right from lipsticks, concealers, foundation, eyeshadows, shades of tins, serums etc. Given that every person has a different skin type, these applications ensure 100 percent personalized suggestions. This new trend is sending shock waves across the retail sector around the world attracting a massive customer base to adapting to AI Derma logy and retail. The intelligent software used by sever companies not only benefits the customer, but also helps companies with their operational efficiency as they can use AI algorithms to predict and forecast the inventory to help reduce over production and excessive stock production minimizing product wastage and improving sustainably.AI is booming in both clinical diagnosis as well as giant companies such as Loreal and Olay who are dedicated to providing customers with advanced tools like skin analyzers or apps based on predefined rules which help AI-powered tools analyze skin conditions, age, and personal skincare history to provide highly personalized product recommendations. In clinical diagnosis AI offers valuable insight to the patient’s skin and condition be it cancer or other skin diseases making judgments to assist the doctors and dermatologist in making informed decisions regarding the line of treatment for the patient in question. This includes screening, diagnosis, treatments and predictions of the treatment outcomes. These new innovative and robust AI systems leaving customers feeling confident and have not begun relying on AI driven treatments and procedures

Inventory Management Practices and Their Impact on Operational Efficiency: A Case Study of MGSSK Sugars Ltd.

In today’s highly competitive business environment, effective inventory management is vital for maintaining operational efficiency and ensuring long-term sustainability. Proper inventory control reduces excess stock and prevents stock outs, leading to cost reduction and improved cash flow. By utilizing precise forecasting and strategic replenishment methods, companies can enhance their adaptability to market changes and sustain a competitive advantage. This research provides a thorough examination of inventory management metrics spanning five years. The primary objective of the study is to evaluate the effectiveness of inventory management. The data was primarily collected from secondary sources, including five years of company inventory records. To analyze the data, the ratio analysis method was applied. The results demonstrate notable improvements in the company’s operational efficiency. Key performance indicators include a steady rise in the inventory turnover ratio and a reduction in average stock levels, showcasing effective inventory control aligned with increasing demand and minimizing surplus stock. Moreover, the study reveals a decreasing trend in inventory as a proportion of current assets, indicating a strategic shift away from relying on inventory for revenue generation. Additionally, variations in raw material values, coupled with consistent material consumption, suggest fluctuations in raw material usage efficiency. Furthermore, the relationship between the raw material turnover ratio and inventory holding period highlights the company’s proficiency in optimizing inventory management. The declining inventory conversion period indicates successful transformation of inventory into sales, boosting cash flow and operational efficiency. This improvement is attributed to advanced forecasting and stock replenishment strategies.

The Impact Of Stock Price On Investment Decision: Theory & Evidence

Purpose – The purpose of this paper is to present a behavioral explanation of excess stock price volatility relative to present value theory. Design/methodology/approach – The conceptual basis is the impact of effect on investor decisions. The empirical tests involve survey data collected from a sample of semi-professional Investors and investment advisors. Findings – It is suggested that affect causes investors to perceive an inverse ex ante relationship Between risk perceptions and expected returns. Thus, new good or bad information has an amplified effect on stock valuations. In addition, investors tend to extrapolate recent short-term market movements into the future. Practical implications – The primary implications are that ex ante perceptions of risk and return Vary inversely and that affect has a strong influence on valuation. This means that simple statistical Measures of risk are unlikely to fully capture risk perceptions and that market volatility can be Expected to be greater than a simple present value model would imply. Originality/value – This paper is unique as to the conclusion that risk and return perceptions vary Inversely ex ante and that affect can amplify stock price volatility

Utilization of the intersection of ABC and XYZ analysis in stock planning in the warehouse by Covid period

The aim of this article is to find the most appropriate inventory storage strategies in a new warehouse according to the Covid period. Based on the company's analysis and preferences, we have concluded that the most suitable inventory storage strategy will be ABC, XYZ and penetration analysis according to which the inventory will be produced to the company's warehouse. The result of the paper is the intersection of these analyses. Based on the penetration analysis, we found that AAXX group has 27% of the product items. The CXX group of manufactured items has a high turnover, but accounts for only 1% of the total items. The AA category has a low turnover but accounts for only 0.63% of the product items. As a result of the penetration analysis, we concluded that the categories AAXX, AAX, AXX, AX and BXX are suitable to be produced in large quantity in stock. For categories AAY, AY, BX and BY, it is recommended to plan the production of items for stock with caution and not to produce them in such large quantities. The regularity of the analysis of these methods is very important. The intersection of ABC and XYZ analyses indicates the regularity of applying these methods due to the existence of excess or non-replenishable stocks.

The Utilization of Time Series Data Forecasting Techniques on Hospitals Pharmaceutical Inventory

Good inventory management is essential in the hospital industry to overcome inventory problems. Ineffective inventory prediction methods can lead to shortages or excess stock inventory. Ultimately, this can impact the budget and availability of pharmaceutical items in the hospital. Previous traditional prediction methods often show inaccuracies. This research utilizes ARIMA (Autoregressive Integrated Moving Average) and FB Prophet methods to predict the demand for pharmaceutical items in hospitals. In an attempt to evaluate the effectiveness of both methods, an experiment was conducted on five pharmaceutical items. The results showed that the ARIMA method produced better performance compared to the FB Prophet method, with the smallest error of 0.07310.

PENGGUNAAN K-MEANS DAN HIERARCHICAL CLUSTERING SINGLE LINKAGE DALAM PENGELOMPOKKAN STOK OBAT

Adequate and efficient availability of medicines is necessary to ensure patients receive optimal care. However, inefficient drug stock management can result in various problems, such as waste of resources, lack of necessary drugs, or even excessive stock. This study aims to improve the efficiency of the drug stock management process by using KMeans Clustering and Hierarchical Clustering methods on drug stock data. The data used includes information on initial stock, purchase, incoming distribution, service, outgoing distribution, outgoing adjustment, and final stock. Clustering analysis was performed to identify patterns in the drug stock data, which was then validated using Silhouette Score. The results showed that Hierarchical Clustering was able to achieve a Silhouette Score of 0.976, while KMeans achieved a Silhouette Score of 0.954

Return and volatility spillovers between the raw material and electric vehicles markets

This paper investigates the return and volatility spillovers between the upstream electric vehicles (EV) battery raw materials market and the individual downstream EV producers. The study uses the daily stock returns of two lithium producers and a new model in the GARCH family to capture the jump component of volatility in the EV battery raw materials market. Return and volatility spillovers are studied using an EGARCH(1,1) model including the excess stock returns of lithium producers in the mean equation and their jump component intensity in the variance equation. The results indicate that jumps exist in the EV battery raw materials market and that there exist significant return spillovers between lithium and EV producers. However, this paper did not find any strong evidence of the existence of volatility spillovers between these two markets through lithium unexpected news.

Optimization of Raw Material Inventory using Always Better Control (ABC) Analysis and Economic Order Quantity (EOQ) Method Approach in the Warehouse of a Bolt Manufacturing Factory in Indonesia

There is a problem in the raw material procurement process at the Contractor Company, such as running out and excess stock of raw materials, as well as difficulties in determining how many raw materials to order that meet the company's economic value. Running out of raw material stock results in delays in production activities, while excess raw material stock can fill warehouse capacity, thereby increasing storage costs. To overcome this problem, research was carried out using a quantitative descriptive method to determine the level of production cost efficiency and production effectiveness level in order to achieve optimization of raw material supplies using Always Better Control (ABC) Analysis and the Economic Order Quantity (EOQ) Method at Bolt Companies. ABC analysis plays a role in determining which raw materials have the highest level of demand and the EOQ method plays a role in determining the amount of raw materials to be ordered in order to meet the company's economic value. The research results show that the combination of ABC Analysis and EOQ Method can reduce ordering costs and raw material inventory. There are 4 items out of 10 raw material items that are included in Category A or the most prioritized category. From the results of calculations using the EOQ method, the Bolt Company can save total orders and raw material inventory (TIC) in the period January to December 2023 amounting to IDR 2,147,403,-.

Income Smoothing and Overvaluation

Purpose: This research evaluates two views of the effect of income smoothing on stock overvaluation. There is a view that income smoothing impairs the usefulness of profit information by distorting the economic substance of a company. While another view is income smoothing can serve as a means of conveying classified information within a company. With the two views, it is unclear to predict income smoothing's relevance to overvaluation of stocks. Therefore, this paper aims to analyze the relationship between income smoothing and stock overvaluation in the capital market. Design/methodology/approach: The study conducted on the KOSPI and KOSDAQ markets from 2011 to 2020, and measured income smoothing using the methods suggested by Leuz et al. (2003), Park et al. (2011), and Tucker and Zarowin (2006). For stock overvaluation, the method of Rhodes-Kropf et al. (2005) used. Findings: This study provided empirical evidence that there is a negative relation of income smoothing with stock overvaluation, which may be interpret that income smoothing may lower stock overvaluation. In other words, priv-ileged information delivered by the manager through income smoothing may alleviate the overvaluation of stocks caused by excessive stock price relative to its intrinsic value. This result was more observable as the greater majority shareholder ownership interest, the greater the foreign investors share, and for companies listed on the KOSDAQ. Research limitations/implications: This study makes contribution to the literature by supplying other evidence on the effect of income smoothing on capital market and supplies meaningful guidance to capital market stakeholders. Originality/value: This study is valuable not only because it expands earlier research on income smoothing and stock overvaluation, but also because it empirically confirms the usefulness of income smoothing in the capital market.

Forecast Analysis of Fruit Supply Using Time-Series Method: A Study at PT Aerofood Indonesia

PT Aerofood Indonesia is an entity operating in the aviation logistics industry, specifically as a partner of the Garuda Indonesia airline. The main problem faced is the tendency to have excessive supplies of raw materials, especially in the aspect of purchasing fruit because it is susceptible to damage. This phenomenon often recurs and peaks beyond dry goods capacity limits, especially the availability of papaya fruit which often exceeds capacity by more than 50%. Therefore, this research aims to identify the optimal forecasting method for papaya fruit to overcome the problem of excessive stock. In this research, four forecasting approaches were tested, namely Trend Analysis, Single Average Exponential, Double Average Exponential, and Holt's Winter Method. Forecasting calculations were carried out using a manual approach and supported by Minitab 18 software. The research results showed that the Holt's Winter method with a multiplicative approach produced the lowest Mean Absolute Percentage Error (MAPE), namely 16%. The Holt's Winter method with a multiplicative approach has proven to be effective in producing accurate forecasts. By implementing this recommended forecasting method, it is hoped that companies can be more efficient in managing inventory and reduce the impact of losses due to excess stock.

Impact of ownership concentration on stock returns: a case of developed economies

PurposeThe primary objective of this study is to determine how concentrated ownership affects stock returns by country and scale (by market capitalization), like large, medium, and small-cap firms in selected developed economies of the world.Design/methodology/approachUsing a dataset comprising 12,751 annual observations from 850 listed companies from developed economies from 2004 to 2018, the study employs panel data models and instrumental variable estimation to mitigate endogeneity bias.FindingsThe findings reveal a significant and positive correlation between ownership concentration and expected returns on corporate equities in developed economies. Furthermore, the study categorizes firms into distinct size categories and finds nuanced differences in the relationship between ownership concentration and stock returns across large, medium, and small-cap enterprises. The results of the study reveal that ownership concentration (by country) and scale (Large, medium, and small) have a significant and positive impact on the stock returns of firms in developed economies.Practical implicationsthe practical implications of this study extend to investors, firms, policymakers, regulators, and other stakeholders involved in the financial markets. By considering these implications, stakeholders can make informed decisions to enhance market efficiency, investor protection, and overall market integrity.Originality/valueTo the authors' understanding, this study is the first to examine the impact of concentrated ownership on excessive stock returns across countries and scales, with an explicit focus on large, medium, and small companies in select developed economies worldwide.

THE IMPACT OF FINANCIAL LEVERAGE ON THE PRICING RISK IN THE EGYPTIAN STOCK MARKET

This paper examines the impact of financial leverage on the risk pricing in the Egyptian Stock Exchange (EGX) by adding an additional risk factor reflecting financial leverage to the three factor model of Fama and French. We used monthly excess stock returns of 50 stocks listed on the (EGX) from January 2014 to December 2018 to test Fama and French model before and after adding the financial leverage factor. Total debt to equity ratio was used to calculate the financial leverage. The results do not support Fama and French model before and after adding the financial leverage factor, therefore there is no effect of financial leverage on the risk pricing.

Overview of Sales and Investment of Generık Drugs "X" Pharmacy, Kampung Satu District, Tarakan City Using ABC Analysis in 2022

Pharmacies as health facilities and businesses, require good management to avoid shortages or excess stock of medicines. This research aims to optimize generic drug inventory management at pharmacy "X" using the ABC method. Using a quantitative and retrospective descriptive approach, generic drug sales data for the period January- December 2022 were analyzed. As a result, Group A consisted of 23 drug items with a total sales transaction of 5,877 (69.89%), Group B consisted of 28 drug items with a total sales transaction of 1,654 (19.67%), and Group C consisted of 71 items with the number of sales transactions was 878 (10.44%). In terms of investment value, Group A consists of 31 medicinal items with an investment value of Rp. 39,058,600 (69.63% of the total), Group B consists of 33 medicinal items with an investment value of Rp. 11,290,000 (20.13% of the total), and Group C consists of 58 medicinal items with an investment value of Rp. 5,743,300 (10.24% of the total). The ABC method can optimize generic drug inventory management at pharmacy “X”, enable prioritization based on sales frequency and investment value, and increase efficiency.

THE HOLIDAY EFFECTS ON AMUSEMENT AND THEME PARK COMPANIES’ STOCK PRICES

This study offers further evidence of the holiday effect on excess stock returns and volatility, and additional insights into its impact on the amusement park and attractions industry in the United States. The generalized auto-regressive conditional heteroscedasticity (GARCH) model and dummy variables are adopted to investigate pre- and post-holiday excess returns and volatility. Empirical results suggest the following: (1) both excess returns and excess volatility happen more frequently in pre-holidays than post-holidays; (2) the frequency of excess volatility is higher than excess returns for the holiday effect; and (3) nearly all significant excess volatilities are negative. We, therefore, conclude that the holiday effect exists in publicly traded amusement and theme parks.

A Two-Warehouse Inventory System with Time-Dependent Demand and Preservation Technology

Because of rapid environmental changes in current worldwide society, preserving technique is becoming increasingly crucial. With the aim to examine this idea, we created a model for two-warehouse inventory system that incorporates preservation technique investments. The model considers time as a linear function representing the rate of demand. Time-dependent demand is a common feature in many industries, where demand fluctuates over time due to various factors such as seasonality and market trends. The stock is kept in the restricted storage area (OW) and other warehouse (rented) is utilized for keep any excess stock that exceeds the OW's storage limit. The stock in RW is consumed first, followed by the stock in OW, as the cost of holding of the rented warehouse (RW) is more than that of the owned warehouse (OW). This paper does not allow for shortages. We use numerical simulations to illustrate the effectiveness of our proposed model under various parameters.

Inventory System Development With Trend Moment Method For Optimization Warehouse Inventory Using Rfid Technology ( Case Study At Pt. Jansen Indonesia)

Abstract - In warehouse department or warehouse in the company including PT. Jansen Indonesia has system service still available Not yet maximizing development technology moment this is the medium one develop fast . Including in system inventory Frequent warehouse​ happen No make it available stock And Excessive stock .​ This matter cause function inventory on warehouse No Work in a way maximum. From problem said , PT. Jansen Indonesia requires exists optimization stock with use Trent Moment Method with web- based and use RFID technology . System This covers control supply on warehouse For purchase so that reduce stock excessive nor less so supplies stock controlled , as well as a data input process that utilizes RFID so that speed up time in the data input process. On system This use Language PHP and MYSQL programming as databases as well utilizing the PHP Framework , namely Codeigniter in creation of this website . With exists system web based , makes it easy employee in data processing with appropriate time .

ESG Score Uncertainty and Excess Stock Returns: European Stock Market Case

ESG Score Uncertainty and Excess Stock Returns: European Stock Market Case

Fama and French Three Factor Model

This study seeks to investigate the application of FF3FM in the Nigerian stock market. The study examined the behaviour of stock returns in relation to market beta, firm size (market equity), and book-to-market equity (BE/ME) factors. Sixty- eight (68) sample size was selected from all stocks quoted on the Nigerian Stock Exchange (NSE) from 2013 to 2022. Time series regression analysis was adopted. Monthly excess portfolio returns were regressed on firm size, excess market returns and book-to-market-equity ratio. The findings showed a strong correlation between book-to-market equity variables, firm size, and excess stock market returns and predicted portfolio returns. This suggests that the variation in stock returns in the Nigerian stock market can be explained by the FF3FM.

An Index of Skilled Analysts and Stock Market Returns

ABSTRACT This study constructs a monthly index of skilled analysts (ISA) regarding the coverage by such analysts and explores their predictive ability on the future excess returns of Chinese A-share market. The empirical results reveal that ISA significantly and positively predicts excess stock market returns, with R 2 s of 4.39% and 4.13% in- and out-of-sample respectively, which surpasses the predictive ability of most commonly used economic variables. High ISA precedes a higher investor sentiment index (ISI) and lower idiosyncratic volatility (IVOL) at firm level. The conclusion remains valid after controlling for a series of other predictor variables and performing robustness tests.