Value Of Strategy Research Articles

Coordinated Cyber Security Enhancement for Grid-Transportation Systems With Social Engagement

Effective coordination of energy and transportation systems is fundamental and vital to smart city management. Yet, the deeply intertwined information and communication technologies have exposed smart city management to malicious cyberattacks vastly. This study develops a two-stage mitigation strategy for integrated transportation-energy systems (TESs) by coordinating energy and transportation systems to safeguard against false data injection attacks (FDIAs). Our strategy targets social engagements by electric vehicle (EV) users who can be incentivized to alter their regular EV usage patterns for supporting the energy system via vehicle-to-grid actions. We consider a TES that contains a multi-energy system comprised of power and gas systems as well as an urban transportation system. Integrated system operators can take emergency measures to coordinate important system assets (e.g., traditional generators, renewable generators, EV fleets) in a sensible and intelligent way, and thereby mitigate the consequences of FDIAs. Specifically, we take a two-stage distributionally robust approach to cope with uncertain FDIAs, with which a moment-based ambiguity set is employed to yield the worst-case uncertainty distribution. We leverage constraint generation-based relaxation to solve the problem iteratively. To demonstrate our strategy's value and practical utilities, we use a coupled urban TES to conduct case studies. According to the evaluation results, the optimized EV scheduling and energy dispatch scheme produced by the proposed strategy can contain cyberattacks’ impacts and enhance cyber resilience in smart city management more effectively.

Research on Corporate Value Investing: The Case of CATL

Purpose - In the context of a significant global shift in energy structures, the development of new energy enterprises has entered a strategic opportunity period. Contemporary Amperex Technology Co., Limited. (CATL), as the world’s largest producer of electric vehicle batteries, is one of the biggest beneficiaries in the global new energy wave. This research aims to assess the intrinsic value of CATL, analyze CATL’s current situation, and explore its potential for future development. This study seeks to provide significant insights and information to investors interested in the new energy business.
 Design/Methodology/Approach - Using Contemporary Amperex Technology as a case study, this research employs qualitative and quantitative analysis methods to assess the investment value of CATL comprehensively. In order to determine CATL’s valuation, a variety of analyses are applied, such as financial, industry, and economic, as well as relative and absolute valuation methods. The study reveals CATL’s competitive advantages, market potential, and investment value in the new energy vehicle and power battery industry.
 Findings - The research finds that CATL operates in a favorable market environment with ample growth opportunities. The company maintains a healthy financial condition, strong operational and profit-making capabilities, and has high growth potential. Furthermore, CATL’s stock price is currently undervalued, offering investment opportunities.
 Research Implications - This research applies value investing theory to a specific case, making a significant contribution to the development of value investing theory. It enriches the field of corporate value investment research in the new energy industry and its related sectors. Additionally, it provides valuable references for investors in actual investment decisions.

Factors Affecting Investment Decisions of Permanent School Teachers in Pokhara

Investing is the use of money to increase its worth or generate more revenue. This article has been designed to examine the factors affecting investment decision of permanent school teachers in Pokhara. This study is based on causal comparative research design. It has used structured questionnaire to collect information. Samples were selected by multi sampling technique, selecting the than Chhorepatan Resource Center by purposive sampling in the first and selecting 139 permanent school teachers by simple random sampling in the second stage. The Total population of permanent school teachers of Pokhara Metropolitan City was 1,588 and targeted population was 211. The reliability of data is checked by calculating Cronbach Alpha and it was 0.77. Accounting information (AI), Firm`s Image (FI), Advocate Recommendation (AR), Personal Financial Need (PFA) and Dividend Policy (DP) were independent variable and Investment Decision (ID) was dependent variable. This research discovered that 61.2% of permanent teachers invest their fund in equity share. Lump sum investment method was more popular than systematic investment plan and monthly investment. 80% of permanent teachers invest less than 20% of their savings. Respondents prefers both cash and stock dividend policy. Regular income was found as main objective of investment. Friends and coworker’s advice was also considering while investing in equity share. This research has also presumed that there was positive significant relation between investment decisions and decision factors. It is suggested to the investors of stock market, to analyze the fundamental factors of issuer and the issuer should follow regular dividend policy to attract the value investors toward their securities.

A Comprehensive Analysis of Stock Investment Recommendations Based on the Liquor Industry: Risk, Profitability, and Ratio Perspectives

Focusing on the liquor industry, this study takes Kweichow Moutai Liquor Co., LTD., Shanxi Xinghuacun Fen Distillery Co., LTD., and Sichuan Tuopai Shed Liquor Co., LTD., as the objects, and provides targeted investment suggestions for different types of investors by analyzing risk, profitability, valuation and other indicators. The results show that Kweichow Moutai has an excellent performance in market value and ROA, which is suitable for index investment and ratio analysis investors. Shanxi Xinghuacun Fen Distillery attracts the attention of income investors with its high dividend rate; Sichuan Tuopai Shede Wine's low PE Ratio may attract value investors. Depending on the type of investment, we provide investment advice for index investors, ratio analysis investors, income investors, value investors, PEG investors, discounted cash flow investors, momentum investors, insider trading investors and share buyback investors. The results and analysis of this study can help investors more accurately evaluate the investment value of different liquor companies to meet their specific investment objectives and risk preferences.

Is value investing based on scoring models effective? The verification of F-Score-based strategy in the Polish stock market

The aim of the paper is to analyse the effectiveness of F-Score-like models using the example of the Polish stock market. F-Score is a scoring model based on a high B/M investing strategy, which uses fundamental signals to assess the economic condition of an entity. So far, its effectiveness has been generally proven in numerous stock markets worldwide. However, no comprehensive study focusing on the Polish market has been conducted. Therefore, F-Score and similar models (FS-Score and PiotroskiTrfm) were analysed in this regard. It was shown that companies with higher scores generated positive both raw and market-adjusted returns on average. However, they were lower than the mean returns of low-score companies (for FS-Score) or total high B/M portfolio (regarding F-Score and PiotroskiTrfm). The results of the study show that F-Score, FS-Score and PiotroskiTrfm are generally effective investing tools. However, it might be more advisable for value investors to choose a total high B/M portfolio instead of shares of high-score entities according to F-Score or PiotroskiTrfm.

Clustering-based value investing strategy in the Helsinki Stock Exchange: k-means algorithm

The purpose of this research is to study the possibility of combining quantitative clustering of stocks and value investing. The feasibility of this approach is tested using Finnish market data from the period 2005 to 2021. The benchmark index used in this research is the OMX Helsinki Growth Index. The strategy is based on the combination of P/E, P/CF, and P/B ratios, which serve as the basis for the k-means algorithm. The data is pre-processed by removing stocks that have not generated positive earnings and cash flow during the previous 12 months. The k-means algorithm assigns stocks to clusters, and the cluster with the lowest financial ratios is chosen as the value portfolio. The research also includes a sensitivity analysis of value portfolios, where the initial number of clusters in the clustering phase ranges from three to ten. Returns of different value portfolios are compared to each other and the benchmark index. The quality of results is evaluated using the Sharpe ratio and Jensen's alpha. According to the findings, the value portfolio constructed using nine clusters generated the highest risk-adjusted return, with an annual return of 30.27% over the 2005 to 2021 period. Furthermore, the best-performing value portfolio from 2005 to 2017 was compared to the benchmark index from 2018 to 2021. The value portfolio achieved an annual return of 26.05% during the 2018-2021 period, while the corresponding return of the benchmark index was 11.74%.

Tencent's Acquisition of China Music Corporation: A Case Study

Since the 21st century, the rapid development of the internet has led to the digitization of the music industry. In order to expand its business areas and scale, Tencent acquired China Music Corporation. This move will not only help Tencent and China Music Corporation achieve complementary advantages and work together to seize the dividends of the internet era, but also fill the gaps in related areas and enhance Tencent's overall competitiveness. However, both Tencent and China Music Corporation have not disclosed much information about this acquisition, and the media has not reported extensively on it. The purpose of this article is to integrate and summarize the relevant information of this acquisition, analyze the strategic objectives and financial effects of Tencent's acquisition of China Music Corporation, and fill the gaps in related information on the internet. Based on the analysis of the financial statements before and after the acquisition, this article will rationally analyze the strategic objectives of the acquisition and the financial effects of the acquisition. The choice of Tencent's acquisition target is correct, as China Music Corporation can effectively make up for Tencent's shortcomings in the field of music. This acquisition not only improves Tencent's music industry chain structure, but also conforms to Tencent's diversified development strategy. From a decision-making perspective, Tencent is a trustworthy company for value investors.

Application of Value Investing and Market Strategy Analysis in ORCL, ADBE, CRM, PANW and MSFT

Technology, a new star rising, changes peoples lives dramatically through continuous innovation and support from all areas of society. Technology companies undoubtedly become the major storm of the stock market. The findings of this study aim to help stakeholders invest in a stock with good future prospects and the most significant potential to earn money through tons of technology stocks in the market. The methodologies that are applied in this research include P/E ratio, growth rates, and profitability ratios. All the methods help analyze which stock is better than the others from a comprehensive point of view. This research also includes non-numerical analysis, providing a more thoughtful conclusion for stakeholders to make investing decisions. The results point out that Microsoft is a wise investment company based on its top growth rates, growing and stable profitability, and relatively low p/e ratio. This research helps shareholders to identify their target when making technology investments.

Decision Tree Evaluation on Sensitive Datasets for Secure e-Healthcare Systems

Collecting and analyzing patients' e-healthcare data in Medical Internet-of-Things (MIOT), e-Healthcare providers can offer reliable medical services that will achieve better treatment for patients. For example, the diagnosis of disease and predictions of health offer an alternative and helpful evaluation of the risk of diseases, thereby helping patients lead a healthier life. However, e-Healthcare providers cannot cope with the huge volumes of data and respond to this online service such that a feasible solution is adopted to outsource the medical data to powerful medical cloud servers. Since medical data are very sensitive and outsourced servers are not fully trusted, a direct outsourcing decision tree evaluation service will inevitably result in huge privacy risks with regards to patient identity or original medical data. It is hard to hide the results of an evaluation from the single-server model unless a fully homomorphic cryptosystem is used, or the requester must communicate online with the cloud multiple times; and even then the efficiency issues between outsourced servers and patients must also be considered. With regards to these issues, this paper proposes a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u> ecure and <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</u> rivacy- <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</u> reserving <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</u> ecision <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</u> ree <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</u> valuation scheme ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">namely</i> SPP-DTE) to achieve the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">secure disease diagnosis classification under e-Healthcare systems without revealing the sensitive information of patients such as physiological data or the private data of medical providers such as the structure of decision trees</i> . Our proposed scheme uses <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">modified KNN computation to match the similarity and preserve the confidentiality of raw data</i> , and also applies <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">matrix randomization and monotonically increasing and one-way function to confuse the intermediate results</i> . The experiment is conducted in data sets from UCI machine learning repository of medical health data, our analysis indicates that the proposed SPP-DTE scheme is efficient in terms of computational cost and communication overhead that is practical and efficient for privacy protection in e-Healthcare classification and diagnosis system.

Whether to Invest in Luxury goods based on Risk, Background, and Market

The luxury goods industry, the aviation industry, and the hotel industry all fall into the category of discretionary goods in people's lives. However, in the last 3 years, the spread of Covid-19 has affected all three sectors to a greater or lesser extent. Through the method of comparison, we can intuitively show the differences in the investment of financial stocks in these three industries. LVMH, AAR.Corp and Marriott International are representatives of luxury goods, aerospace, and hotels respectively, among which AAR.Corp is a small-cap stock with more characteristics. Analyse from a risk perspective, risk: LVMH&lt;Marriott International&lt;AAR.Corp.Analyse from a profitability perspective, profitability: AAR.Corp&lt;Marriott International&lt;LVMH.Analyse from a market perspective: value investors will invest in AAR.Corp.PEG investors may invest in Marriott, and LVMH would be on their watch list until its PEG ratio is under 2. Income investors won't invest in these three stocks since their dividend yield is less than 3%. This paper can make investors more clear about the stock market situation of non-essential goods, to help them choose suitable stocks.

The Implementation of Value Investment Based on Various Indicators for the Building Materials Industry

With the advent of post COVID-19 era, value investing strategy has popularized again in the global stock markets as the changing economic conditions, rising interest rates and different risk appetites. Therefore, it is reasonable to know how to distinguish between value stocks and growth stocks before investing. This paper aims to examine the application of value investment strategies based on the indicators’ performance of five companies selected from the building materials industry. Besides, valuation metrics are derived from three primary dimensions, i.e., growth, profitability and value per unit of growth. This study first identifies the classification and recent performance of value stocks and then compares the financial indicators of companies with value stocks. According to the analysis, the suitable P/E range of value stocks is from 10 to 20, with returns beginning to rise in 2021. By means of this method (utilizes one indicator to identify value stocks), researchers engaged in the financial industry may discover more characteristics about them. Moreover, results also illustrate that value stocks with excellent indicators are more endurable in preventing outside shocks, whereas growth stocks can outperform in profitability as long as they possess ever-increasing revenue and EBITDA. Thus, value investing still remains profitable and practical in the real world.

Exergoeconomics evaluation on optimal operation conditions in crude oil gathering and transportation system

ABSTRACT At present, most of the energy analysis of the engineering system is only from the energy point of view. In this paper, the theory of exergoeconomics is combined with the operation optimization of the gathering and transportation system. In terms of exergy flow distribution and the construction of each equipment, the exergy value of total 17 exergy flows and the non-energy cost of 6 main equipment in the process are calculated. An exergoeconomic model in technological process of gathering and transportation system is established. Combined with the exergoeconomic cost valuation strategy, 11 auxiliary equations are used to get the economic cost of each flow unit in the process. Taking the minimum operation exergy cost as the objective function, a mathematical model of operation optimization in exergoeconomics is established, and each decision variable is constrained on the basis of the actual site conditions. The objective function within the range of process requirements is solved by iterative method. The optimal water mixing temperature is 47.1°C, and the optimal water mixing volume is 840.7 m3/d under the actual working condition of the site in light of the calculation results.

Management techniques for value investors

The paper seeks to identify proper management techniques for value investors. Thereby, a literature review is carried out, revealing behavioral aspects in the area of value investing. Even though a large body of literature exists, there are still many concerns regarding the techniques used by the individual investor, leading to poor investment decisions. Against this backdrop, the article shares techniques that are beneficial when it comes to value investing. By doing so, events influencing human psychology are displayed and approaches to bypass adverse effects on the value investor are developed. As a result, better long-term results of value investors shall be achieved.

Value Investing: From Perspective of Interpretivism

Value Investing: From Perspective of Interpretivism

A case study of a strategic initiative in pediatric rehabilitation transition services: An insiders' perspective on team principles and practices.

The aim was to describe an innovative initiative that took place in a pediatric rehabilitation hospital. The goal of this organization-wide strategic initiative, called the Transition Strategy, was to improve service delivery to children/youth with disabilities and their families at times of life transition. The research question was: What are the key elements that have contributed to the success of the Strategy, from the perspective of team members? The objectives were to describe: (a) the guiding principles underlying team functioning and team practices, (b) key enablers of positive team functioning, (c) the nature of effective team practices, and (d) lessons learned. A holistic descriptive case study was conducted, utilizing historical documents, tracked outcome data, and the experiences and insights of multidisciplinary team members (the authors). Reflecting an insiders' perspective, the impressions of team members were key sources of data. The perspectives of team members were used to generate key teamwork principles, enablers of team functioning, team practices, and key learnings. Team members identified four guiding humanistic principles (respect, support, partnership, and open communication). These principles underpinned three novel practices that contributed to team effectiveness in the eyes of team members: supportive relational practices, human-centered co-design, and solution-focused communication. Key enablers were the relational style of leadership, and a team climate of innovation, autonomy, and trust, supported by the organizational vision. This team climate fostered a sense of psychological safety, thereby encouraging both experimentation and learning from failure. This article provides information for other healthcare organizations interested in understanding the Strategy's value and its implementation. It provides a practical example of how to adopt a humanistic approach to health care, leading to both innovative service development and thriving among team members.

Pricing strategy for household energy-saving option (HESO): A novel option-based intervention for promoting household energy efficiency

Household energy-saving interventions are essential in reducing energy consumption in residential buildings. One of the effective interventions is Household Energy-Saving Option (HESO). However, the pricing strategy of this innovative intervention has not been explored. This study aims to establish a feasible valuation strategy for HESO to facilitate the application of market-based energy-saving interventions among households. This study first provides a pricing strategy of HESO from a market zero-profit perspective. It continues by developing a price cap and floor for HESO's market price. The theoretical pricing model was validated by a field experiment consisting of two-tiered HESO trading among 67 households in Singapore. The results revealed decisive implications for both environmental policymakers and HESO suppliers. Policymakers are suggested to launch HESO in countries or regions with stable and relatively high electricity prices and low discount rates. HESO suppliers may choose to adjust rewards and duration accordingly when the market price deviates from the zero-profit equilibrium price of HESO. The valuation strategy of HESO also helps quantitative estimation of households' perceived value of HESO.

ANALISIS KINERJA PORTOFOLIO MAGIC FORMULA PADA INDEKS LQ45 DI BURSA EFEK INDONESIA

The rapid growth of active investors in Indonesia stock market raises awareness on the importance of investors’ skill needed in analyzing and choosing profitable stock. One of the method knows to analyze profitable stock in the market is Magic Formula introduce by Joel Grenblatt -part of value investing. Magic Formula is a method on choosing a profitable stock in a simple way based on combination of both High Earnings Yield and High Return on Capital. The period use in this research is from 2016 – 2020. This research use LQ 45 stock listed in Indonesia Stock Exchange. This qualitative research used secondary data which is analyzed using backtesting simulation. The result of this research shows that Magic Formula’s Stock Portfolio build based on data consist of different number of stock: 15, 20, and 25 stock; combination of both high Earnings Yield and High Return on Capital. The Magic Formula’s Portfolio formed based on the LQ 45 stock has higher aritmathic average return compare to LQ 45 return and even the 15-stock-based portfolio beat the Indonesia Composite Index average return. However on the CAGR rate of return, the calculation show that the return of the Magic Formula Portfolio below the return of Indonesia Composite Index

Long-Only Value Investing: Does Size Matter?

The academic value factor (long cheap stocks, short expensive stocks) earns higher returns among small-cap stocks. When viewed through the lens of a long-only value investor, however, size is a less important factor. For example, equally weighted large-cap value portfolios have historically earned similar returns as small-cap value portfolios. This finding is robust to different value measures and markets. Despite realized returns being statistically similar, the liquidity profile of the two value portfolios is dramatically different: Equally weighted large-cap value portfolios have approximately 11 times (or more) the liquidity of small-cap value portfolios.

Foreign investor engagement: Stock market liberalization and corporate green innovation in China

To confront the growing threat of climate change and achieve carbon neutrality, green governance has come under the spotlight globally. This paper investigates the effect of stock market liberalization on corporate green innovation, aiming to explore whether foreign investor engagement contributes to the green development of Chinese enterprises. Employing a staggered DID estimation, we find that firms generate a higher level of green innovation output after they experience the liberalization, and this effect is more pronounced when foreign investors become the focal firms’ top ten shareholders. Meanwhile, foreign investors who enter China’s A-share market with the implementation of this policy are value investors, indicating that stock market liberalization can help lead firms’ investment decision more future-oriented. We also find that financing constraints play a significant role in the association between stock market liberalization and corporate green innovation. The results of heterogeneity analyses show that the positive implication of liberalization on corporate green innovation is stronger for non state-owned enterprises, firms in high-tech industries and firms in less polluting industries. Our paper provides new insights into the economic effect of foreign investor engagement in emerging capital market and the factors affecting corporate green innovation in China.

Predicting long-term stock movements with fused textual features of Chinese research reports

By shaping investors’ perceptions and assessments of the stock, research reports have significant impacts on the stock market. Due to the limitations of text mining technology, it is difficult for researchers to effectively utilize long research reports, and most studies mainly focus on investor sentiment. However, due to the lack of appropriate open-domain toolkits, the annotations of sentiment often require expensive manual labeling. In addition, most existing studies have shown the success of using textual data as a supplement to historical price data in short-term forecasting, but not in long-term forecasting. To cover this gap and solve the problem of difficult annotations, we introduce a novel knowledge-driven approach for long-term stock movement prediction based on Chinese research reports. In detail, a new long-term Stock Movement Prediction dataset composed of Research Reports is proposed, namely SMPRR. It is mainly composed of long, formal, and professional research reports and historical prices. Furthermore, we propose the Multi-module Feature Fusion method based on the pre-trained language model FinBERT (MFF-FinBERT), which can effectively fuse textual features from research reports. The experiment results show that the proposed model has achieved better performance than existing methods in the forecasting of one-year stock movements, and the accuracy reaches 79.2%. The results also indicate that the basic information of stocks plays an important role in long-term forecasting, which is in line with the theory of value investing.