Pub Date : 2023-02-23DOI: 10.1142/s2424786322500396
Jyotirmoi Jena, Rashmiranjan Panigrahi, A. Shrivastava
Due to the availability of innovative financial products and services, financial engineering has expanded to include more practices and engineering techniques (FinTech, InsurTech, and other technologies). Financial engineering (FE) has succeeded through the stock market, financial instruments, and service developments. This study combines qualitative and quantitative approaches with bibliometric analysis to address a vacuum in financial literature. Co-citation, co-occurrence, and bibliographic coupling analysis techniques are used to make inferences about the structure of FE research in finance from January 2007 to December 2022. The study used 347 filtered research articles from the Scopus database and processed through VOS-Viewer and Biblioshiny through “R” to justify study objectives. The relevance of authors, journals, and organizations in a contemporary topic study is recognized using bibliometrics analysis. The study topic analysis revealed that modern portfolio theory acknowledges the importance of FE’s revolutionary products, such as FinTech and InsurTech, as recent advances in risk management techniques. Future research could take a multi-dimensional approach based on the current theme. New research themes emerged from the study, i.e., Financial Engineering and emerging financial markets and risk management, investment and financial crisis, FinTech, and InsurTech innovation, and Option pricing.
{"title":"A bibliometric analysis on financial engineering studies","authors":"Jyotirmoi Jena, Rashmiranjan Panigrahi, A. Shrivastava","doi":"10.1142/s2424786322500396","DOIUrl":"https://doi.org/10.1142/s2424786322500396","url":null,"abstract":"Due to the availability of innovative financial products and services, financial engineering has expanded to include more practices and engineering techniques (FinTech, InsurTech, and other technologies). Financial engineering (FE) has succeeded through the stock market, financial instruments, and service developments. This study combines qualitative and quantitative approaches with bibliometric analysis to address a vacuum in financial literature. Co-citation, co-occurrence, and bibliographic coupling analysis techniques are used to make inferences about the structure of FE research in finance from January 2007 to December 2022. The study used 347 filtered research articles from the Scopus database and processed through VOS-Viewer and Biblioshiny through “R” to justify study objectives. The relevance of authors, journals, and organizations in a contemporary topic study is recognized using bibliometrics analysis. The study topic analysis revealed that modern portfolio theory acknowledges the importance of FE’s revolutionary products, such as FinTech and InsurTech, as recent advances in risk management techniques. Future research could take a multi-dimensional approach based on the current theme. New research themes emerged from the study, i.e., Financial Engineering and emerging financial markets and risk management, investment and financial crisis, FinTech, and InsurTech innovation, and Option pricing.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48877636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-23DOI: 10.1142/s2424786323500019
Shrutika Mishra, Priyanshu Mishra
Recently, a lot of research was done on how to evolve the artificial intelligence business model framework. However, one issue was still undeveloped, which was immature to understand. This has been vital for budding and progressive managers, policy decision makers, and academics alike, namely, how businesses transform and develop their AI business models framework to accomplish continuous value formation. Businesses, which achieve to make value over prolonged stages of time effectively, figure, acclimate and recommence their business models with AI technology to fuel such value formation. Sketch on verdicts from a research program on uninterruptedly budding businesses is given. This paper categorizes three perilous competences, namely, an alignment towards investigating with and manipulating innovative business openings, a well-adjusted use of properties, as well as attaining lucidity between management, ethos, and member of staff obligations, together they all decisive key maneuvering schedules. We conclude the paper by signifying the consequences for AI business model framework research and experts and by providing a tool for executives which permits them to reproduce and classify perilous problems relevant for shifting and emerging their business model to sustain value creation. In this paper, we try to explore the keys of Business Model Framework, which will revolutionize business market ecosystem.
{"title":"AI Business Models and Its Impact on Business Strategic Framework","authors":"Shrutika Mishra, Priyanshu Mishra","doi":"10.1142/s2424786323500019","DOIUrl":"https://doi.org/10.1142/s2424786323500019","url":null,"abstract":"Recently, a lot of research was done on how to evolve the artificial intelligence business model framework. However, one issue was still undeveloped, which was immature to understand. This has been vital for budding and progressive managers, policy decision makers, and academics alike, namely, how businesses transform and develop their AI business models framework to accomplish continuous value formation. Businesses, which achieve to make value over prolonged stages of time effectively, figure, acclimate and recommence their business models with AI technology to fuel such value formation. Sketch on verdicts from a research program on uninterruptedly budding businesses is given. This paper categorizes three perilous competences, namely, an alignment towards investigating with and manipulating innovative business openings, a well-adjusted use of properties, as well as attaining lucidity between management, ethos, and member of staff obligations, together they all decisive key maneuvering schedules. We conclude the paper by signifying the consequences for AI business model framework research and experts and by providing a tool for executives which permits them to reproduce and classify perilous problems relevant for shifting and emerging their business model to sustain value creation. In this paper, we try to explore the keys of Business Model Framework, which will revolutionize business market ecosystem.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48793606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-02DOI: 10.1142/s2424786322500372
Matteo Michielon, A. Khedher, P. Spreij
The credit default swap (CDS) market plays an important role for financial institutions. This is not only for their trading activities, but also as it provides a source of information to extract default probabilities to be used for (counterparty) credit risk purposes, as for instance in credit valuation adjustment calculations. Nonetheless, the number of entities for which liquid single-name CDSs are traded is of the order of a few thousands. This requires financial institutions to employ proxy methodologies to estimate the credit risk they face when trading with counterparties for which no (liquid) CDSs are available in the market. In this paper, we propose and compare different approaches to take into account counterparty-specific information in terms of rating, region, sector, etc. at cross-sectional level to strip risk-neutral default probabilities from CDSs. This is achieved by taking into account the intrinsic probabilistic information characterizing each CDS by means of suitably-defined Wasserstein distances and barycenters. The results suggest that default probabilities are likely to be overestimated if the construction of the proxy credit curves overlooks the probability structure underlying the CDS market, potentially resulting in a too conservative counterparty credit risk pricing framework.
{"title":"On Wasserstein distances, barycenters, and the cross-section methodology for proxy credit curves","authors":"Matteo Michielon, A. Khedher, P. Spreij","doi":"10.1142/s2424786322500372","DOIUrl":"https://doi.org/10.1142/s2424786322500372","url":null,"abstract":"The credit default swap (CDS) market plays an important role for financial institutions. This is not only for their trading activities, but also as it provides a source of information to extract default probabilities to be used for (counterparty) credit risk purposes, as for instance in credit valuation adjustment calculations. Nonetheless, the number of entities for which liquid single-name CDSs are traded is of the order of a few thousands. This requires financial institutions to employ proxy methodologies to estimate the credit risk they face when trading with counterparties for which no (liquid) CDSs are available in the market. In this paper, we propose and compare different approaches to take into account counterparty-specific information in terms of rating, region, sector, etc. at cross-sectional level to strip risk-neutral default probabilities from CDSs. This is achieved by taking into account the intrinsic probabilistic information characterizing each CDS by means of suitably-defined Wasserstein distances and barycenters. The results suggest that default probabilities are likely to be overestimated if the construction of the proxy credit curves overlooks the probability structure underlying the CDS market, potentially resulting in a too conservative counterparty credit risk pricing framework.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47416766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-02DOI: 10.1142/s2424786322500360
Yuping Song, Yan Sun, Yueh-Ching Ma
Taking the Sino–US trade war as the background, we study the co-movement changes on horizontal return and volatility of the daily logarithmic return data of global stock indices from 2016 to January 23, 2020 from static and dynamic perspectives. Through static tools such as correlation coefficient matrices, complex networks, and Granger causality, it is found that the trade war has significantly strengthened the correlation between the Chinese stock market and the global stock market, and highlighted the position of the Hong Kong stock market. On dynamic analysis, the news impact surface shows the asymmetry of the co-movement for positive and negative news. The aDCC-EGARCH model is used to observe the dynamic co-movement changes between the Chinese stock market and the global stock market. It shows that trade conflicts have enhanced the co-movement between the Chinese stock market and the global stock market to varying degrees. At the same time, the Chinese stock market is strategically tilted towards the Asian market. Based on the research results in this paper, countries around the world need to pay more attention to the risk contagion between stock markets after the outbreak of the trade war. China’s inland markets should be alert to risk contagion from the Hong Kong market.
{"title":"The impact of Sino–US trade war on the co-movement between China’s stock market and global stock markets","authors":"Yuping Song, Yan Sun, Yueh-Ching Ma","doi":"10.1142/s2424786322500360","DOIUrl":"https://doi.org/10.1142/s2424786322500360","url":null,"abstract":"Taking the Sino–US trade war as the background, we study the co-movement changes on horizontal return and volatility of the daily logarithmic return data of global stock indices from 2016 to January 23, 2020 from static and dynamic perspectives. Through static tools such as correlation coefficient matrices, complex networks, and Granger causality, it is found that the trade war has significantly strengthened the correlation between the Chinese stock market and the global stock market, and highlighted the position of the Hong Kong stock market. On dynamic analysis, the news impact surface shows the asymmetry of the co-movement for positive and negative news. The aDCC-EGARCH model is used to observe the dynamic co-movement changes between the Chinese stock market and the global stock market. It shows that trade conflicts have enhanced the co-movement between the Chinese stock market and the global stock market to varying degrees. At the same time, the Chinese stock market is strategically tilted towards the Asian market. Based on the research results in this paper, countries around the world need to pay more attention to the risk contagion between stock markets after the outbreak of the trade war. China’s inland markets should be alert to risk contagion from the Hong Kong market.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43621960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-28DOI: 10.1142/s2424786322500281
R. Arora, Rishi Mehra
Government, regulators, exchanges, banks, and institutions collaborate to develop rules and devote significant time and resources to improving the financial system, with the ultimate goal of creating a more effective market. The statistics on turnover and earnings only show the market’s Quantitative’ growth. The figures do not demonstrate how the market has improved in terms of Quality and Market Efficiency. A robust market structure and long-term growth in any market are only possible when development is based on both qualitative (market efficiency) and quantitative factors (Turnovers and Earnings). Historically, studies and research have laid great emphasis on determining the market’s level of efficiency. However, market efficiency was always checked using staggered time frames and efficiency tests. The need of the hour is a transparent and simple-to-understand tool that can continuously measure market efficiency and has universal applicability. This study proposes a tool for measuring efficiency called the Financial Market Efficiency Index — FMEI. The Index would derive its parameters from the broad market Index of any country to assess and compare market efficiency. The index would not only measure the qualitative growth (Market Efficiency) of any market, but it would also compare the market efficiency of all countries around the world. This would allow stakeholders to make the best decisions for their respective markets.
{"title":"Are capital markets turning efficient? need for financial market efficiency index","authors":"R. Arora, Rishi Mehra","doi":"10.1142/s2424786322500281","DOIUrl":"https://doi.org/10.1142/s2424786322500281","url":null,"abstract":"Government, regulators, exchanges, banks, and institutions collaborate to develop rules and devote significant time and resources to improving the financial system, with the ultimate goal of creating a more effective market. The statistics on turnover and earnings only show the market’s Quantitative’ growth. The figures do not demonstrate how the market has improved in terms of Quality and Market Efficiency. A robust market structure and long-term growth in any market are only possible when development is based on both qualitative (market efficiency) and quantitative factors (Turnovers and Earnings). Historically, studies and research have laid great emphasis on determining the market’s level of efficiency. However, market efficiency was always checked using staggered time frames and efficiency tests. The need of the hour is a transparent and simple-to-understand tool that can continuously measure market efficiency and has universal applicability. This study proposes a tool for measuring efficiency called the Financial Market Efficiency Index — FMEI. The Index would derive its parameters from the broad market Index of any country to assess and compare market efficiency. The index would not only measure the qualitative growth (Market Efficiency) of any market, but it would also compare the market efficiency of all countries around the world. This would allow stakeholders to make the best decisions for their respective markets.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48144327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-18DOI: 10.1142/s2424786322500335
Siyu Liu, Chaoyi Zhao, Lan Wu
Order type plays an important role in algorithmic trading and is a key factor of price impact. In this paper, we propose a new framework for studying the discrete price change process, which focuses on the impacts of aggressive orders (market orders and aggressive limit orders) and cancelations. The price change process is driven by states and events of best quotes, and we define the event-based price change as the “natural price change” (NPC). Under the framework, we propose a heteroscedastic linear econometric model for the NPC to explore the impact of different types of orders on the price dynamics. To verify the usability of our model and explore the driving factors of price dynamics, we conduct a thorough empirical analysis for 786 large-tick stocks traded on the Shenzhen Stock Exchange. Empirical results statistically demonstrate that aggressive orders can introduce stronger impact on the NPC than cancelations. Meanwhile, splitting a big order into several small orders can lead to a larger NPC. Our framework can also be applied for the prediction of price change.
{"title":"Order types and natural price change: Model and empirical study of the Chinese market","authors":"Siyu Liu, Chaoyi Zhao, Lan Wu","doi":"10.1142/s2424786322500335","DOIUrl":"https://doi.org/10.1142/s2424786322500335","url":null,"abstract":"Order type plays an important role in algorithmic trading and is a key factor of price impact. In this paper, we propose a new framework for studying the discrete price change process, which focuses on the impacts of aggressive orders (market orders and aggressive limit orders) and cancelations. The price change process is driven by states and events of best quotes, and we define the event-based price change as the “natural price change” (NPC). Under the framework, we propose a heteroscedastic linear econometric model for the NPC to explore the impact of different types of orders on the price dynamics. To verify the usability of our model and explore the driving factors of price dynamics, we conduct a thorough empirical analysis for 786 large-tick stocks traded on the Shenzhen Stock Exchange. Empirical results statistically demonstrate that aggressive orders can introduce stronger impact on the NPC than cancelations. Meanwhile, splitting a big order into several small orders can lead to a larger NPC. Our framework can also be applied for the prediction of price change.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45538887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.1142/s2424786322500323
Muhammad Atif Sattar, Z. Hailiang, Samra Kanwal, B. Gardi
The purpose of this paper is to assess unbiased options pricing predictions via ad hoc Black–Scholes model approaches. This paper investigates a number of technical issues when fitted values of implied volatility from linear regression are plugged into the Black–Scholes model, which leads to biased estimation. First, the study observes that the implied volatility linear regression can yield a negative outcome, which is meaningless. Therefore, a logarithmic transformation is applied to the linear function to ensure that the forecast is positive. Second, the retransformation from log to original metric to fitted values of implied volatility and the nonlinearity of Black–Scholes to implied volatility yields biased forecasts. A smearing technique has been applied in this study to correct this bias. Finally, the smearing estimation method also provides biased results if there is heteroscedasticity in the OLS estimation residuals. This study applies the weighted least square regression technique in order to avoid heteroscedasticity. According to the performance measures such as mean bias (MB), mean absolute error (MAE) and mean absolute relative error, the study concludes that the smearing method is the most effective to correct the bias in ad hoc Black–Scholes approaches as well as that an absolute smile approach is better than a relative smile approach without the smearing technique, but with smearing methods, relative smile performs superior to absolute.
{"title":"Improvized implied volatility function and nonparametric approach to unbiased estimation","authors":"Muhammad Atif Sattar, Z. Hailiang, Samra Kanwal, B. Gardi","doi":"10.1142/s2424786322500323","DOIUrl":"https://doi.org/10.1142/s2424786322500323","url":null,"abstract":"The purpose of this paper is to assess unbiased options pricing predictions via ad hoc Black–Scholes model approaches. This paper investigates a number of technical issues when fitted values of implied volatility from linear regression are plugged into the Black–Scholes model, which leads to biased estimation. First, the study observes that the implied volatility linear regression can yield a negative outcome, which is meaningless. Therefore, a logarithmic transformation is applied to the linear function to ensure that the forecast is positive. Second, the retransformation from log to original metric to fitted values of implied volatility and the nonlinearity of Black–Scholes to implied volatility yields biased forecasts. A smearing technique has been applied in this study to correct this bias. Finally, the smearing estimation method also provides biased results if there is heteroscedasticity in the OLS estimation residuals. This study applies the weighted least square regression technique in order to avoid heteroscedasticity. According to the performance measures such as mean bias (MB), mean absolute error (MAE) and mean absolute relative error, the study concludes that the smearing method is the most effective to correct the bias in ad hoc Black–Scholes approaches as well as that an absolute smile approach is better than a relative smile approach without the smearing technique, but with smearing methods, relative smile performs superior to absolute.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41571554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.1142/s242478632250030x
Dakshayini Rasadurai, M. Raguraman
Purpose: This paper aims to analyze the effectiveness of service quality provided in Tirupattur Head Post Office toward Postal Life Insurance (PLI) and Rural Postal Life Insurance (RPLI) polices. Service quality is an important element in the management of service. The post office is a very big service-oriented institution. It started its insurance business from 1 February 1884. Design, methodology, approach: A descriptive research design were used to study the objective such as analyzing the various service quality provided by Postal Insurer and also to find the best service quality, to achieve this the researcher used questionnaire to collect 85 samples using simple random technique from PLI and RPLI policyholders in Tirupattur district. The primary data are analyzed by applying percentage analysis, mean and standard deviation, [Formula: see text]-test and [Formula: see text]-test in SPSS tools. Finding: A finding of the study shows that postal insurance industry was providing high quality services regarding financial stability accessible location, flexible payments and were providing low quality services regarding online transaction, approaching from the customers point of view, introducing new products. Mean and SD value show positive rating. The [Formula: see text]-test shows the assurance is the best service quality provided by postal insurer among six service quality factors. All the service quality statements are above average level. [Formula: see text]test shows a significant difference of all statement if service quality factors to demographic factors. Practical implications: This research paper is important for the investors, postal insurer, and post office. Service quality will have positive impact on customer satisfaction that will lead to investment behavior. Social implications: This study provides awareness to investors about postal insurance, important of service quality to the postal insurer, in the study area and trends-related research for future. Originality: This study provides a comprehensive review of theories, methods, discussion points, and conclusions of studies on service quality, customer satisfaction, PLI published in selected investment journals over past 20 years. Research limitations: This study was confined only to Tirupattur Head Post Office and Conclusions drawn may not be applicable to other district post office and, therefore, the findings of this study cannot be generalized.
{"title":"Analyzing effectiveness of service quality in Tirupattur post office toward postal life insurance (PLI) and rural postal life insurance (RPLI)","authors":"Dakshayini Rasadurai, M. Raguraman","doi":"10.1142/s242478632250030x","DOIUrl":"https://doi.org/10.1142/s242478632250030x","url":null,"abstract":"Purpose: This paper aims to analyze the effectiveness of service quality provided in Tirupattur Head Post Office toward Postal Life Insurance (PLI) and Rural Postal Life Insurance (RPLI) polices. Service quality is an important element in the management of service. The post office is a very big service-oriented institution. It started its insurance business from 1 February 1884. Design, methodology, approach: A descriptive research design were used to study the objective such as analyzing the various service quality provided by Postal Insurer and also to find the best service quality, to achieve this the researcher used questionnaire to collect 85 samples using simple random technique from PLI and RPLI policyholders in Tirupattur district. The primary data are analyzed by applying percentage analysis, mean and standard deviation, [Formula: see text]-test and [Formula: see text]-test in SPSS tools. Finding: A finding of the study shows that postal insurance industry was providing high quality services regarding financial stability accessible location, flexible payments and were providing low quality services regarding online transaction, approaching from the customers point of view, introducing new products. Mean and SD value show positive rating. The [Formula: see text]-test shows the assurance is the best service quality provided by postal insurer among six service quality factors. All the service quality statements are above average level. [Formula: see text]test shows a significant difference of all statement if service quality factors to demographic factors. Practical implications: This research paper is important for the investors, postal insurer, and post office. Service quality will have positive impact on customer satisfaction that will lead to investment behavior. Social implications: This study provides awareness to investors about postal insurance, important of service quality to the postal insurer, in the study area and trends-related research for future. Originality: This study provides a comprehensive review of theories, methods, discussion points, and conclusions of studies on service quality, customer satisfaction, PLI published in selected investment journals over past 20 years. Research limitations: This study was confined only to Tirupattur Head Post Office and Conclusions drawn may not be applicable to other district post office and, therefore, the findings of this study cannot be generalized.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43163798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.1142/s2424786322500311
Yijiao Liu, Yukun Gao, Yufeng Shi, Yuxue Zhang, Li Li, Qimeng Han
Along with developing the commodity futures market, its promoting effect on China’s economic development has gradually increased. Research on the price prediction of commodity futures has important practical significance to society and enterprises. However, commodity futures price series often show nonstationary and nonlinear characteristics In this paper, a new multi-scale combined prediction model is proposed, which combines variational mode decomposition (VMD), long short-term memory neural network (LSTM), and improved self-attention mechanism (XNSA). First, VMD decomposes futures prices into several components to reduce their nonstationarity. Then, the LSTM model with an improved self-attention mechanism (XNSA) is used to model and optimize the decomposed sub-sequences so that the model can concentrate on learning more important data features and further improve the prediction performance. In order to verify the effectiveness of this method, this paper takes No. 1 Soybeans Futures, Corn Futures, and Soybean Meal Futures daily closing price series from Dalian Commodity Exchange as representatives to predict their future return trend. The results show that compared with the existing combination forecasting models, the proposed multi-scale combination model (VMD-LSTM-XNSA) has better forecasting performance. It lays the foundation for developing a corresponding quantitative investment strategy.
{"title":"Commodity futures price forecast based on multi-scale combination model","authors":"Yijiao Liu, Yukun Gao, Yufeng Shi, Yuxue Zhang, Li Li, Qimeng Han","doi":"10.1142/s2424786322500311","DOIUrl":"https://doi.org/10.1142/s2424786322500311","url":null,"abstract":"Along with developing the commodity futures market, its promoting effect on China’s economic development has gradually increased. Research on the price prediction of commodity futures has important practical significance to society and enterprises. However, commodity futures price series often show nonstationary and nonlinear characteristics In this paper, a new multi-scale combined prediction model is proposed, which combines variational mode decomposition (VMD), long short-term memory neural network (LSTM), and improved self-attention mechanism (XNSA). First, VMD decomposes futures prices into several components to reduce their nonstationarity. Then, the LSTM model with an improved self-attention mechanism (XNSA) is used to model and optimize the decomposed sub-sequences so that the model can concentrate on learning more important data features and further improve the prediction performance. In order to verify the effectiveness of this method, this paper takes No. 1 Soybeans Futures, Corn Futures, and Soybean Meal Futures daily closing price series from Dalian Commodity Exchange as representatives to predict their future return trend. The results show that compared with the existing combination forecasting models, the proposed multi-scale combination model (VMD-LSTM-XNSA) has better forecasting performance. It lays the foundation for developing a corresponding quantitative investment strategy.","PeriodicalId":54088,"journal":{"name":"International Journal of Financial Engineering","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46586180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-10DOI: 10.1142/s2424786322500268
Rupsa Mahapatra, K. Das
Equity fund in Indian corporate sector plays a pivotal role for the advancement trade and business across the sector. The composition of equity fund and its share in the total capitalization is the reflection of financial health of the organization. The real stake holders are the equity shareholders, who are the real owners of the organization. The companies raise the part of required capital in the form of equity share from individuals as well as institutions. Major contributions are from the investment in equity-linked mutual funds. Present research is undertaken to address the number questions related to equity fund investment, trends, return to the stake-holder, performance, etc. To understand the present issues, it needs introspection of past research in these areas and formulation of a sustainable model to overcome these problems. The study considers the secondary data for analysis with help of the statistical tools like descriptive statistics and regression model with ANOVA and others.
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