Pub Date : 2021-01-01DOI: 10.47654/v25y2021i3p92-118
{"title":"Review on Behavioral Finance with Empirical Evidence","authors":"","doi":"10.47654/v25y2021i3p92-118","DOIUrl":"https://doi.org/10.47654/v25y2021i3p92-118","url":null,"abstract":"","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70851544","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 : 2021-01-01DOI: 10.47654/v25y2021i3p1-25
{"title":"Inflation and Economic Growth in Kenya: An Empirical Examination","authors":"","doi":"10.47654/v25y2021i3p1-25","DOIUrl":"https://doi.org/10.47654/v25y2021i3p1-25","url":null,"abstract":"","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70851880","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 : 2021-01-01DOI: 10.47654/v25y2021i4p115-151
G. Srilakshminarayana
The study also recommends estimating the tail index and then deciding upon any other methodology for analyzing the stock market prices. According to the history, price of stocks and other assets are an important part of economic activity and can act as an indicator of social mood. Modelling the stock market prices is an age-old problem, and for many years researchers have modelled the stock prices using a normal model. The presence of the extremes increases the volatility of the stock price random variable and affects its symmetric nature at the tails.
{"title":"Tail Behaviour of the Nifty-50 Stocks during Crises Periods","authors":"G. Srilakshminarayana","doi":"10.47654/v25y2021i4p115-151","DOIUrl":"https://doi.org/10.47654/v25y2021i4p115-151","url":null,"abstract":"The study also recommends estimating the tail index and then deciding upon any other methodology for analyzing the stock market prices. According to the history, price of stocks and other assets are an important part of economic activity and can act as an indicator of social mood. Modelling the stock market prices is an age-old problem, and for many years researchers have modelled the stock prices using a normal model. The presence of the extremes increases the volatility of the stock price random variable and affects its symmetric nature at the tails.","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70851821","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 : 2021-01-01DOI: 10.47654/v25y2021i4p152-172
{"title":"Existence of Cointegration between the Public and Private Bank Index: Evidence from Indian Capital Market","authors":"","doi":"10.47654/v25y2021i4p152-172","DOIUrl":"https://doi.org/10.47654/v25y2021i4p152-172","url":null,"abstract":"","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70852434","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 : 2021-01-01DOI: 10.47654/v25y2021i4p89-114
{"title":"A Comparative Assessment of the Global Effects of US Monetary and Fiscal Policy Uncertainty Shocks","authors":"","doi":"10.47654/v25y2021i4p89-114","DOIUrl":"https://doi.org/10.47654/v25y2021i4p89-114","url":null,"abstract":"","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70851981","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 : 2020-09-01DOI: 10.47654/v24y2020i3p63-83
M. McAleer
The SARS-CoV-2 that causes the COVID-19 disease is a one-in-a-century disaster that has led to profound structural change in every conceivable aspect of the worldwide community. The COVID-19 pandemic is the most topical subject in the academic community across all disciplines, but especially in the medical and biomedical research disciplines, where attempts to discover a safe, effective, timely, inexpensive, and accessible vaccine is at the top of everyone’s wish list. There is a substantial amount of confusion, ambiguity, and misinformation in the academic community, and far more so in social mass media. Leading medical journals, such as the Journal of the American Medical Association (JAMA), The Lancet, and the New England Journal of Medicine, have published informative case studies that seek to provide guidance on COVID-19 at the earliest possible opportunity.
{"title":"Comments on Recent COVID-19 Research in JAMA","authors":"M. McAleer","doi":"10.47654/v24y2020i3p63-83","DOIUrl":"https://doi.org/10.47654/v24y2020i3p63-83","url":null,"abstract":"The SARS-CoV-2 that causes the COVID-19 disease is a one-in-a-century disaster that has led to profound structural change in every conceivable aspect of the worldwide community. The COVID-19 pandemic is the most topical subject in the academic community across all disciplines, but especially in the medical and biomedical research disciplines, where attempts to discover a safe, effective, timely, inexpensive, and accessible vaccine is at the top of everyone’s wish list. There is a substantial amount of confusion, ambiguity, and misinformation in the academic community, and far more so in social mass media. Leading medical journals, such as the Journal of the American Medical Association (JAMA), The Lancet, and the New England Journal of Medicine, have published informative case studies that seek to provide guidance on COVID-19 at the earliest possible opportunity.","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"24 1","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46176725","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 : 2020-06-01DOI: 10.47654/v24y2020i2p1-14
P. Franses
The Ordinary Least Squares (OLS) estimator for the slope parameter in a first-order autoregressive model is biased when the variable is measured with error. Such an error may occur with revisions of macroeconomic data. This paper illustrates and proposes a simple procedure to alleviate the bias, and is based on Total Least Squares (TLS). TLS is, in general, consistent, and also works well in small samples. Simulation experiments and an empirical example show the usefulness of this method.
{"title":"Measurement Error in a First-order Autoregression","authors":"P. Franses","doi":"10.47654/v24y2020i2p1-14","DOIUrl":"https://doi.org/10.47654/v24y2020i2p1-14","url":null,"abstract":"The Ordinary Least Squares (OLS) estimator for the slope parameter in a first-order autoregressive model is biased when the variable is measured with error. Such an error may occur with revisions of macroeconomic data. This paper illustrates and proposes a simple procedure to alleviate the bias, and is based on Total Least Squares (TLS). TLS is, in general, consistent, and also works well in small samples. Simulation experiments and an empirical example show the usefulness of this method.","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"24 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42787789","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 : 2020-01-01DOI: 10.47654/v24y2020i3p1-27
Mapitsi Rangata, Sonali Das, Montaz Ali
The paper uses Functional Data Analysis (FDA) to explore space and time variation of monthly maximum temperature data of 16 locations in South Africa for the period 1965 - 2010 at intervals of 5 years. We explore monthly maximum temperature variation by first representing data using the B-spline basis functions. Thereafter registration of the smooth temperature curves was performed. This data was then subjected to analysis using phase-plane plots which revealed the constant shifting of energy over the years analysed. We next applied functional Principal Component Analysis (fPCA) to reduce the dimension of maximum temperature curves by identifying the maximum variation without loss of relevant information, which revealed that the first functional PCA explains mostly summer variation while the second functional PCA explains winter variation. We next explored the functional data using functional clustering using K-means to reveal the spatial location of maximum temperature clusters across the country, which revealed that maximum temperature clusters were not consistent over the 45 years of data analysed, and that the cluster points within a cluster were not necessarily always spatially adjacent. The overall analysis has displayed that maximum temperature clusters have not been static across the country over time. To the best of our knowledge, this the first instance of performing in-depth analysis of maximum temperature data for 16 locations in South Africa using various FDA methods.
本文采用功能数据分析(Functional Data Analysis, FDA)方法，对南非16个地点1965—2010年逐月最高气温数据进行了以5年为间隔的时空变化分析。我们通过首先使用b样条基函数表示数据来探索月最高温度变化。然后进行光滑温度曲线的配准。然后使用相平面图对这些数据进行分析，这些图揭示了所分析的年份中能量的不断变化。利用功能主成分分析(functional Principal Component Analysis, fPCA)在不丢失相关信息的情况下，通过识别最大变化来降低最高温度曲线的维数，结果表明，第一个功能主成分分析可以解释夏季变化，而第二个功能主成分分析可以解释冬季变化。接下来，我们利用K-means的功能聚类方法对功能数据进行了探索，揭示了全国最高温度集群的空间位置，结果表明，在45年的数据分析中，最高温度集群并不一致，集群内的集群点不一定总是空间相邻。总体分析显示，随着时间的推移，全国各地的最高温度集群并不是一成不变的。据我们所知，这是第一次使用各种FDA方法对南非16个地点的最高温度数据进行深入分析。
{"title":"Analysing Maximum Monthly Temperatures in South Africa for 45 years Using Functional Data Analysis","authors":"Mapitsi Rangata, Sonali Das, Montaz Ali","doi":"10.47654/v24y2020i3p1-27","DOIUrl":"https://doi.org/10.47654/v24y2020i3p1-27","url":null,"abstract":"The paper uses Functional Data Analysis (FDA) to explore space and time variation of monthly maximum temperature data of 16 locations in South Africa for the period 1965 - 2010 at intervals of 5 years. We explore monthly maximum temperature variation by first representing data using the B-spline basis functions. Thereafter registration of the smooth temperature curves was performed. This data was then subjected to analysis using phase-plane plots which revealed the constant shifting of energy over the years analysed. We next applied functional Principal Component Analysis (fPCA) to reduce the dimension of maximum temperature curves by identifying the maximum variation without loss of relevant information, which revealed that the first functional PCA explains mostly summer variation while the second functional PCA explains winter variation. We next explored the functional data using functional clustering using K-means to reveal the spatial location of maximum temperature clusters across the country, which revealed that maximum temperature clusters were not consistent over the 45 years of data analysed, and that the cluster points within a cluster were not necessarily always spatially adjacent. The overall analysis has displayed that maximum temperature clusters have not been static across the country over time. To the best of our knowledge, this the first instance of performing in-depth analysis of maximum temperature data for 16 locations in South Africa using various FDA methods.","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"24 1","pages":"1-27"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70849521","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 : 2020-01-01DOI: 10.47654/v24y2020i3p110-141
Adrián Mendieta-Aragón, Teresa GarÃn-Muñoz
This paper studies the main determinants of the inbound international tourism in Andalusia and quantify its incidence. Based on the classical theoretical framework for tourism demand, we incorporate dynamics into the model by adding the lagged dependent variable as an explanatory variable, along with the per capita income of the tourist's country of origin, the relative prices between the origin and destination countries and the cost of travel. The empirical model is applied to a panel data set consisting of 21 countries of origin of the tourists for the period 2008–2018. Data were collected from the Hotel Occupancy Survey (HOS), published by the National Statistics Institute of Spain (INE). The results have been obtained using the GMM DIFF estimator of Arellano and Bond. The parameters estimated reflect a high level of consumer loyalty and the importance of the word-of-mouth effect. Moreover, the income elasticity indicates that the demand for tourism in Andalusia may be considered as a luxury good. Prices have a negative relationship with tourism demand. The cost of travel, which has a negative effect, is statistically significant to explain the number of tourists' arrivals and, however, it is not significant for the overnight stays model.
{"title":"Foreign Tourism in Andalusia: A Dynamic Panel Data Analysis","authors":"Adrián Mendieta-Aragón, Teresa GarÃn-Muñoz","doi":"10.47654/v24y2020i3p110-141","DOIUrl":"https://doi.org/10.47654/v24y2020i3p110-141","url":null,"abstract":"This paper studies the main determinants of the inbound international tourism in Andalusia and quantify its incidence. Based on the classical theoretical framework for tourism demand, we incorporate dynamics into the model by adding the lagged dependent variable as an explanatory variable, along with the per capita income of the tourist's country of origin, the relative prices between the origin and destination countries and the cost of travel. The empirical model is applied to a panel data set consisting of 21 countries of origin of the tourists for the period 2008–2018. Data were collected from the Hotel Occupancy Survey (HOS), published by the National Statistics Institute of Spain (INE). The results have been obtained using the GMM DIFF estimator of Arellano and Bond. The parameters estimated reflect a high level of consumer loyalty and the importance of the word-of-mouth effect. Moreover, the income elasticity indicates that the demand for tourism in Andalusia may be considered as a luxury good. Prices have a negative relationship with tourism demand. The cost of travel, which has a negative effect, is statistically significant to explain the number of tourists' arrivals and, however, it is not significant for the overnight stays model.","PeriodicalId":38875,"journal":{"name":"Advances in Decision Sciences","volume":"24 1","pages":"110-141"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70849599","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}
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