{"title":"The Problem of Timing in Decisions to Buy or to Charter a Vessel","authors":"Alexandros M. Goulielmos, Marcos A Goulielmos","doi":"10.1400/115954","DOIUrl":null,"url":null,"abstract":"This paper dealt with the concept of timing in reaching decisions, especially in connection with freight markets and sale and purchase of second hand ships. Timing is “the calendar time we accept as right just before we take a decision”. First, an extensive literature search has been attempted in such disciplines as Management, Decision- making and Decision Support Systems. Unfortunately, traditional disciplines have frequently offered the excuse for not dealing with timing of decision- making due to ‘lack of information’ and to ‘limited predictive techniques’. Moreover, modern disciplines (in particular chaos theory) also excuse themselves from addressing the question of timing on the grounds that real phenomena are ‘inherently unpredictable’. The concept of time in finance has been presented here as applied by Mandelbrot (1997) [and Albert Einstein (in 1905)] and stressed that time is flexible. Moreover found that time series have a speed and a long-term memory. A non-parametric method called ‘Rescaled Range Analysis’ applied which indeed deals with cycles and long term memories. The research directed also to the discipline of modeling and forecasting, both classical and chaotic (fractal). This brought us to address the question : should ARIMA (random) or ARFIMA (fractal) models be here and in similar applications employed ? The final conclusion was that Rescaled Range Analysis was the most appropriate for the analysis of both freight market and second hand ship price market. Additionally, the normality test by Jarque-Bera test (33>5.99) for freight market has shown the absence of normality and the existence of excess kurtosis (-1.51) as well as excess skewness (0.21). Moreover, a strong memory in freight rates of H=0.92","PeriodicalId":365370,"journal":{"name":"Rivista Internazionale de Economia dei Trasporti","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rivista Internazionale de Economia dei Trasporti","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1400/115954","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper dealt with the concept of timing in reaching decisions, especially in connection with freight markets and sale and purchase of second hand ships. Timing is “the calendar time we accept as right just before we take a decision”. First, an extensive literature search has been attempted in such disciplines as Management, Decision- making and Decision Support Systems. Unfortunately, traditional disciplines have frequently offered the excuse for not dealing with timing of decision- making due to ‘lack of information’ and to ‘limited predictive techniques’. Moreover, modern disciplines (in particular chaos theory) also excuse themselves from addressing the question of timing on the grounds that real phenomena are ‘inherently unpredictable’. The concept of time in finance has been presented here as applied by Mandelbrot (1997) [and Albert Einstein (in 1905)] and stressed that time is flexible. Moreover found that time series have a speed and a long-term memory. A non-parametric method called ‘Rescaled Range Analysis’ applied which indeed deals with cycles and long term memories. The research directed also to the discipline of modeling and forecasting, both classical and chaotic (fractal). This brought us to address the question : should ARIMA (random) or ARFIMA (fractal) models be here and in similar applications employed ? The final conclusion was that Rescaled Range Analysis was the most appropriate for the analysis of both freight market and second hand ship price market. Additionally, the normality test by Jarque-Bera test (33>5.99) for freight market has shown the absence of normality and the existence of excess kurtosis (-1.51) as well as excess skewness (0.21). Moreover, a strong memory in freight rates of H=0.92
本文讨论了决策中的时间概念,特别是与货运市场和二手船买卖有关的决策。时间是“在我们做出决定之前,我们认为正确的日历时间”。首先,在管理学、决策制定和决策支持系统等学科中进行了广泛的文献检索。不幸的是,由于“缺乏信息”和“有限的预测技术”,传统学科经常为不处理决策的时机提供借口。此外,现代学科(尤其是混沌理论)也以真实现象“本质上不可预测”为理由,为自己解决时间问题找借口。在这里,Mandelbrot(1997)[和Albert Einstein(1905)]应用了金融中的时间概念,并强调时间是灵活的。而且发现时间序列具有速度性和长期记忆性。应用了一种非参数方法,称为“重标度极差分析”,它确实处理了周期和长期记忆。该研究还针对建模和预测学科,包括经典和混沌(分形)。这给我们带来了一个问题:ARIMA(随机)或ARFIMA(分形)模型应该在这里和在类似的应用中使用吗?最后得出的结论是,无论是对货运市场还是二手船价格市场的分析,Rescaled Range Analysis都是最合适的。此外,通过Jarque-Bera检验(33>5.99),货运市场的正态性检验显示不存在正态性,存在超额峰度(-1.51)和超额偏度(0.21)。而且,在运价方面有较强的记忆H=0.92