Pub Date : 2023-11-02DOI: 10.1007/s11135-023-01761-1
Kokulo K. Lawuobahsumo, Bernardina Algieri, Arturo Leccadito
Abstract This study aims to jointly predict conditional quantiles and tail expectations for the returns of the most popular cryptocurrencies (Bitcoin, Ethereum, Ripple, Dogecoin and Litecoin) using financial and macroeconomic indicators as explanatory variables. We adopt a Monotone Composite Quantile Regression Neural Network (MCQRNN) model to make one- and five-steps-ahead predictions of Value-at-Risk (VaR) and Expected Shortfall (ES) based on a rolling window and compare the performance of our model against the Historical simulation and the standard ARMA(1,1)-GARCH(1,1) model used as benchmarks. The superior set of models is then chosen by backtesting VaR and ES using a Model Confidence Set procedure. Our results show that the MCQRNN performs better than both benchmark models for jointly predicting VaR and ES when considering daily data. Models with the implied volatility index, treasury yield spread and inflation expectations sharpen the extreme return predictions. The results are consistent for the two risk measures at the 1% and 5% level both, in the case of a long and short position and for all cryptocurrencies.
{"title":"Forecasting cryptocurrencies returns: Do macroeconomic and financial variables improve tail expectation predictions?","authors":"Kokulo K. Lawuobahsumo, Bernardina Algieri, Arturo Leccadito","doi":"10.1007/s11135-023-01761-1","DOIUrl":"https://doi.org/10.1007/s11135-023-01761-1","url":null,"abstract":"Abstract This study aims to jointly predict conditional quantiles and tail expectations for the returns of the most popular cryptocurrencies (Bitcoin, Ethereum, Ripple, Dogecoin and Litecoin) using financial and macroeconomic indicators as explanatory variables. We adopt a Monotone Composite Quantile Regression Neural Network (MCQRNN) model to make one- and five-steps-ahead predictions of Value-at-Risk (VaR) and Expected Shortfall (ES) based on a rolling window and compare the performance of our model against the Historical simulation and the standard ARMA(1,1)-GARCH(1,1) model used as benchmarks. The superior set of models is then chosen by backtesting VaR and ES using a Model Confidence Set procedure. Our results show that the MCQRNN performs better than both benchmark models for jointly predicting VaR and ES when considering daily data. Models with the implied volatility index, treasury yield spread and inflation expectations sharpen the extreme return predictions. The results are consistent for the two risk measures at the 1% and 5% level both, in the case of a long and short position and for all cryptocurrencies.","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"16 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135934625","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 : 2023-10-31DOI: 10.1007/s11135-023-01766-w
Sakiru Adebola Solarin, Mufutau Opeyemi Bello
{"title":"Modelling labour productivity and the role of research intensity in 129 years: evidence from a new dynamic instrumental variable estimation approach","authors":"Sakiru Adebola Solarin, Mufutau Opeyemi Bello","doi":"10.1007/s11135-023-01766-w","DOIUrl":"https://doi.org/10.1007/s11135-023-01766-w","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"22 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809198","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 : 2023-10-28DOI: 10.1007/s11135-023-01769-7
Julien Noble, Antoine Jardin
{"title":"Correction: Mapping fear of crime: defining methodological orientations","authors":"Julien Noble, Antoine Jardin","doi":"10.1007/s11135-023-01769-7","DOIUrl":"https://doi.org/10.1007/s11135-023-01769-7","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"20 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136232767","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 : 2023-10-21DOI: 10.1007/s11135-023-01756-y
Fatma Kürüm Varolgüneş, Sadık Varolgüneş, María de la Cruz del Río-Rama, Amador Durán-Sánchez
{"title":"A proposal for the selection of green building standards through the analytical hierarchy process (AHP): a roadmap for green hotels in Turkey","authors":"Fatma Kürüm Varolgüneş, Sadık Varolgüneş, María de la Cruz del Río-Rama, Amador Durán-Sánchez","doi":"10.1007/s11135-023-01756-y","DOIUrl":"https://doi.org/10.1007/s11135-023-01756-y","url":null,"abstract":"","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"10 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135513175","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 : 2023-10-18DOI: 10.1007/s11135-023-01753-1
Anna Malandrino
Abstract The literature that reflects on the application of Social Network Analysis (SNA) in combination with other methods is flourishing. However, there is a dearth of studies that compare qualitative and quantitative methods to complement structural SNA. This article addresses this gap by systematically discussing the advantages and disadvantages relating to the use of qualitative text analysis and interviewing as well as quantitative text mining and Natural Language Processing (NLP) techniques such as word frequency analysis, cluster analysis, topic modeling, and topic classification to understand policy networks. This method-oriented comparative study features two empirical studies that respectively examine the Employment Thematic Network, established under the aegis of the European Commission, and the intergovernmental cooperation network set up within the Bologna Process. The article compares and discusses the underlying research processes in terms of time, human resources, research resources, unobtrusiveness, and effectiveness toward the goal of telling meaningful stories about the examined networks in light of specific guiding hypotheses. In doing so, the paper nurtures the debate on mixed-methods research on social networks amidst the well-known paradigm war between qualitative and quantitative methods in network analysis.
{"title":"Comparing qualitative and quantitative text analysis methods in combination with document-based social network analysis to understand policy networks","authors":"Anna Malandrino","doi":"10.1007/s11135-023-01753-1","DOIUrl":"https://doi.org/10.1007/s11135-023-01753-1","url":null,"abstract":"Abstract The literature that reflects on the application of Social Network Analysis (SNA) in combination with other methods is flourishing. However, there is a dearth of studies that compare qualitative and quantitative methods to complement structural SNA. This article addresses this gap by systematically discussing the advantages and disadvantages relating to the use of qualitative text analysis and interviewing as well as quantitative text mining and Natural Language Processing (NLP) techniques such as word frequency analysis, cluster analysis, topic modeling, and topic classification to understand policy networks. This method-oriented comparative study features two empirical studies that respectively examine the Employment Thematic Network, established under the aegis of the European Commission, and the intergovernmental cooperation network set up within the Bologna Process. The article compares and discusses the underlying research processes in terms of time, human resources, research resources, unobtrusiveness, and effectiveness toward the goal of telling meaningful stories about the examined networks in light of specific guiding hypotheses. In doing so, the paper nurtures the debate on mixed-methods research on social networks amidst the well-known paradigm war between qualitative and quantitative methods in network analysis.","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135883015","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 : 2023-10-13DOI: 10.1007/s11135-023-01762-0
Artur Roland Kozlowski
Abstract The effects of war have far-reaching consequences. They bring numerous victims—also civilians, destruction of infrastructure, enterprises, and citizens’ property. They cause political instability and lead to great security concerns, especially in tourist destinations. Experience with various wars indicates a minimum three-year negative effect of warfare on the tourism industry. The terrorist industry is also negatively affected by terrorism, which can occur regardless of the duration of the war itself. Terrorist attacks are deliberately organized in such a way as to evoke images of human victims, which affects the fear of tourist arrivals to such heavily burdened places. The paper discusses potential scenarios for the continuation of the war and its impact on the operational activity of international business with Russia. Russia’s unprovoked war against Ukraine brings closer the threat of war itself and shock to various industries, including the tourism industry. The paper presents the effects of the war on tourist trips from Russia but also Ukraine and its effects on traditional touristic destinations. Issues of threats to business are raised but also opportunities appearing on the horizon. The visa ban for Russians introduced by the EU with the simultaneous escalating and ruthless Russian attacks on Ukrainian civilians does not inspire optimism. It should be expected that the 2023 tourist season will remain burdened with the stigma of war and the limited movement of Russians around Europe.
{"title":"The war and tourism: security issues and business opportunities in shadow of Russian war against Ukraine","authors":"Artur Roland Kozlowski","doi":"10.1007/s11135-023-01762-0","DOIUrl":"https://doi.org/10.1007/s11135-023-01762-0","url":null,"abstract":"Abstract The effects of war have far-reaching consequences. They bring numerous victims—also civilians, destruction of infrastructure, enterprises, and citizens’ property. They cause political instability and lead to great security concerns, especially in tourist destinations. Experience with various wars indicates a minimum three-year negative effect of warfare on the tourism industry. The terrorist industry is also negatively affected by terrorism, which can occur regardless of the duration of the war itself. Terrorist attacks are deliberately organized in such a way as to evoke images of human victims, which affects the fear of tourist arrivals to such heavily burdened places. The paper discusses potential scenarios for the continuation of the war and its impact on the operational activity of international business with Russia. Russia’s unprovoked war against Ukraine brings closer the threat of war itself and shock to various industries, including the tourism industry. The paper presents the effects of the war on tourist trips from Russia but also Ukraine and its effects on traditional touristic destinations. Issues of threats to business are raised but also opportunities appearing on the horizon. The visa ban for Russians introduced by the EU with the simultaneous escalating and ruthless Russian attacks on Ukrainian civilians does not inspire optimism. It should be expected that the 2023 tourist season will remain burdened with the stigma of war and the limited movement of Russians around Europe.","PeriodicalId":49649,"journal":{"name":"Quality & Quantity","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135854000","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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