In financial applications, understanding the asset correlation structure is crucial to tasks such as asset pricing, portfolio optimisation, risk management, and asset allocation. Thus, modelling the volatilities and correlations of multivariate stock market returns is of great importance. This paper proposes the iterated filtering algorithm for estimating the bivariate stochastic volatility model of Yu and Meyer. The iterated filtering method is a frequentist-based approach that utilises particle filters and can be applied to estimating the parameters of non-linear or non-Gaussian state-space models. The paper presents an empirical example that demonstrates the way in which the proposed estimation method might be used to estimate the correlation between the returns of two assets: Standard and Poor’s 500 index and the price of gold in US dollars. This is accompanied by a simulation study that proves the validity of the approach.
{"title":"Estimation of Yu and Meyer bivariate stochastic volatility model by iterated filtering","authors":"Piotr Szczepocki","doi":"10.59139/ps.2022.04.1","DOIUrl":"https://doi.org/10.59139/ps.2022.04.1","url":null,"abstract":"In financial applications, understanding the asset correlation structure is crucial to tasks such as asset pricing, portfolio optimisation, risk management, and asset allocation. Thus, modelling the volatilities and correlations of multivariate stock market returns is of great importance. This paper proposes the iterated filtering algorithm for estimating the bivariate stochastic volatility model of Yu and Meyer. The iterated filtering method is a frequentist-based approach that utilises particle filters and can be applied to estimating the parameters of non-linear or non-Gaussian state-space models. The paper presents an empirical example that demonstrates the way in which the proposed estimation method might be used to estimate the correlation between the returns of two assets: Standard and Poor’s 500 index and the price of gold in US dollars. This is accompanied by a simulation study that proves the validity of the approach.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129730031","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}
This article examines the impact of the COVID-19 pandemic on the accuracy of forecasts for three currency pairs before and after its outbreak based on neural networks (ELM, MLP and LSTM) in terms of three factors: the forecast horizon, hyper parameterisation and network type.
{"title":"Comparison of the accuracy of forecasts bsed on neural networks before and after the outbreak of the COVID-19 pandemic on the example of selected exchange rates","authors":"Jakub Morkowski","doi":"10.59139/ps.2022.04.4","DOIUrl":"https://doi.org/10.59139/ps.2022.04.4","url":null,"abstract":"This article examines the impact of the COVID-19 pandemic on the accuracy of forecasts for three currency pairs before and after its outbreak based on neural networks (ELM, MLP and LSTM) in terms of three factors: the forecast horizon, hyper parameterisation and network type.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128565994","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}
The aim of this paper is to present the results of experiments relating to voting methods based on the bounded rationality theory. The research demonstrated that a positive nudge changes the voting results. The study focused on three methods of voting: the Borda Count method, the Condorcet winner method and the anti-manipulation method. In a laboratory experiment, the subjects were asked to select the best musician. They were to manipulate their voting so that a predetermined winner is chosen. In the first voting, the subjects did not receive any a priori information, while in the second voting, some a priori information was provided, i.e. the true, objective ranking of the musicians. What followed was another voting. It was initially assumed that the participants would manipulate their voting the same way as in the first voting. The results, however, were different. The obtained second ranking of musicians was closest to the true, objective ranking, thus proving that the manipulation effect was neutralised by the a priori positive information about the true, objective order.
{"title":"Impact of a priori positive information on the results of voting methods","authors":"H. Sosnowska, M. Ramsza, Paweł Zawiślak","doi":"10.59139/ps.2022.04.3","DOIUrl":"https://doi.org/10.59139/ps.2022.04.3","url":null,"abstract":"The aim of this paper is to present the results of experiments relating to voting methods based on the bounded rationality theory. The research demonstrated that a positive nudge changes the voting results. The study focused on three methods of voting: the Borda Count method, the Condorcet winner method and the anti-manipulation method. In a laboratory experiment, the subjects were asked to select the best musician. They were to manipulate their voting so that a predetermined winner is chosen. In the first voting, the subjects did not receive any a priori information, while in the second voting, some a priori information was provided, i.e. the true, objective ranking of the musicians. What followed was another voting. It was initially assumed that the participants would manipulate their voting the same way as in the first voting. The results, however, were different. The obtained second ranking of musicians was closest to the true, objective ranking, thus proving that the manipulation effect was neutralised by the a priori positive information about the true, objective order.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115128891","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}
Sample size estimation is a necessary and crucial step in clinical trial research. Statistical requirements, limited patient availability and high financial risk of a clinical trial necessitate the proper calculation of this measure. The aim of this paper is to discuss the reasons why the estimation of the sample size is important and, based on the obtained results, to show how this process may be completed in selected cases. Stochastic simulations based on the Monte Carlo methods approach are applied. Therefore, new challenges facing this area of research are mentioned.
{"title":"Sample size in clinical trials – challenges and approaches","authors":"A. Tomski, Barbara Gorzawska","doi":"10.59139/ps.2022.04.2","DOIUrl":"https://doi.org/10.59139/ps.2022.04.2","url":null,"abstract":"Sample size estimation is a necessary and crucial step in clinical trial research. Statistical requirements, limited patient availability and high financial risk of a clinical trial necessitate the proper calculation of this measure. The aim of this paper is to discuss the reasons why the estimation of the sample size is important and, based on the obtained results, to show how this process may be completed in selected cases. Stochastic simulations based on the Monte Carlo methods approach are applied. Therefore, new challenges facing this area of research are mentioned.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131558011","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 : 2023-02-01DOI: 10.5604/01.3001.0016.2377
Karolina Siemaszkiewicz
The coronavirus pandemic, like the Russian aggression on Ukraine, had a significant impact on many financial markets and asset prices. The latter additionally led to large fluctuations on financial markets. In this paper, we try to compare the performance of safe haven assets during turbulent times, such as the recent global financial crises, eurozone debt crises, the COVID-19 pandemic and the Russian aggression on Ukraine. We investigate the dynamic relationship between indices from the European countries like the Czech Republic, France, Germany, Great Britain, Poland, Slovakia, Spain, and popular instruments such as gold, silver, Brent Crude Oil, Crude Oil WTI, US Dollar, Swiss Franc, and Bitcoin. The study estimated the parameters of either DCC or CCC models, to compare the dynamic relation between the above-mentioned stock markets and financial instruments. The results showed that in most cases, the US Dollar and Swiss Franc were able to protect investors from stock market losses during turbulent times. In those periods, gold was the closest to being a safe haven instrument for investors from France, Poland, the Czech Republic and Slovakia. Our findings are in line with other literature which points out that safe haven instruments can change over time and across countries. In that literature, we can find research performed for the USA, China, Canada, and Great Britain, but there is no such research for Poland, Italy, the Czech Republic or Slovakia. The purpose of this paper is therefore to try to fill this research gap.
{"title":"Alternative investments during turbulent times comparison of dynamic relationship","authors":"Karolina Siemaszkiewicz","doi":"10.5604/01.3001.0016.2377","DOIUrl":"https://doi.org/10.5604/01.3001.0016.2377","url":null,"abstract":"The coronavirus pandemic, like the Russian aggression on Ukraine, had a significant impact on many financial markets and asset prices. The latter additionally led to large fluctuations on financial markets. In this paper, we try to compare the performance of safe haven assets during turbulent times, such as the recent global financial crises, eurozone debt crises, the COVID-19 pandemic and the Russian aggression on Ukraine. We investigate the dynamic relationship between indices from the European countries like the Czech Republic, France, Germany, Great Britain, Poland, Slovakia, Spain, and popular instruments such as gold, silver, Brent Crude Oil, Crude Oil WTI, US Dollar, Swiss Franc, and Bitcoin. The study estimated the parameters of either DCC or CCC models, to compare the dynamic relation between the above-mentioned stock markets and financial instruments. The results showed that in most cases, the US Dollar and Swiss Franc were able to protect investors from stock market losses during turbulent times. In those periods, gold was the closest to being a safe haven instrument for investors from France, Poland, the Czech Republic and Slovakia. Our findings are in line with other literature which points out that safe haven instruments can change over time and across countries. In that literature, we can find research performed for the USA, China, Canada, and Great Britain, but there is no such research for Poland, Italy, the Czech Republic or Slovakia. The purpose of this paper is therefore to try to fill this research gap.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128379316","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 : 2023-01-31DOI: 10.5604/01.3001.0016.2352
M. Virén
When assessing future growth prospects, does the current structure of demand matter, i.e. does it affect the future growth? This question is analysed in our paper by using global and EU panel data. The result is quite striking: consumption-led growth either in terms of private or public or total consumption is slower than investment-led or exports-led growth. The same qualitative result is obtained irrespectively of the length of the past growth period (lag window), yet the more often the past is characterised by consumption-led growth, the slower the growth rate is in the future. In this context, our research provides important insights from the point of view of both structural and cyclical policies.
{"title":"Consumption-led expansions lead to lower future output growth","authors":"M. Virén","doi":"10.5604/01.3001.0016.2352","DOIUrl":"https://doi.org/10.5604/01.3001.0016.2352","url":null,"abstract":"When assessing future growth prospects, does the current structure of demand matter, i.e. does it affect the future growth? This question is analysed in our paper by using global and EU panel data. The result is quite striking: consumption-led growth either in terms of private or public or total consumption is slower than investment-led or exports-led growth. The same qualitative result is obtained irrespectively of the length of the past growth period (lag window), yet the more often the past is characterised by consumption-led growth, the slower the growth rate is in the future. In this context, our research provides important insights from the point of view of both structural and cyclical policies.","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130576831","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 : 2022-12-01DOI: 10.5604/01.3001.0016.1165
Maciej Fronc, M. Jakubczyk
Data-driven decisions can be suboptimal when the data are distorted by fraudulent behaviour. Fraud is a common occurrence in finance or other related industries, where large datasets are handled and motivation for financial gain may be high. In order to detect and prevent fraud, quantitative methods are used. Fraud, however, is also committed in other circumstances, e.g. during clinical trials. The article aims to verify which analytical fraud-detection methods used in finance may be adopted in the field of clinical trials. We systematically reviewed papers published over the last five years in two databases (Scopus and Web of Science) from the field of economics, finance, management and business in general. We considered the broad scope of data mining techniques including artificial intelligence algorithms. As a result, 37 quantitative methods were identified with the potential of being fit for application in clinical trials. The methods were grouped into three categories: pre-processing techniques, supervised learning and unsupervised learning. Our findings may enhance the future use of fraud-detection methods in clinical trials.
当数据被欺诈行为扭曲时，数据驱动的决策可能是次优的。欺诈在金融或其他相关行业很常见，在这些行业中，处理的数据集很大，获取经济利益的动机可能很高。为了发现和防止欺诈，使用了定量的方法。然而，在其他情况下，例如在临床试验期间，也存在欺诈行为。本文旨在验证金融学中使用的分析欺诈检测方法可用于临床试验领域。我们系统地回顾了过去五年在两个数据库(Scopus和Web of Science)中发表的论文，这些论文来自经济、金融、管理和商业领域。我们考虑了包括人工智能算法在内的数据挖掘技术的广泛范围。结果，37种定量方法被确定为适合应用于临床试验的潜力。方法分为预处理技术、监督学习和无监督学习三大类。我们的发现可能会在临床试验中加强欺诈检测方法的使用。
{"title":"From business to clinical trials: a systematic review of the literature on fraud detection methods to be used in central statistical monitoring","authors":"Maciej Fronc, M. Jakubczyk","doi":"10.5604/01.3001.0016.1165","DOIUrl":"https://doi.org/10.5604/01.3001.0016.1165","url":null,"abstract":"Data-driven decisions can be suboptimal when the data are distorted by fraudulent behaviour. Fraud is a common occurrence in finance or other related industries, where large datasets are handled and motivation for financial gain may be high. In order to detect and prevent fraud, quantitative methods are used. Fraud, however, is also committed in other circumstances, e.g. during clinical trials. The article aims to verify which analytical fraud-detection methods used in finance may be adopted in the field of clinical trials. We systematically reviewed papers published over the last five years in two databases (Scopus and Web of Science) from the field of economics, finance, management and business in general. We considered the broad scope of data mining techniques including artificial intelligence algorithms. As a result, 37 quantitative methods were identified with the potential of being fit for application in clinical trials. The methods were grouped into three categories: pre-processing techniques, supervised learning and unsupervised learning. Our findings may enhance the future use of fraud-detection methods in clinical trials.\u0000\u0000","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124512433","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 : 2022-10-31DOI: 10.5604/01.3001.0016.0364
Przemysław Szufel
This paper presents a model for short-term time-horizon production and distribution planning of a manufacturing company located in the middle of a supply chain. The model focuses on an unbalanced market with broken supply chains. This reflects the state of the current post-COVID-19 economy, which is additionally struggling with even more uncertainty and disruptions due to the Russian aggression against Ukraine. The manufacturer, operating on the post-pandemic and post-war market, on the one hand observes a soaring demand for its products, and on the other faces uncertainty regarding the availability of components (parts) used in the manufacturing process. The goal of the company is to maximise profits despite the uncertain availability of intermediate products. In the short term, the company cannot simply raise prices, as it is bound by long-term contracts with its business partners. The company also has to maintain a good relationship with its customers, i.e. businesses further in the supply chain, by proportionally dividing its insufficient production and trying to match production planning with the observed demand. The post-COVID-19 production-planning problem has been addressed with a robust mixed integer optimisation model along with a dedicated heuristic, which makes it possible to find approximate solutions in a large-scale real-world setting.
{"title":"On planning production and distribution with disrupted supply chains","authors":"Przemysław Szufel","doi":"10.5604/01.3001.0016.0364","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0364","url":null,"abstract":"This paper presents a model for short-term time-horizon production and distribution planning of a manufacturing company located in the middle of a supply chain. The model focuses on an unbalanced market with broken supply chains. This reflects the state of the current post-COVID-19 economy, which is additionally struggling with even more uncertainty and disruptions due to the Russian aggression against Ukraine. The manufacturer, operating on the post-pandemic and post-war market, on the one hand observes a soaring demand for its products, and on the other faces uncertainty regarding the availability of components (parts) used in the manufacturing process. The goal of the company is to maximise profits despite the uncertain availability of intermediate products. In the short term, the company cannot simply raise prices, as it is bound by long-term contracts with its business partners. The company also has to maintain a good relationship with its customers, i.e. businesses further in the supply chain, by proportionally dividing its insufficient production and trying to match production planning with the observed demand. The post-COVID-19 production-planning problem has been addressed with a robust mixed integer optimisation model along with a dedicated heuristic, which makes it possible to find approximate solutions in a large-scale real-world setting.\u0000\u0000","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114824709","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 : 2022-10-31DOI: 10.5604/01.3001.0016.0363
Barbara Będowska-Sójka, Agata Kliber
This paper aims to contribute to the existing studies on the Granger-causal relationship between volatility and liquidity in the stock market. We examine whether liquidity improves volatility forecasts and whether volatility allows the improvement of liquidity forecasts. The forecasts based on the mixed-data sampling models, MIDAS, are compared to those obtained from models based on daily data. Our results show that volatility and liquidity forecasts from MIDAS models outperform naive forecasts. On the other hand, the application of mixed-data sampling models does not significantly improve the performance of the forecasts of either liquidity or volatility based on a univariate autoregressive model or a vectorautoregressive one. We found that in terms of the forecasting ability, the VAR models and the AR models seem to perform equally well, as the differences in forecasting errors generated by these two types of models are not statistically significant.
{"title":"Do mixed-data sampling models help forecast liquidity and volatility?","authors":"Barbara Będowska-Sójka, Agata Kliber","doi":"10.5604/01.3001.0016.0363","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0363","url":null,"abstract":"This paper aims to contribute to the existing studies on the Granger-causal relationship between volatility and liquidity in the stock market. We examine whether liquidity improves volatility forecasts and whether volatility allows the improvement of liquidity forecasts. The forecasts based on the mixed-data sampling models, MIDAS, are compared to those obtained from models based on daily data. Our results show that volatility and liquidity forecasts from MIDAS models outperform naive forecasts. On the other hand, the application of mixed-data sampling models does not significantly improve the performance of the forecasts of either liquidity or volatility based on a univariate autoregressive model or a vectorautoregressive one. We found that in terms of the forecasting ability, the VAR models and the AR models seem to perform equally well, as the differences in forecasting errors generated by these two types of models are not statistically significant.\u0000\u0000","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124738187","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 : 2022-06-30DOI: 10.5604/01.3001.0015.8791
Jakub Pacholec
The REIT (Real Estate Investment Trust) returns demonstrate a time-varying linear correlation with various equity indexes, therefore they are fit for multi-asset portfolio enhancement. On the one hand, each REIT sector is characterised by a unique set of return properties, and on the other, companies within those sectors remain homogenous. The aim of this research is twofold: firstly, to verify the earlier studies on how adding REITs to mixed equities/bonds portfolios affects their risk and return characteristics, and secondly, to contribute to these studies by examining the impact of adding different REIT sectors to such portfolios over a relatively long and more up-to-date sample, i.e. the period of 1990–2019. The results indicate that, in contrast to what some previous studies suggested, adding the REIT index exposure leads to a limited portfolio enhancement only. More significant and consistent effects can be achieved by the inclusion of individual REIT sectors in an investment portfolio. Apartment REITs offered diversification benefits across the entire spectrum in all the periods, while Industrials were useful across the curve in 1990s and 2010s. Self-storage exposure, on the other hand, improved the investment portfolio performance in each of the studied decades. In general, it was enough for investors who strived for portfolio improvement over the three decades between 1990 and 2019 to have a small portion of their Value holdings replaced with the REIT sector exposure to obtain a positive impact on both the returns and the risk.
{"title":"REITs impact on typical investment portfolio – further evidence of the sector split importance","authors":"Jakub Pacholec","doi":"10.5604/01.3001.0015.8791","DOIUrl":"https://doi.org/10.5604/01.3001.0015.8791","url":null,"abstract":"The REIT (Real Estate Investment Trust) returns demonstrate a time-varying linear correlation with various equity indexes, therefore they are fit for multi-asset portfolio enhancement. On the one hand, each REIT sector is characterised by a unique set of return properties, and on the other, companies within those sectors remain homogenous. The aim of this research is twofold: firstly, to verify the earlier studies on how adding REITs to mixed equities/bonds portfolios affects their risk and return characteristics, and secondly, to contribute to these studies by examining the impact of adding different REIT sectors to such portfolios over a relatively long and more up-to-date sample, i.e. the period of 1990–2019. The results indicate that, in contrast to what some previous studies suggested, adding the REIT index exposure leads to a limited portfolio enhancement only. More significant and consistent effects can be achieved by the inclusion of individual REIT sectors in an investment portfolio. Apartment REITs offered diversification benefits across the entire spectrum in all the periods, while Industrials were useful across the curve in 1990s and 2010s. Self-storage exposure, on the other hand, improved the investment portfolio performance in each of the studied decades. In general, it was enough for investors who strived for portfolio improvement over the three decades between 1990 and 2019 to have a small portion of their Value holdings replaced with the REIT sector exposure to obtain a positive impact on both the returns and the risk.\u0000\u0000","PeriodicalId":357447,"journal":{"name":"Przegląd Statystyczny","volume":"7 20","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120854999","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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