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  • 1.
    Ahnesjö, Jonas
    et al.
    Linnaeus University, Faculty of Social Sciences, Department of Sport Science.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Bergman, Patrick
    Linnaeus University, Faculty of Social Sciences, Department of Sport Science.
    Benefits of outdoor exercise and recovery outdoors in elderly2019In: HEPA Europe, Odense, Denmark, August 28-30, 2019: abstract book, 2019, p. 38-38Conference paper (Refereed)
    Abstract [en]

    Purpose: The purpose of this study was to test the hypothesis that the ”outdoors” has an added health effect on top of that of physical activity. This hypothesis is based on the fairly extensive volume of evidens suggesting that the outdoor environment is beneficial for overall health. We, however, consider most previous studies insufficiently designed in order to draw causal relationship between spending time outdoors and examined health parameters. In this study we state that our experimental design allows us to do just that. 

    Methods:

    In this randomized cross-over experimental design, 49 healthy subjects (+65 years, 27 female) performed a standardized submaximal bike ergometer test in three different environments (indoors, simulated outdoors and outdoors). The test consisted of 20 minutes cycling and subjects were instructed to stay between 11-13 at the Borg RPE scale (i.e. moderate intensity). Each test was followed by two hours of passive recovery. We measured power output, heart rate, lactate and counts of five fractions (lymphocytes, monocytes, neutrophiles, basophiles and eosinophiles) of white blood cells (leukocytes) in circulation.

    Results:

    Our results revealed that the outdoor treatment resulted in higher levels of lactate, higher heart rate and higher power output despite that there were no differences in Borg RPE-rating between the treatments. The white blood cell analysis showed an increase of circulating leukocytes in almost all fractions immediately post exercise in all treatments. Numbers decreased rapidly post exercise and the lymphocyte numbers stayed well under baseline for more than one hour during recovery. This is referred to as an “open window” where the immune function is temporarily suppressed and there is an elevated risk of infection of primarily URTI.

    Conclusions:

    Our results not only suggest that exercise is more efficient out of doors such that more exercise/effort is obtained but also that recovery outdoors may be a way to decrease the risk of infections due to exercise induced immune suppression. The risk of getting an infection is known to be generally lower out of doors. Taken together, our results support the notion that exercising and spending time outdoors indeed is beneficial for health in senior citizens.

  • 2.
    Dai, Deliang
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Holgersson, Thomas
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Expected and unexpected values of Individual Mahalanobis Distances2017In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, no 18, p. 8999-9006Article in journal (Refereed)
    Abstract [en]

    This paper derives first-order sampling moments of individual Mahalanobis distances (MD) in cases when the dimension p of the variable is proportional to the sample size n. Asymptotic expected values when n, p → ∞ are derived under the assumption p/n → c, 0 ⩽ c < 1. It is shown that some types of standard estimators remain unbiased in this case, while others are asymptotically biased, a property that appears to be unnoticed in the literature. Second order moments are also supplied to give some additional insight to the matter.

  • 3.
    Holgersson, Thomas
    et al.
    Högskolan i Jönköping.
    Karlsson, Peter S.
    Högskolan i Jönköping.
    An Investigation and Development of Three Estimators of Inverse Covariance Matrices With Applications to the Mahalanobis Distance2010Report (Other academic)
    Abstract [en]

    This paper treats the problem of estimating the inverse covariance matrix in an   increasing   dimension   context.   Specifically,   three   ridge-type   estimators   are considered,  of  which  two  new  are  proposed  by  the  authors  and  one  has  been considered previously. Risk functions for deciding an appropriate value of the ridge coefficient  are  developed  and  the  finite  sample  properties  of  the  estimators  are investigated   in   a   Monte   Carlo   simulation.   Moreover,   risk   functions   for   the Mahalanobis distance are derived which, in turn, leads to three new estimators which has not been considered previously.

  • 4. Holgersson, Thomas
    et al.
    Karlsson, Peter S.
    Jönköping International Business School, Sweden.
    Model Based vs. Model Independent Tests for Cross-correlation2010In: Journal of Modern Applied Statistical Methods, ISSN 1538-9472, Vol. 9, no 1, p. 75-89Article in journal (Refereed)
    Abstract [en]

    This article discusses the issue of whether cross correlation should be tested by model dependent or model independent methods. Several different tests are proposed and their main properties are investigated analytically and with simulations. It is argued that model independent tests should be used in applied work.

  • 5.
    Holgersson, Thomas
    et al.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Karlsson, Peter S.
    Linnaeus University, Faculty of Business, Economics and Design, Linnaeus School of Business and Economics.
    Three estimators of the Mahalanobis distance in high-dimensional data2012In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 12, p. 2713-2720Article in journal (Refereed)
    Abstract [en]

    This paper treats the problem of estimating the Mahalanobis distance for the purpose of detecting outliers in high-dimensional data. Three ridge-type estimators are proposed and risk functions for deciding an appropriate value of the ridge coefficient are developed. It is argued that one of the ridge estimator has particularly tractable properties, which is demonstrated through outlier analysis of real and simulated data.

  • 6.
    Holgersson, Thomas
    et al.
    Jönköping University.
    Karlsson, Peter S.
    Jönköping University.
    Mansoor, Rashid
    Jönköping University.
    Estimating mean-standard deviation ratios of financial data2012In: Journal of Applied Statistics, ISSN 0266-4763, E-ISSN 1360-0532, Vol. 39, no 3, p. 657-671Article in journal (Refereed)
    Abstract [en]

    This article treats the problem of linking the relation between excess return and risk of financial assets when the returns follow a factor structure. The authors propose three different estimators and their consistencies are established in cases when the number of assets in the cross-section (n) and the number of observations over time (T) are of comparable size. An empirical investigation is conducted on the Stockholm stock exchange market where the mean-standard deviation ratio is calculated for small- mid- and large cap segments, respectively.

  • 7.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Stephan, Andreas
    Linnaeus University, School of Business and Economics, Department of Management Accounting and Logistics.
    A risk perspective of estimating portfolio weights of the Global Minimum Variance portfolio2016In: Presented at Statistischen Woche 2016, Augsburg, Germany, September 13-16, 2016, 2016Conference paper (Other academic)
    Abstract [en]

    The problem of how to maximize the return on a given portfolio of assets within the theory of Markowitz has been given considerable attention in the literature and improvements of standard methods continues to progress. Recent developments, often based on Stein estimators or other regularized estimators, usually focus on settings when the numbers of assets (say p) is close to the number of observations (n) since this is the scenario met in most real applications. Before any specific method is applied investors would want to know the basic properties and the relative performance of them. The performance of any estimation method, however, depends on which quality criterea of judgement is being used. Proposed methods may be optimal with respect to precision of the parameters involved in the portfolio procedure, on the proximity between estimated vs true global minimum variance portfolio (GMVP) weights, on the out-of-sample performance etc. Moreover, regularized estimators are often associated with very complicated or even unknown sampling distributions, which in turn complicate statistical inference drastically. The extent to which a method allows for statistical inference therefore also becomes an important matter when judging the properties of a data driven GMVP estimator. In this paper we give an in-depth discussion of risk critereas and their impact on GMVP optimization. A Monte Carlo simulation investigating the properties of some common estimators, including a new one proposed by the authors, with respect to several quality critereas is included to compare and contrast recent proposals. An empirical study is also included using Stockholm stock exchange data. 

  • 8.
    Holgersson, Thomas
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Stephan, Andreas
    Jönköping University, Sweden.
    A risk perspective of estimating portfolio weights of the global minimum-variance portfolio2019In: AStA Advances in Statistical Analysis, ISSN 1863-8171, E-ISSN 1863-818X, p. 1-22Article in journal (Refereed)
    Abstract [en]

    The problem of how to determine portfolio weights so that the variance of portfolio returns is minimized has been given considerable attention in the literature, and several methods have been proposed. Some properties of these estimators, however, remain unknown, and many of their relative strengths and weaknesses are therefore difficult to assess for users. This paper contributes to the field by comparing and contrasting the risk functions used to derive efficient portfolio weight estimators. It is argued that risk functions commonly used to derive and evaluate estimators may be inadequate and that alternative quality criteria should be considered instead. The theoretical discussions are supported by a Monte Carlo simulation and two empirical applications where particular focus is set on cases where the number of assets (p) is close to the number of observations (n).

  • 9.
    Karlsson, Hyunjoo Kim
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Karlsson, Peter S.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
    Månsson, Kristofer
    Jönköping University.
    Sjölander, Pär
    Jönköping University.
    Wavelet quantile analysis of asymmetric pricing on the Swedish power market2017In: Empirica, ISSN 0340-8744, E-ISSN 1573-6911, Vol. 44, no 2, p. 249-260Article in journal (Refereed)
    Abstract [en]

    In this article we investigate if the Swedish consumer prices for electricity are adjusted equally fast regardless of whether the NordPool power market prices are decreased or increased. Due to relatively moderate variations in the variables, we have applied quantile regression, since it is mainly the large changes (above the median) that essentially tend to have a considerable effect on the consumer prices. Moreover, in order to adjust for stochastic- and deterministic trends, autocorrelation, structural breaks as well as to measure APT effects in the short- and in the medium-run, we apply a wavelet decomposition approach. Our results show evidence that significantly positive asymmetric price transmission (APT) effects exist in this market. More specifically, in the short-run (based on the wavelet decomposition D1 for 1–2 months cycles), we find that that there is a higher propensity to rapidly and systematically increase the consumer prices subsequently to an increase in the NordPool market price, compared with the propensity to decrease their customers prices subsequently to a corresponding drop in the NordPool market prices. However, no significant APT effects were detected in the medium- or in the long-run (i.e. the asymmetric price transmission effects are observed only in the short-run). In summary, we could isolate significant APT effects in the short-run (1–2 months decomposition cycles), and for large changes in the dependent variable (percentiles = 0.9). Therefore, only large changes in the NordPool prices lead to feedback effects in the form of asymmetric price transmission effects. Our evidence supports the notion of firms’ downward stickiness of retail prices for maximizing profit, which are not expected to be found on a fully efficient market. Although our finding shows that the price inefficiency is short-lived, these large temporal inefficiencies are still costly for the consumers. It should be noted that blunt traditional powerless methods do not detect these APT effects, while our wavelet quantile methods are powerful and make a significant contribution in the literature by providing new empirical evidence.

  • 10.
    Karlsson, Peter S.
    Jönköping University.
    The Incompleteness Problem of the APT Model2011In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 38, no 2, p. 129-151Article in journal (Refereed)
    Abstract [en]

    The Arbitrage Pricing Theory provides a theory to quantify risk and thereward for taking it. While the theory itself is sound from most perspectives, its empirical version is connected with several shortcomings. One extremely delicate problemarises because the set of observable asset returns rarely has a history of complete observations. Traditionally, this problem has been solved by simply excluding assets withouta complete set of observations from the analysis. Unfortunately, such a methodologymay be shown to (i) lead for any fixed time period to selection bias in that only thelargest companies will remain and (ii) lead to an asymptotically empty set containingno observations at all. This paper discusses some possible solutions to this problemand also provides a case study containing Swedish OMX data for demonstration.

  • 11.
    Karlsson, Peter S.
    et al.
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Behrenz, Lars
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics.
    Shukur, Ghazi
    Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University, Sweden.
    Performances of model selection criteria when variables are ill conditioned2019In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 54, no 1, p. 77-98Article in journal (Refereed)
    Abstract [en]

    Model selection criteria are often used to find a "proper" model for the data under investigation when building models in cases in which the dependent or explained variables are assumed to be functions of several independent or explanatory variables. For this purpose, researchers have suggested using a large number of such criteria. These criteria have been shown to act differently, under the same or different conditions, when trying to select the "correct" number of explanatory variables to be included in a given model; this, unfortunately, leads to severe problems and confusion for researchers. In this paper, using Monte Carlo methods, we investigate the properties of four of the most common criteria under a number of realistic situations. These criteria are the adjusted coefficient of determination (R2-adj), Akaike's information criterion (AIC), the Hannan–Quinn information criterion (HQC) and the Bayesian information criterion (BIC). The results from this investigation indicate that the HQC outperforms the BIC, the AIC and the R2-adj under specific circumstances. None of them perform satisfactorily, however, when the degree of multicollinearity is high, the sample sizes are small or when the fit of the model is poor (i.e., there is a low R2) . In the presence of all these factors, the criteria perform very badly and are not very useful. In these cases, the criteria are often not able to select the true model.

1 - 11 of 11
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