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Brännäs, Kurt
Publications (10 of 49) Show all publications
Brännäs, K. (2014). Adaptations of Conventional Spatial Econometric Models to Count Data.
Open this publication in new window or tab >>Adaptations of Conventional Spatial Econometric Models to Count Data
2014 (English)Report (Other academic)
Abstract [en]

The paper suggests and studies count data models corresponding to previously studied spatial econometric models for continuous variables. A novel way of incorporating spatial weights is considered for both time and space dynamic models with or without simultaneity. The paper also contains a brief discussion about estimation issues

Publisher
p. 19
Series
Umeå economic studies, ISSN 0348-1018 ; 883
Keywords
Integer-valued, Space, Time, Regional, Thinning, Estimation
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-99678 (URN)
Available from: 2015-02-11 Created: 2015-02-11 Last updated: 2018-06-07Bibliographically approved
Brännäs, K. (2014). The number of shareholders: time series modelling and some empirical results. In: Johan Knif, Bernd Pape (Ed.), Contributions to mathematics, statistics, econometrics, and finance: essays in honour of Professor Seppo Pynnönen (pp. 195-205). Vasa: Vaasan Yliopisto
Open this publication in new window or tab >>The number of shareholders: time series modelling and some empirical results
2014 (English)In: Contributions to mathematics, statistics, econometrics, and finance: essays in honour of Professor Seppo Pynnönen / [ed] Johan Knif, Bernd Pape, Vasa: Vaasan Yliopisto , 2014, p. 195-205Chapter in book (Refereed)
Place, publisher, year, edition, pages
Vasa: Vaasan Yliopisto, 2014
Series
Acta Wasaensia, ISSN 0355-2667 ; 296
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-99679 (URN)978–952–476–522–0 (ISBN)978–952–476–523–7 (ISBN)
Available from: 2015-02-11 Created: 2015-02-11 Last updated: 2018-06-07Bibliographically approved
Brännäs, K. (2013). Simultaneity in the Multivariate Count Data Autoregressive Model. Umeå: Umeå universitet
Open this publication in new window or tab >>Simultaneity in the Multivariate Count Data Autoregressive Model
2013 (English)Report (Other academic)
Abstract [en]

This short paper proposes a simultaneous equations model formulation for time seriesof count data. Some of the basic moment properties of the model are obtained.The inclusion of real valued exogenous variables is suggested to be through the parametersof the model. Some remarks on the application of the model to spatial dataare made. Instrumental variable and generalized method of moments estimators ofthe structural form parameters are also discussed.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2013. p. 13
Series
Umeå economic studies, ISSN 0348-1018 ; 870
Keywords
Integer-valued, Spatial, INAR, Interdependence, Properties, Estimation
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-99680 (URN)
Available from: 2015-02-11 Created: 2015-02-11 Last updated: 2018-06-07Bibliographically approved
Brännäs, K. (2013). The number of Shareholders: Time series modelling and some empirical results. Umeå: Umeå universitet
Open this publication in new window or tab >>The number of Shareholders: Time series modelling and some empirical results
2013 (English)Report (Other academic)
Abstract [en]

The paper discusses some model related issues for time series of the number of shareholders in a stock. The point of departure is an integer-valued autoregressive model of order one. Empirical results are presented for some frequently traded stocks on the Finnish and Swedish stock markets. In these stock markets public records of the number of owners are reported monthly (Finland) and quarterly (Sweden, and initially at biannual) intervals. The aggregate records are useful for, e.g., indirectly estimating average holding times, which are found to vary but to mostly exceed one year.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2013. p. 11
Series
Umeå economic studies, ISSN 0348-1018 ; 855
Keywords
integer-valued, autoregression, nonlinear, holding time, stock, share
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-65601 (URN)
Projects
-
Available from: 2013-02-08 Created: 2013-02-08 Last updated: 2018-06-08Bibliographically approved
Brännäs, K., De Gooijer, J., Lönnbark, C. & Soultanaeva, A. (2012). Simultaneity and asymmetry of returns and volatilities: the emerging Baltic States' stock exchanges. Studies in Nonlinear Dynamics and Econometrics, 16(1)
Open this publication in new window or tab >>Simultaneity and asymmetry of returns and volatilities: the emerging Baltic States' stock exchanges
2012 (English)In: Studies in Nonlinear Dynamics and Econometrics, ISSN 1081-1826, E-ISSN 1558-3708, Vol. 16, no 1, p. 22Article in journal (Refereed) Published
Abstract [en]

The paper suggests a nonlinear and multivariate time series model framework that enables the study of simultaneity in returns and in volatilities, as well as asymmetric effects arising from shocks. Using daily data 2000-2006 for the Baltic state stock exchanges and that of Moscow we find recursive structures with Riga directly depending in returns on Tallinn and Vilnius, and Tallinn on Vilnius. For volatilities both Riga and Vilnius depend on Tallinn. In addition,we find evidence of asymmetric effects of shocks arising in Moscow and in the Baltic state on both returns and volatilities.

Place, publisher, year, edition, pages
Walter de Gruyter, 2012. p. 22
Keywords
Time series, nonlinear, multivariate, finance, value at risk, portfolio allocation
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-22196 (URN)10.1515/1558-3708.1855 (DOI)
Distributor:
Institutionen för nationalekonomi, 90187, Umeå
Available from: 2009-04-28 Created: 2009-04-27 Last updated: 2018-06-08Bibliographically approved
Brännäs, K. (2012). The asymmetric count data moving average model. Umeå: Umeå universitet
Open this publication in new window or tab >>The asymmetric count data moving average model
2012 (English)Report (Other academic)
Abstract [en]

This note defines the asymmetric count data, first order moving average model and gives some of its basic properties. A brief account of conditional least squares estimation of unknown parameters is also given.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2012. p. 6
Series
Umeå economic studies, ISSN 0348-1018 ; 841
Keywords
moments, dual autoregression invertibility, nonlinear, least squares estimation
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-65602 (URN)
Available from: 2013-02-08 Created: 2013-02-08 Last updated: 2018-06-08Bibliographically approved
Brännäs, K. & Soultanaeva, A. (2011). Influence of news in Moscow and New York on returns and risks on Baltic States' stock markets. Baltic Journal of Economics, 11(1), 109-124
Open this publication in new window or tab >>Influence of news in Moscow and New York on returns and risks on Baltic States' stock markets
2011 (English)In: Baltic Journal of Economics, ISSN 1406-099X, Vol. 11, no 1, p. 109-124Article in journal (Refereed) Published
Abstract [en]

The impact of news from the Moscow and New York stock exchanges on the daily returns and volatilities of the Baltic stock market indices is studied. A nonlinear time series model that accounts for asymmetries in the conditional mean and variance functions is used for the empirical work. News from New York has stronger e¤ects on returns in Tallinn than news from Moscow. High-risk shocks in New York have a stronger impact on volatility in Tallinn, whereas volatility of Vilnius is more in.uenced by high-risk shocks from Moscow. Riga seems not to be a¤ected by news arriving from abroad.

Keywords
Estonia, Latvia, Lithuania, Time series, Estimation, Finance
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-16097 (URN)000294512400006 ()
Available from: 2007-08-17 Created: 2007-08-17 Last updated: 2018-06-09Bibliographically approved
Lönnbark, C., Holmberg, U. & Brännäs, K. (2011). Value at risk for large portfolios. Finance Research Letters, 8(2), 59-68
Open this publication in new window or tab >>Value at risk for large portfolios
2011 (English)In: Finance Research Letters, ISSN 1544-6123, E-ISSN 1544-6131, Vol. 8, no 2, p. 18p. 59-68Article in journal (Refereed) Published
Abstract [en]

We argue that the practise used in the valuation of the portfolio is important for the calculation of the Value at Risk. In particular, when liquidating a large portfolio the seller may not face horizontal demand curves. We propose a partially new approach for incorporating this fact in the Value at Risk and in an empirical illustration we compare it to a competing approach. We find substantial differences.

Place, publisher, year, edition, pages
Elsevier, 2011. p. 18
Keywords
Demand, Supply, Liquidity Risk, Limit Order Book, Bank, Sweden
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-22199 (URN)10.1016/j.frl.2010.10.002 (DOI)
Distributor:
Institutionen för nationalekonomi, 90187, Umeå
Available from: 2009-04-28 Created: 2009-04-27 Last updated: 2018-06-08Bibliographically approved
Brännäs, K. & Quoreshi, A. M. (2010). Integer-valued moving average modelling of the number of transactions in stocks. Applied Financial Economics, 20(18), 1429-1440
Open this publication in new window or tab >>Integer-valued moving average modelling of the number of transactions in stocks
2010 (English)In: Applied Financial Economics, ISSN 0960-3107, E-ISSN 1466-4305, Vol. 20, no 18, p. 1429-1440Article in journal (Refereed) Published
Abstract [en]

The integer-valued moving average model is advanced to model thenumber of transactions in intra-day data of stocks. The conditional mean andvariance properties are discussed and model extensions to includeexplanatory variables are offered. Least squares and generalized method ofmoment estimators are presented. In a small Monte Carlo study a feasibleleast squares estimator comes out as the best choice. Empirically we findsupport for the use of long-lag moving average models in a Swedish stockseries. There is evidence of asymmetric effects of news about prices on thenumber of transactions.

Place, publisher, year, edition, pages
Taylor & Francis, 2010
National Category
Economics
Research subject
Econometrics
Identifiers
urn:nbn:se:umu:diva-36433 (URN)10.1080/09603107.2010.498343 (DOI)
Available from: 2010-09-30 Created: 2010-09-30 Last updated: 2018-06-08Bibliographically approved
Brännäs, K. & Simonsen, O. (2007). Discretized time and conditional duration modelling for stock transaction data. Applied Financial Economics, 17, 647-658
Open this publication in new window or tab >>Discretized time and conditional duration modelling for stock transaction data
2007 (English)In: Applied Financial Economics, ISSN 0960-3107, E-ISSN 1466-4305, Vol. 17, p. 647-658Article in journal (Refereed) Published
Abstract [en]

This article considers conditional duration models in which durations are in continuous time, but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators for intra-day duration models. A few estimators that account for the discreteness are discussed and compared in a Monte Carlo experiment. An EM-algorithm accounting for the discrete data performs better than those that do not. Empirical results are reported for trading durations in Ericsson B at Stockholmsbörsen for a 3-week period of July 2002. The incorporation of level variables for past trading is rejected in favour of change variables. This enables an interpretation in terms of news effects. No evidence of asymmetric responses to news about prices and spreads is found.

Place, publisher, year, edition, pages
Routledge, Taylor & Francis Group, 2007
Keywords
Economics, Macroeconomics
National Category
Economics
Research subject
Econometrics; Econometrics
Identifiers
urn:nbn:se:umu:diva-5233 (URN)10.1080/09603100600690044 (DOI)
Available from: 2006-08-30 Created: 2006-08-30 Last updated: 2018-06-09Bibliographically approved
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