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  • 1.
    Brännäs, Kurt
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    De Gooijer, Jan
    Department of Quantitative Economics, University of Amsterdam.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Soultanaeva, Albina
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Simultaneity and asymmetry of returns and volatilities: the emerging Baltic States' stock exchanges2012In: Studies in Nonlinear Dynamics and Econometrics, ISSN 1081-1826, E-ISSN 1558-3708, Vol. 16, no 1, p. 22Article in journal (Refereed)
    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.

  • 2.
    Hellström, Jörgen
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE).
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Identification of jumps in financial price seriesArticle, review/survey (Other academic)
    Abstract [en]

    The paper outlines and tests, by means of Monte-Carlo simulations, a simple strategy of using existing non-parametric tests for jumps at the daily frequency to identify jumps at higher sampling frequencies. The suggested strategy allow for identification of the number of jumps and jump times during a day, as well as, the size and direction (negative or positive) of the jumps. The method is of importance in order to facilitate detailed empirical studies concerning, for example, causes for jumps in financial price series at finer levels than the daily. The Monte Carlo study reveals that the strategy works reasonably well, particular for lower jump intensities. An application of the studied strategy on the Handelsbanken stock is provided.

  • 3.
    Holmberg, Ulf
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Lundström, Christian
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Assessing the profitability of intraday opening range breakout strategies2013In: Finance Research Letters, ISSN 1544-6123, E-ISSN 1544-6131, Vol. 10, no 1, p. 27-33Article in journal (Refereed)
    Abstract [en]

    Is it possible to beat the market by mechanical trading rules based on historical and publicly known information? Such rules have long been used by investors and in this paper, we test the success rate of trades and profitability of the Open Range Breakout (ORB) strategy. An investor that trades on the ORB strategy seeks to identify large intraday price movements and trades only when the price moves beyond some predetermined threshold. We present an ORB strategy based on normally distributed returns to identify such days and find that our ORB trading strategy result in significantly higher returns than zero as well as an increased success rate in relation to a fair game. The characteristics of such an approach over conventional statistical tests is that it involves the joint distribution of low, high, open and close over a given time horizon.

  • 4.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Department of Economics.
    A corrected value-at-risk predictor2010In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 17, no 12, p. 1193-1196Article in journal (Refereed)
    Abstract [en]

    In this note it is argued that the estimation error in Value-at-Risk predictors gives rise to underestimation of portfolio risk. We propose a simple correction and in an empirical illustration we find that it is economically relevant.

  • 5.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Approximation methods for multiple period Value at Risk and Expected Shortfall prediction2016In: Quantitative finance (Print), ISSN 1469-7688, E-ISSN 1469-7696, Vol. 16, no 6, p. 947-968Article in journal (Refereed)
    Abstract [en]

    In this paper, we are interested in predicting multiple period Value at Risk and Expected Shortfall based on the so-called iterating approach. In general, the properties of the conditional distribution of multiple period returns do not follow easily from the one-period data generating process, rendering this a non-trivial task. We outline a framework that forms the basis for setting approximations and study four different approaches. Their performance is evaluated by means of extensive Monte Carlo simulations based on an asymmetric GARCH model, implying conditional skewness and excess kurtosis in the multiple period returns. This simulation-based approach was the best one, closely followed by that of assuming a skewed t-distribution for the multiple period returns. The approach based on a Gram-Charlier expansion was not able to cope with the implied non-normality, while the so-called Root-k approach performed poorly. In addition, we outline how the delta-method may be used to quantify the estimation error in the predictors and in the Monte Carlo study we found that it performed well. In an empirical illustration, we computed 10-day Value at Risk's and Expected Shortfall for Brent Crude Oil, the EUR/USD exchange rate and the S&P 500 index. The Root-k approach clearly performed the worst and the other approaches performed quite similarly, with the simulation based approach and the one based on the skewed t-distribution somewhat better than the one based on the Gram-Charlier expansion.

  • 6.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics. Umeå University.
    Asymmetry with respect to the memory in stock market volatilities2016In: Empirical Economics, ISSN 0377-7332, E-ISSN 1435-8921, Vol. 50, no 4, p. 1409-1419Article in journal (Refereed)
    Abstract [en]

    The empirically most relevant stylized facts when it comes to modeling time-varying financial volatility are the asymmetric response to return shocks and the long memory property. Up till now, these have largely been modeled in isolation. To capture asymmetry also with respect to the memory structure, we introduce a new model and apply it to stock market index data. We find that although the effect on volatility of negative return shocks is higher than for positive ones, the latter are more persistent and relatively quickly dominate negative ones.

  • 7.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    Long vs. short term asymmetry in volatility and the term structure of risk2017In: Finance Research Letters, ISSN 1544-6123, E-ISSN 1544-6131, Vol. 23, p. 202-209Article in journal (Refereed)
    Abstract [en]

    This short paper introduces the distinction between short and long term asymmetric effects in volatilities. With short term asymmetry we refer to the conventional one, i.e. the asymmetric response of current volatility to the most recent return shocks. In addition, we argue that there may be asymmetries with respect to the way the effect of past return shocks propagate over time. We refer to this as long term asymmetry and propose a model that enables the study of the potential occurrence of such a feature. In an empirical application using stock market index data we find evidence of the joint presence of short and long term asymmetric effects and demonstrate important implications for risk predictions. In particular, positive return shocks is ascribed substantial significance for long term risk prediction.

  • 8.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Department of Economics.
    On Risk Prediction2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis comprises four papers concerning risk prediction.

    Paper [I] 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 states

    on both returns and volatilities.

    Paper [II] argues that the estimation error in Value at Risk predictors

    gives rise to underestimation of portfolio risk. A simple correction is

    proposed and in an empirical illustration it is found to be economically

    relevant.

    Paper [III] studies some approximation approaches to computing the

    Value at Risk and the Expected Shortfall for multiple period asset re-

    turns. Based on the result of a simulation experiment we conclude that

    among the approaches studied the one based on assuming a skewed t dis-

    tribution for the multiple period returns and that based on simulations

    were the best. We also found that the uncertainty due to the estimation

    error can be quite accurately estimated employing the delta method. In

    an empirical illustration we computed five day Value at Risk's for the

    S&P 500 index. The approaches performed about equally well.

    Paper [IV] argues that the practise used in the valuation of the port-

    folio is important for the calculation of the Value at Risk. In particular,

    when liquidating a large portfolio the seller may not face horizontal de-

    mandcurves. 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.

  • 9.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Economics.
    On the role of the estimation error in prediction of expected shortfall2013In: Journal of Banking & Finance, ISSN 0378-4266, E-ISSN 1872-6372, Vol. 37, no 3, p. 847-853Article in journal (Refereed)
    Abstract [en]

    In the estimation of risk measures such as Value at Risk and Expected shortfall relatively short estimation windows are typically used rendering the estimation error a possibly non-negligible component. In this paper we build upon previous results for the Value at Risk and discuss how the estimation error comes into play for the Expected Shortfall. We identify two important aspects where it may be of importance. On the one hand there is in the evaluation of predictors of the measure. On the other there is in the interpretation and communication of it. We illustrate magnitudes numerically and emphasize the practical importance of the latter aspect in an empirical application with stock market index data. (C) 2012 Elsevier B.V. All rights reserved.

  • 10.
    Lönnbark, Carl
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Uncertainty of multiple period risk predictors2009Report (Other academic)
  • 11.
    Lönnbark, Carl
    et al.
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Holmberg, Ulf
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Brännäs, Kurt
    Umeå University, Faculty of Social Sciences, Department of Economics.
    Value at risk for large portfolios2011In: Finance Research Letters, ISSN 1544-6123, E-ISSN 1544-6131, Vol. 8, no 2, p. 18p. 59-68Article in journal (Refereed)
    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.

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