Browsing by Subject "C14"

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  • Vuorenmaa, Tommi A. (2005)
    Bank of Finland Research Discussion Papers 27/2005
    This paper investigates the dependence of average stock market volatility on the timescale or on the time interval used to measure price changes, which dependence is often referred to as the scaling law.Scaling factor, on the other hand, refers to the elasticity of the volatility measure with respect to the timescale.This paper studies, in particular, whether the scaling factor differs from the one in a simple random walk model and whether it has remained stable over time.It also explores possible underlying reasons for the observed behaviour of volatility in terms of heterogeneity of stock market players and periodicity of intraday volatility.The data consist of volatility series of Nokia Oyj at the Helsinki Stock Exchange at five minute frequency over the period from January 4, 1999 to December 30, 2002.The paper uses wavelet methods to decompose stock market volatility at different timescales.Wavelet methods are particularly well motivated in the present context due to their superior ability to describe local properties of times series.The results are, in general, consistent with multiscaling in Finnish stock markets.Furthermore, the scaling factor and the long-memory parameters of the volatility series are not constant over time, nor consistent with a random walk model.Interestingly, the evidence also suggests that, for a significant part, the behaviour of volatility is accounted for by an intraday volatility cycle referred to as the New York effect. Long-memory features emerge more clearly in the data over the period around the burst of the IT bubble and may, consequently, be an indication of irrational exuberance on the part of investors. Key words: long-memory, scaling, stock market, volatility, wavelets JEL classification numbers: C14, C22
  • Funke, Michael; Yu, Hao (2009)
    BOFIT Discussion Papers 10/2009
    In this paper we analyse the impact of R&D on total factor productivity across Chinese provinces. We introduce innovations explicitly into a production function and evaluate their contribution to economic growth in 1993 - 2006. The empirical results highlight the importance and the interaction between local and external research. The evidence indicates that growth in China is not explained simply by factor input accumulation. Keywords: China, R&D, R&D Spillovers, patents, regional economic growth, semiparametric estimators JEL-Classification: C14, O47, R11, R12
  • Jokipii, Terhi (2006)
    Bank of Finland Research Discussion Papers 22/2006
    This paper studies the extent to which market crashes are predictable for a set of six countries, focusing in particular on possible differences between transition economies (The Czech Republic, Hungary and Poland) and mature markets (UK, US and EU). We estimate a set of individual country and pooled specifications to find that market crashes, in the broader sense, are predictable for all countries analysed.We additionally investigate the role that investor heterogeneity, proxied by trading volume, plays in this predictability and find some varying results between countries.For the Central and Eastern European Countries (CE3), an increase in trading volume relative to trend appears to have great predictive power, a result that is supportive of the theory of investor heterogeneity outlined in the relevant background studies. For the more mature markets (G5), on the other hand, market crashes appear more likely to follow a period of increased stock prices and returns, a result fitting a number of traditional theories, in particular the stochastic bubble model.Further analysis, allowing for time-varying coefficients, confirms the volume-crash relationship for the CE3 and provides preliminary evidence that macro news releases may additionally contribute to the predictability of market crashes. Keywords: aggregate market returns, skewness, trading volume, market crash JEL classification numbers: C14, G12, G15
  • Laakkonen, Helinä (2004)
    Suomen Pankin keskustelualoitteita 24/2004
    This study investigates the impact of new information on the volatility of exchange rates.The impact of scheduled US and European macroeconomic news on the volatility of USD/EUR 5-minute returns was tested by using the Flexible Fourier Form method.The results were consistent with earlier studies.Macroeconomic news increased volatility significantly, and news on the United States was the most important.The much-tested hypothesis of bad news having a greater impact on volatility was re-confirmed in this study.The announcements were also divided into two categories, the first containing the news that gave conflicting information on the state of the economy (bad and good news at the same time) and the other containing the news that was consistent (where either good or bad news was announced).Conflicting news was found to increase volatility significantly more than consistent news.The impact of 'no-surprise' news was also tested.Even news the forecast of which was equal to an announcement seemed to increase volatility.Key words: Exchange rates, microstructure theory, volatility, news JEL classification numbers: G14, C14, C12, C22
  • Bask, Mikael; Liu, Tung; Widerberg, Anna (2006)
    Bank of Finland Research Discussion Papers 9/2006
    Published in Physica A, 376, 2007: 565-572
    The aim of this paper is to illustrate how the stability of a stochastic dynamic system is measured using the Lyapunov exponents. Specifically, we use a feedforward neural network to estimate these exponents as well as asymptotic results for this estimator to test for unstable (chaotic) dynamics.The data set used is spot electricity prices from the Nordic power exchange market.Nord Pool, and the dynamic system that generates these prices appears to be chaotic in one case.Key words: feedforward neural network, Nord Pool, Lyapunov exponents, spot electricity prices, stochastic dynamic system JEL classification numbers: C12, C14, C22