Search for dissertations about: "Pär Stockhammar"

Found 3 swedish dissertations containing the words Pär Stockhammar.

  2. 1. Some Contributions to Filtering, Modeling and Forecasting of Heteroscedastic Time Series

    Author : Pär Stockhammar; Lars-Erik Öller; Daniel Thorburn; Agustin Maravall; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Heteroscedasticity; variance stabilizing filters; the mixed Normal - Asymmetric Laplace distribution; density forecasting; detrending filters; spectral analysis; the connection between financial data and economic growth; Statistics; Statistik; Statistics; statistik;

    Abstract : Heteroscedasticity (or time-dependent volatility) in economic and financial time series has been recognized for decades. Still, heteroscedasticity is surprisingly often neglected by practitioners and researchers. This may lead to inefficient procedures. READ MORE

  4. 2. Some Contributions to Heteroscedastic Time Series Analysis and Computational Aspects of Bayesian VARs

    Author : Oskar Gustafsson; Pär Stockhammar; Domenico Giannone; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Time series; heteroscedasticity; variance stabilizing filters; Bayesian vector autoregressions; Bayesian optimization; variational inference; Statistics; statistik;

    Abstract : Time-dependent volatility clustering (or heteroscedasticity) in macroeconomic and financial time series has been analyzed for more than half a century. The inefficiencies it causes in various inference procedures are well known and understood. Despite this, heteroscedasticity is surprisingly often neglected in practical work. READ MORE

  5. 3. Variational Inference of Dynamic Factor Models

    Author : Erik Spånberg; Pär Stockhammar; Gebrenegus Ghilagaber; Sune Karlsson; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; dynamic factor models; variational inference; missing data; nowcasting; expectation maximization; statistik; Statistics;

    Abstract : When we make difficult and crucial decisions, forecasts are powerful and important tools. For that purpose, statistical models can be our most effective aid. Ideally, these models can incorporate large sets of multifaceted data. READ MORE