Sökning: "Exponentially weighted moving average EWMA"

Visar resultat 1 - 5 av 9 uppsatser innehållade orden Exponentially weighted moving average EWMA.

1. 1. Volatility forecasting using the GARCH framework on the OMXS30 and MIB30 stock indices

   Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

   Författare :Peter Johansson; [2019-01-22]
   Nyckelord :Volatility forecasting; Random Walk; Moving Average; Exponentially Weighted Moving Average; GARCH; EGARCH; GJR-GARCH; APGARCH; volatility model valuation; regression; information criterion;

   Sammanfattning : There are many models on the market that claim to predict changes in financial assets as stocks on the Stockholm stock exchange (OMXS30) and the Milano stock exchange index (MIB30). Which of these models gives the best forecasts for further risk management purposes for the period 31st of October 2003 to 30th of December 2008? Is the GARCH framework more successful in forecasting volatility than more simple models as the Random Walk, Moving Average or the Exponentially Weighted Moving Average? The purpose of this study is to find and investigate different volatility forecasting models and especially GARCH models that have been developed during the years. LÄS MER

3. 2. Implementation of Anomaly Detection on a Time-series Temperature Data set

   Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Jelena Novacic; Kablai Tokhi; [2019]
   Nyckelord :machine learning; anomaly detection; linear regression; exponentially weighted moving average; EWMA; probabilistic exponentially weighted moving average; PEWMA; time-series data set;

   Sammanfattning : Aldrig har det varit lika aktuellt med hållbar teknologi som idag. Behovet av bättre miljöpåverkan inom alla områden har snabbt ökat och energikonsumtionen är ett av dem. En enkel lösning för automatisk kontroll av energikonsumtionen i smarta hem är genom mjukvara. LÄS MER

4. 3. Volatility and variance swaps : A comparison of quantitative models to calculate the fair volatility and variance strike

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Johan Röring; [2017]
   Nyckelord :;

   Sammanfattning : Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. LÄS MER

5. 4. An empirical study of the Value-at-Risk of the renewable energy market and the impact of the oil price

   Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen

   Författare :Euan Anderson; [2015]
   Nyckelord :Two-sided Kupiec test; Student-t distribution; Normal distribution; Threshold GARCH TGARCH ; Oil; Generalized Autoregressive Heteroskedasticity GARCH ; Exponentially weighted moving average EWMA ; Volatility weighted historical simulation VWHS ; Basic historical simulation BHS ; rolling-window; Value-at-Risk VaR ; Renewable energy; Business and Economics;

   Sammanfattning : Renewable energy is gaining increasing importance in the generation of power due to the finite existence of fossil fuels and concerns about climate change. As its demand grows financial interest from investors’ increases, thus it is important to find the most effective way of quantifying the risk of the renewable energy market. LÄS MER

7. 5. Volatility Forecasting In the Nordic Stock Market

   Kandidat-uppsats, Lunds universitet/Nationalekonomiska institutionen

   Författare :Niklas Hummel; [2015]
   Nyckelord :GARCH; volatility; forecasting; Business and Economics;

   Sammanfattning : This paper studies volatility prediction on OMX Stockholm 30, OMX Helsinki 25 and OMX Nordic 40. The models used are a historical variance model, an exponentially weighted moving average model and three models from the GARCH family. These are GARCH(1,1), EGARCH(1,1) and GJR(1,1), with normal and t-distribution respectively. LÄS MER