Sökning: "Conditional Forecasting"

Visar resultat 1 - 5 av 47 uppsatser innehållade orden Conditional Forecasting.

1. 1. Volatility Forecasting - A comparative study of different forecasting models.

   Kandidat-uppsats,

   Författare :Emil Sturesson; Anton Wennström; [2023-06-29]
   Nyckelord :Volatility; GARCH; EGARCH; t-GAS; HAR-RV; Realized GARCH; Volatility Forecasting; Volatility Modelling;

   Sammanfattning : This study evaluates the out-of-sample forecasting performance of different volatility mod- els. When applied to XACT OMXS30, we use GARCH(1,1), EGARCH(1,1), and t- GAS(1,1) to forecast squared daily returns while Realized GARCH(1,1) and HAR-RV are used to forecast Realized Variance. LÄS MER

3. 2. Forecasting Value-at-Risk and Expected Shortfall: A comparison of non- and parametric methods for crude oil amidst extreme volatility

   Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen

   Författare :Otto Colbin; Yugam Sharma; [2023]
   Nyckelord :Value-at-Risk VaR ; Expected Shortfall ES ; Nonparametric estimation methods; Parametric estimation methods; Crude oil.; Business and Economics;

   Sammanfattning : Practitioners primarily utilise nonparametric methods when estimating Value-at- Risk (VaR) and Expected Shortfall (ES) for computing capital requirements. However, various researchers assert that there are issues with those estimates, particularly amidst periods of market turmoil. LÄS MER

4. 3. Highway Traffic Forecasting with the Diffusion Model : An Image-Generation Based Approach

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Pengnan Chi; [2023]
   Nyckelord :Diffusion model; Traffic forecasting; Generative model; Image processing; Spatial temporal modelling; Diffusionsmodell; Trafikprognos; Generativ modell; Bildbehandling; Rumsligtemporal modellering;

   Sammanfattning : Forecasting of highway traffic is a common practice for real traffic information system, and is of vital importance to traffic management and control on highways. As a typical time-series forecasting task, we want to propose a deep learning model to map the historical sensory traffic values (e.g., speed, flow) to future traffic forecasts. LÄS MER

5. 4. Volatility & The Black Swan : Investigation of Univariate ARCH-models, HARRV and Implied Volatility in Nasdaq100 amid Covid19

   Master-uppsats, Uppsala universitet/Nationalekonomiska institutionen

   Författare :Karl Tingstedt; [2022]
   Nyckelord :SV; ARCH; GARCH; TARCH; EGARCH; HARRV; IV; RV; Integrated Volatility; TINA;

   Sammanfattning : Covid19 hit the world’s financial markets by surprise in March 2020 and ensuing volatility marked an end to the prior low-volatility environment. This Black Swan engendered numerous publications establishing how the equity market responded to the exogenous shock. LÄS MER

7. 5. A Comparison of Statistical Methods to Generate Short-Term Probabilistic Forecasts for Wind Power Production Purposes in Iceland

   Master-uppsats, Uppsala universitet/Luft-, vatten- och landskapslära

   Författare :Arnór Tumi Jóhannsson; [2022]
   Nyckelord :Wind power; Iceland; Atmospheric Boundary Layer; atmospheric stability; probabilistic forecasting; Machine Learning; Quantile Regression Forest; Vindkraft; Island; gränsskikt; atmosfärisk stabilitet; probabilistisk prognos; Machine Learning; Quantile Regression Forest;

   Sammanfattning : Accurate forecasts of wind speed and power production are of great value for wind power producers. In Southwest Iceland, wind power installations are being planned by various entities. LÄS MER