<p>The main idea of our work is the calibration parameters for the Heston stochastic volatility model. We make this procedure by using the OMXS30 index from the NASDAQ OMX Nordic Exchange Market. We separate our data into the stable period and high-volatility period on this Nordic Market. Deviation detection problem are solved using the Bayesian analysis of change-points. We estimate parameters of the Heston model for each of periods and make some conclusions.</p>

The main idea of our work is the calibration parameters for the Heston stochastic volatility model. We make this procedure by using the OMXS30 index from the NASDAQ OMX Nordic Exchange Market. We separate our data into the stable period and high-volatility period on this Nordic Market. Deviation detection problem are solved using the Bayesian analysis of change-points. We estimate parameters of the Heston model for each of periods and make some conclusions.

Reliable evaluation methods is needed to ensure that investments in energy conservation measures (ECMs) and the construction of new energy efficient buildings lives up to the promised and expected performance. This thesis presents and evaluates a regression method for estimation of influential building parameters: transmission losses above ground (including air leakage), ground heat loss, and overall heat loss coefficient. The analysis is conducted with separately metered electricity, heating and weather data using linear regression models based on the simplified steady-state power balance for a whole building. The evaluation consists of analyzing the robustness of the extracted parameters, their suitability to be used as input values to building energy simulations (BES) tools. In addition, differences between uncalibrated and calibrated BES models are analyzed when they are used to calculate energy savings. Finally the suitability of using a buildings overall heat loss coefficient as a performance verification tool is studied. The presented regression method exhibits high robustness and good agreement with theory. Knowledge of these parameters also proved beneficial in BES calibration procedures as well as in performance verifications. Thus, the presented method shows promising features for reliable energy performance assessments of buildings.