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Optimal Length of Rolling Window in Parameter Estimation of Financial Models

Student: Usatova Ekaterina

Supervisor: Mikhail Kamrotov

Faculty: Faculty of World Economy and International Affairs

Educational Programme: World Economy (Bachelor)

Year of Graduation: 2017

The construction of predictive models of the financial market includes the assessment of parameters on a certain window and the construction of trade rules according to the expected behavior of asset prices. Often researchers empirically select the window length for estimating model parameters, but applying an appropriate methodology to estimate window length for particular data can possibly improve the accuracy of model prediction. For the financial market data, different lengths of windows were tested to determine the optimal number of observations that should be included in the forecast model. Also, the MACD model was used with a constant reassessment of the model parameters at different window lengths and maximization by the two criteria of the model: the window size and the lengths of fast and slow averages.

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