Tid: 18 maj 2017 kl 16.15-17.00.

Föredragshållare: Yang Zhou

Titel: Modelling Swedish inflation using market data (Master's thesis)

Abstract This study is an attempt to model Swedish CPI inflation using ARIMA and variations of distributed lag model with market data as explanatory variables. The model will be constructed on the CPI subcomponents level and the results are aggregated to the CPI. Three approaches are tested in this report. In the first approach, only ARIMA model is used to model each of the subcomponents. In the second approach we use a distributed lag model (DLM) on subcomponents with significant correlation to the market data, the residual of the DLM is then modelled using ARIMA. In the third approach we use an restricted nite distributed lag model (RFDLM) instead of DLM. The study found that RFDLM was the best approach to model inflation with 20% RMSE compared to 32% of the naive forecast. However, there is little forecast potential using this approach due to the short lag of market data used as input. The model would be most useful in testing CPI inflation scenarios using predictions or assumptions of market data as input.

The full report (pdf)

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