KTH Matematik  

Matematisk Statistik

Tid: 7 april 2017 kl 13.45-14.15.

Seminarierummet 3721, Institutionen för matematik, KTH, Lindstedtsvägen 25, plan 7. Karta!

Föredragshållare: Ludvig Hällman (Master thesis)

Titel: The Rolling Window Method: Precisions of Financial Forecasting

Abstract In this thesis we set out to study the prediction accuracy of statistical quantities related to portfolio analysis and risk management implied by a given set of historical data. The considered forecasting procedure rely on rolling window estimates over varying prediction horizons where the resulting empirical return distributions can be considered the corresponding stationary distributions. Using scenarios generated from a joint interest rate- equity framework the rolling window method allows to, empirically, study the uncertainty of return statistics as well as risk measures related to market risk over varying prediction horizons. The study shows that, given the chosen models, the method is valid in predicting future statistical quantities related to portfolio return of up to one year maximum, whilst for risk measures the forecasting uncertainty is found to be to significant and highlights the difficulty in foreseeing extremities of future market movements.

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Sidansvarig: Filip Lindskog
Uppdaterad: 25/02-2009