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  • Search: subject:"Haar wavelets"
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Year of publication
Subject
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Adaptive trend estimation 1 Binary segmentation 1 Change-point detection 1 Climate change 1 Credit risk 1 Financial time series 1 Forecasting model 1 Frequency-domain modelling 1 Haar wavelets 1 Insolvency 1 Insolvenz 1 Klimawandel 1 Kreditrisiko 1 Merton model 1 Option pricing theory 1 Optionspreistheorie 1 Probability theory 1 Prognoseverfahren 1 Regression analysis 1 Regressionsanalyse 1 Risiko 1 Risk 1 State space model 1 Unbalanced Haar wavelets 1 Wahrscheinlichkeitsrechnung 1 Zustandsraummodell 1 breakpoint 1 climate risk 1 credit risk 1 probability of default 1 temperature anomalies 1 wavelet regression 1
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Online availability
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Free 2 CC license 1
Type of publication
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Article 1 Book / Working Paper 1
Type of publication (narrower categories)
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Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 1 Undetermined 1
Author
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Blanc-Blocquel, Augusto 1 Fryzlewicz, Piotr 1 Ortiz-Gracia, Luis 1 Sanfelici, Simona 1 Schröder, Anna Louise 1
Institution
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Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München 1
Published in...
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MPRA Paper 1 Risks : open access journal 1
Source
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ECONIS (ZBW) 1 RePEc 1
Showing 1 - 2 of 2
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Climate-related default probabilities
Blanc-Blocquel, Augusto; Ortiz-Gracia, Luis; Sanfelici, … - In: Risks : open access journal 12 (2024) 11, pp. 1-19
Climate risk refers to the risks associated with climate change and has already started to impact various sectors of the economy. In this work, we focus on the impact of physical risk on the probability of default for a firm in the agribusiness sector. The probability of default is estimated...
Persistent link: https://www.econbiz.de/10015137901
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Cover Image
Adaptive trend estimation in financial time series via multiscale change-point-induced basis recovery
Schröder, Anna Louise; Fryzlewicz, Piotr - Volkswirtschaftliche Fakultät, … - 2013
Low-frequency financial returns can be modelled as centered around piecewise-constant trend functions which change at certain points in time. We propose a new stochastic time series framework which captures this feature. The main ingredient of our model is a hierarchically-ordered oscillatory...
Persistent link: https://www.econbiz.de/10011108954
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