
Ranik Raaen WahlstrømNorwegian University of Science and Technology | NTNU · NTNU Business School
Ranik Raaen Wahlstrøm
PhD in Economics and Management
About
15
Publications
2,742
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
69
Citations
Publications
Publications (15)
We shed light on computational challenges when fitting the Nelson-Siegel, Bliss and Svensson parsimonious yield curve models to observed US Treasury securities with maturities up to 30 years. As model parameters have a specific financial meaning, the stability of their estimated values over time becomes relevant when their dynamic behavior is inter...
The purpose of our paper is to investigate whether any differences between International Financial Reporting Standards (IFRS) and local Generally Accepted Accounting Principles (GAAP) impact the transparency of financial reporting of non-listed companies through bankruptcy prediction. This contributes to extant research that has focused on the effe...
We utilize machine learning methods to model the credit risk of mortgages in a significant emerging market. For this purpose, we investigate a multitude of variables that explain the characteristics of the loans, the demographics of the borrowers, and macroeconomic factors. We employ SHapley Additive exPlanations (SHAP) values in conjunction with f...
We investigate non-financial variables for predicting bankruptcy in small and medium-sized enterprises (SMEs). The variables encompass management, board and ownership structures and are sourced from universally accessible information, rendering them available to all stakeholders and allowing for the analysis of all SMEs within a market. Using a lar...
The aim of this paper is to empirically investigate the potential association between a firm’s cost behavior, characterized as cost stickiness or anti-stickiness, and working capital management (WCM), as measured by the working capital to total assets ratio and the trade cycle measures net trade cycle and cash conversion cycle. We measure cost sti...
We examine the reactions of the cryptocurrency market to two events that occurred during the escalation of the Russia–Ukraine war in February 2022. Using hourly data, we find that the escalation exerted a negative influence on both liquidity and returns. Interestingly, the actual escalation triggered a more pronounced drop than the threat of escala...
This document details a data set which contains all unconsolidated annual financial statements of the universe of Norwegian private and public limited liability companies from the accounting years 2006-2019. In addition, the data set contains all the financial statements of other companies, e.g., sole proprietorships and general partnerships, which...
Sannsynligheten for konkurs er av interesse for flere aktører. Mange forsøker derfor å unngå eller redusere fremtidige tap ved å predikere konkurs ved hjelp av statistiske modeller. Det er derfor viktig å forstå hvilke faktorer som kan påvirke disse konkursmodellene. I denne studien undersøker vi hvorvidt bedriftens størrelse har betydning ved pred...
Full text available at SSRN: http://dx.doi.org/10.2139/ssrn.3911490
In this paper, we test alternative feature selection methods for bankruptcy prediction and illustrate their superiority versus popular models used in the literature. We test these methods using a comprehensive dataset of more than one million financial statements from privately he...
We empirically compare the Nelson-Siegel, Bliss and Svensson parsimonious yield curve models that are commonly used by central banks for monetary policy decisions and recommend the use of the former. Results shed light on the patterns of confounding effects in the Svensson model. We review estimation challenges and show implications of using differ...
Formålet med denne studien er å undersøke hvorvidt maskinlæringsteknikker er bedre i stand til å estimere modeller for konkursprediksjon enn tradisjonelle statistiske metoder. Konkursprediksjonsmodeller estimeres ved hjelp av tre maskinlæringsteknikker (nevrale nettverk, støttevektormaskiner og k-nærmeste naboer) og to regresjonsmetoder (logistisk...