49 citations · 64 across the 12 of their papers we have counts for
15 papers
Deep learning bank distress from news and numerical financial data
Paola Cerchiello, Giancarlo Nicola, Samuel Ronnqvist +1
In this paper we focus our attention on the exploitation of the information contained in financial news to enhance the performance of a classifier of bank distress. Such informatio…
News-sentiment networks as a risk indicator
Thomas Forss, Peter Sarlin
To understand the relationship between news sentiment and company stock price movements, and to better understand connectivity among companies, we define an algorithm for measuring…
Bank distress in the news: Describing events through deep learning
Samuel Rönnqvist, Peter Sarlin
While many models are purposed for detecting the occurrence of significant events in financial systems, the task of providing qualitative detail on the developments is not usually…
RiskRank: Measuring interconnected risk
József Mezei, Peter Sarlin
This paper proposes RiskRank as a joint measure of cyclical and cross-sectional systemic risk. RiskRank is a general-purpose aggregation operator that concurrently accounts for ris…
Detect & Describe: Deep learning of bank stress in the news
Samuel Rönnqvist, Peter Sarlin
News is a pertinent source of information on financial risks and stress factors, which nevertheless is challenging to harness due to the sparse and unstructured nature of natural t…
Toward robust early-warning models: A horse race, ensembles and model uncertainty
Markus Holopainen, Peter Sarlin
This paper presents first steps toward robust models for crisis prediction. We conduct a horse race of conventional statistical methods and more recent machine learning methods as…
Aggregation operators for the measurement of systemic risk
Jozsef Mezei, Peter Sarlin
The policy objective of safeguarding financial stability has stimulated a wave of research on systemic risk analytics, yet it still faces challenges in measurability. This paper mo…
Interactive Visual Exploration of Topic Models using Graphs
Samuel Rönnqvist, Xiaolu Wang, Peter Sarlin
Probabilistic topic modeling is a popular and powerful family of tools for uncovering thematic structure in large sets of unstructured text documents. While much attention has been…
Bank Networks from Text: Interrelations, Centrality and Determinants
Samuel Rönnqvist, Peter Sarlin
In the wake of the still ongoing global financial crisis, bank interdependencies have come into focus in trying to assess linkages among banks and systemic risk. To date, such anal…
The process of macroprudential oversight in Europe
Peter Sarlin, Henrik J. Nyman
The 2007--2008 financial crisis has paved the way for the use of macroprudential policies in supervising the financial system as a whole. This paper views macroprudential oversight…
Automated and Weighted Self-Organizing Time Maps
Peter Sarlin
This paper proposes schemes for automated and weighted Self-Organizing Time Maps (SOTMs). The SOTM provides means for a visual approach to evolutionary clustering, which aims at pr…
From Bits to Atoms: 3D Printing in the Context of Supply Chain Strategies
Henrik J Nyman, Peter Sarlin
A lot of attention in supply chain management has been devoted to understanding customer requirements. What are customer priorities in terms of price and service level, and how can…
Cluster coloring of the Self-Organizing Map: An information visualization perspective
Peter Sarlin, Samuel Rönnqvist
This paper takes an information visualization perspective to visual representations in the general SOM paradigm. This involves viewing SOM-based visualizations through the eyes of…
From Text to Bank Interrelation Maps
Samuel Rönnqvist, Peter Sarlin
In the wake of the ongoing global financial crisis, interdependencies among banks have come into focus in trying to assess systemic risk. To date, such analysis has largely been ba…
Self-Organizing Time Map: An Abstraction of Temporal Multivariate Patterns
Peter Sarlin
This paper adopts and adapts Kohonen's standard Self-Organizing Map (SOM) for exploratory temporal structure analysis. The Self-Organizing Time Map (SOTM) implements SOM-type learn…