105.762 AKFVM Introduction to Financial Networks
Diese Lehrveranstaltung ist in allen zugeordneten Curricula Teil der STEOP.
Diese Lehrveranstaltung ist in mindestens einem zugeordneten Curriculum Teil der STEOP.

2023S, VU, 2.0h, 3.0EC
TUWEL

Merkmale

  • Semesterwochenstunden: 2.0
  • ECTS: 3.0
  • Typ: VU Vorlesung mit Übung
  • Format der Abhaltung: Präsenz

Lernergebnisse

Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...

After successful completion of the course, students are able to...

  • Explain basic concepts of network science
  • Apply these methods to financial markets
  • Do their own analysis of the financial network, and identify the most important properties of the market
  • Identify the riskiest elements of financial networks and learn ways how to manage the risk

Inhalt der Lehrveranstaltung

  • Networks – definitions, basic concepts (node, link, degree, adjacency matrix)
  • Basic types of networks (undirected, directed, weighted, bipartite, multiplex)
  • Node degree (distribution, in-degree, and out-degree, nearest-neighbor degree, assortativity)
  • Centrality measures (degree, closeness, betweenness, eigenvector, Katz, clustering coefficient, Pagerank)
  • Random network models (Erdös-Rényi network, percolation transition, Wigner law)
  • Complex network models (Configuration model, small-world networks, Strogratz-Watts model, scale-free network, Albert-Barabási model)
  • Community detection algorithms (Betweenness, Modularity, Infomap, Louvain, Leiden, Hierarchical clustering)
  • Correlation networks (eigenvector decomposition, random and non-random modes)
  • Network filtering algorithms (minimum spanning tree, planar maximally filtered graph)
  • Information-theoretic measures (entropy, mutual information, transfer entropy)
  • Financial networks analysis (in R project)
  • Multilayer financial networks (DebtRank, risk management)
  • Basic types of networks (undirected, directed, weighted, bipartite, multiplex)
  • Node degree (distribution, in-degree, and out-degree, nearest-neighbor degree, assortativity)
  • Centrality measures (degree, closeness, betweenness, eigenvector, Katz, clustering coefficient, Pagerank)
  • Random network models (Erdös-Rényi network, percolation transition, Wigner law)
  • Complex network models (Configuration model, small-world networks, Strogratz-Watts model, scale-free network, Albert-Barabási model)
  • Community detection algorithms (Betweenness, Modularity, Infomap, Louvain, Leiden, Hierarchical clustering)
  • Correlation networks (eigenvector decomposition, random and non-random modes)
  • Network filtering algorithms (minimum spanning tree, planar maximally filtered graph)
  • Information-theoretic measures (entropy, mutual information, transfer entropy)
  • Financial networks analysis (in R project)
  • Multilayer financial networks (DebtRank, risk management)

Methoden

lecture and exercises/homework

Prüfungsmodus

Prüfungsimmanent

Vortragende Personen

Mitwirkende

Institut

LVA Termine

TagZeitDatumOrtBeschreibung
Mi.14:00 - 16:0008.03.2023 - 28.06.2023Sem.R. DA grün 06A .
AKFVM Introduction to Financial Networks - Einzeltermine
TagDatumZeitOrtBeschreibung
Mi.08.03.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.22.03.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.29.03.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.19.04.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.26.04.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.03.05.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.10.05.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.17.05.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.24.05.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.31.05.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.07.06.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.14.06.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.21.06.202314:00 - 16:00Sem.R. DA grün 06A .
Mi.28.06.202314:00 - 16:00Sem.R. DA grün 06A .

Leistungsnachweis

exercises/homework and oral exam

LVA-Anmeldung

Von Bis Abmeldung bis
01.02.2023 00:00 31.03.2023 23:50 31.03.2023 23:50

Curricula

StudienkennzahlVerbindlichkeitSemesterAnm.Bed.Info
860 GW Gebundene Wahlfächer - Technische Mathematik Gebundenes Wahlfach

Literatur

  • S. Thurner, R. Hanel, P. Klimek, Introduction to the Theory of Complex Systems (Oxford University Press 2018, ISBN: 978-0198821939).
  • M. Newman, Networks: An Introduction (Oxford University Press 2010, ISBN: 978-0199206650).
  • K. Soramäki, S. Cook, Network Theory and Financial Risk (Risk, 2022, ISBN: 978-1-78272-432-2).
  • M. Bardoscia et al., The physics of financial networks, Nature Reviews Physics 3, p. 490–507 (2021). DOI: 10.1038/s42254-021-00322-5.

Sprache

Englisch