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Network View to Market Risk
 

Network View to Market Risk

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Slides from panel presentation at Russia Risk Conference in Moscow on 21 Novemeber 2012

Slides from panel presentation at Russia Risk Conference in Moscow on 21 Novemeber 2012

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    Network View to Market Risk Network View to Market Risk Presentation Transcript

    • Russia Risk ConferencePRMIA and CbondsMoscow, 21 November 2012Network view tomarket riskCorrelation and Tail networks Dr. Kimmo Soramäki Founder and CEO FNA, www.fna.fi
    • Network Theory and Financial CartographyMain premise of network theory: Maps reduce data and encodeStructure of links between nodes relevant data to graphical elementsmatters within a representation system + Network Theory provides the representation system for financial maps like Cartography does to geographic maps 2
    • OutlineMaps enable visual insights from The maps: Heat Maps, Trees,complex financial data Networks and Sammon’s Projections – Reduce complexity – Identify price driving themes and market dynamics – Spot anomalies – Build intuition – Aid communication of resultsThese methods are showcased forvisualizing correlations among a widerange of assets around the collapse ofLehman Brothers on 15 September2008 3
    • i) Heat Maps 2004-2007CorporateBonds 151 assets in 5 asset classes:CDS on equities, gov.GovernmentDebt bonds, corp. bonds, cds and foreignFX Rates exchangeGovernmentBond Yields Correlation +1StockExchange 0Indices -1 4
    • Collapse of Lehman, t=month2004-2007 t-2 t-1 t+1 t+2 t+3
    • ii) Asset TreesOriginally proposed by Rosario Mantegna in 1999Used currently by some major financial institutionsfor market analysis and portfolio optimization andvisualizationMethodology in a nutshell MST 1. Calculate (daily) asset returns 2. Calculate pairwise Pearson correlations of returns 3. Convert correlations to distances 4. Extract Minimum Spanning Tree (MST) 5. Visualize 6
    • DemoClick here for interactive visualization 7
    • Correlation filteringBalance between too much and too New graph, information-theory,little information (Tumminello, economics & statistics -based modelsLillo, Mantegna 1999) are being actively developed E.g.: Network Estimation for Time- Series (Barigozzi & Brownlees)One of many methods to createnetworks from correlation/distancematrices (PMFGs, PartialCorrelation Networks, InfluenceNetworks, Granger Causality, etc.) 8
    • iii) Sammon’s ProjectionProposed by John W. Sammon in IEEE Transactions on Computers 18: 401–409(1969)A nonlinear projection method to map ahigh dimensional space onto a space oflower dimensionality. Example: Iris Setosa Iris Versicolor Iris Virginica 9
    • DemoClick here for interactive visualization 10
    • Tail dependence• Correlation is a linear dependence. The same visual maps can be extended to non-linear dependences.• Joint work with Firamis (Jochen Papenbrock) and RC Banken (Frank Schmielewski), see www.extreme-value-theory.com• Instead of correlation, links and positions measure similarity of distances to tail losses Tail Tree Tail Sammon (Click here for interactive visualization) (click here for interactive visualization) 11
    • Blog, Library and Demos at www.fna.fiDr. Kimmo Soramäkikimmo@soramaki.netTwitter: soramaki