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VISUALIZING EUROZONE BOND CRISIS
London 19 June 2015
FNA
Alan LaubschDirector FNA Ltd. www.fna.fi
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Agenda
1. Managing Emerging Risk
2. Visualizing Correlations with FNA HeavyTails
3. Eurozone Case Study
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Systemic implications?
Amplifiers?
Crisis = structural risk + spark
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Adaptive Stress Testing: Macro and Micro intelligence
I. Macro: identify potential risks (hidden, structural)
•Stress Library based on Thought Leaders •Focus on cycles (e.g., credit bubbles), amplifiers, imbalances, critical points •E.g., Robert Shiller: (a) tech bubble (2000), (b) housing bubble (2005)
II. Micro: monitor visible risk with market signals
•Construct Stress Indices using traded factors to represent scenarios •Monitor market signals, focusing on outliers and critical points •Examples: vol spike in (a) tech stocks and (b) US mortgages & financials
See: Adaptive Stress Testing: Amplifying Network Intelligence by Integrating Outlier Information (Laubsch 2014)
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Diffusion of Disruptive Innovation
Source: Wikipedia; see Geoffrey Moore’s “Crossing the Chasm” (1999)
1.Macro: Scenarios from Innovators
2. Micro: Market signals from Early Adopters
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Agenda
1. Managing Emerging Risk
2. Visualizing Correlations with FNA HeavyTails
3. Eurozone Case Study
Time Series and Correlations
…" Example: Daily returns of asset prices (ETFs)
Difficult to understand large-scale correlation or other dependence structures of financial assets.
Objective is to:
Efficiently represent a complex system moving in time
Visualize and predicts stress events in their context
Overlay multiple dimensions of the data to allow for visual inference
Correlation Networks
Not all correlations are statistically significant.
A sparse matrix is often well represented as a network.
We encode correlations as links between the correlated nodes/assets.
Red link = negative correlation Black link = positive correlation
Absence of link marks that asset is not significantly correlated.
A B C
A 1 0.5 0.8
B 0.5 1 0.2
C 0.8 0.2 1
Dimensionality Reduction
Next, we identify the Minimum Spanning Tree (MST) and filter out other correlations.
Rosario Mantegna (1999) ‘Hierarchical Structure in Financial Markets’
This shows us the backbone correlation structure where each asset is connected with the asset with which its correlation is strongest.
Visualization
We use a radial tree layout algorithm by
Bachmaier & Brandes (2005)
that places the assets so that:
• Shorter links in the tree indicate higher correlations
• Longer links indicate lower correlations
As a result, we also see how the assets cluster (analogous to single linkage clustering).
Encoding Non-spatial DataNode color indicates last daily return
Green = positiveRed = negative
Node size indicates magnitude of absolute return
Large node = high returnSmall node = small return
‘Here be Dragons’
Didier Sornette (2009)Dragon King: “Extreme events can be predicted”
Benoit B. Mandelbrot (1963)Volatility Clustering: “Large changes tend to be followed by large changes”
-> Identify Value at Risk (VaR) exceptions (return outside 95% VaR bounds)
-> Map them as bright green or red nodes
Summing up
Linkages are critical: interconnections, covariances, dependencies, flows, exposures, co-occurances, etc …
Challenge: Filter signal from noise, present efficiently
In Summary
Creating a Map - Placing you on Map - Providing Directions
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Agenda
1. Managing Emerging Risk
2. Visualizing Correlations with FNA HeavyTails
3. Eurozone Case Study
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Bond Tremors in June 2007
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Subprime cascades: June 2008
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EU Periphery Phase Transition Jan 2009
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Austerity & Baltic Riots
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Greek Crisis 2009-2015View Interactive Dashboard
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Greece almost decoupled: May 2015View Interactive Dashboard
Only positive correlation to Portugal, Italy, Spain
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May 2015 Eurozone bond transitionMost outliers since June 2008
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DAX cascade 16 & 17 April 2015
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Classic Bund Cascade 22 & 28 April 2015
Record prices & low vol followed by escalating outlier cluster
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SUMMARY & CONCLUSIONS
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Current Systemic Risk ObservationsEscalating Eurozone bond volatility + coupling
Credit & liquidity risk amplify systemic fragility
Greece decoupling but connected to Portugal, Italy, Spain
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Conclusions
1. See a Connected Picture of Risk
2. “Sense and Respond”
3. Amplify Social Intelligence
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