Agenda 1. Managing Emerging Risk 2. HeavyTails Systemic Risk Monitor 3. Eurozone Early Warning Case Study

1. VISUALIZING EUROZONE BOND
CRISIS
London
19 June 2015
FNA
Alan Laubsch
Director
FNA Ltd.
www.fna.fi

2. 2
Agenda
1. Managing Emerging Risk
2. Visualizing Correlations with FNA HeavyTails
3. Eurozone Case Study

3. 3
Systemic implications?
Amplifiers?
Crisis = structural risk + spark

4. 4
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)

5. 5
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

6. 6
Agenda
1. Managing Emerging Risk
2. Visualizing Correlations with FNA HeavyTails
3. Eurozone Case Study

7. 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

8. 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

9. 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.

10. 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).

11. Encoding Non-spatial Data
Node color indicates last daily
return
Green = positive
Red = negative
Node size indicates magnitude
of absolute return
Large node = high return
Small node = small return

12. ‘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

13. 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

14. 14
Agenda
1. Managing Emerging Risk
2. Visualizing Correlations with FNA HeavyTails
3. Eurozone Case Study

15. 15
Bond Tremors in June 2007

16. 16
Subprime cascades: June 2008

17. 17
EU Periphery Phase Transition Jan
2009

18. 18
Austerity & Baltic Riots

19. 19
Greek Crisis 2009-2015
View Interactive Dashboard

20. 20
Greece almost decoupled: May 2015
View Interactive Dashboard
Only positive correlation to Portugal, Italy, Spain

21. 21
May 2015 Eurozone bond transition
Most outliers since June 2008

22. 22
DAX cascade 16 & 17 April 2015

23. 23
Classic Bund Cascade 22 & 28 April
2015
Record prices & low vol followed by escalating outlier cluster

24. 24
SUMMARY & CONCLUSIONS

25. 25
Current Systemic Risk Observations
Escalating Eurozone bond volatility + coupling
Credit & liquidity risk amplify systemic fragility
Greece decoupling but connected to Portugal, Italy, Spain

26. 26
Conclusions
1. See a Connected Picture of Risk
2. “Sense and Respond”
3. Amplify Social Intelligence

27. Alan Laubsch
Director, VP Risk Products
alan@fna.fi
FNA

28. The FNA Software consists of FNA
Platform and FNA Apps.
FNA Platform is the server side workhorse for
analysis, simulation and visualization of
financial networks used by all FNA Apps.
FNA Software
FNA Apps master particular uses
cases with an interactive user
experience.
FNA Maps
FNA Payments
FNA HeavyTails

29. FNA Platform
Over a decade in making and with a wider selection of
financial network algorithms than any other software, the
FNA Platform offers a comprehensive end-to-end solution
for advanced analysis and visualizations of financial
networks.
FNA Platform is the backbone of all FNA Apps and available
as a cloud-based solution with a RESTful API, as an
enterprise installation, as a Desktop software and as a Java
library.
Cutting-edge analytics
Calculate hundreds of graph metrics, perform
cluster analysis and carry out predictive stress
tests and simulations.
Complete documentation
with over 500 pages of manuals describing the
platform’s functionality with examples, tutorials
and real-life applications.
End-to-end automation
Develop scripts for fully automated and regular
analytics or use FNA REST API from external
applications.
Easy integration
tap to data most common online data sources and
vendors directly, or from local databases.
More at www.fna.fi/platform

30. FNA HeavyTails
FNA HeavyTails helps risk managers and portfolio managers
identify and communicate emerging risks and design
adaptive stress tests.
FNA combines advanced network theory and interactive data
visualizations to detect hidden patterns in complex data.
FNA HeavyTails implements cutting edge research in Financial
CartographyTM by FNA and its collaborations with top
universities. The HeavyTails dashboard makes these analytics
readily accessible through a beautiful user interface.
Monitor systemic risk
with FNA’s unique correlation maps, Value-at-Risk
(VaR) analytics and outlier detection.
Stress test portfolios
with FNA’s interactive ‘Rapid stress testing’
functionality and integrate them with your portfolio
management and risk systems.
Identify emerging risks
with statistical and visual detection of outlier
assets, days, and periods.
Evaluate investment strategies
with correlation and clustering analysis against
benchmarks, and quickly identify hidden
concentration risk.
More at www.fna.fi/heavytails

31. FNA Maps
FNA NetworkMaps helps financial institutions explore
complex financial data for managing risks, identifying new
opportunities and making better, data driven decisions.
Combining advanced network theory with interactive
visualizations FNA NetworkMaps gives its users the analytical
power to answer the most difficult questions that they face.
Find hidden patters
with the help of hundreds of graph metrics,
clustering analysis and and predictive stress tests
and simulations.
Connect the dots
with fast interactive data exploration powered by
algorithms that filter signal from noise and FNA’s
beautiful network maps.
Monitor
the network in real-time and get alerted by
abnormal events.
Communicate
Create interactive network maps from public or
internal data sources and share them freely online
or within your organization.
More at www.fna.fi/maps