Financial Cartography - PRMIA Webinar

• Audio: Use your microphone and speakers (VoIP) or call in using your telephone.

• Direct your questions to Staff via the Questions or Chat pane.

• To access this webinar audio via the internet, select “Mic & Speakers” under your Audio pane.

• Check that the audio on your computer is on and the volume is turned up.

• For technical assistance contact the Citrix webinar utility customer number: 1-888-259-8414

Kimmo SoramäkiFounder and CEO of Financial Network Analytics (FNA)

This material is the intellectual property of the presenterand shall not be reproduced or used without the express written permission .

Financial CartographyFebruary 6, 2013 – 12 p.m. U.S. Eastern Time

Financial Cartography

Dr. Kimmo SoramäkiFounder and CEOFNA, www.fna.fi

PRMIA Webinar6 February 2013

3

“When the crisis came, the serious limitations of existing economic and financial models immediately became apparent. [...] As a policy-maker during the crisis, I found the available models of limited help. In fact, I would go further: in the face of the crisis, we felt abandoned by conventional tools.”

in a Speech by Jean-Claude Trichet, President of the European Central Bank, Frankfurt, 18 November 2010

4

We did not have maps …

5Eratosthenes' map of the known world c. 194 BC

6

… but what are maps

“A set of points, lines, and areas all defined both by position with reference to a coordinate system and by their non-spatial attributes”

Data is encoded as size, shape, value, texture or pattern, color and orientation of the points, lines and areas – everything has a meaning

Political map of Europe

7

… but what are maps (contd.)

Cartographer selects only the information that is essential to fulfill the purpose of the map

Maps reduce multidimensional data into a two dimensional space that is better understood by humans

Maps are intelligence amplification, they aid in decision making and build intuition 

Map by John Snow showing the clusters of cholera cases in the London epidemic of 1854

8

I. Mapping Systemic Risk

II. Mapping Financial Markets

9

Systemic risk ≠ systematic risk

The risk that a system composed of many interacting parts fails (due to a shock to some of its parts).

In Finance, the risk that a disturbance in the financial system propagates and makes the system unable to perform its function – i.e. allocate capital efficiently.

Domino effects, cascading failures, financial interlinkages, … -> i.e. a process in the financial network

News articles mentioning “systemic risk”, Source: trends.google.com

Not:

10

Network Theory can be to Financial Maps what Cartography is to Geographic Maps

Main premise of network theory: Structure of links between nodes matters

To understand the behavior of one node, one must analyze the behavior of nodes that may be several links apart in the network

Topics: Centrality, Communities, Layouts, Spreading and generation processes, Path finding, etc.

11

Network aspect is an unexplored dimension of data

Variables

Obs

erva

tions

Time

12

First Maps Fedwire Interbank Payment Network, Fall 2001

Around 8000 banks, 66 banks comprise 75% of value,25 banks completely connected

Similar to other socio-technological networks

Soramäki, Bech, Beyeler, Glass and Arnold (2007), Physica A, Vol. 379, pp 317-333.See: www.fna.fi/papers/physa2007sbagb.pdf

M. Boss, H. Elsinger, M. Summer, S. Thurner, The network topology of the interbank market, Santa Fe Institute Working Paper 03-10-054, 2003.

13

Source: Bech, M.L. and Atalay, E. (2008), “The Topology of the Federal Funds Market”. ECB Working Paper No. 986.

More Maps: Federal Funds1997 - 2006

• 2600 loans worth $335 billion per day

• First Circle: 165Second Circle: 271Rest: 42

14

Source: Iori G, G de Masi, O Precup, G Gabbi and G Caldarelli (2008): “A network analysis of the Italian overnight money market”, Journal of Economic Dynamics and Control, vol. 32(1), pages 259-278

More Maps: Italian money market

Italian (very small)Italian (small)Italian (large)Foreign

15

More Maps: DebtRank

Source: Battiston et al, Nature Scientific Reports 2-54, 2012

Nodes: Financial institutionsLinks: Impact of an institution to another

Nodes closer to center are more important (as are big and red)

August 2007 to April 2008 October 2008 to April 2010

16

Where are we today?

Regulatory response to recent financial crisis was to strengthen macro-prudential supervision with mandates for more regulatory data

“Big data” and “Complex Data”-> Providing tools and challenge to understand, utilize and operationalize the data

Financial Networks are starting to get their own literature and metrics different from other fields of Network Theory

17

Case: Oversight Monitor

The monitor will allow the identification of systemically important banks and evaluation of the impact of bank failures on the interbank payment system

(network is fictional)

Intraday Liquidity Network -example

The visualizations are available at www.fna.fi/webinar/prmia

18

Polling Question 1

Which types of networks are most important for financial institutions and regulators?

1) Exposure/contagion networks2) Trade/payment networks3) Supply chain networks4) Social networks

19

II. Mapping Financial Markets

I. Mapping Systemic Risk

20

Outline

Purpose of the maps– Identify price driving themes and

market dynamics – Reduce complexity– Spot anomalies– Build intuition

The maps: Heat Maps, Trees, Networks and Sammon’s Projections

Based on asset correlations or tail dependence

These methods are showcased for visualizing markets around the collapse of Lehman Brothers

21

Collapse of Lehman

Lehman was the fourth largest investment bank in the US (behind Goldman Sachs, Morgan Stanley, and Merrill Lynch) with 26.000 employees

At bankruptcy Lehman had $750 billion debt and $639 billion assets

Collapse was due to losses in subprime holdings and inability to find funding due to extreme market conditions

Is seen as a divisive point in the 2007-2009 financial crisis

22

The DataPairwise correlations of return on 118 global assets in 4 asset classes

• Stock Exchange Indices (e.g. Dow Jones)

• Foreign Exchange Rates (e.g EUR/USD)

• Government Bonds (e.g. Irish 10 year bond)

• Corportate Bonds (e.g. EMU Corporate AAA, 1-3 years)

23

Corporate Bonds

FX Rates

Government Bond Yields

Stock Exchange Indices

January 2007

-1

0

+1

Correlation

i) Heat Maps

24

t-2 t-1January 2007

t+1 t+2

Corporate Bonds

FX Rates

GovernmentBonds

Stocks

Corporate Bonds

FX Rates

GovernmentBonds

Stocks

25

ii) Asset Trees

Originally proposed by Rosario Mantegna in 1999

Used currently by some major financial institutions for market analysis and portfolio optimization and visualization

Methodology in a nutshell

1. Calculate (daily) asset returns2. Calculate pairwise correlations of returns3. Convert correlations to distances4. Extract Minimum Spanning Tree (MST)

5. Visualize

Minimum Spanning TreeA spanning tree of a graph is a subgraph that: 1. is a tree and 2. connects all the nodes together

Length of a tree is the sum of its links. Minimum spanning tree (MST) is a spanning tree with shortest length.

MST reflects the hierarchical structure of the correlation matrix

27

Demo: Asset Trees

Color of node denotes asset class:

Links between nodes reflect 'backbone' correlations

- short link = high correlation- long link = low correlation

Size of node reflects volatility (variance) of returns

Dow Jones

EUR/USD

Ireland 10 year government bond

EMU Corporate AAA, 1-3 years

The visualizations are available at www.fna.fi/webinar/prmia

28

Correlation filtering

Balance between too much and too little information, signal vs noise

One of many methods to create networks from correlation/distance matrices

– PMFGs, Partial Correlation Networks, Influence Networks, Granger Causality, NETS, etc.

New graph, information-theory, economics & statistics -based models are being actively developed

PMFG

Influence Network

29

iii) NETS

• Network Estimation for Time-Series

• Forthcoming paper by Barigozzi and Brownlees

• Estimates an unknown network structure from multivariate data

• Based on partial correlations

• Captures both comtemporenous and serial dependence (partial correlations and lead/lag effects)

30

iv) Sammon’s Projection

Iris Setosa

Iris Versicolor

Iris Virginica

Proposed by John W. Sammon in IEEE Transactions on Computers 18: 401–409 (1969)

A nonlinear projection method to map a high dimensional space onto a space oflower dimensionality. Example:

31

Demo: Sammon Projection

Color of node denotes asset class:

Distance between nodes reflects similarity of correlation profiles- close = similar- far apart = different

Size of node reflects volatility (variance) of returns

Dow Jones

EUR/USD

Ireland 10 year government bond

EMU Corporate AAA, 1-3 years

The visualizations are available at www.fna.fi/webinar/prmia

32

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(Click here for interactive visualization)

Tail Sammon (click here for interactive visualization)

33

Polling Question

Where can financial data visualization provide most value?

1. Data validation and exploration2. Enhancing intuition3. Add on to statistical analysis4. Risk Management5. Trading

34

“In the absence of clear guidance from existing analytical frameworks, policy-makers had to place particular reliance on our experience. Judgment and experience inevitably played a key role.”

in a Speech by Jean-Claude Trichet, President of the European Central Bank, Frankfurt, 18 November 2010

Blog, Library and Demos at www.fna.fi

Dr. Kimmo Soramäki [email protected]: soramaki

To learn more about this topic and attend a live training course with Dr. Kimmo Soramaki, please click on the following course session for more information and how to register.

FINANCIAL NETWORKS – LESSONS FOR RISK MANGEMENT

NEW YORKApril 26, 2013

One-Day Training Course

37

Questions for the Presenter?

Send them in now by using your Question Pane in the webinar utility panel

Did you know that Sustaining Members attend thought leadership webinars at no additional cost? Find out more about Sustaining Membership at http://prmia.org/index.php?page=membership

Find upcoming and recorded webinars at www.prmia.org/webinars

38

Thank you for attending this PRMIA Webinar!

Go to www.prmia.org/webinars to find a full schedule of

upcoming webinars