Econophysics Colloquium 2013 Asia Pacific Econophysics...

Econophysics Colloquium 2013

&

Asia Pacific Econophysics Conference 2013

Date: July 29-31, 2013

Venue: POSTECH, Pohang, Korea

Sponsored by

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Invited Speakers

Siew Ann Cheong (Nanyang Technological University, Singapore)

Hiroshi Iyetomi (Niigata University, Japan)

Hawoong Jeong (KAIST, Korea)

Woo-Sung Jung (POSTECH, Korea)

Taisei Kaizoji (International Christian University, Japan)

Beom Jun Kim (Sungkyunkwan University, Korea)

Kyungsik Kim (Pukyong National University, Korea)

Seunghwan Kim (POSTECH, Korea)

Yong-Cheol Kim (University of Wisconsin, USA)

Okyu Kwon (National Institute for Mathematical Sciences, Korea)

Jae Woo Lee (Inha University, Korea)

Sai-Ping Li (Academia Sinica, Taiwan)

Thomas Lux (University of Kiel, Germany)

Rosario Nunzio Mantegna (University of Palermo, Italy)

Tiziana Di Matteo (King's College London, UK)

Gabjin Oh (Chosun University, Korea)

Tobias Preis (University of Warwick, UK)

Aki-Hiro Sato (Kyoto University, Japan)

Seung-Woo Son (Hanyang University, Korea)

Misako Takayasu (Tokyo Institute of Technology, Japan)

Stefan Thurner (Medical University of Vienna, Austria)

Yougui Wang (Beijing Normal University, China)`

Victor Yakovenko (University of Maryland, USA)

Wei-Xing Zhou (East China University of Science and Technology, China)

Scientific Committee

Tomaso Aste (University College London, London)

Damiano Brigo (Imperial College, London)

Carl Chiarella (University of Technology, Sydney)

Guido Caldarelli (Universita' La Sapienza, Rome)

Shu-Heng Chen (National Chengchi University, Taipei)

Siew Ann Cheong (Nanyang Technological University, Singapore)

Carmen Costea (Spiru Haret University, Bucharest)

Michel Dacorogna (SCOR SE Zurich Branch, Zurich)

Tiziana Di Matteo (King's College London, London)

J.Doyne Farmer (Santa Fe Institute, Santa Fe)

Mauro Gallegati (Universita Politecnica delle Marche, Ancona)

Giulia Iori (City University, London)

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Woo-Sung Jung (POSTECH, Pohang)

Taisei Kaizoji (International Christian University, Tokyo)

Janos Kertesz (Technical University of Budapest, Budapest)

Seunghwan Kim (POSTECH, Pohang)

Alan Kirman (G.R.E.Q.A.M, Aix-en-Provence)

Sai-Ping Li (Academia Sinica, Taipei)

Fabrizio Lillo (University of Palermo, Palermo)

Thomas Lux (University of Kiel, Kiel)

Rosario N. Mantegna (Universita' di Palermo, Palermo)

Luciano Pietronero (University of Rome, Roma)

Peter Richmond (Trinity College, Dublin)

Aki-Hiro Sato (Kyoto University, Kyoto)

Enrico Scalas (Universita' del Piemonte Orientale, Alessandria)

Frank Schweitzer (ETH, Zurich)

Eugene H. Stanley (Boston University, Boston)

Hideki Takayasu (Sony Computer Science, Tokyo)

Stefan Thurner (Medical University of Vienna, Vienna)

Constantino Tsallis (CBPF, Rio de Janeiro and Santa Fe Institute, Santa Fe)

Yougui Wang (Beijing Normal University, Beijing)

Yi-Cheng Zhang (University of Fribourg, Fribourg)

Local Organizing Committee

Hawoong Jeong (KAIST)

Jaeseung Jeong (KAIST)

Woo-Sung Jung (POSTECH, Secretary)

Hyungtae Kook (Gachon niversity)

Beom Jun Kim (Sungkyunkwan University)

Kyungsik Kim (Pukyong National University)

Seunghwan Kim (POSTECH, Chair)

Okyu Kwon (National Institute for Mathematical Sciences)

Jae Woo Lee (Inha University)

Gabjin Oh (Chosun University)

Seung-Woo Son (Hanyang University)

Soon-Hyung Yook (Kyung Hee University)

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Guidance for Participants

A. Venue

Invited Talks:

Auditorium, 1st floor, POSCO International Center

Parallel session (Monday afternoon, Tuesday afternoon):

A, E: Auditorium, 1st floor, POSCO International Center

B, F: International Conference Room, 1st floor, POSCO International Center

Parallel session (Tuesday morning):

C: Physics Building (#3) - 109

D: Physics Building (#3) – 111

B. Meals

Breakfast:

Light snack will be provided at 9:00 (Mon) and at 8:30 (Tue & Wed)

Place: The front of the Auditorium, 1st floor, POSCO International Center

Lunch:

Invited speakers: D’medley, 2nd floor, POSCO International Center

Others: Wisdom Restaurant, 2nd floor, Jigok Community Center (Meal ticket will be provided)

Welcoming Reception:

Time: 19:00~21:00, Jul. 29(Mon)

Place: Phoenix, 5th floor, POSCO International Center

Standing Lunch:

Time: 12:30~14:00, Jul. 30(Tue)

Place: APCTP Common Room (501), 5th floor, Hogil Kim Memorial Hall

Banquet:

Time: 19:00~21:00, Jul. 30(Tue)

Place: Grand Ballroom, 2nd floor, POSCO International Center

C. Accommodation

POSCO International Center

(1) Check-in: after 2 p.m. / -Check-out: before 12 p.m.

(2) Wireless Internet: POSCO_IC

Student Dormitory Bldg. 20 & 21 (for women)

(1) Check-in: after 1 p.m. / -Check-out: before 10 a.m.

(2) You should pick up an entry card for dormitory building during registration. It must be

returned before departure.

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(3) Cleaning equipments are NOT provided at dormitory room. Please bring your own

towels, toothbrush, shampoo, etc.

(4) Laundry: Free laundry machines are available on the 1st floor of the building for use

from 7:00 am to 22:00. Laundry room on the 1st floor is for male and the room on the

11th floor is female

(5) Dormitory Regulations strictly prohibit smoking and drinking.

(6) How to use door lock at Dorm Room.

- Pin number is 1234✻. If you need to change the pin number during your stay, please

refer to the following guidance. *Please be sure to reset the Pin Number to 1234✻

before check-out.

-To change the pin number: Press the button ● for 2 sec. → 1234✻→ Press the new pin

number✻→Press the new pin number✻

- To reset: Press the button ● for 10 sec. → press 4560852580✻

(7) Wireless Internet is available.

SSID: postech

ID: visit_34253

PW: a624141

D. Travel Information

Call Taxi

Choose and call one of the following taxi companies. It will be easier to ask a concierge of

your hotel or a Staff of APCTP to call a taxi on behalf of you.

- Haemaji Call Taxi: 054-283-8282

- Yoogil Call Taxi: 054-282-6161

- Pos Call Taxi: 054-252-1111

From Pohang Intercity Bus Terminal to the Incheon / Gimhae Airport

DESTINATION DEPARTURE TIME TRAVEL TIME FARE

Incheon Airport 05:30, 08:20, 11:00

Night 23:30, 01:00, 02:30 5hrs 30mins

KRW44,300 (Night-KRW48,700)

Gimhae Airport

05:00, 05:40, 06:20, 07:20, 08:20, 09:20, 10:20, 11:20, 12:20, 13:20, 14:20, 15:20, 16:20, 17:20, 18:20, 19:20

2hrs KRW11,000

From Pohang Airport to Gimpo(Seoul) Airport

Departure Arrival Flight

10:10 11:25 15:40 17:40

11:00 12:15 16:30 18:30

OZ8332 KE1532 OZ8334 KE1534

*KE: Korean Air http://www.koreanair.com *OZ: Asiana Air http://www.flyasiana.com

http://www.koreanair.com/

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From Pohang to Seoul by Train

1) Pohang Intercity Bus Terminal → Singyeongju Station

Please take a Limousine Bus from the Bus Terminal to Singyeongju station. The Bus starts

at 5:00(Sat.& Sun. excluded), 6:00, 7:00, 7:50, 8:10, 8:50, 9:45, 10:10, 11:50, 12:20, 13:50,

15:00, 16:00, 17:00, 17:30, 18:00, 19:00, 20:00, 20:45, 22:30 and 23:30. The cost is KRW 5,000

and it takes about 40 min. from Pohang to Singyeongju Station.

2) Singyeongju Station → Seoul Station

Please refer to below website for the timetable of KTX (Korea Train Express).

http://info.korail.com/2007/eng/eng_index.jsp

3) Seoul Station → Incheon Airport, please take Airport railroad.

For the airport railroad, please refer to the website, http://english.arex.or.kr/jsp/eng/index.jsp.

E. Excursion:

Departure: 13:30, Jul. 31(Wed), POSCO International Center

http://english.arex.or.kr/jsp/eng/index.jsp

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The available Cafeteria and Restaurant in POSTECH

Jigok Community Center

Location Available time

Freedom

(Student Dining Hall) 2nd floor

Breakfast: 7:30 to 9:30

Lunch: 11:30 to 13:30

Dinner: 17:30 to 19:00

Wisdom

Faculty & Staff

Dining Hall 2nd floor

Lunch: 11:50 to 13:00

(closed on Saturday & Sunday)

Cafeteria 2nd floor

Breakfast: 8:00 to 10:30

Lunch: 11:30 to 15:00

Dinner: 16:00 to 20:30

Yeonji (Korean Restaurant) 1st floor 13:00 to 20:00 (closed on Sunday)

Burger King 1st floor 10:00 to 22:00

Campus Store 1st floor 8:00 to 2:00



D’medley

(Buffer Restaurant) 2nd floor 7:00 to 20:30

Phoenix

(Chinese Restaurant) 5th floor

12:00 to 20:30

(closed on Sunday)

Student Union


OASIS 1st floor 8:00 to 19:30

Campus Store 1st floor 8:00 to 21:00

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POSTECH Campus Map

Physics Building

(Science Bldg. #3)


Hogil Kim Memorial Hall

(APCTP Common Room)

Jigok Community Center

(Yeonji, Wisdom)

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POSTECH Dormitory Map

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Korean Expression

1. Please call a taxi on behalf of me.

콜택시를 불러 주세요.

2. Please take me to POSCO International center.

포항공대 국제관에 내려주세요.

3. Please take me to Dormitory at POSTECH.

포항공대 기숙사에 내려주세요.

4. Please take me to APCTP.

포항공대 무은재 기념관에 내려주세요.

(포항공대 내 국제관 올라가는 길인 무은재길 정면)

5. Please take me to the Pohang Intercity Bus Terminal.

포항시외버스 터미널에 내려주세요.

6. Please take me to the Pohang Express Bus Terminal.

포항고속버스 터미널에 내려주세요.

7. Please take me to Pohang Airport.

포항공항에 내려주세요.

8. I would like to go to Singyeongju Station.

신경주역에 가려고 합니다.

9. I would like to go to Gimhae Airport.

김해공항에 가려고 합니다.

10. I would like to go to Incheon Intl. airport.

인천공항에 가려고 합니다.

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Program

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Day 1

Invited speaker

Time Speaker Title

Chair : Beom Jun Kim

11:00 ~ 11:30 Rosario Nunzio

Mantegna

Statistically validated networks of market members

trading at the LSE electronic and dealers' market

11:30 ~ 12:00 Tobias Preis Quantifying Economic Behavior Using Big Data

12:00 ~ 12:30 Hawoong Jeong Google knows (almost) everything! - Big-data and

Network Science

12:30 ~ 1:30 Lunch

Chair : Victor Yakovenko

1:30 ~ 2:00 Tiziana Di Matteo Spread of risk across financial markets: better to invest

in the peripheries

2:00 ~ 2:30 Hiroshi Iyetomi Frustrated Correlation Structures Embedded in Well-

Developed Stock Markets

2:30 ~ 3:00 Yougui Wang Incorporating Debt into the Modern Macroeconomics

3:00 ~ 3:30 Break

3:30 ~ 5:00 Parallel session A

Parallel session B

5:00 ~ 5:30 Break

Chair : Rosario Nunzio Mantegna

5:30 ~ 6:00 Misako Takayasu Estimation of flows in Businesses to Business transaction

network

6:00 ~ 6:30 Gabjin Oh Measuring systemic risk through contagion effect of

industry sector

6:30 ~ 7:00 Wei-Xing Zhou Liquidity, trade size and immediate price impact

7:00 ~ 9:00 Welcoming Reception

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Day 1

Parallel session A

Time Speaker Title

Chair : Hawoong Jeong

3:30 ~ 3:45 Jongwook Kim Non-Gaussianity defined by Auto-Correlated Random

Walk

3:45 ~ 4:00 Wen-Jie Xie Extreme value statistics and recurrence intervals of NYMEX

energy futures volatility

4:00 ~ 4:15 Rudi Schaefer Nonstationary correlations: From market states to random

matrix averages

4:15 ~ 4:30 Alejandro Raul

Hernandez Montoya

An statistical analysis of short term price trends symmetry

in daily stock-market index data

4:30 ~ 4:45 Sebastian Poledna Leverage-induced systemic risk under Basle II and other

credit risk policies

4:45 ~ 5:00 Il Gu Yi Fat tailed return distribution and fractal structure in profit

landscapes

Parallel session B

Time Speaker Title

Chair : Misako Takayasu

3:30 ~ 3:45 Hideki Takayasu Dealer model simulation of the intervention event of

foreign exchange markets

3:45 ~ 4:00 aurelien sylvain

christophe cassagnes

Heterogeneous Computation of Rainbow Option Prices

Using Fourier Cosine Series Expansion Under A Mix

4:00 ~ 4:15 Kyubin Yim Bubbles and Crashes in Artificial Double Auction Market

4:15 ~ 4:30 Tat-Shing CHOI Competition as Particle Interactions: From Duopoly to

General Market Structures

4:30 ~ 4:45 Hyejin Youn The Hidden Structure in Urban Economic Diversity

4:45 ~ 5:00 Zhi-Qiang Jiang Trading networks, abnormal motifs and stock manipulation

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Day 2

Invited speaker

Time Speaker Title

Chair : Tiziana Di Matteo

9:00 ~ 9:30 Thomas Lux Hubs and resilience: towards more realistic models of the

interbank markets

9:30 ~ 10:00 Aki-Hiro Sato Parameter estimation methods of a multiplicative

stochastic process for the analysis of financial time series:

An application to inference of tail-risks

10:00 ~ 10:30 Siew Ann Cheong Forecasting Crashes in Financial and Housing Markets

10:30 ~ 11:00 Break

11:00 ~ 12:30 Parallel session C

Parallel session D

12:30 ~ 1:30 Lunch

Chair : Hiroshi Iyetomi

1:30 ~ 2:00 Stefan Thurner DebtRank-transparency: Eliminating systemic risk in

financial networks

2:00 ~ 2:30 Jae Woo Lee Network Topologies of a Financial Market around the

2008 Global Financial Crisis

2:30 ~ 3:00 Sai-Ping Li Volatility Clustering and Stochasticity in Nonlinear Time

Series

3:00 ~ 3:30 Break

3:30 ~ 5:00 Parallel session E

Parallel session F

5:00 ~ 5:30 Break

Chair : Thomas Lux

5:30 ~ 6:00 Victor Yakovenko Statistical Mechanics of Money, Income, Debt, and Energy

Consumption

6:00 ~ 6:30 Okyu Kwon Big Data, Data Science and Econophysics

6:30 ~ 7:00 Seunghwan Kim Understanding complexity of the microstructure of

financial markets

7:00 ~ 9:00 Banquet

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Day 2

Parallel session C

Time Speaker Title

Chair : Sai-Ping Li

11:00 ~ 11:15 Franck Raynaud Statistical properties, networks and information flows in

derivative markets

11:15 ~ 11:30 Leonidas Sandoval Causality relations in a network of financial institutions

11:30 ~ 11:45 Ashadun Nobi Nonlinear dynamic properties and network topology of

global financial indices

11:45 ~ 12:00 Tae Seok Jang Productivity shocks and monetary policy in a two-country

model

12:00 ~ 12:15 Hai-Chuan Xu Short-term Market Reaction after Trading Halts in Chinese

Stock Market

12:15 ~ 12:30

Parallel session D

Time Speaker Title

Chair : Jae Woo Lee

11:00 ~ 11:15 Hongwei Xu Analysis of overlapping community structure in a large-

scale social network

11:15 ~ 11:30 Hang-Hyun Jo Contextual analysis framework for bursty dynamics

11:30 ~ 11:45 Wanting Xiong The Emergence of Fair offers in Ultimatum Game on

Bipartite Networks

11:45 ~ 12:00 Sang Hoon Lee Overlapping Community Detection of Multilayer Networks

12:00 ~ 12:15 Jinzhong Guo Money Circulation and Credit Circulation

12:15 ~ 12:30

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Day 2

Parallel session E

Time Speaker Title

Chair : Siew Ann Cheong

3:30 ~ 3:45 Tian Qiu Correlation dynamics between price return and trading volume

3:45 ~ 4:00 Ming-Xia Li Correlation analysis in Chinese stock trading network

4:00 ~ 4:15 Kihong Chung Generalized Epidemic Process on Modular Networks

4:15 ~ 4:30 Chih-Hao Lin Adaptive Trading for Anti-correlated Pairs of Stocks

4:30 ~ 4:45 Seok-won Ahn Portfolio selection using complex network

4:45 ~ 5:00

Parallel session F

Time Speaker Title

Chair : Wei-Xing Zhou

3:30 ~ 3:45 CHI WUN CHOI A Study on the Rock-Paper-Scissors game in Co-evolving

Networks

3:45 ~ 4:00 Min-Woo Ahn Network structure of national R&D activity in Korea

4:00 ~ 4:15 Eiichi Umehara Relationship between Stock BBS and Stock Market using stock

prices intra-day: As Case of SoftBank

4:15 ~ 4:30 Byounghwa Lee Prediction of Congestion Sites in Pohang

4:30 ~ 4:45 Jianzhong Zhang Scaling Structure in Game-Locked Aggregation

4:45 ~ 5:00 Inho Hong Intra-city Bus Network in Korean Mid-Size Cities

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Day 3

Invited speaker

Time Speaker Title

Chair : Thomas Lux

9:00 ~ 9:30 Yong-Cheol Kim Banking Concentration and Moral Hazard

9:30 ~ 10:00 Taisei Kaizoji Bubbles and crashes: Modeling from the point of

view of statistical physics

10:00 ~ 10:30 Kyungsik Kim Analysis of future prices from the structure of

correlations

10:30 ~ 11:00 Break

Chair : Taisei Kaizoji

11:00 ~ 11:30 Beom Jun Kim Human dynamics of spending: Study of a coalition

loyalty program

11:30 ~ 12:00 Seung-Woo Son Thinking fast and slow in a poker game

12:00 ~ 12:30 Woo-Sung Jung Complex network analysis of social data in Korea

12:30 ~ 1:30 Lunch

1:30 ~ Excursion

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Day 1

Invited Talk (at Auditorium)

11:00 – 11:30 Invited Talk 1 Rosario Nunzio Mantegna

11:30 – 12:00 Invited Talk 2 Tobias Preis

12:00 – 12:30 Invited Talk 3 Hawoong Jeong

1:30 – 2:00 Invited Talk 4 Tiziana Di Matteo

2:00 – 2:30 Invited Talk 5 Hiroshi Iyetomi

2:30 – 3:00 Invited Talk 6 Yougui Wang

Parallel Session A, B (Contributed Talk)

3:30 – 5:00 Parallel session A Auditorium

Parallel session B International Conference Room


5:30 – 6:00 Invited Talk 7 Misako Takayasu

6:00 – 6:30 Invited Talk 8 Gabjin Oh

6:30 – 7:00 Invited Talk 9 Wei-Xing Zhou

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Invited Talk

STATISTICALLY VALIDATED NETWORKS OF MARKET

MEMBERS TRADING AT THE LSE ELECTRONIC AND

DEALERS' MARKET

Rosario Nunzio Mantegna

University of Palermo, Argentina

We empirically detect and analyze trading networks, which are present among all market members of

the London Stock Exchange (LSE) trading shares of a specific stock in a selected period of time. We

analyze the anonymous electronic book and the networked dealers' market separately, and we

statistically validate a link between two market members if the number of transactions of a selected

stock that occur between the two market members is too large to be explained according to a null

hypothesis of random trading between them. The statistical validation is obtained by generalizing to

directed networks a procedure of statistical validation of networks recently introduced in [1].

Specifically, we separately analyze the trading networks of market members trading five highly liquid

stocks, in the two LSE venues, from daily to yearly time scale, during the calendar year 2005. For the

selected stocks, we find that statistically validated trading networks for the dealers' market are bigger

and more stable over time than those observed for the electronic market. Our results therefore confirm

that anonymity in the electronic order book minimizes the probability of preferential pair trading

interactions and implies that concerns about adverse selection in the dealers' market are somewhat

compensated by other positive aspects, which are specific to the dealers' market, such as the

possibility of exchanging large volumes in a single transaction or obtaining a transaction price within

the spread observed at the anonymous electronic book venue.

This work is done in collaboration with A. Carollo, F. Lillo, M. Tumminello, and G. Vaglica

References:

[1] Tumminello M, Miccichè S, Lillo F, Piilo J, Mantegna RN (2011) Statistically Validated

Networks in Bipartite Complex Systems. PLoS ONE 6(3): e17994. doi:10.1371/journal.pone.0017994

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Invited Talk

QUANTIFYING ECONOMIC BEHAVIOR USING BIG DATA

Tobias Preis

University of Warwick, UK

In this talk, I will outline some recent highlights of our research, addressing two questions.

Firstly, can big data resources provide insights into crises in financial markets which affect

humans worldwide? By analyzing Google query volumes for search terms related to finance

[1,2] and views of Wikipedia articles [3], we find patterns which may be interpreted as early

warning signs of stock market moves. Secondly, can we provide insight into international

differences in economic wellbeing by comparing patterns of interaction with the Internet? To

answer this question, we introduce a future-orientation index to quantify the degree to which

Internet users seek more information about years in the future than years in the past. We

analyze Google logs and find a striking correlation between the country's GDP and the

predisposition of its inhabitants to look forward [4]. Our results illustrate the potential that

combining extensive behavioral data sets offers for a better understanding of large scale

human economic behavior.

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Invited Talk

GOOGLE KNOWS (ALMOST) EVERYTHING! - BIG-DATA AND

NETWORK SCIENCE

Hawoong Jeong

KAIST, Korea

Network science is an interdisciplinary academic field which studies complex networks such

as engineered networks, information networks, biological networks, cognitive and semantic

networks and social networks. This field has received a major boost caused by the availability

of huge network data resources on the Internet. The field draws on theories and methods

including graph theory from mathematics, statistical mechanics from physics, data mining

and information visualization from computer science, inferential modeling from statistics,

and social structure from sociology to understand the complex systems, the problem to be

solved in 21st century. Another research field gaining huge attention nowadays is about big-

data. Big-data is defined as “high-volume, high-velocity, and/or high-variety information

assets that require new forms of processing to enable enhanced decision making, insight

discovery and process optimization.” by Gartner, Inc. This field of research has huge

potential for practical applications but it also promises new discovery in science. However,

these big-data should be combined and analyzed together to be useful, and in this respect,

network science will shed a light on analyzing these big-data in more combined way. In this

presentation, I will briefly review what we can do by combining big-data, especially using

Google and network science together to study various complex systems such as social

network between people, prediction of science and technology trends etc.

22

Invited Talk

SPREAD OF RISK ACROSS FINANCIAL MARKETS: BETTER

TO INVEST IN THE PERIPHERIES

Tiziana Di Matteo

King's College London, UK

In this talk I will introduce a methodology and a set of tools to filter complex dependency structures

in financial datasets by using networks [1-2]. The topology of these networks efficiently encodes the

complex dependency structure reducing data complexity while preserving the fundamental

characteristics of the dataset. This methodology has the added advantage of visualizing directly the

complex organization of the dependency structure over the graphic layout of the network.

I will discuss how this approach can be used to build a well-diversified portfolio that effectively

reduces investment risk. Specifically I will show that investments in stocks that occupy peripheral,

poorly connected regions in the financial filtered networks are most successful in diversifying

investments even for small baskets of stocks. On the contrary, investments in subsets of central,

highly connected stocks are characterized by greater risk and worse performance [3].

I will also introduce a general graph-theoretic approach that use these filtered networks to

simultaneously extract clusters and hierarchies in an unsupervised and deterministic manner, without

the use of any prior information and without need to specify any threshold [4-5]. I will show that

applications to financial data-sets can meaningfully identify industrial activities and structural market

changes [6].

References:

[1] T. Aste, T. Di Matteo, S. T. Hyde, Physica A 346 (2005) 20-26.

[2] M. Tumminello, T. Aste, T. Di Matteo, R. N. Mantegna, PNAS 102, n. 30 (2005) 10421.

[3] F. Pozzi, T. Di Matteo and T. Aste, Scientific Reports 3 (2013) 1665.

[4] Won-Min Song, T. Di Matteo, T. Aste, Discrete Applied Mathematics 159 (2011) 2135.

[5] Won-Min Song, T. Di Matteo, T. Aste, PLoS One 7(3) (2012) e31929.

[6] N. Musmeci, T. Di Matteo, T. Aste, in preparation (2013).

23

Invited Talk

FRUSTRATED CORRELATION STRUCTURES EMBEDDED IN

WELL-DEVELOPED STOCK MARKETS

Hiroshi Iyetomi

Department of Mathematics, Niigata University, Niigata 950-2181, Japan

We analyze daily stock prices data in S&P 500 and Tokyo Stock Exchange (TSE) to

elucidate correlations among stock price movements in the period of January 2001 through

December 2011. The correlation matrix is purified by random matrix theory and also the

market mode associated with the largest eigenvalue of the matrix is excluded from our study.

Here we take advantage of the concept of community in networks. That is, the purified

correlation matrix is regarded as the adjacency matrix for a stock correlation network. The

network thus constructed has links with weights of either sign depending on whether stocks

are correlated (positive) or anti-correlated (negative). Community is defined as a group of

comoving stocks, which are mutually related with positive correlation coefficients.

The community detection allows us to find that the stocks in S&P 500 are split up into four

communities conflicting to each other with negative correlation coefficients. In TSE, on the

other hand, there exists three communities of stocks forming a conflicting triangle. We also

report temporal change of the frustrated correlation structures embedded in both of the well-

developed markets.

24

Invited Talk

INCORPORATING DEBT INTO THE MODERN

MACROECONOMICS

Yougui Wang

School of Systems Science, Beijing Normal University, Beijing 100875, P.R. China

The current financial crisis has been recognized as a crisis of economics. In this talk, I will

argue that this financial turmoil is a crisis of macroeconomics in a strict sense and the culprit

is the bank run of expanded shadow banking system. The resulting attack on the mainstream

economics calls for reconstruction of modern macroeconomics. The deficiencies and faults in

macroeconomics are reviewed and the main challenge facing it is identified as how to

incorporate financial markets into existing canonical models. Some competing and/or

mutually complementary theoretical attempts to meet the challenge are set forth and the

stock-flow consistent model is deemed to be the effective solution. I highlight the role of debt

in the performance of complex and variable contemporary economies, which can retrospect

to even earlier than the birth of money. Once we put debt in a proper position in the new

macroeconomics building, we would better understand not only how the conventional

banking system works but also the way that the bank run of shadow banking jeopardizes the

whole financial system as well as the sustainable development.

25

Invited Talk

ESTIMATION OF FLOWS IN BUSINESES TO BUSINESS

TRANSACTION NETWORK

Misako Takayasu

Tokyo Institute of Technology, Japan

We analyze the data of business partnership in Japan and confirm that the network structure

is characterized by scale-free properties. The annual sales and transaction volumes between

pairs of firms are confirmed to be related with the underlying complex network structure. We

approximate the whole business-to-business money flow on the network by introducing a

non-linear interaction model which is formulated by the adjacency matrix of transaction

network.

Based on this model we estimate the flow of transaction for each directed link.

26

Invited Talk

MEASURING SYSTEMIC RISK THROUGH CONTAGION

EFFECT OF INDUSTRY SECTOR

Gabjin Oh

Division of Business Administration, Chosun University, Korea

Systemic risk is the risk that a negative feedback of one company is propagated to other

companies through their specific relation channel. To measure systemic risk that is

characterized by interconnected feature between economy units, we employ the generalized

variance decomposition method (GVDM) with the volatility data set of 354 companies listed

on KOSPI index. Based on the contagion behavior of industry sector or conglomerate module

in the financial market, we propose a novel approach to quantify a systemic risk and calculate

quantities of systemic risk for KOSPI market. We find that the systemic risks are closely

related to the financial crisis such as the Asian currency crisis and Subprime mortgage crisis.

In addition, we analyze whether the conglomerate is related to the systemic risk and find that

the conglomerate have influence on both the contagion effect of the real economy sectors

except construction and the systemic risk.

27

Invited Talk

LIQUIDITY, TRADE SIZE AND IMMEDIATE PRICE IMPACT

Wei-Xing Zhou

East China University of Science and Technology, China

The trade size has a direct impact on the price formation of the stock traded. Using order

book data from the Chinese market, we show that trades from filled and partially filled limit

orders have very different price impacts. The price impact of trades from partially filled

orders is constant when the volume is not too large, while that of filled orders shows power-

law behavior with an exponent 2/3. When returns and volumes are normalized by stock-

dependent averages, capitalization-independent scaling laws emerge for both types of trades.

However, no scaling relation in terms of stock capitalization can be constructed. We further

propose two regression models to investigate the influence of microscopic factors (trade size,

the bid-ask spread, the price gaps and the outstanding volumes at the bid and ask sides of the

limit order book) on the price impact of buyer-initiated partially filled trades, seller-initiated

partially filled trades, buyer-initiated filled trades and seller-initiated filled trades. We find

that they have quantitatively similar explanatory powers and these factors can account for up

to 44% of the price impacts. Large trade sizes, wide bid-ask spreads, high liquidity at the

same side and low liquidity at the opposite side will cause a large price impact. We also find

that the liquidity at the opposite side has a more influential impact than the liquidity at the

same side. Our results shed new light on the determinants of immediate price impacts.

References:

[1] W.-X. Zhou, Universal price impact functions of individual trades in an order-driven

market, Quantitative Finance 12 (8), 1253-1263 (2012).

[2] W.-X. Zhou, Determinants of immediate price impacts at the trade level in an emerging

order-driven market, New Journal of Physics 14 (2), 023055 (2012).

28

Parallel Session A

NON-GAUSSIANITY DEFINED BY AUTO-CORRELATED

RANDOM WALK

Jongwook Kim

APCTP, Korea

We relate the auto-correlation and the non-Gaussian diffusion in the newly proposed discrete

model, which is simply built by the single correlation parameter. The moment generating

function is exactly solved. The rightness of our proposal is tested using high frequency data

of Korea and U.S. stock market.

29

Parallel Session A

EXTREME VALUE STATISTICS AND RECURRENCE

INTERVALS OF NYMEX ENERGY FUTURES VOLATILITY

Wen-Jie Xiea), b), c)

, Zhi-Qiang Jianga), b)

, Wei-Xing Zhoua), b), c), d)

a) School of Business, East China University of Science and Technology, Shanghai 200237, China

b) Research Center for Econophysics, East China University of Science and Technology, Shanghai 200237, China

c) Department of Mathematics, East China University of Science and Technology, Shanghai 200237, China

d) Key Laboratory of Coal Gasification and Energy Chemical Engineering (MOE), East China University of Science and Technology, Shanghai 200237, China

Energy markets and the associated energy futures markets play a crucial role in global economies. It is of great

theoretical and practical significance to gain a deeper understanding of extreme value statistics of the volatility

of energy futures traded on the New York Mercantile Exchange (NYMEX). We investigate the statistical

properties of the recurrence intervals of daily volatility time series of four NYMEX energy futures, which are

defined as the waiting times between consecutive volatilities exceeding a given threshold . We find that the

recurrence intervals are distributed as a stretched exponential ( ) , where the exponent decreases

with increasing , and there is no scaling behavior in the distributions for different thresholds after the

recurrence intervals are scaled with the mean recurrence interval ̅. These findings are significant under the

Kolmogorov-Smirnov test and the Cramér-von Mises test. We show that empirical estimations are in nice

agreement with the numerical integration results for the occurrence probability ( ) of a next event above

the threshold within a (short) time interval after an elapsed time from the last event above . We also

investigate the memory effects of the recurrence intervals. It is found that the conditional distributions of large

and small recurrence intervals differ with each other and the conditional mean of the recurrence intervals scales

as a power law of the preceding interval ̅( ) ̅ ( ̅) , indicating that the recurrence intervals have short-

term correlations. Detrended fluctuation analysis and detrending moving average analysis further uncover that

the recurrence intervals possess long-term correlations. We confirm that the “clustering” of the volatility

recurrence intervals is caused by the long-term correlations well known to be present in the volatility. Our

findings shed new lights on the behavior of large volatility and have potential implications in risk management

of energy futures.

30

Parallel Session A

NONSTATIONARY CORRELATIONS: FROM MARKET STATES

TO RANDOM MATRIX AVERAGES

Rudi Schaefer

Faculty of Physics, University of Duisburg-Essen, Germany

We propose a definition of state for a financial market and use it to identify points of drastic

change in the correlation structure. These points are mapped to occurrences of financial crises.

In our observation time window we find a wide variety of characteristic correlation patterns,

which can be classified into several typical "market states" using a k-means clustering

analysis. Using this classification we recognize transitions between different market states

and an overall development towards new market states.

In statistical modeling, the nonstationarity of correlations can be taken into account by

averaging the multivariate normal distribution over an ensemble of random covariance

matrices. For this average we consider the Wishart ensemble and show analytical results as

well as a comparison to empirical data.

"

31

Parallel Session A

AN STATISTICAL ANALYSIS OF SHORT TERM PRICE TRENDS

SYMMETRY IN DAILY STOCK-MARKET INDEX DATA

Alejandro Raul Hernandez Montoya

University of Veracruz, Mexico

In financial time series there are periods in which the value increases or decreases

monotonically. We call those periods elemental trends and study the symmetry of their

probability distribution of their duration for the indices DJIA, NASDAQ and IPC. We try to

understand if uptrends and downtrends are governed by the same stochastic process.

32

Parallel Session A

LEVERAGE-INDUCED SYSTEMIC RISK UNDER BASLE II AND

OTHER CREDIT RISK POLICIES

Sebastian Poledna

Medical University of Vienna, Austria

We use a simple agent based model of value investors in financial markets to test three credit

regulation policies. The first is the unregulated case, which only imposes limits on maximum

leverage. The second is Basle II, which also imposes interest rate spreads on loans and

haircuts on collateral, and the third is a hypothetical alternative in which banks perfectly

hedge all of their leverage-induced risk with options that are paid for by the funds. When

compared to the unregulated case both Basle II and the perfect hedge policy reduce the risk of

default when leverage is low but increase it when leverage is high. This is because both

regulation policies increase the amount of synchronized buying and selling needed to achieve

deleveraging, which can destabilize the market. None of these policies are optimal for

everyone: Risk neutral investors prefer the unregulated case with a maximum leverage of

roughly four, banks prefer the perfect hedge policy, and fund managers prefer the unregulated

case with a high maximum leverage. No one prefers Basle II.

33

Parallel Session A

FAT TAILED RETURN DISTRIBUTION AND FRACTAL

STRUCTURE IN PROFIT LANDSCAPES

Il Gu Yi

Sungkyunkwan University, Korea

We study the origin of fractality of profit landscape in stock markets using simple trading

strategy for real financial data and artificial stock prices. The strategy we used is consists of

only two parameters p and q, and if the log return is larger (smaller) than p (-q) then we

decided to sell (buy) some stock. The parameter space lies on unit square (p, q) ∈ [0, 1] ×

[0, 1] and we discretize one into the N × N square grid and calculate the profit Π(p, q) at the

center of each grid. We find local maxima in profit landscapes are distributed in fractal-like

geometry and the number of local maxima M follows the power-law form M ∼ Na, a ≈ 1.6

for real financial data. We test the other artificial time series in order to find the origin of

fractality of profit landscape, and we find that the fat-tailed return distribution is closely

related to the exponent a ≈ 1.6 observed for real stock markets.

34

Parallel Session B

DEALER MODEL SIMULATION OF THE INTERVENTION

EVENT OF FOREIGN EXCHANGE MARKETS

Hideki Takayasu

Sony Computer Science Laboratories, and Meiji University, Japan

We pay attention to the historically largest central bank intervention event in the history of

foreign exchange market that occurred in October 2011. The bank of Japan bought USD by

JPY intensively for a few hours intermittently and the market exchage rate showed quite non-

random walk behavior. We apply a generalized dealer model to simulate this extraordinary

market state. We firstly prepare the basic dealer model which reproduces the ordinary market

fluctuations, and then we introduce an intervention dealer into the market. By tuning the

parameters of the model, we can reproduce the whole market bahavior.

35

Parallel Session B

HETEROGENEOUS COMPUTATION OF RAINBOW OPTION

PRICES USING FOURIER COSINE SERIES EXPANSION UNDER

A MIX

Aurelien Sylvain Christophe Cassagnes

The University of Tokyo, Japan

In this study we focused on comparing different heterogeneous computational designs for the

calculation of Rainbow options prices using the Fourier-cosine series expansion (FCSE)

method. We also propose a simple enough way to automatically decide ratio of load

balancing at runtime. A GPGPU implementation of the two-dimensional composite Simpson

rule free of conditional statements with some degree of loop unrolling is also introduced. We

will also show how to reduce the integration domain of coefficients appearing in the option

pricing and by doing so, achieve a substantial speed-up versus a straightforward

implementation. Major improvement in scalability when leveraging over all available

resources will serve as our empirical proof for the need of considering mixed computational

architectures.

36

Parallel Session B

BUBBLES AND CRASHES IN ARTIFICIAL DOUBLE AUCTION

MARKET

Kyubin Yim

POSTECH, Korea

In order to understand the intrinsic market microstructure properties and origin of market

bubbles and crashes, we introduce an Artificial Double Auction Market(ADAM). We make

ADAM using Agent Based Modelling(ABM) with heterogenous agents. Agents consist of

two types, such as fundamentalist and chartist. Fundamentalist makes strategy using

fundamental value which is independent on market. Chartist makes strategy using trend of

past price which is dependent on market. Specifically, chartist strategy has two options such

as optimistic and pessimistic. Optimisitic(Pessimistic) chartist forcasts that the future price

increases(decreases). And we make our trading system using double auction. Double auction

market is an order-driven market where traders set bids and asks and post market or limit

orders accordingly trader’s specific strategies. We simulate our model during long time

period and analyze the data model generated. As a result, stylized facts in real financial

market, such as market bubble and crash, fat-tails and long memory effect are observed in

market microstructure in ADAM. More specifically, chartist contributes that market goes to

bubble and crash. Whereas, when all agents in market are fundamentalists, there are no

bubble, crash, fat-tails and memory effects. Therefore,our model shows that increase of

chartist makes market extreme states such as bubble and crash.

37

Parallel Session B

COMPETITION AS PARTICLE INTERACTIONS: FROM

DUOPOLY TO GENERAL MARKET STRUCTURES

Tat-Shing CHOI

Department of Physics, The Hong Kong University of Science and Technology, Hong Kong

We study competition starting from a duopoly. There are only two players deciding their best

prices so as to optimize their profits in a small market. When they play the game recursively,

they adjust their own price according to information received from the market. By varying

the information parameters in this game, competitive states and cooperative states are

produced. We analyze this game by treating the agents as 1-D interacting particles. The

agents experience local fields due to their current prices. The market information is modeled

as an interaction arising from the price difference with their opponents. Agents move in the

price space following the equation of motion. We then generalize the model to some more

general market structures, and show how their behavior follows that in the duopoly model.

* Supported by the Research Grants Council of Hong Kong (grant numbers 605010 and

604512).

38

Parallel Session B

THE HIDDEN STRUCTURE IN URBAN ECONOMIC DIVERSITY

Hyejin Youn

Santa Fe Institute, USA

Cities are now home to a majority of the worlds population, and play a major role in many of

the most pressing challenges facing humanity such as climate change, sustainability, and

economic recovery [1]. Thus, understanding urban dynamics is crucial for effective economic,

social, and environmental policy-making. Recent availability of large, consistent datasets

enables us to study the structure and dynamics of cities in a more quantitative, mathematical

way [2,3]. Here we focus on two salient characteristics of urban areas associated with

innovation and wealth creation – population size and economic diversity [4]. By analysing

the distributions of establishments (work places), the fundamental units of economic analysis,

we show that the diversity of metropolitan areas in the United States manifests a remarkable

universal structure. This suggests that cities are indeed self-similar not only in terms of their

aggregated quantities (such as GDP, patents, crime) [3] but also in their internal abundance

structure, implying a generic mechanism for urban economic development at work. We

generalized Yule-Simon model the economic diversification diminishes its marginals once

the core economy establishes to explain the empirical distribution [5]. Multi-dimensional

allometric scaling reveals the hidden order in this developmental process. We believe our

integrated analysis sheds light on the general development process of urban economy in

association with the systematic economic merits of agglomeration and the division of labor.

[1] UN-HABITAT (United Nations Human Settlements Program), State of the worlds cities

2010/2011.

[2] M. Batty, Science 319, 769-771 (2008)

[3] L. M. A. Bettencourt, G. B. West, Nature 467, 912913 (2010).

[4] J. V. Henderson, Am Econ Rev 64, 640 (1974).

[5] H. A. Simon, Biometrika 42, 425 (1955).

39

Parallel Session B

TRADING NETWORKS, ABNORMAL MOTIFS AND STOCK

MANIPULATION

Zhi-Qiang Jiang


We study trade-based manipulation of stock prices from the perspective of complex trading

networks constructed by using detailed information of trades. A stock trading network

consists of nodes and directed links, where every trader is a node and a link is formed from

one trader to the other if the former sells shares to the latter. Specifically, three abnormal

network motifs are investigated, which are found to be formed by a few traders, implying

potential intention of price manipulation. We further investigate the dynamics of volatility,

trading volume, average trade size and turnover around the transactions associated with the

abnormal motifs for large, medium and small trades. It is found that these variables peak at

the abnormal events and exhibit a power-law accumulation in the pre-event time period and a

power-law relaxation in the post-event period. We also find that the cumulative excess

returns are significantly positive after buyer-initiated suspicious trades and exhibit a mild

price reversal after seller-initiated suspicious trades. These findings can be better understood

in favor of price manipulation. Our work sheds new lights into the detection of price

manipulation resorting to the abnormal motifs of complex trading networks.

41

Day 2


9:00 – 9:30 Invited Talk 10 Thomas Lux

9:30 – 10:00 Invited Talk 11 Aki-Hiro Sato

10:00 – 10:30 Invited Talk 12 Siew Ann Cheong

Parallel Session C, D (Contributed Talk)

11:00 – 12:30 Parallel session C Physics Building - Room 109

Parallel session D Physics Building - Room 111


1:30 – 2:00 Invited Talk 13 Stefan Thurner

2:00 – 2:30 Invited Talk 14 Jae Woo Lee

2:30 – 3:00 Invited Talk 15 Sai-Ping Li

Parallel Session E, F (Contributed Talk)

3:30 – 5:00 Parallel session E Auditorium

Parallel session F International Conference Room


5:30 – 6:00 Invited Talk 16 Victor Yakovenko

6:00 – 6:30 Invited Talk 17 Okyu Kwon

6:30 – 7:00 Invited Talk 18 Seunghwan Kim

43

Invited Talk

HUBS AND RESILIENCE: TOWARDS MORE REALISTIC

MODELS OF THE INTERBANK MARKETS

Thomas Lux

University of Kiel, Germany

This paper uses a toy financial system to study systemic risk in scale-free interbank networks.

Networks are produced according to a fitness algorithm, combined with a representation of

the balance sheets of the banks. Our generating processes for interbank networks are designed

in a way to reproduce the frequently documented features of disassortative behavior, power

laws in the degree distributions and power laws in the distribution of bank sizes. The results

show the presence of a particular shell structure affecting the spread of an endogenous shock.

44

Invited Talk

PARAMETER ESTIMATION METHODS OF A

MULTIPLICATIVE STOCHASTIC PROCESS FOR THE

ANALYSIS OF FINANCIAL TIME SERIES: AN APPLICATION

TO INFERENCE OF TAIL-RISKS

Aki-Hiro Sato

Kyoto University, Japan

This study considers Pearson type IV distribution and stochastic differential equations with

both mutually independent multiplicative and additive noises. A one-dimensional Pearson

type IV distribution can be theoretically derived as an equilibrium distribution of the

multiplicative stochastic differential equation. By using the stochastic differential equation,

we propose methods to estimate parameters from observations based on the maximum

likelihood procedure. We employ two kinds of log-likelihood functions: the one associated

with the stationary distribution and the other coming from the conditional distribution that is

calculated by solving the Fokker-Planck equation corresponding to the stochastic differential

equation. Finally we evaluate ruin probabilities under a given risk buffer and numerically

implement the proposed methods in order to assess tail risks for log-return time series of

foreign exchange rates.

45

Invited Talk

FORECASTING CRASHES IN FINANCIAL AND HOUSING

MARKETS

Siew Ann Cheong

Nanyang Technological University, Singapore

Drawing insights from statistical and nonlinear physics, we demonstrate that critical

transitions in strongly adaptive systems such as the financial and housing markets can also be

forecasted, after we understand the characters of universal precursors that must be present

prior to crashes. In this talk, we present two forecasting methods, the first based on the

statistical physics of a fusion-fission model of collective interactions [1], the second based on

the universal statistical and nonlinear physics of critical slowing down [2] preceding a crash.

We start by using the results of our time series clustering study of the Singapore Stock

Exchange (SGX) within the year 2008 to justify the use of a statistical model of fusions and

fissions. We then explain precursor signatures that accompany the growth of a giant cluster in

the fusion-fission model, before using these signatures to ‘predict’ the October 2008 crash in

the SGX. Thereafter, we turn our attention to the US housing market, where we use

signatures of critical slowing down and critical fluctuations to ‘predict’ the Asian Financial

Crisis-Technology Bubble Crisis-Subprime Loans Transition-Subprime Crisis sequence of

critical transitions.

References:

[1] Bohorquez, Juan Camilo, Sean Gourley, Alexander R. Dixon, Michael Spagat, and Neil F.

Johnson. "Common ecology quantifies human insurgency." Nature 462, no. 7275 (2009):

911-914.

[2] Scheffer, Marten, Jordi Bascompte, William A. Brock, Victor Brovkin, Stephen R.

Carpenter, Vasilis Dakos, Hermann Held, Egbert H. Van Nes, Max Rietkerk, and George

Sugihara. "Early-warning signals for critical transitions." Nature 461, no. 7260 (2009): 53-59.

46

Invited Talk

DEBTRANK-TRANSPARENCY: ELIMINATING SYSTEMIC

RISK IN FINANCIAL NETWORKS

Stefan Thurnera), b), c)

a) Section for Science of Complex Systems; Medical University of Vienna; Spitalgasse 23; A-1090; Austria,

b) Santa Fe Institute; 1399 Hyde Park Road; Santa Fe; NM 87501; USA, c) IIASA, Schlossplatz 1, A-2361 Laxenburg; Austria.

Nodes in a financial network, such as banks, cannot assess the true risks associated with

lending to other nodes in the network, unless they have full information on the riskiness of all

other nodes. These risks can be estimated by using network metrics (as DebtRank) of the

interbank liability network. With a simple agent based model we show that systemic risk in

financial networks can be drastically reduced by increasing transparency, i.e. making the

DebtRank of individual banks visible to others, and by imposing a rule, that reduces

interbank borrowing from systemically risky nodes. This scheme does not reduce the

efficiency of the financial network, but fosters a more homogeneous risk-distribution within

the system in a self-organized critical way. The reduction of systemic risk is due to a massive

reduction of cascading failures in the transparent system. A regulation-policy implementation

of the proposed scheme is discussed.

47

Invited Talk

NETWORK TOPOLOGIES OF A FINANCIAL MARKET

AROUND THE 2008 GLOBAL FINANCIAL CRISIS

Jae Woo Lee

Inha University, Korea

We consider effects of the global financial crisis in a local Korean financial market around

the 2008 global financial crisis. We analyze 185 individual stock prices belonging to the

KOSPI (Korea Composite Stock Price Index). We consider three time periods, before, during,

and after the crisis. The complex networks extract from the cross-correlation coefficients

among the stock price time series of the companies. We generate the threshold networks (TN),

the minimal spanning tees (MST), and the hierarchical network (HN) from the fully

connected cross-correlation networks. By assigning a threshold value of the cross-correlation

coefficient, we obtain the threshold networks. The power law of the degree distribution in the

threshold networks is observed in the limited range of the threshold. The threshold networks

during the crisis are fatter than other periods. The clustering coefficient of the threshold

networks follows the power law in the scaling range. We also generate the minimal spanning

trees from the fully connected correlation networks. The MST during the crisis period shrinks

in comparison to the periods before and after the crisis. The cophenetic correlation coefficient

increases during the crisis which indicates that the hierarchical structure increases in this

period. When the crisis hits the market, the companies’ behavior synchronously and their

correlations become stronger than the normal period.

48

Invited Talk

VOLATILITY CLUSTERING AND STOCHASTICITY IN

NONLINEAR TIME SERIES

Sai-Ping Li

Academina Sinica, Taiwan

Complex systems display common behavior such as volatility clustering and stochasticity in

their corresponding time series. In this talk, I'll give a brief review of these properties.

Applications to several complex systems, from financial markets to earthquakes and

cardiology will be discussed.

49

Invited Talk

STATISTICAL MECHANICS OF MONEY, INCOME, DEBT, AND

ENERGY CONSUMPTION

Victor Yakovenko

University of Maryland, USA

By analogy with the probability distribution of energy in physics, entropy maximization

results in the exponential Boltzmann-Gibbs probability distribution of money among the

agents in a closed economic system. Analysis of empirical data shows that income

distributions in USA, EU, and other countries has a well-defined two-class structure. The

majority of the population (about 97%) belongs to the lower class characterized by the

exponential ("thermal") distribution. The upper class (about 3% of the population) is

characterized by the Pareto power-law ("superthermal") distribution, and its share of the total

income expands and contracts dramatically during bubbles and busts in financial markets.

Globally, inequality in energy consumption per capita around the world has decreased in the

last 30 years and now approaches to the exponential probability distribution, in agreement

with the maximal entropy principle. All papers are available at

http://physics.umd.edu/~yakovenk/econophysics/

50

Invited Talk

BIG DATA, DATA SCIENCE AND ECONOPHYSICS

Okyu Kwon

National Institute for Mathematical Science, Korea

Recently, the big data becomes very big issue. We address what big data is and the relation

between data-driven science, which is new science paradigm as a big data era, and

econophysics. As data-driven research, we will introduce two data analysis studies. One is for

stock market data. We observed asymmetric information flow between the stock market

index and their component stocks using a transfer entropy measure. We found that the

amount of information flow from an index to a stock is larger than from a stock to an index.

This finding indicates that the market index is a major driving force in determining individual

stocks. Another one is for transportation data. We investigated the express bus flow in Korea

and its network topology. By using a gravity type model, we found that the bus flow between

cities depends on the square root of the product of the population size of city A and the

population size of city B. On the other hand, the total bus flow of a city depends on only its

population size. These different dependences on population originate from the network

property of the express bus network.

51

Invited Talk

UNDERSTANDING COMPLEXITY OF THE MICROSTRUCTURE

OF FINANCIAL MARKETS

Seunghwan Kim

POSTECH, Korea

Economic systems as extremely complex systems have recently become an interesting area of

research for physicists as well as economists. Numerous studies analyzing financial data have

been carried out to understand the nonlinearity and the complexity of economics systems

consisting of heterogeneous interacting agents, which reveals stylized facts different from

random-walk processes based on the efficiency market hypothesis.

The purpose of this talk is to understand the intrinsic characteristics of financial markets, for

example, long-term memory and clustering behavior of volatility data and interactions

between individual stocks using both the nonlinear time series analysis and the agent based

model. The statistical and nonlinear characteristics of financial systems have been analyzed,

which exhibits a strong long-term memory property in the volatility clustering. We also

propose an agent based model (ABM) to understand the intrinsic properties of abnormal

events such as the market crashes and bubbles with a focus on the artificial double auction

market (ADAM) as a trading system. We find that the chartist strategy is mainly responsible

for the fat tails in the return and the bid-ask spread time series, large fluctuations of which are

found to be closely related to the market crashes and bubbles.

52

Parallel Session C

STATISTICAL PROPERTIES, NETWORKS AND INFORMATION

FLOWS IN DERIVATIVE MARKETS

Franck Raynaud

Laboratory of Cell Biophysics, EPF Lausanne, France

We present an empirical study of future derivative markets for commodities and financial

assets. One of the main features of the future markets is the Samuelson effect which proposes

that the volatility of future prices increases when the contract reaches its expiration date. In

other words, the fluctuations of future prices decrease along the term structure.

In this study we explore different aspects of the Samuelson effect. First we examine this

pattern of volatility along the term structure as well as the distributions of prices returns. We

observe an ubiquitous behaviour for commodities as well as a segmentation of rare events

along the term structure.

Then we investigate correlation-based networks. The topology of the corresponding

minimum spanning trees reveals a chain-like organization reflecting the presence of a

Samuelson effect. Whereas introducing directionality of price movements between

commodities and financial assets will be a very important goal to reach, we present

preliminary results on shared and transferred information between maturities of the most

important commodity market, the American crude oil market.

53

Parallel Session C

CAUSALITY RELATIONS IN A NETWORK OF FINANCIAL

INSTITUTIONS

Leonidas Sandoval

Insper, Instituto de Ensino e Pesquisa, Brazil

After the Suprime Crisis of 2008 and the ongoing Credit Crisis that has been affecting

financial markets worldwide, much attention has been given to the interrelations between

banks and, in general, between financial institutions, with the aim to understand how

volatility may migrate between institutions. Most of the research uses networks based on the

lending and borrowing among banks in order to build models of propagation of crises. Such

networks, although asymmetric, do not display all the complex interrelations among financial

institutions.

The perception the market has of the stock price of a company is often a good measure of the

many complex factors that act on such firm, since it takes into account a myriad of factors

beyond the level of borrowing or lending of that company. So, we hypothesize that the value

of the stock of a firm is a good indicator of its current state and of the expectations the market

has of it. Networks based on the correlation between stocks may be built from the log-returns

of the time series of those stocks, but that is a measure that is both symmetric and not causal,

which may be used to study which stocks behave alike, but gives no results concerning

causality relations between them.

The present work uses the variations of the stocks of the 200 largest financial institutions of

the world in order to build a network based on Transfer Entropy, which is a concept

developed in Information Theory that has been used in a variety of applications, such as the

mapping the relations between regions in the human brain. Transfer Entropy is model-

independent, asymmetric and dynamic, in the sense that it can be used to establish causal

effects among nodes of a network. With some restrictions, it can be reduced to Granger

causality, although it does not have most of the limitations of the former.

54

Parallel Session C Such measure has been used by the author in the analysis of the international stock market

indices, using 92 benchmark indices of stock markets across the globe and their lagged

counterparts, with results that corroborate the idea that stock markets tend to influence one

another in a structure that depends much on the opening and closing hours of the stock

exchanges, from East to West and then back to the East, with Europe having the most

influence, contrary to the belief that the American stock market dominates the others.

In the present work, Transfer Entropy is used in order to establish a directed network of

stocks of financial institutions. Such network is then studied using the tools of network theory,

establishing which companies may be seen as most influential according to different

centrality measures. Then, the totality of stocks of financial institutions of some of the

countries that are seen today as representing the greatest risks to the international financial

market, such as Greece, Spain, Portugal, Cyprus and Italy, are added separately, and their

influences on the 200 original stocks is evaluated, pinpointing which institutions are most

affected by the financial institutions of those countries. By doing this, we try draw a map of

risk in financial institutions when affected by sudden changes in some key economies.

55

Parallel Session C

NONLINEAR DYNAMIC PROPERTIES AND NETWORK

TOPOLOGY OF GLOBAL FINANCIAL INDICES

Ashadun Nobi

Inha University, Korea

We investigated quantitative nonlinear dynamic and network topology of thirty one global

financial indices from 1998 to 2012. We calculated the Lyapunov exponents and Hurst

exponents by detrended fluctuation analysis. Network analysis has been done by minimum

spanning tree and threshold method. In addition, we constructed hierarchical network by the

average linkage hierarchical clustering algorithm and also calculated cophentic correlation

coefficient. We observed some abrupt changes of nonlinear dynamic exponents and also

network topology due to crisis and also globalization.

56

Parallel Session C

PRODUCTIVITY SHOCKS AND MONETARY POLICY IN A

TWO-COUNTRY MODEL

Tae-Seok Janga)

and Eiji Okanob)

a) Duksung Womans University, Dongyang Mirae University, Ewha Womans University, Korea

b) Chiba Keizai University, Japan

This paper examines the effects of foreign productivity shocks on a domestic monetary stance

in a new-Keynesian two-country model. The model shows that a positive productivity shock

derives up output from its natural level with a low natural interest rate. In the IS equation, a

relative rise of the foreign interest rate results in an increase of the output gap, provided that

agents take forward-looking rational expectations. This will provide downward pressures on

the foreign demand side, but put a positive impetus for the domestic output gap. This can

accelerate inflation dynamics in domestic price level. In the end, the monetary authority may

react to this situation by raising the key interest rate. By varying the degree of openness, we

show that impulse and response functions identify shock transmission mechanisms between

symmetric two economies.

57

Parallel Session C

SHORT-TERM MARKET REACTION AFTER TRADING HALTS

IN CHINESE STOCK MARKET

Hai-Chuan Xu

Tianjin University, China

In this paper, we study the dynamics of price changes, volume and ask-bid spread after the

trading halts using high-frequency data from Shenzhen Stock Exchange in China. The

method we used is similar with Mu., et al. (2010), Tóth., et al. (2009) and Zawadowski., et al.

(2006), while the definition of filter is not needed because trading halts are extreme events

intrinsically. We deal with all the trading halts of 120 stocks in Shenzhen Stock Exchange

from 2009 to 2010. Both the positive trading halts and the negative trading halts have a

reversal and decay as a power law, which forms a well-established peak. Then we divided the

trading halts into 3 groups according to their halt types, which kind of classification is also

consistent with their halt duration, we find the dynamics of abnormal fluctuation halts (last

for one hour or two hours) are very different from the stockholders meeting halts (last for one

day) and the significant matter halts(lasts for more than one day). These differences

demonstrate that the information asymmetry and traders' behavior play an influential role in

the efficiency of trading halts.

58

Parallel Session D

ANALYSIS OF OVERLAPPING COMMUNITY STRUCTURE IN A

LARGE-SCALE SOCIAL NETWORK

Hongwei Xu

The Chinese University of Hong Kong, China

Overlapping community structures are quite common in social networks. Finding out these

communities and the relationships between each other may provide a better understanding of

the structure of social network in a mesoscopic view. Here we propose an efficient method of

finding overlapping communities in huge social networks based on a statistical approach. We

first explore the local community structure around each vertex and find communities which

they belong to, then combine highly overlapped communities which are actually the same

community. We test the method on a friendship network of Sina Weibo with millions of

vertices and find tens of thousands of communities. We construct a web of communities by

exploring their relationships and show some statistical properties of the web.

59

Parallel Session D

RELEVANCE OF CONTEXT AND TIME-FRAME IN BURSTY

DYNAMICS

Hang-Hyun Jo

Aalto University, Finland

Inhomogeneous temporal processes in natural and social phenomena have been described by

bursts that are rapidly occurring events within short periods alternating with long periods of

low activity. Such a temporal process can be decomposed into sub-processes, according to

the contexts, i.e. circumstances in which the events occur. Then contextual bursts for each

sub-process are related to context-blind bursts for the original process. This requires to study

contextual bursts in real time-frame as well as in ordinal time-frame, where the real timings

of events are replaced by their orders in the event sequence. By analyzing a model of

uncorrelated inter-event times we find that contextual bursts in real time-frame can be

dominated by either context-blind bursts or contextual bursts in ordinal time-frame, or be

characterized by both. These results on the relevance of context and time-frame give insight

into the origin of bursts.

60

Parallel Session D

THE EMERGENCE OF FAIR OFFERS IN ULTIMATUM GAME

ON BIPARTITE NETWORKS

Wanting Xiong

Department of Systems Science, School of Management, Beijing Normal University, China

Simple and intriguing as it is, ultimatum game has been a widely applied analytical tool in

bargaining behaviors between two populations who periodically bargaining pairwise over

their shares of a common pie. This paper examines the dynamics of how fair offers come

about in ultimatum game within the framework of bipartite network where proposers and

responders are divided into two disjoint sets with links representing one game experience

between two agents. links only existing between different sets. Under the postulation that

both fairness motive and adaptive learning play a role in the fair behavior of human players,

we portray proposers as adaptive learners trying to maximize their payoffs and responders as

two types of agents with either pure money concern or fairness motivation. The notion of

“fairness leverage” is introduced as indicators of the influence of “tough” responders who

reject any unfair offers on the behavior group. Through experiments with different network

structures, we find that fair offers would be provided by the proposers as long as a small

proportion of the responders play “tough” against unfair offer.

61

Parallel Session D

OVERLAPPING COMMUNITY DETECTION OF MULTILAYER

NETWORKS

Sang Hoon Lee

University of Oxford, UK

We introduce a community detection method for multilayer networks generalized to consider

overlapping communities. A community detection framework incorporating multilayer

structures has been developed [1]. Both time-dependent and multiplex (different types of

interactions) networks can be represented using that framework, and we extend it by allowing

an important notion of node overlapping (nodes assigned to multiple community

memberships) [2,3,4]. The method is applied to various data sets such as temporally varying

weighted fungal networks of different species, networks of brain regions from functional

magnetic resonance imaging (fMRI) signals, and Congressperson networks from similarity in

senators’ roll-call voting patterns and cosponsoring bills.

References:

[1] P. J. Mucha, T. Richardson, K. Macon, M. A. Porter, and J.-P. Onnela, Science 328, 876

(2010).

[2] Y.-Y. Ahn, J. P. Bagrow, and S. Lehmann, Nature 466, 761 (2010).

[3] I. Psorakis, S. Roberts, M. Ebden, and B. Sheldon, Phys. Rev. E 83, 066114 (2011).

[4] J. Yang and J. Leskovec, e-print arXiv:1205.6228.

62

Parallel Session D

MONEY CIRCULATION AND CREDIT CIRCULATION

Jinzhong Guo

Department of Systems Science, School of Management, Beijing Normal University, China

In this paper, a multi-agent model has been constructed to illustrate the circulation process of

both money and credit. The system contains individual agents who play the roles of

households and business firms and a virtual bank which creates money as well as credit. As

proverbially elaborated in economics literature, money functions in the working of an

economy through its circulation. Here we argue that credit affects the economy in the same

way. As money is received and disbursed by households, it is circulating among them.

Likewise, with money is borrowed and repaid by firms, credit is also circulating among

debtors. Based on a money exchange model in which agents can be in debt, we portray how

credit circulates from one debtor to another as the bank makes advances and takes them back.

When agents expend money based on both their savings and loans borrowed from the bank,

both the money circulation and credit circulation can be tracked by following each unit of

them and characterized by the holding time of them. The simulation results show that holding

times of money and credit obey the exponential distribution. Thus the velocities of money

and credit can be expressed in terms of corresponding expected value of holding time. The

circulation velocities of money and credit obtained from simulation results are fitted very

well with those theoretical predictions. This agent-based model opens a venue to studying

how individuals’ behavior and decision influence the macroeconomic variables such as the

velocity of money and that of credit.

63

Parallel Session E

CORRELATION DYNAMICS BETWEEN PRICE RETURN AND

TRADING VOLUME

Tian Qiu

School of Information Engineering, Nanchang Hangkong University, China

How trading volume dynamically correlates with price return is investigated for the Chinese

and the United States stock markets. A positive correlation is observed for the Chinese stock

markets, while a transition from the positive correlation to the negative correlation is found

for the United States stock markets. For the United States stock markets, negative return-

volume correlations are found for several big financial crashes. Nonlocal dynamics of the

return-volume correlation shows an opposite correlation between the United States and

Chinese stock markets.

64

Parallel Session E

CORRELATION ANALYSIS IN CHINESE STOCK TRADING

NETWORK

Ming-Xia Li


The transactions of a stock over a given time period can be presented as a stock trading

network, where each trader is a node and two nodes are linked if one node sells stock shares

to the other. We construct 11472 networks over time period of five minutes using order flow

data. Strong correlations between network metrics and financial variables are observed in our

results. Furthermore, most network metrics Ganger cause financial variables.

65

Parallel Session E

GENERALIZED EPIDEMIC PROCESS ON MODULAR

NETWORKS

Kihong Chung

Department of Physics, KAIST, Daejeon 305-701, Korea

Social reinforcement and existence of communities are two salient features observed in the

emergence of collective behavior through social contacts. To investigate the combined effects

of those two features, we numerically study generalized epidemic process [1] on modular

networks with equal-sized finite communities and adjustable modularity. Our results [2] show

that the system has a continuous phase transition of the bond percolation universality class for

weak social reinforcement, whereas a discontinuous phase transition is observed for

sufficiently strong social reinforcement. We use bimodality coefficient to indicate the

boundary between different types of transition, which is shown to be dependent on the

modularity.

[1] G. Bizhani, M. Paczuski, and P. Grassberger, Phys. Rev. E 86, 011128 (2012).

[2] Kihong Chung, Yongjoo Baek, Daniel Kim, Meesoon Ha, and Hawoong Jeong (in

preparation). This work was supported by the NRF grant (No. 2011-0011550).

66

Parallel Session E

ADAPTIVE TRADING FOR ANTI-CORRELATED PAIRS OF

STOCKS

Chih-Hao Lin

Institute of Physics, Academia Sinica, Nankang, Taipei 115, Taiwan

The effect of anti-correlation between stocks in real stock market can be exploited for profit

if one can also properly set the criterion for trading that takes into account the volatility of the

stock pair. This complex problem of resource allocation for portfolio management of stocks

is here simplified to a problem of adaptive trading with an investment criterion that evolves

along with the time series of the stock data. The trend of the stock is modeled with the

standard stochastic dynamics, from which the volatility of the stock provides a criterion for

investment on a two stock portfolio that consists of the anti-correlated pair using mean

variance analysis that optimizes the return. The action of buy and sell of the two-stock

portfolio will be based on the fractional return of the pair : when the fractional return of the

pair is greater than an upper threshold of 1.01, the action “buy” is taken; and when this

fractional return is less than a lower threshold of 0.99, the action “sell” is taken. Since both

the volatility criterion for investment and the fractional return of the two-stock portfolio are

time dependent, the entire trading scheme is adaptive. Comparison of this evolving strategy

of investment with time-average performance of the respective stocks indicates a consistent

superiority.

67

Parallel Session E

PORTFOLIO SELECTION USING COMPLEX NETWORK

Seok-won Ahna)

, Gabjin Ohb)

a) Department of English Education, Chosun University, Korea b) Division of Business Administration , Chosun University, Korea

Portfolio management is an essential problem of financial investment literature. Since

Markowitz's portfolio theory introduced, the numerous methods for constructing portfolio set

have been proposed in the traditional technology such as the several clustering algorithm and

the random matrix theory, while there has been relatively little study of network approach.

We used an individual stocks listed on the KOSPI index from 01.03 2000 to 12. 31. 2012. To

make a diverse portfolio sets, we constructed the stock network with the links above given

threshold value. Because the intrinsic network properties such as degree distribution,

clustering coefficient, and etc. will change according to threshold values, we analyze a

network property through the growing pattern of the largest size module created by threshold

value. We find that the increase of the largest size module for stock market which has the

information on interactions between individual firms is much slower than that of random

network. We consider Pearson correlation in order to check the performance of proposed

method and calculated the correlation between the KOSPI and the artificial index. We find

that the correlation value was high enough in overall threshold value to regard it as a

secondary stock index. Besides, the performance of portfolio sets created through the network

approach against the investment rate of return of KOSPI index was much better within certain

parameter regions.

68

Parallel Session F

A STUDY ON THE ROCK-PAPER-SCISSORS GAME IN CO-

EVOLVING NETWORKS

CHI WUN CHOI

The Chinese University of Hong Kong, Hong Kong

In complex network, the Rock-Paper-Scissors (RPS) game is one of the interesting research

topics. In the RPS game, three strategies cyclically dominate each other. We propose and

study an Adaptive Rock-Paper-Scissor (ARPS) model, in which each agent adapts by either

rewiring an unfavourable link or switching his strategy in a co-evolving network. We study

the model by computational simulations and establishing a theory. The analytic results

capture the main features in the simulation results, including the emergence of different

phases. We proposed and studied two different rewiring schemes for selecting the rewiring

target randomly and intentionally. Results related to the probability of winning, losing and

drawing in the steady state are also studied.

69

Parallel Session F

NETWORK STRUCTURE OF NATIONAL R&D ACTIVITY IN

KOREA

Min-Woo Ahn

POSTECH, Korea

Technology is essential for our life, so R&D activity is crucial for the improvement of our

quality of life. Therefore, many agency, especially government, support R&D activity. We

confirm the structure of the R&D activity supported by government by constructing network

and observing the network structure. We used the data from the NTIS (National Technology

& science Information Service), which includes the information about the research projects

such as the title, category, and keywords, which are supported by government. First, we

construct research project network. Each node is research project, and two nodes are

connected if two projects have common keywords. From this network, we construct 6T

network. Nodes are constructed by combining research projects into one node those are

included in the same category, and two node are connected if there are connection between

two category. We will describe the property of this network and will discuss about the

meaning of the results.

70

Parallel Session F

RELATIONSHIP BETWEEN STOCK BBS AND STOCK MARKET

USING STOCK PRICES INTRA-DAY: AS CASE OF SOFTBANK

Eiichi Umehara

Tokyo City University, Japan

Internet stock BBS is a tool that can directly know the voices of other investors. According to

a previous study using daily prices in Japan, the number and the contents of messages posted

on BBS can explain volumes and volatilities of stocks, and also can explain overnight returns

though it is difficult to gain economical profit when considering a commission fee. In this

study, we analyze the relationship between the Internet stock BBS and intra-day stock prices.

Focusing on the intraday stock prices of Soft Bank, we analyze the relationship, using natural

language processing. As a result, we find that the number of messages, the number of bullish

messages, and bullishness is the coincident and lagging indicator of return, the number of

messages is the coincident and lagging indicator of the volatility, and the number of messages,

the number of bull messages, and bullishness are the leading, coincident and lagging

indicator of the volume.

71

Parallel Session F

PREDICTION OF CONGESTION SITES IN POHANG

Byounghwa Lee

POSTECH, Korea

I investigated the roads network of the city of Pohang. By using several topological methods,

I obtained the degree distribution of the network which, similarly to that of other cities,

displayed a peak around its average value. Also, basic network measures such as the average

shortest path length and clustering coefficient reflect the basic property of planar networks,

i.e. planarity, which means that the links do not cross each other. I compared roads network

in Pohang with that of other cities, by lo

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