Science Explorer Interactive view Map

Complex Systems and Time Series Analysis

Complex Systems and Time Series Analysis is a research topic within Economics and Econometrics. Science Explorer counts 49k research works in it since 1950. 29.6% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the application of complex systems and statistical physics concepts to understand and model financial markets. It covers topics such as multifractal analysis, agent-based modeling, power laws in wealth distribution, market correlations, and the impact of nonstationarity on time series data.

  • Econophysics
  • Multifractal Analysis
  • Agent-Based Modeling
  • Financial Fluctuations
  • Power Laws
  • Market Correlations
  • Complex Systems
  • Statistical Mechanics
  • Wealth Distribution
  • Nonstationary Time Series
Research works
49k
fractional, since 1950
In the world top 10%
14k
per year above
Top-10% rate
29.6%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+8%
the tick is no change

Which countries lead Complex Systems and Time Series Analysis research?

By volume, China and the United States publish the most (1.2k and 899 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.2k works
  2. 2 United States 899 works
  3. 3 India 389 works
  4. 4 United Kingdom 336 works
  5. 5 Italy 305 works
  6. 6 Russia 249 works
  7. 7 France 239 works
  8. 8 Germany 235 works
  9. 9 Japan 194 works
  10. 10 Brazil 163 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 28.3%United States: 21.4%India: 9.3%United Kingdom: 8.0%6 others listed: 33.0%28%largest
China1,188 · 28.3%United States899 · 21.4%India389 · 9.3%United Kingdom336 · 8.0%6 others listed1,385 · 33.0%

Shares of the rows listed above, not of the whole node.

Which institutions lead Complex Systems and Time Series Analysis research?

By volume in 2022–2025, National Research University Higher School of Economics publishes the most Complex Systems and Time Series Analysis research, followed by Beijing Jiaotong University and Southwestern University of Finance and Economics.

Who are the leading researchers in Complex Systems and Time Series Analysis?

The most-cited researchers publishing on Complex Systems and Time Series Analysis include M. Hashem Pesaran, Robert F. Engle and Tim Bollerslev.

  1. 1 M. Hashem Pesaran United States 9.1k citations
  2. 2 Robert F. Engle United States 8.7k citations
  3. 3 Tim Bollerslev United States 7.8k citations
  4. 4 Joseph E. Stiglitz United States 7.4k citations
  5. 5 Yongcheol Shin United Kingdom 6.8k citations
  6. 6 Philip S. Yu United States 6.6k citations
  7. 7 H. Eugene Stanley United States 5.5k citations
  8. 8 Witold Pedrycz Canada 5.4k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Complex Systems and Time Series Analysis research done?

The largest centres of Complex Systems and Time Series Analysis research in 2022–2025 are Beijing (China), Moscow (Russia), London (United Kingdom) and Shanghai (China).

Largest cities, 2022–2025

  1. 1 Beijing China 236 works
  2. 2 Moscow Russia 115 works
  3. 3 London United Kingdom 111 works
  4. 4 Shanghai China 107 works
  5. 5 Tokyo Japan 90 works
  6. 6 Nanjing China 83 works
  7. 7 Paris France 81 works
  8. 8 Rome Italy 66 works
  9. 9 New York United States 65 works
  10. 10 Chengdu China 59 works
See Complex Systems and Time Series Analysis on the map

Where is the best place to study Complex Systems and Time Series Analysis?

Among universities, judged by research, University of Monastir, National Research University Higher School of Economics and Southwestern University of Finance and Economics score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%25%50%75%mean 34.91%fractional works in this node (log) →share in the world top 10% →University of Monastir: 10, 64.6%National Research University Higher School of Economics: 26, 24.4%Southwestern University of Finance and Economics: 23, 17.9%Bucharest University of Economic Studies: 16, 34.2%Beijing Jiaotong University: 23, 26.8%Zhejiang Gongshang University: 12, 40.8%Nanjing University of Finance and Economics: 11, 43.8%Xi’an Jiaotong-Liverpool University: 10, 22.4%Nanjing University of Information Science and Technology: 16, 39.8%Imperial College London: 20, 34.4%University of MonastirBucharest University…National Research Un…Southwestern Univers…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 University of MonastirTunisia 65.664.6%10.7×10 -39.9%
2 National Research University Higher School of EconomicsRussia 61.224.4%9.7×26 +15.2%
3 Southwestern University of Finance and EconomicsChina 59.317.9%24.9×23 +39.0%
4 Bucharest University of Economic StudiesRomania 55.034.2%14.2×16 -3.6%
5 Beijing Jiaotong UniversityChina 52.826.8%5.8×23 +65.8%
6 Zhejiang Gongshang UniversityChina 51.740.8%11.7×12 -70.8%
7 Nanjing University of Finance and EconomicsChina 51.643.8%13.5×11 -46.5%
8 Xi’an Jiaotong-Liverpool UniversityChina 50.722.4%7.1×10 +183.3%
9 Nanjing University of Information Science and TechnologyChina 49.539.8%5.9×16 -3.3%
10 Imperial College LondonUnited Kingdom 49.434.4%3.5×20 -9.1%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Complex Systems and Time Series Analysis research growing?

Output in 2018–2022 was 8% higher than in 2013–2017, peaking in 2021. The fastest-growing topics are Complex Systems and Time Series Analysis.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.