2014/03/04 by Andreas Joseph, Joseph, Andreas, Irena Vodenska +5
Economics, Econometrics and Finance · Physics and Astronomy · #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Economics and business #FOS: Physical sciences #General Finance (q-fin.GN) #Methodology (stat.ME) #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.1403.0848
openalex publication_date 2014/03/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The combination of the network theoretic approach with recently available\nabundant economic data leads to the development of novel analytic and\ncomputational tools for modelling and forecasting key economic indicators. The\nmain idea is to introduce a topological component into the analysis, taking\ninto account consistently all higher-order interactions. We present three basic\nmethodologies to demonstrate different approaches to harness the resulting\nnetwork gain. First, a multiple linear regression optimisation algorithm is\nused to generate a relational network between individual components of national\nbalance of payment accounts. This model describes annual statistics with a high\naccuracy and delivers good forecasts for the majority of indicators. Second, an\nearly-warning mechanism for global financial crises is presented, which\ncombines network measures with standard economic indicators. From the analysis\nof the cross-border portfolio investment network of long-term debt securities,\nthe proliferation of a wide range of over-the-counter-traded financial\nderivative products, such as credit default swaps, can be described in terms of\ngross-market values and notional outstanding amounts, which are associated with\nincreased levels of market interdependence and systemic risk. Third,\nconsidering the flow-network of goods traded between G-20 economies, network\nstatistics provide better proxies for key economic measures than conventional\nindicators. For example, it is shown that a country's gate-keeping potential,\nas a measure for local power, projects its annual change of GDP generally far\nbetter than the volume of its imports or exports.\n