Institute of Information Theory and Automation

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Dynamic networks and financial decision making

Consumers, firms, and countries are creating ever intensifying linkages in a world economy. Monitoring these intimate network connections between many economic variables is central for risk measurement and management, central bankers, and policy makers. The team at the departement is interested in uncovering fundamental sources of network connections in which relationships vary over different horizons and time, and shock propagating over these horizons creates linkages. Contributions that covers this line of our research are important for financial decision making as well as understanding how real economy interacts with financial sector.

We contribute to the literature with a measures of time-frequency dependent network connectedness to estimate networks arising due to heterogeneous responses to shocks at short, medium, or long run cycles. The methodology opens new routes for measurement of linkages [1]. The paper became one of the most cited papers in the journal.

In addition, we document new stylized facts about cyclical properties of the transmission mechanism of the oil-based commodity markets using the network measures [2], and we study asymmetric networks arising due to different shocks in response to good and bad news creating different uncertainty [3 , 4, 5]. Further the team brings new methodology to forecast entire return distribution that is more informative in addition to commonly estimated mean and variance forecasts [6].

Papers/Working Papers:

Uncertainty Network Risk and Currency Returns. M.BabiakJ. Barunik. preprint draft (Jan 2021).

Dynamic industry uncertainty networks and the business cycleJ. Barunik, M. Bevilacqua and R. Faff. preprint draft (Jan 2021).

Dynamic Networks in Large Financial and Economic Systems. J Barunik, M. Ellington. revised (2021).

Dynamic Network Risk J Barunik, M.Ellington. submitted (2020). 

  1. Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk. J. Barunik, T. Krehlik. Journal of Financial Econometrics, 16(2), 2018, pp. 271-296.
  2. Cyclical properties of supply-side and demand-side shocks in oil-based commodity markets. J. Barunik, T. Křehlik. Energy Economics, 65(1), 2017, pp. 208-218.
  3. Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets. J. Barunik, E. Kočenda, Energy Journal, 40(2), 2019, pp. 157-174.
  4. Asymmetric volatility connectedness on the forex market. J. Barunik, E. Kočenda, L. Vacha. Journal of International Money and Finance, 77(1), 2017, pp. 39-56. 
  5. Volatility Spillovers Across Petroleum Markets. J. Barunik, E. Kočenda, L. Vacha. Energy Journal, 36(3), 2015, pp. 309-329.
  6. Forecasting dynamic return distributions based on ordered binary choice. S. Anatolyev, J. Barunik. International Journal of Forecasting ,35(3), 2019, pp. 823-835.

 

 

 

 

2021-03-06 23:00