Commodity Connectedness: Short-run Versus Long-run

• Název práce v češtině: Krátkodobá a dlouhodobá propojenost komoditních trhů
• Název v anglickém jazyce: Commodity Connectedness: Short-run Versus Long-run
• Klíčová slova: Propojenost, komoditní trh, frekvence, volatilita
• Klíčová slova anglicky: Connectedness, commodity market, frequency, volatility
• Akademický rok vypsání: 2016/2017
• Typ práce: bakalářská práce
• Jazyk práce: angličtina
• Ústav: Institut ekonomických studií (23-IES)
• Vedoucí / školitel: doc. PhDr. Jozef Baruník, Ph.D.
• Řešitel: skrytý - zadáno vedoucím/školitelem
• Datum přihlášení: 03.05.2017
• Datum zadání: 03.05.2017
• Datum a čas obhajoby: 12.06.2018 09:00
• Místo konání obhajoby: Opletalova - Opletalova 26, O206, Opletalova - místn. č. 206
• Datum odevzdání elektronické podoby: 09.05.2018
• Datum proběhlé obhajoby: 12.06.2018
• Oponenti: Mgr. Petra Buzková

Seznam odborné literatury

Bibliography

Diebold, F. X. and K. Yilmaz (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting 28 (1), 57-66.

Diebold, F. X. and K. Yilmaz (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics 182 (1), 119-134.

Francis X. Diebold and Kamil Yilmaz (2015). Financial and Macroeconomic Connectedness, A Network Approach to Measurement and Monitoring. Oxford University Press.

Francis X. Diebold, Laura Liu and Kamil Yilmaz(2016). Commodity Connectedness. University of Pennsylvania.

John H. Cochrane (2005). Time Series for Macroeconomics and Finance. University of Chicago.

Ortu, F., A. Tamoni, and C. Tebaldi (2013). Long-run risk and the persistence of consumption shocks. Review of Financial Studies 26 (11), 2876-2915.

Josef Baruník and Tomáš Křehlík (2017). Measuring the frequency dynamics of financial connectedness
and systemic risk. Working paper, Institute of Economic Studies, Charles Univerzity.

Josef Baruník and Tomáš Křehlík (2017). Cyclical properties of supply-side and demand-side
shocks in oil-based commodity markets. Forthcoming in Energy Economics.

Předběžná náplň práce

Outline

Introduction - Introduction of the topic and outline of the thesis.

Literature review – Review of literature related to the topic.

Introduction to Vector autoregressive models (VAR) - In this part the VAR model is defined and MA representation of VAR models is explained.

Establishing measure of connectedness - We will explain how to measure the connectedness of commodities using MA representation of VAR.

Establishing spectral representation of the connectedness measure – In this part the overall measure of connectedness that was introduced in the previous part is decomposed on short-term and long-term components.

Data analysis – The method of connectedness measure is applied to price time series data of the commodity market.

Conclusion – Summary of data analysis, significance of obtained result, implications of the result.

Předběžná náplň práce v anglickém jazyce

Research question and motivation

This thesis analyses the short-term and long-term connectedness of the commodity market. The commodity market is essential for many countries that export or import commodities, especially for less developed countries. In a globalized world which tends to be more and more connected, risk management and regulators need to understand how volatility transmit through the commodity market. The existing literature uses the causal measure of connectedness \citet{Diebold2012} \citet{Diebold2014} based on variance decomposition but these methods are not sufficient because they do not distinguish between short and long persistence of connectedness. There are several reasons why connectedness with short persistence could be different form connectedness with longer persistence. Essentially, agents in the commodity market operate on a different time horizon, since some of them hold short-term positions while other agents hold long-term positions and this distinction causes different connectedness at various time horizons. In this thesis, We will focus on connections among different commodity sectors and stock markets. We will asses connectedness among commodities and financial markets in period before and after the financial crisis 2008-2009 focusing on how persistent the volatility transmission was. In line with previous findings we expect that volatility of commodity market was significantly effected by stock market in the years 2008-2009.

Contribution

The thesis could contribute to a better understanding of the interconnections of traded commodities. For investors that operate on a longer time horizon it is crucial to distinguish between short-term connectedness which is negligible for them and connectedness with a long-term effect.

Methodology

The methods for frequency decomposition of price time series data of the commodity market will be based on methods of the connectedness decomposition in frequency domain proposed by Baruník and K\v{r}ehlík in their paper Measuring the frequency dynamics of financial connectedness and systemic risk (2018). The time series data will be processed by a computer program in R. which calculates an estimate of the short-term and long-term connectedness of commodities.