Volatility spillovers between Cocoa Futures markets and selected currency pairs
| Název práce v češtině: | Přelévání volatility mezi termínovými kontrakty na kakao a vybranými měnovými páry |
|---|---|
| Název v anglickém jazyce: | Volatility spillovers between Cocoa Futures markets and selected currency pairs |
| Klíčová slova anglicky: | cocoa markets, cocoa futures, currency pairs, commodity markets, volatility spillovers, GARCH, volatility modelling |
| Akademický rok vypsání: | 2021/2022 |
| Typ práce: | bakalářská práce |
| Jazyk práce: | angličtina |
| Ústav: | Institut ekonomických studií (23-IES) |
| Vedoucí / školitel: | PhDr. František Čech, Ph.D. |
| Řešitel: | skrytý - zadáno vedoucím/školitelem |
| Datum přihlášení: | 25.08.2022 |
| Datum zadání: | 25.08.2022 |
| Datum a čas obhajoby: | 10.09.2024 09:00 |
| Místo konání obhajoby: | Opletalova, O314, místnost. č. 314 |
| Datum odevzdání elektronické podoby: | 23.07.2024 |
| Datum proběhlé obhajoby: | 10.09.2024 |
| Oponenti: | Mgr. Lenka Nechvátalová |
| Seznam odborné literatury |
| Bibliography
Adusei Jumah, Robert M. Kunst, The effects of dollar/sterling exchange rate volatility on futures markets for coffee and cocoa, European Review of Agricultural Economics, Volume 28, Issue 3, 1 October 2001, Pages 307–328, https://doi.org/10.1093/erae/28.3.307 Aielli, G. P. and M. Caporin (2014). Variance clustering improved dynamic conditional correlation MGARCH estimators. Computational Statistics & Data Analysis 76(C), 556–576. Andersen, T. G., T. Bollerslev, P. Christoffersen, and F. X. Diebold (2006). Practical volatility and correlation modeling for financial market risk man- agement. In M. Carey and R. M. Stulz (Eds.), The Risks of Financial Insti- tutions, pp. 513–548. University of Chicago Press. Antonakakis, N., Kizys, R., 2015. Dynamic spillovers between commodity and currency markets. Int. Rev. Financ. Anal. 41, 303–319. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31(3), 307–327. Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics 72(3), 498–505. Breusch, T. S. and A. R. Pagan (1979). A simple test for heteroskedasticity and random coefficient variation. Econometrica 47(5), 1287–1294. Cifarelli, G. and G. Paladino (2015). Hedging vs. speculative pressures on com- modity futures returns. MPRA Paper No. 41624, Dipartimento di Scienze Economiche, Università degli Studi di Firenze and Economics Department LUISS University of Rome. CME Group. (2015). CME Europe’s Cocoa Futures Seeks to Answer the Industry’s Concerns. https://www.ghfinancials.com/application/files/3414/3429/2710/2015-06-cme-cocoa-futures.pdf Dornbussch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy Vol. 84, No. 6 (Dec., 1976), pp. 1161-1176 Engle, R. F. (2002). Dynamic conditional correlation: A simple class of mul- tivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics 20 (3), 339–350. Engle, R. F. and V. K. Ng (1991). Measuring and testing the impact of news on volatility. NBER Working Paper No. 3681, National Bureau of Economic Research. Elfakhani, S. and Wionzek, R.J. (1997). Intermarket spread opportunities between Canadian and American agricultural futures. International Review of Economics & Finance 6: 361-377 Stan Hurn, Vance Martin, Peter Phillips and Jun Yu (2021): Financial Econometric Modelling Lin, J. W., M. Najand, and K. Yung (1994). Hedging with currency futures: OLS vs. GARCH. Journal of Multinational Financial Management 4(1), 45–67. Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica 59(2), 347–370. Silvennoinen, A. and T. Teräsvirta (2009). Multivariate GARCH models. In T. Mikosch, J.-P. Kreiß, R. Davis, and T. Andersen (Eds.), Handbook of Financial Time Serie, pp. 201–229. Springer. Tse, Y. and A. Tsui (2002). A multivariate generalized autoregressive condi- tional heteroscedasticity model with time-varying correlations. Journal of Business & Economic Statistics 20(3), 351–362. |
| Předběžná náplň práce v anglickém jazyce |
| Research question and motivation
The goal of my bachelor thesis is to study the volatility transmission and spillover dynamics across Cocoa Futures markets and relevant currency pairs. The ambition of this research is to thoroughly map these dynamics and present the results in such a form that could be beneficial for parties involved in cocoa markets, such as policymakers, traders, exporters, the cocoa industry, and other market participants. One of the specificities of the cocoa industry resides in the extreme concentration of the cocoa beans production capacity, with Côte d'Ivoire, Ghana, Cameroon, and Nigeria accounting for approximately two-thirds of the world's production. This fact is reflected in the volatility of the cocoa beans price, which is unusually high, even by the standards of commodity markets, thus posing a significant challenge from the risk management standpoint. At the same time, the export revenues and the cocoa industry have a vital role in the local economies, and setting the right economic policies is crucial for their successful development. The empirical part first examines the dynamics between the two well-established long-standing Cocoa Futures contracts traded on the Intercontinental Exchange (ICE). London Cocoa Futures are denominated in the British pound (GBP) and have delivery locations in various areas across Western Europe. Cocoa Futures, also traded on the ICE, are denominated in the United States dollar (USD), and their delivery locations are situated on the East Coast of the United States. These two contracts continue to retain their position as the global benchmarks for the global cocoa market and the pricing of the physical cocoa. The dominant position of these contacts remained unscathed even after the attempt of CME Europe to introduce the first Euro-denominated cocoa futures contract. This contract aimed to answer the industry’s concerns and the fact that, as of 2015, 38% of the world’s cocoa beans were ground in Europe and the Euro (EUR) was the accounting currency for most of the cocoa industry in Europe (CME Group, 2015). Furthermore, EUR is the currency base for some of the key growers, which are using the CFA Franc (common currency in a number of Central/West African countries). Improving the prospect for the convergence between the futures price and the underlying market was among the main goals that the newly established contract was supposed to achieve. However, despite initial market support, the contract failed to attract sufficient liquidity, and the position of the ICE contracts remained unchallenged. Aside from exploring the dynamics between the futures contracts, the main focus of the thesis is to study the volatility spillover channels between the futures contracts and selected currency pairs. The currency pairs in question will be selected based on their overall importance to the financial markets and their relevance to the cocoa market. The former group mainly consists of currency pairs combining EUR, USD, and GBP. In addition to their overall importance to the financial markets, USD and GBP are the currencies in which the contracts we intend to study are denominated. The need for the inclusion of the EUR stems from the vital role it has in the European cocoa industry and from the fact that the CFA franc is pegged to the EUR. The latter group consists of currency pairs combining important world currencies and the local currencies of the cocoa beans producing countries such as Ghana, Nigeria, Indonesia, Brazil, Peru, and Colombia. The potential use of currency pairs involving the latter group needs to be treated with caution, as those are often countries with a history of dramatic economic developments and significant foreign exchange interventions. Economies, which are affected the most by the cocoa markets developments, can be found in the Central/West African region. Côte d'Ivoire and Ghana together account for more than 60% of the world's cocoa beans production. Cocoa products make up a significant part of their exports (OEC), and understanding the cocoa markets and the related dynamics is absolutely crucial for their well-being. Therefore, the study of the volatility spillovers may yield benefits for the involved parties. Firstly, by producing beneficial results with respect to managing and mitigating related risks. Secondly, by helping to institute economic policies aiming at optimizing export revenues and ultimately enhancing the welfare in these underdeveloped parts of the world. Contribution To this day, the literature covering this topic remains relatively limited. For example, Jumah and Kunst (2001) explore the effects of the USDGBP forward exchange rate on the volatility of coffee and cocoa futures markets, and Antonakakis and Kizys (2015) study dynamic spillover effects between various commodities and currencies. However, to my knowledge, there is no existing literature that would explore the dynamics between Cocoa Futures markets and currency pairs with an emphasis on relevance to the countries producing and exporting cocoa beans and products. The findings of the research could therefore prove beneficial to the governments in order to institute better economic policies and to all cocoa market participants with the aim of improving the management of the related risks. Methodology In order to perform the empirical research, we are going to use daily sampled time-series data for the US Cocoa Futures (USD) and London Cocoa Futures (GBP), traded on the ICE in respective currencies, and daily sampled time-series data of the spot exchange rates for the currency pairs in question. The time interval of our primary focus will be 2009-2020, for which the required data is available. This particular time interval was chosen to fit between the Great Financial Crisis and the Covid Recession in order to avoid market shocks of extreme nature. However, in most cases, the available time interval for the data is even wider. Therefore adjustments to the considered time interval cannot be ruled out. The prices of the futures contracts may be transformed into a single currency (USD) for the fundamental preliminary analysis to ensure better comparability between the contracts. However, this step will be avoided for the main empirical analysis because this kind of standardization would debase the data for the study of the specific volatility components of the contracts. To analyze the effects on volatility and the spillover channels, the family of Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models will be used. Outline Abstract Introduction Literature review Theoretical concepts Cocoa markets overview Data Description Methodology Preliminary Analysis Empirical Analysis Discussion of results and derived implications Conclusion |