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Pairs Trading in Cryptocurrency Markets
Název práce v češtině: Párové obchodování na kryptotrzích
Název v anglickém jazyce: Pairs Trading in Cryptocurrency Markets
Klíčová slova: párové obchodování, kointegrace, statistická arbitráž, vnitrodenní obchodování, kryptoměny, vzdálenostní metoda
Klíčová slova anglicky: pairs trading, cointegration, statistical arbitrage, intra-day trading, cryptocurrencies, distance method
Akademický rok vypsání: 2017/2018
Typ práce: bakalářská práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: prof. PhDr. Ladislav Krištoufek, Ph.D.
Řešitel: skrytý - zadáno vedoucím/školitelem
Datum přihlášení: 28.03.2018
Datum zadání: 28.03.2018
Datum a čas obhajoby: 10.09.2019 09:00
Místo konání obhajoby: Opletalova - Opletalova 26, O206, Opletalova - místn. č. 206
Datum odevzdání elektronické podoby:31.07.2019
Datum proběhlé obhajoby: 10.09.2019
Oponenti: Mgr. Martin Hronec
Kontrola URKUND:
Seznam odborné literatury
1. GATEV, Evan, GOETZMANN, William N. and ROUWENHORST, K. Geert. Pairs Trading: Performance of a Relative-Value Arbitrage Rule. [online]. 2006. [Accessed 25 May 2018]. DOI 10.1093/RFS/HHJ020. Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1095996
2. ELLIOTT, Robert J., VAN DER HOEK *, John and MALCOLM, William P. Pairs trading. Quantitative Finance [online]. June 2005. Vol. 5, no. 3, p. 271–276. [Accessed 25 May 2018]. DOI 10.1080/14697680500149370. Available from: http://www.tandfonline.com/doi/abs/10.1080/14697680500149370
3. RAD, Hossein, LOW, Rand Kwong Yew and FAFF, Robert. The profitability of pairs trading strategies: distance, cointegration and copula methods. Quantitative Finance [online]. 2 October 2016. Vol. 16, no. 10, p. 1541–1558. [Accessed 25 May 2018]. DOI 10.1080/14697688.2016.1164337. Available from: https://www.tandfonline.com/doi/full/10.1080/14697688.2016.1164337
4. BOWEN, David, HUTCHINSON, Mark C. and O’SULLIVAN, Niall. High Frequency Equity Pairs Trading: Transaction Costs, Speed of Execution and Patterns in Returns [online]. 1 March 2010. [Accessed 25 May 2018]. Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1611623
5. HUANG, Chien-Feng, HSU, Chi-Jen, CHEN, Chi-Chung, CHANG, Bao Rong and LI, Chen-An. An Intelligent Model for Pairs Trading Using Genetic Algorithms. Computational Intelligence and Neuroscience [online]. 3 August 2015. Vol. 2015, p. 1–10. [Accessed 25 May 2018]. DOI 10.1155/2015/939606. Available from: http://www.hindawi.com/journals/cin/2015/939606/
6. LINTILHAC, P. S. and TOURIN, A. Model-based pairs trading in the bitcoin markets. Quantitative Finance [online]. 4 May 2017. Vol. 17, no. 5, p. 703–716. [Accessed 8 June 2018]. DOI 10.1080/14697688.2016.1231928. Available from: https://www.tandfonline.com/doi/full/10.1080/14697688.2016.1231928
7. NYBERG, Peter and VAIHEKOSKI, Mika. A new value-weighted total return index for the Finnish stock market. Research in International Business and Finance [online]. September 2010. Vol. 24, no. 3, p. 267–283. [Accessed 8 June 2018]. DOI 10.1016/j.ribaf.2009.12.006. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0275531909000506
Předběžná náplň práce v anglickém jazyce
Research question and motivation
This thesis aims to examine the efficiency of pairs trading, a strategy mostly examined in traditional equity markets, in newly formed cryptocurrency markets. I aim to research various implementations of the pairs trading strategy, all based around the idea of mean-reversion to long-term equilibria, and how they compare to the benchmark strategy, both in and out of sample.
The thesis should explain whether pairs trading is a viable strategy in cryptocurrency markets, using methods centered around statistical arbitrage and developed for traditional equity markets.

The thesis should assess the difference between trading in cryptocurrency markets and well-established markets such as the US equity market, compared to which it has significantly lower trade volume. It should also examine the differences between approaches to modelling the pairs trading signals, as well as discuss the formation of suitable pairs in the rather unorthodox cryptocurrency market.

Gatev et al. (2006) have examined the performance of pairs trading in the US equity market and found significant overperformance over the market benchmark, with those results also supported by Elliot et al. (2005) using a wide range of approaches.

Research focusing on cryptocurrency markets is limited due to their novelty. Lintilhac and Tourin (2017) have found evidence for the feasibility of pairs trading in bitcoin markets. Evidence in general is limited when evaluating smaller markets (which are more illiquid and potentially more inefficient) rather than the US equity market. Nonetheless, Vaihekoski and Nyberg (2010) found excess returns when the strategy was applied to the Finnish market, indicating that it may indeed be applicable to markets of limited size.

I thus hope to contribute to the very limited body of literature on pairs trading in cryptocurrency markets (which are also quickly evolving, rendering dated results obsolete) with possible outreach of the findings to small markets in general.

The pairs trading strategy is centered around long-term mean-reversion found in suitable pairs, which generates trading signals upon short-term divergences from the assumed equilibria. I conduct appropriate backtesting for pairs trading based on various approaches applied in previous literature on data from selected highly liquid cryptocurrency exchanges and analyze it using statistical software executing my implementations of the selected trading strategies.

1. Introduction
2. Pairs trading
3. Data analysis
4. Results
5. Conclusion
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