Miroslav Svoboda – Masaryk University, Faculty of Economics and Administration, Department of Finance, Lipová 41a, 603 00 Brno, Czech Republic
Martina Sponerová – Masaryk University, Faculty of Economics and Administration, Department of Finance, Lipová 41a, 603 00 Brno, Czech Republic
DOI: https://doi.org/10.31410/ITEMA.2020.121
4th International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2020, Online/virtual, October 8, 2020, CONFERENCE PROCEEDINGS published by the Association of Economists and Managers of the Balkans, Belgrade; Printed by: SKRIPTA International, Belgrade, ISBN 978-86-80194-36-3, ISSN 2683-5991, DOI: https://doi.org/10.31410/ITEMA.2020
Abstract
Random strategy is currently an interesting alternative to traditional trading of financial instruments. The paper builds on existing research into the trading of investment instruments through random strategy and strategies based on technical analysis. The highly liquid USD/CAD currency pair was chosen for the US market research. We analyze five years of data, and in every intraday trading session, only a single position will be opened. Technical analysis strategy uses essential indicators such as Bollinger Bands, relative strength index (RSI), moving averages (MA) and other. Every trading position will have the risk-reward ratio (RRR) 3 to 1. In addition, another trading positions on the USD/CAD currency pair will be opened without technical analysis. The time of entry into position will be indicated randomly with a similar risk-reward ratio (RRR) 3 to 1. The aim of this paper is to assess which of the above strategies is more suitable for the investor. In other words, this paper aims to compare the strategy of technical analysis and the random strategy in intraday trading concerning the profitability of these trades. We expect that a random strategy will be more suitable for the investor in many points.
Keywords
Investment decisions, Foreign exchange markets, Moving average, Backtesting, US market, Relative strength index.
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