Browsing by Subject "Technical analysis"
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ItemThe effectiveness of confirming indicators: a case study of Stocks in ThailandThis paper developed a model that tested trading signals (including double and triple indicators) on the security traded in the Stock Exchange of Thailand (SET). One indicator from each of the six groups of technical indicators, including MACD, Parabolic SAR (PSAR), RSI, Twiggs Money Flow, Volume Oscillator, and Bollinger Bands, were tested in order to determine whether their use could generate excess returns for investors. PSAR was the most profitable indicator as it alone or when used in combined with other indicators could generate excess returns. The findings showed that the AND function could be use to combine trading signals but with proper interpretation of inputs. Findings also showed that combined indicators increase abnormal profits above individual indicators. A combined indicators model had the best performance in terms of End of Period Wealth and the least downside risk which was measured by Maximum Drawdown. The significance of this research is that it identifies confirming indicators that can be used effectively to generate excess profits, although the findings do have some limitations which is discussed in this paper however further study on similar concept is highly recommended.
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ItemTrading Profits of Simple Moving Average Strategies for Major Currency Pairs( 2018-05-25) Panwichit, K. ; Sethjinda, P. ; Boonchuaymetta, E.This research studied the effectiveness of simple moving average rules in generating trading profits on major currency pairs which are AUD, EUR, GBP, NZD, CAD, CHF and JPY during 2013 – 2016. The test covered 50-Day moving average, 200-Day moving average, 10/50-Day moving average, 10/200-Day moving average and 50/200-Day moving average. The study revealed that trading based on 10/50-Day moving average resulted in superior returns, among all trading rules with average return generated for all currencies during the sample period of 4.21% per year, followed by 50/200-Day moving average with average return for all currencies of 1.26% per year. In comparison to the return generated from buy and hold strategy, the study suggested that simple moving average strategies generated higher average return and reduced the magnitude of trading losses. Given that the study assumed no transaction cost or SWAP fee, further studies should be conducted on the following areas: 1) comparative analysis of trading profit generated for ‘in-sample’ and ‘out-of-sample’ datasets, 2) comparative analysis of trading profits after taking transaction cost into account, and 3) comparative analysis of trading profits between moving average and other technical trading rules, commonly used by FX Traders.