Technical Trading Rules Empirical Evidence from Future Data

Business & Finance, Finance & Investing, Banks & Banking
Cover of the book Technical Trading Rules Empirical Evidence from Future Data by Philipp Jan Siegert, GRIN Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Philipp Jan Siegert ISBN: 9783638432443
Publisher: GRIN Publishing Publication: October 27, 2005
Imprint: GRIN Publishing Language: English
Author: Philipp Jan Siegert
ISBN: 9783638432443
Publisher: GRIN Publishing
Publication: October 27, 2005
Imprint: GRIN Publishing
Language: English

Master's Thesis from the year 2005 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: A, Sophia Antipolis Campus (France); SKEMA Business School (Global Finance Chair), 27 entries in the bibliography, language: English, abstract: Most banks and the recently upcoming hedge fund industry rely to a different extent on technical trading rules and technical analysis. The fact that these technical trading rules yield superior returns in practice raises several questions that will be examined in the thesis. First, one of the most crucial questions is in which assets technical trading rules perform extraordinarily well. This analysis is based on a risk-return approach with an assessment of the negative standard deviation of each asset as a risk indicator. Second, the statistical significance of technical trading is examined by using a simulation method known as bootstrap. Third, null models are simulated to answer the question to what extent autoregressive models and GARCH models are able to capture the dependencies in the time series. Finally, a rule optimizer is used to assess if any rule parameters yield superior returns over a wide range of assets. We find that under a risk-return perspective trading rules look very attractive as most rules are able to significantly reduce the negative standard deviation compared to a buy-and-hold strategy. However, not all rules are able to outperform a simple buy-and-hold strategy in terms of absolute return. Statistical significance is generally weak and only some rules can be qualified as highly statistically significant. We do not find much evidence that autoregressive and GARCH null models perform well in capturing the dependencies that lead to superior returns of technical trading rules. With respect to trading rule parameters we find that shorter rules generally perform better when trading costs are not considered and that currencies benefited from a larger standard deviation trading band.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Master's Thesis from the year 2005 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: A, Sophia Antipolis Campus (France); SKEMA Business School (Global Finance Chair), 27 entries in the bibliography, language: English, abstract: Most banks and the recently upcoming hedge fund industry rely to a different extent on technical trading rules and technical analysis. The fact that these technical trading rules yield superior returns in practice raises several questions that will be examined in the thesis. First, one of the most crucial questions is in which assets technical trading rules perform extraordinarily well. This analysis is based on a risk-return approach with an assessment of the negative standard deviation of each asset as a risk indicator. Second, the statistical significance of technical trading is examined by using a simulation method known as bootstrap. Third, null models are simulated to answer the question to what extent autoregressive models and GARCH models are able to capture the dependencies in the time series. Finally, a rule optimizer is used to assess if any rule parameters yield superior returns over a wide range of assets. We find that under a risk-return perspective trading rules look very attractive as most rules are able to significantly reduce the negative standard deviation compared to a buy-and-hold strategy. However, not all rules are able to outperform a simple buy-and-hold strategy in terms of absolute return. Statistical significance is generally weak and only some rules can be qualified as highly statistically significant. We do not find much evidence that autoregressive and GARCH null models perform well in capturing the dependencies that lead to superior returns of technical trading rules. With respect to trading rule parameters we find that shorter rules generally perform better when trading costs are not considered and that currencies benefited from a larger standard deviation trading band.

More books from GRIN Publishing

Cover of the book Syntactic Movements by Philipp Jan Siegert
Cover of the book Population and Security: Water disputes - on the way to a major global problem? by Philipp Jan Siegert
Cover of the book Microfinance Institutions in Ghana: Analysis of the Kraban Support Foundation (KSF) by Philipp Jan Siegert
Cover of the book Environmental Auditing by Philipp Jan Siegert
Cover of the book Transformations and changes in contemporary Ukrainian femininity models by Philipp Jan Siegert
Cover of the book Comparison of adverts in typical men and women magazines by Philipp Jan Siegert
Cover of the book The Present of the Past - Drafts of Memory in T.S. Eliot's 'The Waste Land' and Toni Morrison's 'Beloved' by Philipp Jan Siegert
Cover of the book Comparative Perspectives on Imperialism and Empire in Late Imperial Russia by Philipp Jan Siegert
Cover of the book eOctopus in Hong Kong - A feasibility study by Philipp Jan Siegert
Cover of the book Media in cuba by Philipp Jan Siegert
Cover of the book Fashioning Gender in Texts from Joseph Addison's Spectator by Philipp Jan Siegert
Cover of the book Code-switching in computer-mediated communication - a case study of croatian-english discussion forums by Philipp Jan Siegert
Cover of the book Effect of maternal employment on children's home and emotional adjustment by Philipp Jan Siegert
Cover of the book Process Virtualization Theory in the Public Sector: A Scale Development Study by Philipp Jan Siegert
Cover of the book Sport stocks. Investment risk or opportunity? by Philipp Jan Siegert
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy