Experimental Results Presented In New Book Show That Data Mining Is an Effective Approach for Discovering Useful Rules - 'Evidence-Based Technical Analysis.DUBLIN, Ireland -- Research and Markets (http://www.researchandmarkets.com/reports/c47135) has announced the addition of Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference Inferential statistics or statistical induction comprises the use of statistics to make inferences concerning some unknown aspect of a population. It is distinguished from descriptive statistics. to Trading Signals to their offering. Evidence-Based Technical Analysis is a breakthrough book in that it rigorously applies the scientific method and recently developed statistical tests to determine the true effectiveness of trading strategies, rules or systems discovered by data mining. Traditional technical analysis - as currently practiced - is more like a faith-based folk art folk art, the art works of a culturally homogeneous people produced by artists without formal training. The forms of such works are generally developed into a tradition that is either cut off from or tenuously connected to the contemporary cultural mainstream. than a science, the author asserts. These subjective interpretive methods cannot be back-tested or evaluated, yet many believe that they are effective. The author explains that because of various cognitive biases Cognitive bias is distortion in the way humans perceive reality (see also cognitive distortion). See also the lists of thinking-related topics. Some of these have been verified empirically in the field of psychology, others are considered general categories of bias. and illusions, such as hindsight bias "Hindsight" redirects here. For other uses, see Hindsight (disambiguation). Hindsight bias is the inclination to see events that have occurred as more predictable than they in fact were before they took place. , illusory correlations, etc., people often adopt beliefs that are unsupported by evidence or even contradicted by evidence. For example, the famous head and shoulders pattern - a cornerstone of traditional TA when tested objectively - has been shown to have no predictive power The predictive power of a scientific theory refers to its ability to generate testable predictions. Theories with strong predictive power are highly valued, because the predictions can often encourage the falsification of the theory. . Yet many TA texts and most TA experts believe in the pattern's efficacy. To move technical analysis forward, the author proposes a new type of technical analysis, which he calls: evidence-based technical analysis or EBTA EBTA European Brief Therapy Association EBTA European Bobath Tutors Association EBTA Electronic Bonding Trouble Administration EBTA Evaluasi Belajar Tahap Akhir EBTA Evidence-Based Technical Analysis EBTA Employer Based Training Accreditation . Unlike traditional technical analysis, EBTA is restricted to objective methods whose historical profitability can be quantified and then rigorously scrutinized. The author provides a new statistical methodology specifically designed for evaluating the performance of rules that are discovered by data mining, a process in which many rules are back-tested and the best performing rule(s) is selected. Experimental results presented in the book show that data mining is an effective approach for discovering useful rules. However, the historical performance of the best rule (s) is upwardly biased - a combined effect of randomness and data mining. Thus new statistical tests are needed to make reasonable inferences about the future profitability of rules discovered by data mining. Most importantly Adv. 1. most importantly - above and beyond all other consideration; "above all, you must be independent" above all, most especially , in a data mining case study the author evaluates more than 6,400 signalling rules applied to the S&P500 Index using these new tests. For technical analysts and traders, the book is a wake-up call to abandon subjective, interpretive methods and embrace an approach that is scientifically and statistically valid. For other traders, the rigorous testing of trading signals/rules may make their data mining efforts more productive and stimulate the development of new systems, signalling rules. Author information David Aronson is an adjunct professor at Baruch College Baruch College: see New York, City University of. , where he teaches a graduate-level course in technical analysis. He is also a Chartered Market Technician Chartered Market Technician (CMT) is a professional designation that confirms proficiency in technical analysis of the financial markets. To hold the designation, membership in the Market Technicians Association is required. and has published articles on technical analysis. Previously, Aronson was a proprietary trader In a financial institution, a proprietary trader ( also known as a securities trader ) is a trader who trades securities on the account of the institution he/she works for, not for client-based business. and technical analyst for Spear Leeds & Kellogg. He founded Raden Research Group, a firm that was an early adopter of data mining within financial markets. Prior to that, Aronson founded AdvoCom, a firm that specialized in the evaluation of commodity money managers and hedge funds, their performance, and trading methods. Content Outline: Acknowledgments. About the Author. Introduction. PART I Methodological, Psychological, Philosophical, and Statistical Foundations. CHAPTER 1 Objective Rules and Their Evaluation. CHAPTER 2 The Illusory Validity of Subjective Technical Analysis. CHAPTER 3 The Scientific Method and Technical Analysis. CHAPTER 4 Statistical Analysis. CHAPTER 5 Hypothesis Tests and Confidence Intervals. CHAPTER 6 Data-Mining Bias: The Fool's Gold fool's gold: see pyrite. of Objective TA. CHAPTER 7 Theories of Nonrandom Price Motion. PART II Case Study: Signal Rules for the S&P 500 Index. CHAPTER 8 Case Study of Rule Data Mining for the S&P 500. CHAPTER 9 Case Study Results and the Future of TA. APPENDIX Proof That Detrending Is Equivalent to Benchmarking Based on Position Bias. Notes Index For more information visit http://www.researchandmarkets.com/reports/c47135 |
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