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Mathematical techniques in financial market trading /
The present book contains much more materials than the author's previous book "The Science of Financial Market Trading". Spectrum analysis is again emphasized for the characterization of technical indicators employed by traders and investors. New indicators are created. Mathematical a...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hackensack, N.J. :
World Scientific,
©2006.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Mak, Don K. | |
| 245 | 1 | 0 | |a Mathematical techniques in financial market trading / |c Don K. Mak. |
| 260 | |a Hackensack, N.J. : |b World Scientific, |c ©2006. | ||
| 300 | |a 1 online resource (xvi, 304 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references (pages 297-300) and index. | ||
| 505 | 0 | |a Cover -- Contents -- Preface -- 1. Introduction -- 2. Scientific Review of the Financial Market -- 2.1 Econophysics -- 2.1.1 Log-Normal Distribution of Stock Market Data -- 2.1.2 Levy Distribution -- 2.1.3 Tsallis Entropy -- 2.2 Non-Randomness of the Market -- 2.2.1 Random Walk Hypothesis and Efficient Market Hypothesis -- 2.2.2 Variance-Ratio Test -- 2.2.3 Long-Range Dependence? -- 2.2.4 Varying Non-Randomness -- 2.3 Financial Market Crash -- 2.3.1 Log-Periodicity Phenomenological Model -- 2.3.2 Omori Law -- 3. Causal Low Pass Filters -- 3.1 Ideal Causal Trending Indicator -- 3.2 Exponential Moving Average -- 3.3 Butterworth Filters -- 3.4 Sinc Function n = 213; -- 3.5 Sinc Function n = 413; -- 3.6 Adaptive Exponential Moving Average -- 4. Reduced Lag Filters -- 4.1 "Zero-lag" EMA (ZEMA) -- 4.2 Modified EMA (MEMA) -- 4.2.1 Modified EMA (MEMA) with a Skip 1 Cubic Velocity -- 4.2.2 Modified EMA (MEMA) with a Skip 2 Cubic Velocity. | |
| 520 | |a The present book contains much more materials than the author's previous book "The Science of Financial Market Trading". Spectrum analysis is again emphasized for the characterization of technical indicators employed by traders and investors. New indicators are created. Mathematical analysis is applied to evaluate the trading methodologies practiced by traders to execute a trade transaction. In addition, probability theory is employed to appraise the utility of money management techniques. The book: identifies the faultiness of some of the indicators used by traders and accentuates the potential of wavelets as a trading tool; describes the scientific evidences that the market is non-random, and that the non-randomness can vary with respect to time; demonstrates the validity of the claim by some traders that, with good money management techniques, the market is still profitable even if it were random; and analyzes why a popular trading tactic has a good probability of success and how it can be improved. | ||
| 588 | 0 | |a Print version record. | |
| 546 | |a English. | ||
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 650 | 0 | |a Investments |x Mathematics. | |
| 650 | 0 | |a Finance |x Mathematical models. | |
| 650 | 0 | |a Speculation |x Mathematical models. | |
| 650 | 6 | |a Investissements |x Mathématiques. | |
| 650 | 6 | |a Finances |x Modèles mathématiques. | |
| 650 | 6 | |a Spéculation |x Modèles mathématiques. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Investments & Securities |x General. |2 bisacsh | |
| 650 | 7 | |a Finance |x Mathematical models |2 fast | |
| 650 | 7 | |a Investments |x Mathematics |2 fast | |
| 650 | 7 | |a Speculation |x Mathematical models |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Mak, Don K. |t Mathematical techniques in financial market trading. |d Hackensack, N.J. : World Scientific, ©2006 |w (DLC) 2006040528 |
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