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The science of financial market trading /

In this title, Dr Mak views the financial market from a scientific perspective. The book attempts to provide a realistic description of what the market is, and how future research should be developed. The market is a complex phenomenon, and can be forecasted only with errors - if that particular mar...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Mak, Don K.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore ; River Edge, NJ : World Scientific, ©2003.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Mak, Don K. 
245 1 4 |a The science of financial market trading /  |c Don K. Mak. 
260 |a Singapore ;  |a River Edge, NJ :  |b World Scientific,  |c ©2003. 
300 |a 1 online resource (xiv, 245 pages) 
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 235-239) and index. 
588 0 |a Print version record. 
520 |a In this title, Dr Mak views the financial market from a scientific perspective. The book attempts to provide a realistic description of what the market is, and how future research should be developed. The market is a complex phenomenon, and can be forecasted only with errors - if that particular market can be forecasted at all. The book reviews the scientific literatures on the financial market and describes mathematical procedures which demonstrate that some markets are non-random. How the markets are modelled - phenomenologically and from first principle - is explained. It discusses indicators, which are quite objective, rather than price patterns, which are rather subjective. Similarities between indicators in market trading and operators in mathematics are noted, and particularly, between oscillator indicators and derivatives in calculus. It illustrates why some indicators, e.g., stochastics, have limited usage. Several new indicators are designed and tested on theoretical waveforms to check their validity and applicability. The indicators have a minimal time lag, which is significant for trading purposes. Common market behaviours like divergences between price and momentum are explained. A skipped convolution technique is introduced to allow traders to pick up market movements at an earlier time. The market is treated as a nonlinear phenomenon. Forecasting of when the market is going to turn is emphasized. 
505 0 |a Preface ; 1. Introduction ; 1.1 Fundamental Analysis ; 1.2 Technical Analysis ; 1.2.1 Pattern Recognition ; 1.2.2 Indicators ; 1.3 Hybrids ; 2. Is the Market Random? ; 3. Models of the Financial Markets ; 3.1 Chaos ; 3.2 Complexity ; 3.3 Wave Model 
505 8 |a 3.4 Time Series Analysis 3.5 Neural Network ; 3.6 Fractal Geometry ; 3.7 Fuzzy Logic ; 3.8 Wavelet Analysis ; 4. Signals and Indicators ; 4.1 Stochastic Indicator ; 4.2 Momentum Indicator ; 5. Trending Indicators ; 5.1 Simple Moving Average (SMA) 
505 8 |a 5.2 Exponential Moving Average (EMA) 5.3 Adaptive Moving Average (AMA) ; 5.4 Trading Rules using Moving Averages ; 6. Oscillator Indicators ; 6.1 Parabolic Velocity Indicator ; 6.2 Parabolic Acceleration Indicator ; 6.3 Cubic Velocity and Acceleration Indicators ; 6.4 Divergences 
505 8 |a 6.4.1 Class A Divergence 6.4.2 Class B Divergence ; 6.4.3 Class C Divergence ; 6.5 Head and Shoulders ; 7. Vertex Indicators ; 7.1 Parabolic Vertex Indicator ; 7.2 Cubic Vertex Indicator ; 8. Various Timeframes ; 8.1 Under-sampling ; 8.2 Frequency Characteristics of an Indicator 
505 8 |a 9. Wavelet Analysis 9.1 High Wavelet Indicator ; 9.2 Middle Wavelet Indicator ; 9.3 Low Wavelet Indicator ; 10. Other New Techniques ; 10.1 Skipped Convolution ; 10.2 Forecasts ; 11. Trading Systems ; 12. Financial Markets are Complex ; Appendix 1 Time Series Analysis 
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650 0 |a Capital market  |x Forecasting. 
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650 7 |a Capital market  |x Forecasting  |2 fast 
650 7 |a Investments  |x Mathematics  |2 fast 
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