| Description |
1 online resource (322 pages) |
| Contents |
1. Introduction -- 2. Scientific review of the financial market. 2.1. Econophysics. 2.2. Non-randomness of the market. 2.3. Financial market crash -- 3. Causal low pass filters. 3.1. Ideal causal trending indicators. 3.2. Exponential moving average. 3.3. Butterworth filters. 3.4. Sine function, n=2. 3.5. Sine function, n=4. 3.6. Adaptive exponential moving average -- 4. Reduced lag filters. 4.1. "Zero-lag" EMA (ZEMA). 4.2. Modified EMA (MEMA) -- 5. Causal wavelet filters. 5.1. Mexican hat wavelet. 5.2. Dilated Mexican hat wavelet. 5.3. Causal Mexican hat wavelet. 5.4. Discrete fourier transform. 5.5. Calculation of zero phase frequencies. 5.6. Examples of filtered signals. 5.7. High, middle and low Mexican hat wavelet filters. 5.8. Limitations of Mexican hat wavelet filters -- 6. Instantaneous frequency. 6.1. Calculation of frequency (4 data points). 6.2. Wave velocity. 6.3. Wave acceleration. 6.4. Examples using 4 data points. 6.5. Alternate calculation of frequency (5 data points). 6.6. Example with a frequency chirp. 6.7. Example with real financial data. 6.8. Example with real financial data (more stringent condition) -- 7. Phase. 7.1. Relation between the real and imaginary parts of the Fourier transform of a causal system. 7.2. Calculation of the frequency response function, H([symbol]). 7.3. Computer program for calculating H([symbol]) and h(n) of a causal system. 7.4. Derivation of H[symbol] in terms of H[symbol] for a causal system -- 8. Causal high pass filters. 8.1. Ideal filters. 8.2. Momentum. 8.3. Cubic indicators. 8.4. Quartic indicators. 8.5. Quintic indicators. 8.6. Sextic indicators. 8.7. Velocity and acceleration indicator responses on smoothed data -- 9. Skipped convolution. 9.1. Frequency response. 9.2. Skipped exponential moving average. 9.3. Skipped convolution and downsampled signal -- 10. Trading tactics. 10.1. Velocity divergence. 10.2. Moving Average Convergence-Divergence (MACD). 10.3. MACD-Histogram. 10.4. Exponential moving average of an exponential moving average -- 11. Trading system. 11.1. Multiple timeframes. 11.2. Multiple screen trading system. 11.3. Test of a trading system -- 12. Money management-time independent case. 12.1. Probability distribution of price variation. 12.2. Money management-time independent case. 12.1. Probability distribution of price variation. 12.2. Probability of being stopped out in trade. 12.3. Expected value of a trade -- 13. Money management-time dependent case. 13.1. Basic probability theory. 13.2. Trailing stop-loss. 13.3. Fixed stop-loss -- 14. The reality of trading. 14.1. Mind. 14.2. Method. 14.3. Money management. 14.4. Technical analysis. 14.5. Probability theory and money management |
| Summary |
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 potentia |
| Bibliography |
Includes bibliographical references (pages 297-300) and index |
| Notes |
Print version record |
| Subject |
Finance -- Mathematical models.
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Investments -- Mathematics.
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Speculation -- Mathematical models
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Finance -- Mathematical models
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Investments -- Mathematics
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Speculation -- Mathematical models
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| Form |
Electronic book
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| ISBN |
9789812774064 |
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9812774068 |
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