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149

Ontogenic statistical networks Cascade Correlation, 296-298 Probabilistic Neural Networks (PNN), 299-300

Option pricing, 252, 261-263

Options, market exit, 98-99

Outlier trades, 150

Out-of-sample data, 129-130, 161

Overbought indicators, 70-71

Overbought stocks, 25, 31

Oversold indicators, 70-71

Oversold stocks, 25, 31

Parabolic SAR, 82-83

Peak-and-valley progression, 14

Percentage charts, 111-113

Percentage of the time in the market, 158

Percent losing trades, 101

Percent rate of change (PROC), 339

Percent winning trades, 101

Performance anxiety, 169

Performance evaluation, see Trading performance evaluation

Performance target, statistical network trading, 308

Persistence, 257-258, 337 Phone lines, data transmission, 365 Placing trades, 122-123 Portfolio diversification

forms of, generally, 210-211

input, 208-209

output, 209-210

risk, 209, 215 Position trading, intraday trading vs., 10-11 Positive outliers, 150 PowerEditor™, 227 Predicted Squared Error (PSE), 303-305 Predictive time period, statistical network trading,

308 Preprocessing

motivation and issues in, 269-272

for nonstationarity, 281

purpose of, generally, 337-338

statistical, 282 Price-based indicators, 19, 24

Price chart, 65-66, 121

Price distribution functions (PDF)

application of, 43-47

congestion and, 52-53

defined, 42

examples and interpretation of, 47-49

nonlinearity pricing, 262-264

reference points, 49-54

Visual Basic program, 58 Price history, 41 Price Layers, 53

Price mobility, assessment of, 58-61. See also Mobility oscillators

Pricing, nonlinear, see Nonlinearity

Proactive trading centering, 167-168 financial objectives, 166, 214 performance anxiety, 168-169 proactive tradi ng, 16 5-167 rate of return, maintaining, 173-176 recovery from last trade, 171-172 stopping points, 169-171, 173 systems trading, 172-173, 176-177, 214 value of, 165-167

Probabilistic Neural Network (PNN), 299-300

Profit factor, 140, 162

Profit objective stops, 91-93

Profit ratios, 140

Profit target, 92

Projection oscillator, 50

Project Nimble, 387-395

Psychology of trading, see Proactive trading

Pull-back-in-trend, 323, 325-327

Put options, 98

Rate of return, maintaining, 173-174 Ratio avg. win/avg. loss, 140 Real-time data, financial data sources

data reliability, 352-353

types of, 345-351 Receiver Operating System (ROS), 369-370 Recovery, psychological aspects of, 171-172 Reference points, 49-54 Reflexivity, 258-259



Ontogenic statistical networks Cascade Correlation, 296-298 Probabilistic Neural Networks (PNN), 299-300

Option pricing, 252, 261-263

Options, market exit, 98-99

Outlier trades, 150

Out-of-sample data, 129-130, 161

Overbought indicators, 70-71

Overbought stocks, 25, 31

Oversold indicators, 70-71

Oversold stocks, 25, 31

Parabolic SAR, 82-83

Peak-and-valley progression, 14

Percentage charts, 111-113

Percentage of the time in the market, 158 \ Percent losing trades, 101 \ Percent rate of change (PROC), 339 \ Percent winning trades, 101

Performance anxiety, 169

Performance evaluation, jrc Trading performance evaluation

Performance target, statistical network trading, 308

Persistence, 257-258, 337 Phone lines, data transmission, 365 Placing trades, 122-123 Portfolio diversification

forms of, generally, 210-211

input, 208-209

output, 209-210

risk, 209, 215 Position trading, intraday trading vs., 10-11 Positive outliers, 150 PowerEditor™, 227 Predicted Squared Error (PSE), 303-305 Predictive time period, statistical network trading,

308 Preprocessing

motivation and issues in, 269-272

for nonstationarity, 281

purpose of, generally, 337-338

statistical, 282 Price-based indicators, 19, 24

Price chart, 65-66, 121

Price distribution functions (PDF)

application of, 43-47

congestion and, 52-53

defined, 42

examples and interpretation of, 47-49

nonlinearity pricing, 262-264

reference points, 49-54

Visual Basic program, 58 Price history, 41 Price Layers, 53

Price mobility, assessment of, 58-61. See also Mobility oscillators

Pricing, nonlinear, see Nonlinearity

Proactive trading centering, 167-168 financial objectives, 166, 214 performance anxiety, 168-169 proactive trading, 165-167 rate of return, maintaining, 173-176 recovery from last trade, 171-172 stopping points, 169-171, 173 systems trading, 172-173, 176-177, 214 value of, 165-167

Probabilistic Neural Network (PNN), 299-300

Profit factor, 140, 162

Profit objective stops, 91-93

Profit ratios, 140

Profit target, 92

Projection oscillator, 50

Project Nimble, 387-395

Psychology of trading, see Proactive trading

Pull-back-in-trend, 323, 325-327

Put options, 98

Rate of return, maintaining, 173-174 Ratio avg. win/avg. loss, 140 Real-time data, financial data sources

data reliability, 352-353

types of, 345-351 Receiver Operating System (ROS), 369-370 Recovery, psychological aspects of, 171-172 Reference points, 49-54 Reflexivity, 258-259



Relative Strength Index (RSI)

applications, 36, 39

defined, 25

market entry and, 70

market exit and, 88 Resistance

price charts, 65-66

reversal roles, 67-68 Resistance levels, 50-51 Return on initial capital, 141 Return measures, 140-142 Reversal-probability analysis, 189-192, J * Reward, risk vs., 114-115 Reward/risk ratio, 114-115, 155-156 RINA Systems, Inc., 138 Risk, generally

bar length and, 196-199

close-to-open, 116

exposure to, 215

portfolio diversification and, 209, 215

reward vs., 114-115

slippage, 116-117 Risk-averse traders, 273 Risk management methods, 198, 215 Risk/reward ratios, 155-156 Robust systems, development of, 238-239,

242-243, 339 Rolling analysis, 142 Rolling period analysis, 248-249 Run-up, 153-155

S&P 500 Index, 23, 77, 84, 208, 223

S&P Crossover Buy, 227-228

Satellites, data transmission, 367-368

Scaling up in time, 204-205

Schwager, Jack, 100

Select net profit, 150

Sell limit orders, 64

Sell stop orders, 63

Sentiment indicators, 15-16, 122

Sharpe ratio, 211, 215

Short position

head-and-shoulders pattern, 330 multiple-bottoms and multiple-tops patterns, pull-back-in-trend, 325-326

Signal, 347

Signal translation, data reception, 369-370 Simple moving averages, 15, 105-106, 108 Sliding analysis, 142 Slippage, 101, 162 Slippage risk, 116-117 Slow Mobility Oscillator (MOS), 43 Software consultants, 384 /Software programs N.

( for financial modeling, 384-386 )

trading performance evaluation, 138 J Soros, George, 253 Specht, Donald, 299 Spreadsheets,

Markowitz/Xu data mining correction formula, sample of, 132-136

price distribution function (PDF), 47-48 Spyglass, 67

Stable distribution curve, 252-253 Standard deviation (STDEV), 24, 147 Starting capital, 101 STATISTICA™, 226, 229 Statistical network data mining™

application of, example, 305-315

statistical network advantages, 305

statistical network algorithm, 301-305 Statistical Network learning algorithm, 305 Statman, Meir, 272 Stochastic Oscillator, 50 Stochastics (STOC)

applications, 39

defined, 27

market entry and, 72

market exit and, 87-88 Stock selection, 252 Stop and Start Trading, 106-107 Stop orders, 63-64 Stopping points

awareness of, 171

defined, 169-170

systems trading and, 173 Stops

in system development, 244-245

value of, 76 Stress, trading success and, 168-169 Subsequent performance analysis, market

potential, 186-189, 216 Summaries, sliding and rolling, 142-143



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