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Copyrighted Material P1: JYS ind JWBK304-Katsanos November 22, 2008 21:44 Printer: Yet to come Index abbreviations’ list 382–3 artificial neural networks 25, 154–5, ABS(DATA ARRAY) 379 168–71, 172, 215, 221–33, 357–65, ADM see Archer Daniels Midlands 371 ADRs 47, 86, 371 see also fuzzy logic; genetic algorithm advance-decline line 371 combined trading strategy 226–33, 360–3 ADX 140–3, 271–3, 276, 280–5 concepts 25, 154–5, 168–71, 172, 215, ADX(PERIODS) 379 221–33, 357–65, 371 AEX 82 conventional system comparisons 215, agricultural commodities 52–5 221–33 ALERT() 379 critique 169–71, 172, 221–33 Allianz 203 disparity 224–33, 359–60 aluminium 59–61, 249, 257, 259, 291 dynamic considerations 233 Amex Gold BUGS Index (HUI) FTSE system 215, 221–33, 357–65 concepts 63 hidden neurons 223, 225–33, 374 weighting method 63 hybrid strategy 172, 226–33, 363–5 Amex Oil Index (XOI) 30, 49–50, input considerations 221–2, 224–9, 233 55–8, 79–82, 216–33, 236–44, network architecture 230–2 357–65 nonlinear relationships 25 composition 56–7 optimization factors 168–71, 226–33 concepts 55–8, 216–33, 236–44 output considerations 226–9 correlations 57–8, 236–44 problems 222–3, 226, 232–3 S&P 500 79–82, 236–44 ROC 222–33, 357–60 weighting method 56–7 sensitivity analysis 226 ANOVA, concepts 161–2 testing procedures 223–9 Apache Corp. 56–7 total net profit 225–33 appendices 297–370COPYRIGHTEDtrading MATERIAL specifications 229–30 arbitrage 371 training 168–71, 172, 223–33 Archer Daniels Midlands (ADM) Asia Pacific Fund 251, 254–9 235 Asian crisis of 1997 78 Aristotle 111 Asian markets 7, 12–15, 74–5, 78 artificial intelligence asset allocations concepts 168–73 see also dynamic . critique 172 concepts 12–15, 247–60 391 P1: JYS ind JWBK304-Katsanos November 22, 2008 21:44 Printer: Yet to come 392 Index asset allocations (Continued) data quality 153, 264 methods 15, 247–60 definition 148 rebalanced portfolios 15 diversification 152 relative strength 247–60 exhaustive search technique 153, 154–5, static asset allocations 11–15, 247, 224–9 254–60, 294 financial markets 152 asset classes 6, 9–15, 247–60, 294–5 forex 264, 271, 280–1 diversification 9–10, 247–60, 294–5 low number of inputs 152 types 9–10, 294 Monte Carlo Simulation 151–2, 153–4 assumptions of correlation optimization factors 149–55, 172–3, concepts 18–30, 47–8, 106–7, 158–9, 217–33 184 paper trades 153, 223–33 linearity 18–19, 20–7, 37–8, 106–7 sample sizes 149, 186–7 normal distributions 17–20, 25–9, 37–8, software considerations 152–3 47–8, 106–7, 158–9, 184 walk forward testing 150–1 assumptions of regression 38 Bank of England (BOE) 266 ‘at the money’ options 42 Bank of Japan 4, 261 Athens General Index 4–6, 86–7 banks ATR see Average True Range BIX 216–33, 357–65 ATR(PERIODS) 379 central banks 261–2 AUD see Australian dollar Barrick Gold 62–3 Australia ASX 47 BASF 203 Australian All Ordinaries 57–8, 249, 257, Bayer 203 290–1 BBANDBOT . 380 Australian dollar (AUD) 54–5, 249, 262, bear markets 149, 171, 192–9, 205–9, 268–9, 278–84, 285–92 218–19, 243–4, 248–50, 259–60, AUD/JPY 288–90 287–8, 294 AUD/USD 55, 262, 289–91 Bear Stearns 27 commodities 285–7, 290–1 benchmarks, relative strength 121–3, 140, concepts 285–92 179–80, 183–7, 255–9, 297, 303–5, correlations 287–92 341–7, 377 gold 287–8, 289–92 Beyond Candlesticks . (Nisen) 124 statistics 285–92 bias factors, divergences 132–3 yen 287–8, 289–91 The Bible 293 autocorrelation 19, 152, 159, 371 bibliography 385–9 average profit per trade, trading system BIX see S&P Bank Index evaluations 155, 161–2, 164 black boxes 172, 372 average profit/average loss (Rwl), trading Black-Scholes options pricing formula 42 system evaluations 155, 161–2, blue chips 41–67 176–87, 191–9, 205–13, 225–33, BOE see Bank of England 237–46, 255–9, 274–7, 283–5 Bollinger bands 123–5, 177, 184–7, Average True Range (ATR) 371–2 218–33, 271–7, 297–8, 310–12, 372, 379–80 back-testing definition 123–4, 372 benefits 148–9 formula 123–4 concepts 148–55, 172–3, 217–33, 264, limitations 124 271, 280–1 MetaStock code 123–4, 297–8, 310–12 P1: JYS ind JWBK304-Katsanos November 22, 2008 21:44 Printer: Yet to come Index 393 bonds 3–4, 7, 9–10, 13–15, 54–6, 77–82, S&P 500 70–6, 82–3 88–92, 189, 247–60, 269–77, 278–85, weighting method 43 294 Calmar Ratio, concepts 165 commodities 7 Canada’s TSX 31, 47–51, 70–6, 83, 86, economic cycles 7–8, 77–82 95–9, 236, 289–91 equities 77–82, 189, 247 Canada’s Venture Index 55, 101–7 forex 269–77, 278–85 Canadian dollars (CADs) 53–5, 249, 262, S&P 500 77–82, 269–77 269, 285, 289–91 bottoms 65–7, 100–1, 122–3 CANSLIM method 171 BP 45, 57, 82 carry trade 4, 264–5, 268–77, 287–8 Brazil’s Bovespa 5, 249 cash 6, 9–10, 13–15, 89, 294 see also emerging markets catastrophic losses 166–7, 209, 232 breadth indices 190–9 CBOE 37–8, 42, 56–8, 63–7, 72–6, 77–83, see also divergence . 95–9, 135, 269–77, 278–85 breakouts 23–4, 143, 262, 272–3 CBOE 10 Year Treasury Yield Index (TNX) Bretton Woods 54–5 37, 78–82, 95–9, 135, 269–77, Britain see UK 278–85 British pound 12–15, 249, 262, see also bonds 268 CBOE oil index (OIX) see also GBP... composition 56–7 brute force approach see exhaustive search concepts 55–8 technique weighting method 56–7 bull markets 8, 98–9, 149, 171, 204–13, CBOE Volatility Index (VIX) 37–8, 42, 238–9, 247–8, 277–8, 287, 294, 63–7, 72–6, 77–83 373 concepts 63–7, 72–6, 77–83 business cycles 7–8, 77–82, 139–40 critique 66–7, 82 ‘butterfly effect’ 4 historical background 64 buy and hold profit 156, 176–87, 191–9, interpretation 64–7 201–2, 205–13, 217–18, 225–33, S&P 500 64–7, 72–6, 77–83 236–46, 248–60, 274–7, 283–5, turning points 65–6 293–4 VXD/VXN variants 64 buy signals 123–4, 126–7, 137–9, 147–8, CCI see Commodity Channel Index 183, 190–9, 202–13, 218–33, 254–6, central banks 261–2 259, 272–3, 274–7, 283–5 Central European time (CET) 42–50, see also entry . 112–19, 195–9, 215 buy/hold index, trading system evaluations central limit theorem 159, 372 156, 176–87, 191–9 see also normal distributions CET see Central European time C 380 CFTC see Commodity Futures Trading CAC40 37–8, 42–4, 47–51, 70–6, 82–3, Commission 85–8, 201–13, 216–33, 249, 327, 333, chaos theory 4, 372 334, 357–65 chart analysis 3–4, 140–3, 148–55, 367–70 capped weightings 43 see also technical analysis concepts 42–4, 70–6, 82–3, 85–8, Chevron Corp. 57 201–13, 216–33 CHF see Swiss franc DAX 85–8, 201–13 Chicago Mercantile Exchange (CME) 46, list of companies 43 61, 88, 268–9 P1: JYS ind JWBK304-Katsanos November 22, 2008 21:44 Printer: Yet to come 394 Index China 47, 55–6, 261, 269, 287, 292 euro 278–86 CI see congestion index futures 60, 294 CI(PERIODS) 380 gold 95–107 cluster spotting, optimization factors 151 historical background 58 CME see Chicago Mercantile Exchange list of commodities 58–9 CNBC 5 S&P 500 77–82, 236 cocoa 59–61 weighting method 59 coefficient of determination Confucius 17, 172 see also Pearson’s product-moment congestion index (CI) correlation coefficient concepts 139–43, 196–9, 203–13, 280–6, concepts 19, 30, 36, 37–8, 135–8, 182–7 301 coefficient of nonlinear correlation (Eta), definition 139–40 concepts 24–5 directional aspects 140–1 coefficient of variation of average profit, Excel calculation examples 142–3 concepts 164–5 formula 140 coffee 59–61, 250 MetaStock code 301 Cognotec 262 Consumer Price Index (CPI) 266 combined trading strategy, artificial neural conventional system comparisons, artificial networks 226–33, 360–3 neural networks 215, 221–33 COMEX see New York Commodities copper 59–61, 249, 259, 289, 291 Exchange corn 51–61, 249 commissions 217–18, 223, 236, 263, 272 CORREL . 159–62, 380 commodities 6, 7, 9–12, 41–67, 77–83, correlation 85–92, 239, 248–60, 285–7, 291–2, see also intermarket analysis; 294, 335–41 Pearson’s . ; Spearman’s . see also oil assumptions 18–30, 47–8, 106–7, 158–9, advantages 294 184 Australia 285–7, 290–1 concepts 3–15, 17–31, 57–8, 69–83, bonds 7 111–19, 125–7, 134–5, 216–33, conclusions 294 235–46, 294–5, 372 DAX 85–92 conclusions 294–5 diversification uses 9–10, 248–60, 294 DAX 85–92, 201–13 economic cycles 7–8, 77–82, 94–5 definition 3, 372 futures 294 diversification uses 9–15, 294–5 gold 94–109 examples 11–15, 20–2 S&P 500 77–83, 94–6 forex 269–77, 278–85, 287–92 Commodity Channel Index (CCI) 179–80 formulas 17, 20 Commodity Futures Trading Commission gold 78–82, 88, 93–109, 215–33, 244–6 (CFTC) 166 homoscedasticity 31 Commodity Research Bureau (CRB) 7–8, interpretation 17–19 14, 54–5, 58–62, 77–82, 95–107, 127, intraday correlations 90–2, 111–19, 134–8, 236, 248, 278–86, 289–91, 189–99 294 linearity assumption 18–19, 20–7, 37–8, AUD 289–91 106–7 concepts 58–62, 77–82, 95–107, 236, matrix 134–8 278–86, 294 multicollinearity 34, 36–7, 216–17, 375 P1: JYS ind JWBK304-Katsanos November 22, 2008 21:44 Printer: Yet to come Index 395 normal distribution assumption 17–20, component stock disparity stocks 331–2 25–9, 37–8, 106–7, 158–9, 184 concepts 41–2, 85–92, 111–19, 201–13 outliers 30, 38, 159 correlations 85–92, 201–13 part correlation coefficient 132–8 daily disparity system 327–9 price percent changes 18–19, 24, 37–8, disparity 202–13, 327–9, 331–2 55–6, 72–6, 89–92, 107, 224–33 ESTX50 85–92, 111–19, 201–13 ROC considerations 9, 18–19, 176–87, FDAX 88, 202–13 222–33, 274–7, 357–60, 377 forex 85–92 S&P 500 69–83, 85–6, 159–62, 269–77 FTSE 100 86–7 statistics 11–15, 69–83 gold 88 cotton 59–61, 259 intermarket enhanced MA crossover countertrend systems, concepts 179–87 system 209–13, 329–31 covariance intraday correlations 90–2, 111–19 concepts 17–31, 372 MA crossover system 209–13, 329–31 definition 17, 372 MetaStock code 327–32 formula 17 S&P 500 85–6 cover 192–9, 205–13, 219, 273–4, 372 S&P 500 e-mini 88–92, 112–19 CPI see Consumer Price Index stocks’ correlations 86–7 crash of 1987 78 time factors 89–92, 111–19, 210–13 CRB see Commodity Research Bureau Tradesim 203–13, 331 credit crunch 27 trading DAX futures 201–13 CROSS .
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