15: March.Meyers, Dennis (1997). “Walk Forward with the Xau Bond Fund System.” Technical Analysisof STOCKS & COMMODITIES. Volume 15: May.Meyers, Thomas (1992). “Four Common Errors in Testing Trading Systems.” Technical Analysis of STOCKS & COMMODITIES. Volume 10: September.Murphy, J. John and Hirschfield, J. David (1988). “Spread Trading the CRB Index.” TechnicalAnalysis of STOCKS & COMMODITIES. Volume 6: May.Murphy, J. John (1992). “The Link between Bonds and Commodities.” Technical Analysis ofSTOCKS & COMMODITIES. Volume 10: May.Murphy, J. John (1992). “The Link between Bonds and Stocks.” Technical Analysis of STOCKS& COMMODITIES. Volume 10: July.Murphy, J. John (1992). “The CRB Index/Bond Ratio.” Technical Analysis of STOCKS &COMMODITIES. Volume 10: August.Murphy, J. John (1992). “Utilities and Stocks.” Technical Analysis of STOCKS & COMMODITIES. Volume 10: October.Murphy, J. John (1992). “Interest Rates and the US Dollar.” Technical Analysis of STOCKS &COMMODITIES. Volume 10: October.Murphy, J. John (1992). “Gold and the US Dollar.” Technical Analysis of STOCKS & COMMODITIES. Volume 10: December.Nauzer, Balsara (1992), “Using Probability Stops in Trading.” Technical Analysis of STOCKS& COMMODITIES. Volume 10: May.Parkinson, Michael (1980). “The Extreme Value Method for Estimating the Variance of theRate of Return.” The Journal of Business 53: 1, January.Penn, D. (2003). “Intermarket Relationships.” Technical Analysis of STOCKS & COMMODITIES. Volume 21: July.Peterson, Dennis (2002). “Moving Averages.” Technical Analysis of STOCKS & COMMODITIES. Volume 20: June.Peterson, Dennis (2002). “Developing a Trading System.” Technical Analysis of STOCKS &COMMODITIES. Volume 20: August.Rothschild, Raymond (1991). “Diversification and Risk.” Technical Analysis of STOCKS &COMMODITIES. Volume 9: May.Ruggiero, M. (1996). “Build a Real Neural Net.” Futures. June.Stake, James (1995). “Designing a Personal Neural Net Trading System.” Technical Analysisof STOCKS & COMMODITIES. Volume 13: January.Sweeny, John (1992). “Where to Put your Stops.” Technical Analysis of STOCKS & COMMODITIES. Volume 10: December.Vakkur, Mark (1996). “Treasury Bond Yields and the S&P 500.” Technical Analysis of STOCKS& COMMODITIES. Volume 14: August.Weiss, Eric (1980). “ARIMA Forecasting.” Technical Analysis of STOCKS & COMMODITIES.Volume 1: February.
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Index
abbreviations’ list 382–3ABS(DATA ARRAY) 379ADM see Archer Daniels MidlandsADRs 47, 86, 371advance-decline line 371ADX 140–3, 271–3, 276, 280–5ADX(PERIODS) 379AEX 82agricultural commodities 52–5ALERT() 379Allianz 203aluminium 59–61, 249, 257, 259, 291Amex Gold BUGS Index (HUI)concepts 63weighting method 63Amex Oil Index (XOI) 30, 49–50,55–8, 79–82, 216–33, 236–44,357–65composition 56–7concepts 55–8, 216–33, 236–44correlations 57–8, 236–44S&P 500 79–82, 236–44weighting method 56–7ANOVA, concepts 161–2Apache Corp. 56–7appendices 297–370arbitrage 371Archer Daniels Midlands (ADM)235Aristotle 111artificial intelligenceconcepts 168–73critique 172
artificial neural networks 25, 154–5,168–71, 172, 215, 221–33, 357–65,371see also fuzzy logic; genetic algorithmcombined trading strategy 226–33, 360–3concepts 25, 154–5, 168–71, 172, 215,221–33, 357–65, 371conventional system comparisons 215,221–33critique 169–71, 172, 221–33disparity 224–33, 359–60dynamic considerations 233FTSE system 215, 221–33, 357–65hidden neurons 223, 225–33, 374hybrid strategy 172, 226–33, 363–5input considerations 221–2, 224–9, 233network architecture 230–2nonlinear relationships 25optimization factors 168–71, 226–33output considerations 226–9problems 222–3, 226, 232–3ROC 222–33, 357–60sensitivity analysis 226testing procedures 223–9total net profit 225–33trading specifications 229–30training 168–71, 172, 223–33Asia Pacific Fund 251, 254–9Asian crisis of 1997 78Asian markets 7, 12–15, 74–5, 78asset allocationssee also dynamic . . .concepts 12–15, 247–60
392
asset allocations (Continued)methods 15, 247–60rebalanced portfolios 15relative strength 247–60static asset allocations 11–15, 247,254–60, 294asset classes 6, 9–15, 247–60, 294–5diversification 9–10, 247–60, 294–5types 9–10, 294assumptions of correlationconcepts 18–30, 47–8, 106–7, 158–9,184linearity 18–19, 20–7, 37–8, 106–7normal distributions 17–20, 25–9, 37–8,47–8, 106–7, 158–9, 184assumptions of regression 38‘at the money’ options 42Athens General Index 4–6, 86–7ATR see Average True RangeATR(PERIODS) 379AUD see Australian dollarAustralia ASX 47Australian All Ordinaries 57–8, 249, 257,290–1Australian dollar (AUD) 54–5, 249, 262,268–9, 278–84, 285–92AUD/JPY 288–90AUD/USD 55, 262, 289–91commodities 285–7, 290–1concepts 285–92correlations 287–92gold 287–8, 289–92statistics 285–92yen 287–8, 289–91autocorrelation 19, 152, 159, 371average profit per trade, trading systemevaluations 155, 161–2, 164average profit/average loss (Rwl), tradingsystem evaluations 155, 161–2,176–87, 191–9, 205–13, 225–33,237–46, 255–9, 274–7, 283–5Average True Range (ATR) 371–2back-testingbenefits 148–9concepts 148–55, 172–3, 217–33, 264,271, 280–1
Index
data quality 153, 264definition 148diversification 152exhaustive search technique 153, 154–5,224–9financial markets 152forex 264, 271, 280–1low number of inputs 152Monte Carlo Simulation 151–2, 153–4optimization factors 149–55, 172–3,217–33paper trades 153, 223–33sample sizes 149, 186–7software considerations 152–3walk forward testing 150–1Bank of England (BOE) 266Bank of Japan 4, 261banksBIX 216–33, 357–65central banks 261–2Barrick Gold 62–3BASF 203Bayer 203BBANDBOT . . . 380bear markets 149, 171, 192–9, 205–9,218–19, 243–4, 248–50, 259–60,287–8, 294Bear Stearns 27benchmarks, relative strength 121–3, 140,179–80, 183–7, 255–9, 297, 303–5,341–7, 377Beyond Candlesticks . . . (Nisen) 124bias factors, divergences 132–3The Bible 293bibliography 385–9BIX see S&P Bank Indexblack boxes 172, 372Black-Scholes options pricing formula 42blue chips 41–67BOE see Bank of EnglandBollinger bands 123–5, 177, 184–7,218–33, 271–7, 297–8, 310–12, 372,379–80definition 123–4, 372formula 123–4limitations 124MetaStock code 123–4, 297–8, 310–12
Index
bonds 3–4, 7, 9–10, 13–15, 54–6, 77–82,88–92, 189, 247–60, 269–77, 278–85,294commodities 7economic cycles 7–8, 77–82equities 77–82, 189, 247forex 269–77, 278–85S&P 500 77–82, 269–77bottoms 65–7, 100–1, 122–3BP 45, 57, 82Brazil’s Bovespa 5, 249see also emerging marketsbreadth indices 190–9see also divergence . . .breakouts 23–4, 143, 262, 272–3Bretton Woods 54–5Britain see UKBritish pound 12–15, 249, 262,268see also GBP . . .brute force approach see exhaustive searchtechniquebull markets 8, 98–9, 149, 171, 204–13,238–9, 247–8, 277–8, 287, 294,373business cycles 7–8, 77–82, 139–40‘butterfly effect’ 4buy and hold profit 156, 176–87, 191–9,201–2, 205–13, 217–18, 225–33,236–46, 248–60, 274–7, 283–5,293–4buy signals 123–4, 126–7, 137–9, 147–8,183, 190–9, 202–13, 218–33, 254–6,259, 272–3, 274–7, 283–5see also entry . . .buy/hold index, trading system evaluations156, 176–87, 191–9C 380CAC40 37–8, 42–4, 47–51, 70–6, 82–3,85–8, 201–13, 216–33, 249, 327, 333,334, 357–65capped weightings 43concepts 42–4, 70–6, 82–3, 85–8,201–13, 216–33DAX 85–8, 201–13list of companies 43
393
S&P 500 70–6, 82–3weighting method 43Calmar Ratio, concepts 165Canada’s TSX 31, 47–51, 70–6, 83, 86,95–9, 236, 289–91Canada’s Venture Index 55, 101–7Canadian dollars (CADs) 53–5, 249, 262,269, 285, 289–91CANSLIM method 171carry trade 4, 264–5, 268–77, 287–8cash 6, 9–10, 13–15, 89, 294catastrophic losses 166–7, 209, 232CBOE 37–8, 42, 56–8, 63–7, 72–6, 77–83,95–9, 135, 269–77, 278–85CBOE 10 Year Treasury Yield Index (TNX)37, 78–82, 95–9, 135, 269–77,278–85see also bondsCBOE oil index (OIX)composition 56–7concepts 55–8weighting method 56–7CBOE Volatility Index (VIX) 37–8, 42,63–7, 72–6, 77–83concepts 63–7, 72–6, 77–83critique 66–7, 82historical background 64interpretation 64–7S&P 500 64–7, 72–6, 77–83turning points 65–6VXD/VXN variants 64CCI see Commodity Channel Indexcentral banks 261–2Central European time (CET) 42–50,112–19, 195–9, 215central limit theorem 159, 372see also normal distributionsCET see Central European timeCFTC see Commodity Futures TradingCommissionchaos theory 4, 372chart analysis 3–4, 140–3, 148–55, 367–70see also technical analysisChevron Corp. 57CHF see Swiss francChicago Mercantile Exchange (CME) 46,61, 88, 268–9
394
China 47, 55–6, 261, 269, 287, 292CI see congestion indexCI(PERIODS) 380cluster spotting, optimization factors 151CME see Chicago Mercantile ExchangeCNBC 5cocoa 59–61coefficient of determinationsee also Pearson’s product-momentcorrelation coefficientconcepts 19, 30, 36, 37–8, 135–8, 182–7coefficient of nonlinear correlation (Eta),concepts 24–5coefficient of variation of average profit,concepts 164–5coffee 59–61, 250Cognotec 262combined trading strategy, artificial neuralnetworks 226–33, 360–3COMEX see New York CommoditiesExchangecommissions 217–18, 223, 236, 263, 272commodities 6, 7, 9–12, 41–67, 77–83,85–92, 239, 248–60, 285–7, 291–2,294, 335–41see also oiladvantages 294Australia 285–7, 290–1bonds 7conclusions 294DAX 85–92diversification uses 9–10, 248–60, 294economic cycles 7–8, 77–82, 94–5futures 294gold 94–109S&P 500 77–83, 94–6Commodity Channel Index (CCI) 179–80Commodity Futures Trading Commission(CFTC) 166Commodity Research Bureau (CRB) 7–8,14, 54–5, 58–62, 77–82, 95–107, 127,134–8, 236, 248, 278–86, 289–91,294AUD 289–91concepts 58–62, 77–82, 95–107, 236,278–86, 294
Index
euro 278–86futures 60, 294gold 95–107historical background 58list of commodities 58–9S&P 500 77–82, 236weighting method 59Confucius 17, 172congestion index (CI)concepts 139–43, 196–9, 203–13, 280–6,301definition 139–40directional aspects 140–1Excel calculation examples 142–3formula 140MetaStock code 301Consumer Price Index (CPI) 266conventional system comparisons, artificialneural networks 215, 221–33copper 59–61, 249, 259, 289, 291corn 51–61, 249CORREL . . . 159–62, 380correlationsee also intermarket analysis;Pearson’s . . . ; Spearman’s . . .assumptions 18–30, 47–8, 106–7, 158–9,184concepts 3–15, 17–31, 57–8, 69–83,111–19, 125–7, 134–5, 216–33,235–46, 294–5, 372conclusions 294–5DAX 85–92, 201–13definition 3, 372diversification uses 9–15, 294–5examples 11–15, 20–2forex 269–77, 278–85, 287–92formulas 17, 20gold 78–82, 88, 93–109, 215–33, 244–6homoscedasticity 31interpretation 17–19intraday correlations 90–2, 111–19,189–99linearity assumption 18–19, 20–7, 37–8,106–7matrix 134–8multicollinearity 34, 36–7, 216–17, 375
Index
normal distribution assumption 17–20,25–9, 37–8, 106–7, 158–9, 184outliers 30, 38, 159part correlation coefficient 132–8price percent changes 18–19, 24, 37–8,55–6, 72–6, 89–92, 107, 224–33ROC considerations 9, 18–19, 176–87,222–33, 274–7, 357–60, 377S&P 500 69–83, 85–6, 159–62, 269–77statistics 11–15, 69–83cotton 59–61, 259countertrend systems, concepts 179–87covarianceconcepts 17–31, 372definition 17, 372formula 17cover 192–9, 205–13, 219, 273–4, 372CPI see Consumer Price Indexcrash of 1987 78CRB see Commodity Research Bureaucredit crunch 27CROSS . . . 380‘crosses’, forex 262crossover systems, moving averagecrossover system 138–9, 183–7,192–9, 201–2, 209–13, 218–33,242–6, 329–31, 363–5, 375cubic lines 20–4curve-fittingconcepts 150, 166, 169–70, 202–3, 223,232, 376definition 150, 376curvilinear relationships 20–4‘cut your losses and let your profits run’principle 167, 295Cybernetic Trading Strategies (Ruggiero)126, 173, 189Daimler Chrysler 203data qualityback-testing 153, 264forex problems 264DAX 5, 10, 37–8, 41–2, 47–51, 85–92,111–19, 201–13, 249, 327–32CAC40 85–8, 201–13commodities 85–92
395
component stock disparity stocks 331–2concepts 41–2, 85–92, 111–19, 201–13correlations 85–92, 201–13daily disparity system 327–9disparity 202–13, 327–9, 331–2ESTX50 85–92, 111–19, 201–13FDAX 88, 202–13forex 85–92FTSE 100 86–7gold 88intermarket enhanced MA crossoversystem 209–13, 329–31intraday correlations 90–2, 111–19MA crossover system 209–13, 329–31MetaStock code 327–32S&P 500 85–6S&P 500 e-mini 88–92, 112–19stocks’ correlations 86–7time factors 89–92, 111–19, 210–13Tradesim 203–13, 331trading DAX futures 201–13daylight saving time (DST) 47–50Deep Insight 169Deepinsight Professional 151Denmark, euro opt-out 277dependent variables,