ical Analysis. John Wiley & Sons.DeMark, Thomas. 1998. New Market Timing Techniques. John Wiley & Sons.Jobman, Darrell (1980). Richard Donchian: pioneer of trend trading. Commodities, Sept. 1980,40–42.Kahn, Phyllis. 1980. Who Was W. D. Gann? Commodities, Jan. 2000, 44–48.Kestner, Lars. 1998. Comparison of Popular Trading Systems. Commodity Traders ConsumerReports.Lo, A.W., Harry Mamaysky, and J.Wang. 2000. Foundations of Technical Analysis: ComputationalAlgorithms, Statistical Inference, and Empirical Implementation. Journal of Finance 55:1705–1765.Lukac, Louis, Wade Brorsen, and Scott Irwin. 1990. A Comparison of Twelve Technical TradingSystems. Traders Press.Odean, Terrence. 1998. Are Investors Reluctant to Realize Their Losses? Journal of Finance 53:1775–1798.Rosenberg, Barr, Kenneth Reid, and Ronald Lanstein. 1985. Persuasive Evidence of MarketInefficiency, Journal of Portfolio Management 11: 9–17.Schwartz, Robert. 1993. Reshaping the Equity Markets. McGraw Hill.Schwert, William. 1991. Review of Market Volatility by Robert J. Shiller. Journal of PortfolioManagement 17: 74–78.Shiller, Robert. 1981. Do Stock Prices Move Too Much to Be Justified by Subsequent Changes inDividends? American Economic Review 71: 421–436.331
Copyright 2003 by Lars Kestner. Click Here for Terms of Use.
References
332
Chapter 4: Creating Trading StrategiesGrossman, Sanford, and Joseph Stiglitz. 1980. On the Impossibility of Informationally EfficientMarkets. American Economic Review 70, 393–408.
Chapter 5: Evaluating Trading Strategy PerformanceKestner, Lars. 1996. Getting a Handle on True Performance. Futures, Jan. 1996, 44–46.Kestner, Lars. 1996. Measuring Profitability. Technical Analysis of Stocks and Commodities, March1996, 46–50.Skinner, B. F. 1948. Superstition in the Pigeon. Journal of Experimental Psychology 38: 168–172.Treynor, Jack, and Kay Mazuy. 1966. Can Mutual Funds Outguess the Market? Harvard BusinessReview 43: 63–75.
Chapter 6: Optimizing Parameters and Filtering Entry SignalsZamansky, Leo, and James Goldcamp. 2001. Walking a Fine Line. Futures. Oct. 2001, 48–50.
Chapter 8: New Ideas of Entries, Exits, and FiltersCooper, Michael. 1999. Filter Rules Based on Price and Volume in Individual Security Overreaction.Review of Financial Studies 12: 901–935.
Chapter 9: New Ideas of MarketsDemeterfi, Kresimir, et al. 1999. More than You Ever Wanted to Know About Volatility Swaps.Goldman Sachs Quantitative Strategies Research Notes. March 1999.Gross, Leon, et al. 2002. Once, Twice, Three Times: RD/SC Spread in Play Again. Salomon SmithBarney Equity Derivatives Sales Literature. Feb. 4, 2002.________. 2002. Major Change in the S&P 500, as Non-U.S. Companies Are Removed. SalomonSmith Barney Equity Derivatives Sales Literature. July 10, 2002.________. 1998. Introducing Volatility Swaps: Trading Volatility Made Easy. Salomon Smith BarneyEquity Derivatives Sales Literature. January, 1998.Lowenstein, Roger. 2000. When Genius Failed: The Rise and Fall of Long-Term Capital Management.Random House.
Chapter 10: Investing in the S&P 500Cross, F. 1973. Behavior of Stock Prices on Fridays and Mondays. Financial Analysts’ Journal 29:67–69.Gross, Leon, et al. 2001. Nasdaq Volatility Indices: Why Is the VXN 10 Points Higher? Salomon SmithBarney Equity Derivative Sales Literature. Feb. 26, 2001.Headley, Price. 2002. Big Trends in Trading. John Wiley & Sons.
References
333
Chapter 11: New Techniques in Money ManagementKelly, J. L. 1956. A New Interpretation of Information Rate. Bell System Technical Journal 35: 917–26.Markowitz, Harry. 1959. Portfolio Selection: Efficient Diversification of Investments. Yale UniversityPress.Vince, Ralph. 1990. Portfolio Management Formulas. John Wiley & Sons.
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INDEX
Absolute returns, 78Adjusted stochastic, 219, 223–226ADX (Average Directional Movement Index), 72channel breakout with, 117–12114-day, 109–110, 117, 11819-day, 110VHF versus, 117, 118Amazon.com, 35–37, 38American International Group (AIG), 140Amex Oil Index (XOI), 266, 267Andreassen, Paul, 28Annualized volatility, 51–52, 53Appel, Gerald, 68–69Arbitrage, 31–32, 248–249Arnold, Curtis, 21Artifacts, 43Autocorrelation, 85, 86, 123–124Average Directional Movement Index (ADX). SeeADX (Average Directional Movement Index)Average true range (ATR), 64, 65Bachelier, Louis, 14Back-adjusted methods, 132–133Back-tests, 76–77Barclay Group, 4Barclays Discretionary Traders Index, 4, 5Barclays Systematic Traders Index, 4, 5, 95Behavioral finance, 21–30, 84human nature and, 22–23irrational decision making and, 23–25selling winners and holding losers and, 25–30Bell curve, 46–48
Benchmark strategies:channel breakouts, 90K-ratio, 85–89moving average crossover, 90Sharpe ratio, 84–85Best position profit, 71Big Trends in Trading (Headley), 300Black, Fischer, 31Black-Scholes option pricing model, 13Blodgett, Henry, 35Bollinger bands, 300Bonds:convertible, 13U.S. Treasury, 30–31, 121, 122, 127zero-coupon, 30–31Bottom-up relative value, in relative value trading,249–250Breakdown Statistics, 90–94futures, 167adjusted stochastic, 224Alex Saitta's support and resistance strategy,238channel breakout, 142Divergence Index, 20480 day momentum, 15714-day RSI, 172Kestner's moving average system, 187MACD, 177MACD histogram retracement, 199Moving Average Confluence Method, 210moving average crossover, 147new volatility breakout strategy, 327
335
Copyright 2003 by Lars Kestner. Click Here for Terms of Use.
INDEX
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Breakdown Statistics, futures (Cont.):Normalized Envelope Indicator (NEI), 216sample, 92Second Order Breakout, 193Three in a Row, 22920-day momentum, 152volatility breakout, 162relative valuedifference between 10-day and 40-daymoving average, 288difference from 100-day moving average, 28580-day momentum, 27640-day entry/20-day exit channel breakout, 27114-day Relative Strength Index, 282stochastics, 27910-day/40-day dual moving averagecrossover, 274stocksadjusted stochastic, 226channel breakout, 144Divergence Index, 20680-day momentum, 15914-day RSI, 174Kestner's moving average system, 189MACD, 179MACD histogram retracement, 201Moving Average Confluence Method, 212moving average crossover, 149Normalized Envelope Indicator (NEI), 218Second Order Breakout, 195stochastics, 168Three in a Row, 23120-day momentum, 154volatility breakout, 164volume reversal strategy, 235Broadening bottom, 20Broadening top, 20Brorsen, Wade, 15Brown, Robert, 14Brownian motion, 14, 21Bulowski, Thomas, 21Burke, Gibbons, 10Butterfly trades, 252, 254Buying pressure, 56Call options:defined, 31payoff diagram, 258relative equivalence with put options, 31Cash flow, 24CBOE Volatility Index, 299–303
Channel breakouts, 10, 60–62, 90with ADX, 117–121annual returns, 96example, 62measuring value of, 117–118, 119, 120moving average crossover with, 106, 107performance evaluation, 139–144pyramiding and profit taking versions of,242–243, 244in relative value trading, 269, 270–271rules, 62, 90Second Order Breakout, 184–185, 190–191,192–195“turtle” offspring, 61Chesapeake Capital, 11Chicago Board of Trade (CBT), 31–32Chicago Board Options Exchange (CBOE),Volatility Index (VIX), 257–259, 299–303Chicago Mercantile Exchange (CME), 249, 260Cisco Systems, 35–37Citadel Investment Group, 13Coca-Cola, 196Commissions, 11, 139Commodities:relationships with stocks, 45–46, 138, 265–266S&P correlation with, 45, 135, 136, 138substitution effect, 250, 264–265Commodity Trading Advisors (CTAs), defined, 4Comparison of Popular Trading Systems, A(Kestner), 5–6, 10, 90, 95Confidence intervals, 52Continuous price series, 130–133Convertible bonds, 13Cooper, Michael, 232Correlation, 42–46among assets, 103–104autocorrelation, 85, 86, 123–124correlation matrix, 105in dual moving average crossover, 145–150general states of, 43misuse of, 43negative, 44noncorrelation, 44positive, 43Credit spreads, in relative value markets, 253–257Crossing of moving averages, 8–9Curtis Arnold's PPS Trading System (Arnold), 21Curve fitting, optimization versus, 110–112Data mining, 73Day of the month effects, 297–299
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Day of the week effects, 297–299Day traders, 291DeBondt, Werner, 24Default risk, 254, 256Dell Computer, 145DeMark, Thomas, 10, 69Demeterfi, Kresimir, 259Dennis, Richard, 61Deregulation, 6Descriptive statistics, 39–54lognormality of market prices, 53–54mean, 39, 40, 308median, 308normal distribution, 46–48standard deviation, 39, 40–42, 46, 64, 65volatility, 49–53See also CorrelationDesignated Order Turnaround System (DOT), 11Discretionary traders, 3–5Divergence Index, 197, 202, 203–206Diversification, 100–107across markets, 104–105across parameters within strategies, 106–107across uncorrelated strategies, 105–106benefits of, 100–102best form of, 104–105better form of, 105–106good form of, 106–107importance of, 102–104Dollar volatility, 52–53, 318–319Donchian, Richard, 9–10, 60Double bottom, 18Double top, 18Drawdown, 80–82, 83Drunkard's walk, 14, 21Dual moving average crossover, 10performance evaluation, 145–150in relative value trading, 269, 272, 273–274Eckhardt, William, 61Edwards, Robert, 5, 15Efficient markets/random walk model, 14–15, 56,76, 124–126Einstein, Albert, 14Encyclopedia of Chart Patterns (Bulowski), 21Enron, 254Entries, 56–69defined, 55oscillators, 66–69price patterns, 69trend-following techniques, 56–65
Equity. See Stock markets; StocksEtzkorn, Mark, 219–222Evaluation of performance. See Performanceevaluation of portfoliosExchange traded funds (ETFs), 260, 289, 295–297Exits, 69–72defined, 55fail-safe, 72profit targets, 70stop loss exits, 236–243trailing, 70–71Expected returns, risk and, 307Exponential moving averages, 57Exxon, 32Fail-safe exits, 72Fannie Mae, 155, 160Filtering, 72, 117–123, 181–182defined, 55, 117measuring value of, 117–118, 119–120new trend filters, 243–245profitability and, 55, 117–123regime switching strategies, 118–121similarities in trend filters, 117using profitability of last trade, 121–123See also ADX (Average Directional MovementIndex); VHF (Vertical Horizontal Filter)Financial futures, introduction of, 6Fixed commission structure, 11Fixed-rule trading strategy, 9Ford, 247, 25014-day ADX, 109–110, 117, 11814-day Relative Strength Index (RSI), 165,170–174, 281, 282, 287, 288Framing, 22Frank Russell Company, 260Fundamental analysis, merits and limitations of,33–38Futures contracts, 31–32ADX filter with channel breakout, 119, 120, 121constructing continuous, 130–133defined, 130dynamically weighted contract size, 136–137normalizing volatility of, 133–138number of contracts to trade, 135–136returns on, 78See also Breakdown Statistics, futures; TradingStrategy Evaluation, futuresFutures markets:optimization results in, 112, 114testing, 129–130
INDEX
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Gambling, 99Gann, William D., 9, 12GARCH (Generalized Auto RegressiveConditional Heteroskedasticity), 49–50Gauss, Karl Friedrich, 46Gaussian distribution, 46–48General Electric (GE), 32, 33–34, 36, 51, 116,137, 138, 175, 184, 185General Motors, 33–34, 35, 247, 250Generalized Auto Regressive ConditionalHeteroskedasticity (GARCH), 49–50Goldcamp, James, 115–117Goldman Sachs, 248, 259Griffin, Ken, 12–13Gross, Leon, 258, 259, 300Gross profit, 79–80Grossman, Sanford, 63"Half life" of strategy performance, 94–96Head and shoulders bottom, 16Head and shoulders top, 16Headley, Price, 300Hedge funds, 31, 248, 263, 291–292Henry, John, 11, 12High yield spreads, 255–256Home Depot, 160, 165How to Trade in Commodities (Gann), 9IBM, 241, 242, 257Index funds, 295–297Index options, 32Indexing, 313–314Inefficiencies in capital markets, 30–33call and put contracts, 31futures contracts, 31–32options pricing, 32zero-coupon bonds, 30–31Information disequilibrium, 63Intel, 32, 33–34, 51, 52, 190–191, 241Interest rates, in predicting equity prices, 292–294International Paper, 214, 219Internet revolution, 35–37, 290–291Irwin, Scott, 15Japanese yen, 233, 236Jobman, Darrell, 9–10John W. Henry & Company (JWH), 12Johnson & Johnson, 232Jones, Paul Tudor, 10Journal of Finance, 24Journal of Portfolio Management, 14–15Juno, 290, 291
K-ratios:calculating, 85–89diversification and, 104, 106of filtered and nonfiltered channel breakoutstrategies, 245linear regression in, 86, 87, 88pyramiding and profit-taking versions of channelbreakout strategy, 243risk measurement, 86–87Kahn, Phyllis, 9Kahneman, Daniel, 22–23, 26–27Kelly, J. L., Jr., 315–316Kestner's moving average system, 183–184, 185,186–189Key reversal day, 69, 70Kurtosis, 49Lane, George, 66Lanstein, Ronald, 14–15Last trade, profitability of, 121–123Leptokurtosis, 49Leverage, 306–315danger of, 311–313defined, 307leveraged versus unleveraged strategy, 309optimal, 315–319in the real world, 313–315returns and, 306–311trader with an edge and, 311–312trader with no edge and, 312–313Lo, Andrew W., 15–21Lognormal distribution, 53–54London Interbank Offered Rate (LIBOR), 255Long Term Capital Management (LTCM), 31–32,255, 318Lowenstein, Roger, 255Lukac, Louis, 15MACD histogram retracement, 191, 196–197,198–201Macro trading, 250–251Magee, John, 5, 15Magical thinking fallacy, 98Mamaysky, Harry, 15–21Margin, 307Market timing strategies, 10, 294–303medium-term, 294–295performance of, 296short-term, 295–303Market volatility, 49–53annualized, 51–52, 53creating new strategies, 321–328
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Market volatility (Cont.):day traders and, 291distribution of ending wealth and, 310–311of equities, in relative value markets,257–259of futures, 133–138GARCH (Generalized Auto RegressiveConditional Heteroskedasicity), 49–50hedge funds and, 291–292Internet revolution and, 290–291normalizing, 133–138price versus dollar, 52–53range of volatilities, 50–53of stocks, 133–138Market Wizards (Schwager), 11Markowitz, Harry, 102–103, 104, 316–318Mazuy, Kay, 98McDonalds, 137Mean, 39, 40, 308Mean reversion theory, 25, 27–29, 30Medallion fund, 13Median, 308Medium-term strategies, 294–295Meeker, Mary, 35Microsoft, 165, 170Microsoft Excel, 87Momentum, 3, 62–6380-day, 155, 156–159, 275–276example, 62nature of, 62–63performance evaluation, 150–155, 156–159in relative value trading, 269, 275–276rules, 6320-day, 150–155Money management, 305–319importance of, 305–306leverage and, 306–315Monte Carlo simulator, 82Morgan Stanley, 248Moving Average Confluence Method, 202, 207–208,209–212Moving Average Convergence/Divergence(MACD), 68–69, 170, 175–179MACD histogram retracement, 191, 196–197,198–201Moving average crossover, 90annual returns, 96with channel breakout, 106, 107diversification and, 105–106Kestner's moving average system, 183–184,185, 186–189performance evaluation, 145–150
Moving averages, 57–60, 61example, 59relative value trading versus, 277–278, 280, 283rules, 58–60single and dual, 58trading signals for, 57–58types of, 57Multiple Entry Oscillator System, 213–214,219–220Multiplier, volatility, 64, 65Nasdaq 100, 34, 37, 41relative performance of, 259–262, 297Natural substitutes, 250Negative correlation, 44Neiderhoffer, Victor, 11–12Net asset value (NAV), 314Net profit, 76–78, 87New Concepts in Technical Trading Systems(Wilder), 10, 66New Market Timing Techniques (DeMark), 10New Market Wizards (Schwager), 11, 12New Science of Technical Trading, The (DeMark),10New strategies, 321–328creating, 73–74, 321–324determining optimal leverage and, 325–328testing, 324–32519-day ADX, 110Nokia, 248–249Noncorrelation, 44Normal distribution, 46–48Normalization process, 113for futures contracts, 133–138for 10-day/40-day moving average, 280, 283,284, 285for today's close versus 100-day moving average, 277–280, 284, 285Normalized Envelope Indicator (NEI), 208, 213,215–218Notional value, 52Odean, Terrance, 25, 26100-day moving average, 277–280, 284Open interest, 130–133Optimal leverage, 315–319improved method for calculating, 316–318Kelly criteria, 315–316, 319in new strategies, 325–328paradox of, 319role of dollar and percentage returns in, 318–319Vince's optimal f, 316, 319
INDEX
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Optimization, 109–126curve fitting versus, 110–112defined, 110filtering in, 117–123market trends and, 124–126measuring value of, 112–117normalization process and, 113trading signals in, 109–110of trading systems, 111–112trading the equity curve in, 123–124Option premium, 31Options. See Call options; Put options; StockoptionsOscillators. See Price oscillatorsPairs trading, 3, 263–264Parker, Jerry, 11Penny stocks, 289Percent of profitable trades, 82–84Performance evaluation of portfolios, 99–108in casinos, 99diversification and, 100–107Performance evaluation of trading strategies, 3,75–98, 129–180adjusted stochastic, 219, 223–226Barclay Group Indexes, 4, 5baseline for future trading strategies, 175–180channel breakouts, 139–144commissions in, 11, 139comparison of benchmark strategies, 90continuous price series in, 130–133deterioration of strategies, 97Divergence Index, 197, 202, 203–206dual moving average crossover, 10, 145–150,269, 272, 273–274flaws in performance measures, 76–84gold mines of bad performance, 97–98"half life" of strategy performance, 94–96historical track records in, 6, 7–8Kestner's moving average system, 183–184,185, 186–189MACD histogram retracement, 191, 196–197,198–201magical thinking and, 98momentum, 3, 150–155, 156–159, 275–276Moving Average Confluence Method, 202,207–208, 209–212Moving Average Convergence/Divergence,68–69, 170, 175–179Multiple Entry Oscillator System, 213–214,219–220net profit, 76–78, 87
Performance evaluation of trading strategies (Cont.):Normalized Envelope Indicator (NEI), 208,213, 215–218normalizing volatility in, 133–138other testing methods, 98percent of profitable trades, 82–84Popper's theories and, 75–76profit factor, 78–80profit taking, 242–243, 244profit to drawdown, 80–82, 83pyramiding, 242–243, 244Saitta's support and resistance strategy, 233–236Second Order Breakout, 184–185, 190–191,192–195slippage in, 139stochast