cmt lvl ii 2018 theory and analysis - cmt association · adx line, 89–90 alexander filter ......

bindex 1 November 29, 2017 5:56 PM

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I n d e x

A

Absolute return, 504Accumulation and distribution, 40–53, 211

extended rectangle bottom, 48–49Accumulative average, 112ACD method, 295Active portfolio weights, 506Adaptive markets hypothesis (AMH), 513,

520–521Adaptive Trading Model, 494A/D oscillator, 182–186Advance-decline system, 226–227, 720Advance Market Technologies (AMTEC),

740–741n2ADX line, 89–90Alexander filter, 638Allais Paradox, 537Alpha

description of, 504method, 407–408returns, 504

Amex QQQ volatility index, 386AMH. See Adaptive markets hypothesisAmplitude, 437AMTEC. See Advance Market TechnologiesAnchoring, 548–549Animal spirits, 528Annualized rate of return, 768Apex, 248, 290Appel, Gerry, 221APT, 694n22Arbitrage, 661–663

limits of, 669Arguments, 602–606

ARIMA. See Autoregressive integrated moving average

Aristotle, 596–597, 602Arithmetic moving average, 74Arms, Richard, 204

Arms index, 219–220Arms index (TRIN), 219–220Array

investing and, 402Ascending triangle, 248, 249–250Aspray, Thomas, 212

demand oscillator, 212–213Asset allocation, 394

intrinsic value of, 507Athens General Index, 416–417ATR. See Average true rangeAutoregressive integrated moving average

(ARIMA), 583–589forecast results, 587Kalman filters, 588–589mean-reverting indicator, 595slope, 588trading strategies, 587–588use of highs and lows, 588

Autoregressive model, 100–101

Average-modified method, 107Average-off method, 107Average true range (ATR), 82Average volume, 205

B

Bacon, Francis, 613–614Bailout, 268

Page numbers followed by n indicate note numbers.

CMT LVL II 2018 Theory and Analysis


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role of feedback in systematic price movements, 678–680

sample size neglect, 673–674social factors of, 674–680

Bernard, V., 694n19Beta

description of, 504–505returns, 504–505

Blau, William, 189tick volume indicator, 213–214

Blow-off, 43Bogle, John, 511, 521–522Bold conjecture, 623. See also Popper, KarlBollinger bands, 92–93, 128–132,

133–134combined with other indicators, 134modified, 129–130

Bolton-Tremblay (BT) value, 218Bonds

AAA, 497, 744–745n39learning objective statements, 496long-term interest rates, 399–400model, 496–502to stocks, 400

Bottom reversal bar, 281Bottoms

accumulation and distribution, 40–53double and triple, 44–47extended rectangle, 48–49profit targets after bottom formation, 58rounded, 49–50targeting profits after, 57–60V-bottoms, 41–44wedges, 51

Bottom-up analysis, 405–409, 530Bowl, 258–259Box pattern, 244–245Breadth

as a countertrend indicator, 227highs and lows, 222indicators, 216–223interpreting, 223–227learning objective statements, 197market breadth indicators, 719overview, 197–198

Breadth thrust, 467–469Breakaway gap, 26, 27, 28, 272–273Breakout

failed, 19false and premature, 244

Bands, 21, 92–95, 125–134confidence, 589–591formed by highs and lows, 125rules for using, 131–132trading strategies using, 94–95

Bandwidth indicator, 95Barberis, Shleifer, and Vishny (BSV) hypothesis,

682–684Bar chart, 241

interpretation by Charles Dow, 7–25long-term patterns with best performance

and lowest risk of failure, 264–265practical use of, 64–68price objectives for, 54–60

Bar chart patterns, 234–266. See also Patternsclassic patterns, 243–258learning objective statements, 234overview, 234–235

Base, 248Bat indicator, 466Bayes’ theorem, 693n9Bearish belt-hold, 318Bearish key reversal, 32Bear market

end of, 12formation, 10phases, 11–12signal, 10transition from bull market, 15traps, 67

Behavioral finance, 519–520, 668–687, 697n84

anchoring and adjustment to, 671–672

bias and, 670–671competing hypotheses of, 681–687diffusion of information among investors,

676–677foundations of, 669–670herd behavior, 675–676imitative behavior and, 675information cascades, 675–676investor attention shifts, 677investors’ stories, 672–673limits of arbitrage, 669limits of human rationality, 669–670optimism, 673overconfidence and, 519pattern recognition and, 238–239psychological factors of, 670–674


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3

Candlestick chartsapplications, 336–343best of, 64candle formations, 61to confirm resistance, 337–338to confirm support, 338confluence of candles, 339–340to enter or exit trades, 340implied strategies in, 60–64to preserve capital, 336–337Qstick, 63–64quantifying candle formations, 62–63

Candlestick patterns, 296–302. See also Multi-candle patterns; Single candle lines

description of, 296–297ranking, 307

CANSLIM method, 409–410Capital asset pricing model (CAPM), 656,

694n20Capitalization

EMH and, 665CAPM. See Capital asset pricing modelCaps, 31–32Case studies

of designing “HAL” (2001: A Space Odyssey), 759–763, 771–772

of gaps and classic patterns, 276–278rule data mining for the S&P 500,

699–745Catalysts, 513Cattle cycle, 429, 430CBOE DJIA volatility index, 381–383. See also

Channel breakout operatorCBOE NASDAQ-100 volatility index,

383–384CBOE Russell 2000 volatility index, 384–385CBOE S&P volatility index, 385CCI. See Commodity Channel Index;

Commodity Cycle Index; Continuous Commodity Index

CFTC. See Commodity Futures Trading Commission

CHADTP. See Connors-Hayward Advance-Decline Trading Patterns

Chaiken, Mark, 210, 715, 716volume accumulator, 210–211

Chande, Tushar, 220thrust oscillator, 220–221

Channel breakout operator (CBO), 705–706, 743n12

gaps, 272–273systems, 753

Breakout priceto set price targets, 243

Broadening patterns, 248, 252–255Broad Market Equity Series All-Cap Index,

466, 467BSV. See Barberis, Shleifer, and Vishny

hypothesisBT. See Bolton-Tremblay valueBubbles, 520, 525

Keynes on, 528Buffett, Warren, 675Bulkowski, Thomas N., 28, 235Bullish belt-hold, 317, 318Bullish divergence, 736Bullish engulfing pattern, 322–324Bullish nonconfirmation, 736Bullish piercing pattern, 321–324Bull market

end of, 12formation, 10phases, 10–11transition to bear market, 15traps, 67

Business cycle, 432Busted rectangles, 246“Butterfly effect,” 416Buy

relative strength and, 451signals, 118–124

Buy-and-hold return, 762

C

CADR. See Cumulative advance-decline ratioCADV. See Cumulative accumulation-

distribution volumeCalculation period, 105Calls, 348–350

with alternative characteristics, 354American versus European, 354–356combinations, 351–354early exercise of an American call, 356margins and, 358n6minimum value of a European call, 355parity, 357–359, 363–365profits from, 349VIX and, 376–379

Call writer, 348


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Coil, 250–251Commodity Channel Index (CCI), 759Commodity Cycle Index (CCI), 442–443Commodity Futures Trading Commission

(CFTC), 690Commodity Research Bureau (CRB), 419Commodity Trading Advisors (CTAs), 114Common gap, 26, 27Computers

pattern recognition and, 239–240testing of trend system, 148

Confirmationof double bottom, 46earnings with technical confirmation, 666errors, 519principle of, 13

Connors, Larry, 289, 293Connors-Hayward Advance-Decline Trading

Patterns (CHADTP), 226–227Consolidation

identifying direction from consolidation patterns, 23

Constant forward contracts, 757–758Continuation patterns, 36–39

flags, 37–38pennants, 38run days, 39symmetric, descending, and ascending

triangles, 36–37wedges, 38–39

Continuous Commodity Index (CCI), 485Cooper, Michael, 692–693Correction

within a trend, 288Correlation, 563–576

assumptions, 566–574coefficient, 563–566, 584homoscedasticity, 575–576learning objective statements, 563normality, 571–574outliers, 575

Correlogram, 585–586Counterattack patterns, 324Countertrend trading, 174

breadth as a countertrend indicator, 227CPB. See Cumulative positive volume indexCrabel, Toby, 283, 285–286, 293–294Cradle, 248CRB. See Commodity Research BureauCrime of small numbers, 673–674

Channel-normalization operator (CN), 709–711. See also Stochastic indicator

Channels, 21, 95–96, 125–134creating with trendlines, 23–25description of, 256formation of, 23Keltner, 125–126

Charting, 3–70accumulation and distribution, 40–53bar chart and interpretation by Charles

Dow, 7–25causes of chart patterns, 5–6chart formations, 16–17concepts in chart trading, 39–40consistent patterns, 4–6continuation patterns, 36–39episodic patterns, 53–54evolution in price patterns, 68–70implied strategies in candlestick charts,

60–64learning objective statements, 3major and minor formations, 40one-day patterns, 25–36overview, 3–4practical use of the bar chart, 64–68price moves and trends, 6–7price objectives for bar charting, 54–60trendlines, 17–25trends in retrospect, 16–17

Chicago Board Options Exchangeoptions trading, 348n1

CHLR. See Cumulative new high-lows ratioClimax pattern, 255–257, 278, 279Closing prices, 13–14, 19Cluster, 269CMF. See Cumulative money flowCMT Association

about, ixexam topics and question weightings, xvilevel II content selections, xiiilevel II exam, xvprogram, xi

CN. See Channel-normalization operatorCNV. See Cumulative negative volume indexCNVR. See Cumulative net volume ratioCoarse Theorem, 556n8Coefficient of determination, 565Cognitive consonance, 519Cognitive dissonance, 519–520Cognitive errors, 669


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5

Dark cloud cover, 62, 301–302, 303, 321, 322

Databack-adjusted, 20in-sample, 764special data problems for futures systems,

757–758testing with clean data, 756–757

Data mining. See Rule data mining for the S&P 500

DCB. See Dead cat bounceDead cat bounce (DCB), 278–280Death cross, 142–144Demand Index, 217–218Demand oscillator, 212–213Derivatives, 240Descartes, Rene, 614Descending triangle, 248–249DHS. See Daniel, Hirshleifer, and

Subrahmanyam hypothesisDiamond top pattern, 248,

253–255pullbacks in, 255trading, 255

Directional movementconstructing indicators for, 87description, 87–90using, 88–90

Disposition effect, 558–559Distribution

frequency of, 117–118Divergence index, 170–171Divergence rules, 733–742

limitations of proposed indicator, 737–739

need for double channel normalization, 739–741

objective measure of, 736–737parameter combinations and naming

convention for, 741–742subjective analysis, 735–736types, 740–742

Divisorchanging, 192–193

DJIA. See Dow Jones Industrial AverageDoji pattern, 61, 298, 313–316,

337–338Doji star, 303Dollar, 398–399

stock market and, 401

Crossoversleft and right, 181

CTAs. See Commodity Trading AdvisorsCumulative accumulation-distribution volume

(CADV), 715–716moving averages of, 717

Cumulative advance-decline ratio (CADR), 720Cumulative money flow (CMF), 717Cumulative negative volume index (CNV),

717–718Cumulative net volume ratio (CNVR), 720Cumulative new high-lows ratio (CHLR), 721Cumulative on-balance volume, 714–715Cumulative positive volume index (CPB),

718–719Cups, 31–32, 258–259

with handle, 31Currency rates, 398–399

foreign, 422risk, 688

Curve-fitting, 756, 763Cycle

definition of, 437Cycle analysis, 427–447

business cycle, 432cattle cycle, 429, 430cycle channel index, 442–443identification, 429–432Kondratieff wave, 432–433learning objective statements, 427observing, 428–429overview, 427–428phasing, 445–447removing the trend, 436–437short cycle indicator, 443–444Swiss Franc cycle, 429triangular weighting, 436–437uncovering the cycle, 436–441using Fisher Transform, 440–442using Hilbert Transform, 438–439

Cycle channel index, 442–443Cyclical stocks, 504–505

d

Daily raw figure (DRF), 183Daily Sentiment Composite, 473, 479Danger points, 412Daniel, Hirshleifer, and Subrahmanyam (DHS)

hypothesis, 684–685


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forms of, 694n17nonrandom price motion in, 687–693Ponzi schemes and, 680–681predictability studies contradicting

semistrong EMH, 665–666predictability studies contradicting weak

form of EMH, 666–667price predictability and, 663–665price volatility of, 663smart versus dumb paradox, 657–658understanding, 518–519

Ehlers, John, 188, 427–428Ehrlich Cycle Finder, 430Einstein, Albert, 599, 627Elder, Alex, 206

Force Index, 206–207Ellis, Charles, 522–524

“Levels of the Game,” 522–523“The Winner’s Game,” 523–524

EMA. See Exponentially smoothed moving average; Exponential moving average

EMH. See Efficient markets hypothesisEndowment effect, 552–556Engulfing patterns, 61, 301, 302, 322–324Entropy, 751Entry, 235–236Envelopes, 90–92

trading strategies using, 94–95Environmental model. See Fab FiveEnvironmental Risk Index, 492–493Episodic patterns, 53–54Equity curve, 769–770Equity market, 698n99

risk premium, 688VIX and, 381–385

Equivolume, 204Errors

analysis of, 101–104cognitive, 669confirmation, 519extrapolation, 519hindsight, 519investor, 661judgment, 680

“Eve and Eve” double top pattern, 243Evening Star, 62, 63, 302–303, 304, 328Evidence-based technical analysis (EBTA), 645eVWMA. See Variably weighted moving averageExchange rate, 416Exhaustion gap, 27, 28, 275

Donchian channel, 96, 753. See also Moving averages5- and 20-day moving average system,

140–14220- and 40-day breakout, 142

Dorn, Anne, 524Dorn, Daniel, 524Double bottoms, 44–47, 243–244Double-smoothed momentum, 189–196Double-smoothed stochastic, 191Double tops, 44–47, 243–244Dow, Charles

interpretation of bar chart, 7–25Dow Jones 20 Bond Average, 497Dow Jones Industrial Average (DJIA), 9, 31

industry weightings, 383members of, 382

Dow Jones Industrials, 403–404Dow Jones Transportation Index, 9Downs, Walter, 290–291Dow theory

description of, 8–9futures markets and, 15–16S&P and, 14–15tenets of, 9–10

Dragonfly doji, 315Drawdown, 758

maximum cumulative, 768DRF. See Daily raw figureDrop-off effect, 79

time-based trend calculations and, 113Dysart, Paul, 744n29

e

EasyLanguage, 33EBTA. See Evidence-based technical analysisEfficiency factor, 768Efficient markets hypothesis (EMH), 71, 406,

513–519, 624–626, 651–668. See also Behavioral finance; Nonrandom price motion theories; Random walk hypothesis

assumptions of, 658–659challenges to, 657–668consequences of market efficiency, 651–653contradiction to, 667–668cost of information paradox, 658description of, 651evidence in favor of, 653–657false notions of, 652–653flaws in assumptions of, 659–663


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Flat time, longest, 769Force index, 206–207Forecasting, 100–104, 335–343

elimination of meaningless, 633–635learning objective statements, 335limiting to direction, 102overview, 335–336subjective, 634–635

Forward-looking horizon, 696n56Fosback, Norman, 212, 4694-9-18 crossover model, 146–147Fractal, 236Framing, 545–548Frequency, 438Fries, Charistian, 215Front-loaded technique, 108Full-span moving average, 445Functional relationships, 601Funnel, 252Futures

choosing between stock markets and, 391–393

Dow theory and, 15–16substituting open interest for volume,

215–216volume, 198–199

G

GAAP. See Generally accepted accounting principles

Galilei, Galileo, 598“Gambler’s fallacy,” 673Gann, W. D., 5Gaps, 25–28, 271–278

Bulkowski on, 28case study of, 276–278fading, 333filling, 27one-day patterns and, 25–28trading rules for, 27–28

Gaussian filter, 110Gaussian PDF, 440Generally accepted accounting principles

(GAAP), 517Geometric mean, 111–112Geometric moving average (GMA), 82,

111–112Globalization

Asian markets and, 69–70communication and, 416

Exit, 235–236Exogenous signal systems, 755–756Expected utility theory, 660Exponentially smoothed moving average

(EMA), 79–81variable, 82–83

Exponential moving average (EMA), 80–81, 82, 206–207

Extrapolation errors, 519

F

Fab Five, 464–495combo component, 489–494final tape component, 472monetary component, 482–489overview, 464sentiment component, 472–482tape component, 464–472using, 495

Fading, 164, 755gaps, 333

Failed breakout, 19Failures, 237

in flags and pennants, 263Failure swing, 173Fair value, 201–202Falling window, 333–334Falsification. See also Popper, Karl

limitations of, 622–623scientists’ response to, 626–628

Fama, Eugene, 406, 655Fat tail, 115–117, 154FBNDX. See Fidelity Investment Grade Bond

FundFed. See Federal ReserveFederal Reserve (Fed), 6, 65, 67Feedback

role in systematic price movements, 678–680

Fidelity Investment Grade Bond Fund (FBNDX), 501

Figure charts, 412Financial crisis of 1988, 7–8, 527Financial Data Calculator, 711Fisher, Mark, 295Fisher Transform, 440–442

inverse, 442Flags, 37–38, 262–264

failures in, 263objectives, 59–60


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HLR30. See Moving averages of new highs/lows ratio

HLX. See High-low indexHomoscedasticity, 575–576Hong and Stein (HS) hypothesis,

686–687Hook reversal day, 286Horizontal symmetry rule, 640Horn pattern, 282, 283HPI. See Herrick payoff indexHS. See Hong and Stein hypothesisHulbert, Mark, 511Hulbert Newsletter Stock Sentiment Index,

480–482Hume, David, 614–616, 653Hurst, J. M., 445Hutson, Jack, 192Hypothetico-deductive method, 629–631

example from, 630–631stages of, 629–630

I

Implied volatility, 361–372estimating price movement, 365–366fluctuations based on supply and demand,

368–371historical versus forward-looking volatility,

361–363impact on option prices, 371–372learning objective statements, 361option pricing models, 366overview, 361put-call parity and, 363–365valuing options, 366–368VIX and, 372

Indicators, 713–722predictability, 663–664price and volume functions, 713–714raw time series and, 712–722scripting, 711–712volume and, 205–216

Indicator scripting language (ISL), 711Industrial metals, 396Industrial raw materials, 396Industry

sectors, 698n105Inertial effects, 552–560

disposition effect, 558–559endowment effect, 552–556

GMA. See Geometric moving averageGold, 101, 398–399, 464

long-term interest rates, 399–400performance, 395–396

Golden Cross, 142–144Goldman Sachs, 374Goldman Sachs Commodity Index

(GSCI), 460Government, 460

libertarian paternalism, 557price moves and trends, 6

Grand rush, 5Granville, Joseph, 207

on-balance volume, 207–210Gravestone doji, 315–316, 337–338Gross loss, 761Gross profit, 761GSCI. See Goldman Sachs Commodity Index

H

Half-mast formation, 262–264Hamilton, William P., 7Hammer, 62, 312, 339–340Hammer pattern, 299–300Handle, 258Hanging man pattern, 62, 299–300, 312Happy guess, 618Harami pattern, 299, 325–326Hard assets, 395Harmonics, 428Head, 260Head-and-shoulders formation, 51–53,

259–262back test results, 643–644price objective, 58–59trading, 262

Hedging, 454Herd behavior, 674, 675–676Herrick payoff index (HPI), 195–196, 204Heuristics, 519, 672High-low index (HLX), 221–222High-low logic indicator, 469High wave candle, 311Hikkake, 286, 287Hilbert’s Transform, 83, 438–439Hill, John R., 756Hindsight errors, 519HLR1. See Moving averages of new highs/

lows ratio


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Island reversals, 30–32, 280pivot point reversals and swings, 30–31

Isosceles triangle, 250–251

J

January effect, 519Jegadeesh, Narishimhan, 406Jiler, William L., 3–4

K

Kalman filters, 588–589KAMA. See Kaufman adaptive moving averageKasakasa, 300Kaufman adaptive moving average (KAMA), 83Kelly Criterion, 662Keltner, Chester, 92Keltner band, 92–93Keltner channels, 125–126Kepler’s laws of planetary motion, 649Kernel regression, 647n50Kestner, Lars, 691–692Keynes, John Maynard, 524–528

animal spirits and, 528on bubbles, 528on efficient markets, 525–526on excessive volatility, 526on investment professionals and market

efficiency, 526long-term expectations and stock values, 525long-term expectations for investors,

524–525on professional investing versus beauty

contest, 527on the professional investor, 526–527on reduced role of fundamental investors,

527–528warning for long-term investors, 528

Key reversal bar, 281Key reversal days, 32–34

programming, 33Kirkpatrick, Charles D., 410

method, 410–411KISS philosophy, 464, 497–498Knetsch, Jack, 553–554Knockout pattern (KO), 288–289KO. See Knockout patternKondratieff wave (K-wave), 432–433Kuhn, Thomas, 635K-wave. See Kondratieff wave

learning objective statement, 552overview, 552status quo effect, 557–558

Information cascades, 675–676InPhase, 438In-sample (IS) data, 764Inside bar, 283–286Inside days, 35Integrated probability model, 228Interest rates, 65, 476

changes in, 482decline in, 154long-term, 399–400prices-of-debt instruments from, 722spread, 722

Intermarket analysis, 415–426determining intermarket relations, 420–421example of, 416learning objective statement, 415using correlations for portfolio

diversification, 422–426Intraday intensity, 211Intraday patterns, 229–231, 293–295Intraday volume patterns, 229–231Intrinsic value, 507, 512Inverted hammer, 300, 301Inverted triangle, 252Investing, 389–414

array and, 402issue selection, 393–394perspectives on, 521–528relative strength strategies for, 448–460relative versus absolute return

investment, 504Investment policy statements (IPS), 529–532

overview, 529philosophy, 529–530process of, 530sample investment policy, 531–532

Investmentslosses from, 559n14

Investorsactive versus passive, 504diffusion of information among,

676–677errors, 661rational assumptions of, 660–661shifts in attention, 677

IPS. See Investment policy statementsISL. See Indicator scripting language


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M

MA. See Moving average; Moving-average operator

MACD. See Moving average convergence/divergence

Macrotrends, 154“Major Price Trend Directional Indicator”

(MPTDI), 135–136MAMA-FAMA strategy system, 83, 85–86Market breadth indicators, 719Market facilitation index, 233Markets

crash, 680efficiency of, 513–519entropy and, 751intermarket analysis, 415–426market efficiency, 514–515maturity of, 117–118measuring market strength, 592–594money and, 115sectors, 698n104tone, 33VIX and, 379–381

Market-to-market accounting, 106MAR ratio, 764, 768Maximum adverse excursion, 763Maximum consecutive losses, 768Maximum drawdown (MDD), 768Maximum Entropy Spectral Analysis (MESA),

427–428Maximum favorable and adverse excursions, 769McClellan oscillator, 218–219MDD. See Maximum drawdownMeasured rule, 243, 264Measuring gap, 275Media

underreaction to news, 518Megaphone, 252MESA. See Maximum Entropy Spectral AnalysisMill, John Stuart, 619Minute-to-minute patterns, 239Misunderstanding randomness, 520MLM. See Mt. Lucas Management IndexMode bat, 465, 475Models

Adaptive Trading Model, 494autoregressive model, 100–101Barberis, Shleifer, and Vishny hypothesis,

682–684

L

Lag, 100, 191Landry, David, 272–273Lane, Dr. George, 743n18Law of noncontradiction, 602Law of percentages, 402–403Least-squares model, 101Left and right translation, 438Legislation

Uniform Prudent Investor Act, 532“Levels of the Game,” 522–523Levy, Robert, 405–406

method, 409Libertarian paternalism, 557Linearity, 566–571Linearly weighted moving average (LMA;

LWMA), 79, 725Linear regression model, 589–592Linear regression slope, 591Lines, 12Lip, 258Liquidity

liquidity premium and gains to countertrend trading in stocks, 692–693

premium, 688of trading, 393

LMA. See Linearly weighted moving averageLogic, 601–612

consistency of, 602deductive, 603–610induction by enumeration, 611–612inductive, 610–611propositions and arguments, 602

Long-legged doji, 316Long real bodies, 316–319Long sale, 181Long Term Capital Management

(LTCM), 662Lookback, 407Lorca-Susino, Francisco, 443–444Lorenz, Edward, 416Loss

aversion, 539–541distribution, 117large, 769maximum consecutive losses, 768, 769

Lost motion, 5LTCM. See Long Term Capital ManagementLWMA. See Linearly weighted moving average


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Money flowcumulative, 717moving averages of, 717

Money flow index, 210Money management, 503–534

adaptive markets hypothesis, 520–521alpha returns, 504analysts and, 516–518behavioral finance and, 519–520beta returns, 504–505learning objective statements, 503market efficiency, 513–519money managers’ record, 511–513overview, 503perspectives on investing, 521–528professional investment policy statements,

529–532relative versus absolute return investing, 504top-down fundamental analysis process,

505–510underperformance of money managers,

512–513Monte Carlo permutation, 700, 702–703Morgan Stanley Focus Growth Strategy Profile,

529–532Morning star, 62, 63, 302–303, 304, 327–328Mt. Lucas Management Index (MLM), 691–692Moving average (MA), 71–98. See also

Donchian channelof accumulation distribution volume, 717of advance-decline ratio, 719approaches to, 225–226ARIMA and, 583–589bands, 92–95calculating, 72–78channel, 95–96components of, 106–107crossover projection, 154–155description, 72directional movement and, 87–90envelopes, 90–92full-span, 445learning objective statements, 71length of, 76of money flow, 717multiple, 76–77of negative volume index, 718of net volume ratio, 721overview, 71–72performance of, 150

bonds model, 49–502capital asset pricing model, 656, 694n20Daniel, Hirshleifer, and Subrahmanyarn

hypothesis, 684–685Fab Five model, 464–4954-9-18 crossover model, 146–147Hong and Stein hypothesis, 686–687integrated probability model, 228least-squares model, 101linear regression model, 589–592modified 3-crossover model, 146Nine-Indicator Model, 490–492option pricing models, 366–367real-time models, 496–497stock market model, 461–495Zweig Bond Model, 497–502

Modern Portfolio Theory (MPT), 407Modified 3-crossover model, 146Momentum, 406

adding volume to, 193–194basic exit, 165characteristics of, 159–161comparing stochastic indicator to

momentum and RSI, 178–180comparing stochastic indicator to RSI and,

178–180confirmed by trading volume, 667description, 158–170as the difference between price and trend,

161–162double-smoothed, 189–196geometric representation of, 157high-momentum trading, 168identifying and fading price extremes, 164–168learning objective statements, 156moving convergence/divergence, 168–170nonreversal of, 666–667oscillators and, 156–196overview, 156–158pattern of, 158–159persistence of, 666relative strength and, 448–449reversal of, 666system, 135timing an entry, 163–164as trend indicator, 162–163volume and percentage change, 206–207

Momentum-volume (MV) indicator, 194Money

markets and, 115


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Natural log, 112NAV. See Net asset valueNDR. See Ned Davis ResearchNeckline, 52, 261Ned Davis Research (NDR), 461. See also Fab FiveNegative volume index (NVI), 211–212Net advances (NA), 218–219Net asset value (NAV), 106Net borrowed reserves, 487Net profit, 761Neural network, 765Neuro-Shell, 711Nietzsche, 2009/11, 53–54. See also Price shocksNine-Indicator Model, 490–492Noise, 40

about one-day patterns, 36Non-correlated asset classes, 455–458

hedge risk premium and commodity futures, 689–690

Noninformative event, 694n20Nonparametric regression, 582Nonrandom price motion theories, 648–698.

See also Efficient markets hypothesis; Technical analysis

in the context of efficient markets, 687–693importance of theory, 649learning objective statements, 648liquidity premium and gains to countertrend

trading in stocks, 692–693Mt. Lucas Management Index of trend

following returns, 691–692overview, 648scientific theory, 649systematic price motion and market

efficiency, 687–689Northern doji, 316NR4 day, 292Null hypothesis, 625–626, 702–703NVI. See Negative volume index

O

OBM. See On-balance volumeOckham’s Razor, 599, 632On-balance volume (OBM), 207–210, 232–233

price substitution in moving average, 209–210

One-bar reversal patterns, 281One-day patterns

charting, 25–36

Moving average (MA) (continued)price substitution in, 209–210profile of, 123–124sequences, 151–154simple, 743n13smoothing effect, 707step-weighted, 135–136strategies for using, 83–87systems, 75310-day moving average rule, 137time-based trend calculations and, 104–111types of, 78–83, 107weighted by group, 109

Moving average convergence/divergence (MACD), 168–170, 755

reading the indicator, 169–170RSI version of, 177trading, 170variably weighted, 215volume-weighted, 214

Moving-average operator (MA), 706–709Moving averages of new highs/lows ratio

(HLR1; HLR30), 722MPTDI. See “Major Price Trend Directional

Indicator”; Modern Portfolio TheoryMSCI EAFE Index

description of, 460Multi-candle patterns, 320–334. See also

Candlestick patterns; Single candle lineslearning objective statements, 320

Multi-Cap Equity Series, 475Multiperiod horizons, 695n43Multiple-bar patterns, 302–306Multiple regression, 578, 580–582MV. See Momentum-volume indicator

n

NA. See Net advancesNaked bar upward reversal, 286NAREIT. See National Association of Real

Estate Investment TrustsNarrow-range bar (NR), 292–293NASDAQ 100

sector weightings, 384trend system for, 123–124

NASDAQ Composite Index, 416–417NASDAQ futures

performance statistics, 124National Association of Real Estate Investment

Trusts (NAREIT), 460


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Outlier-adjusted profit, 767Outliers, 575Out-of-sample optimization (OOS), 756, 764–766Outside bar, 286–287Outside days, 35Overbuy, 164Oversell, 164

P

Pairs trading, 738Paper assets, 395Paper umbrella, 300Parameter set, 758Path dependence, 540–541Pattern completion rule, 641–642Pattern recognition systems, 755Patterns. See also Bar chart patterns

broadening, 252–255bull and bear traps, 67causes of chart patterns, 5–6change of character and, 66–67characteristics of, 235–237computers and, 239–240consistent, 4–6continuation, 36–39description of, 235entry and exit, 235–236evolution in price patterns, 68–70existence of, 237–239failures, 66–67future information leakage, 642–643identifying direction from consolidation

patterns, 23, 242long-term bar chart patterns with best

performance and lowest risk of failure, 264–265

market structure and recognizing, 240objective, 637one-day, 25–36postpattern activity, 66profitability of, 242–243recognizing, 67–68, 238–239with rounded edges, 258–265shorter continuation trading patterns, 262–264subjective, 636–644variations from, 199–202in volatility, 519

Payoff ratio, 768PDF. See Probability density function

cups and caps, 31–32gaps, 25–28inside days, 35island reversals, 30–32noise about, 36outside days, 35reversal days and key reversal days, 32–34spikes, 28–30trading rules for gaps, 27–28wide-ranging days, 34–35

O’Neil, William, 409CANSLIM method, 409–410

Oops! pattern, 289, 301OOS. See Out-of-sample optimizationOpening gap, 273–275Open interest

description of, 198learning objective statements, 197overview, 197–198substituting for volume using futures, 215–216volume and, 202–203

Optimizingmeasuring system results for robustness,

767–772methods of, 764–767profit measures, 767–768risk measures, 768–769screening for parameters and, 766smoothness and the equity curve, 769–770

Option pricing, 347–360characteristics of option values, 354–359impact from implied volatility, 371–372implied volatility and, 366–368learning objective statements, 347models, 366overview, 347selling an option, 349n2types of options, 347–354

Oscillatorsdescription, 171–172forecast, 592learning objective statements, 156momentum and, 156–196overview, 156–158relative strength index and, 172–177stochastic indicator, 177–182trending versus sideways markets, 193volume, 207

O’Shaughnessy, James, 410method, 410


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distribution of, 115estimating price movement, 365–366evolution in price patterns, 68–70extremes, 164–168historical data, 646n32history of, 137moves and trends, 6–7objectives for bar charting, 54–60predictability of, 663–665for promoting market efficiency, 689proxy for, 189role of feedback in systematic price

movements, 678–680tick-to-tick, 239volatility of EMH, 663

Price extremesdetermining, 84–85

Pricesclosing prices, 13–14

Price shocks, 4, 53Price targets

using breakout price to set, 243Price-to-book-value effect

EMH and, 665Price-to-earnings ratio (P/E), 518,

530, 661EMH and, 665

Pring, Martin, 34, 397Probability density function (PDF), 440Producer price index (PPI), 483Profit factor, 120, 761, 767

patterns and, 242–243percent profitable, 761

Profitsfrom calls, 349distribution, 117elements of objectives, 55from puts, 350from a straddle, 351–352targeting profits after tops and bottoms,

57–60targets for consolidation areas and channels,

55–57Program trading, 68Propositions, 602–603Prospect theory, 537–543

description of, 540n9drawbacks of, 542learning objective statements, 537loss aversion, 539–541

P/E. See Price-to-earnings ratioPearson’s correlation, 563–565, 567, 568Pennants, 38, 262–264

failures in, 263Percentage bands, 126Percentage change method, 407Percentage envelopes, 90–92Percentage filter, 638Percentage winning trades, 768%R method, 187Perception biases, 544–551

anchoring, 548–549framing, 545–548learning objective statement, 544overview, 544saliency, 544–545sunk-cost bias, 550–551

Perfect fit correlation, 764Period, 437Perpetual contracts, 757–758Phase, 438Phase angle, 438Phasing, 445–447Piercing line, 62, 303Piercing pattern, 321–322Pipe formation, 281Pivot, 272Pivot point reversals, 30–31Pivot-point weighting, 110–111Point-and-figure patterns, 241Point of equilibrium, 45Politics

presidential election cycle, 433–435Ponzi, Charles, 680

schemes, 680–681Popper, Karl, 608, 618–623Portfolio

construction and implementation, 530diversification away from US markets, 418diversification using intermarket analysis,

422–426Positive volume index (PVI), 211–212PPI. See Producer price indexPresidential election cycle, 433–435

1912–1992, 4341983–2010, 435election year analysis, 435

Pricechange over time, 104changing price objectives using channels, 57


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15

learning objective statements, 588measuring market strength, 592–594trading signals using a linear regression

model, 589–592Regression line, 764Regression studies, 765Relative return, 504Relative strength. See Momentum

academic studies of, 405–406bottom up analysis and, 405–409buy rule, 451data, 449data sources, 459–460learning objective statement, 448measuring, 407–409momentum, 448–449overview, 448ranking, 451real world implementation, 458–459sector returns, 449–451sell rule, 451–453solutions to drawbacks of, 454–458strategies for investing, 448–460

Relative strength index (RSI), 172–177, 755countertrend trading, 174creating the stochastic indicator from,

181–182modifying, 173–174net momentum oscillator, 174standard 2-period, 176–1772-day, 174–176ups and downs, 174version of MACD, 177volume-weighted, 194–195

Relative vigor index (RVI), 188–189Reset accumulative average, 113Resistance lines, 18–20

candlestick charts and, 337–338determining, 84trading rules for, 22–23

Return on account, 762Return on invested capital (ROIC), 530Return retracement ratio, 769Reversal days, 32–34

2-bar reversal patterns, 34Reverse triangle, 252Reversions to the mean, 755Rising wedge, 256Rising window, 333–334ROC. See Rate of change

overview, 537in practice, 541reference point, 537–538S-curve, 538–539

Pruitt, George, 756Pseudoscience

versus science, 621–622Pullbacks, 22, 236–237

in diamond patterns, 255Puts, 350–351

combinations, 351–354parity, 357–359, 363–365payoffs, 357profits from, 350VIX and, 376–379

PVI. See Positive volume indexPythagoras, 600Pythagorean Theorem, 600

Q

Qstick, 63–64Quadrature, 438Quadruple witching day, 204

R

Random walk hypothesis (RWH), 71, 406, 651. See also Efficient markets hypothesis

Raschke, Linda Bradford, 292–293Rate of change (ROC), 157, 157n1Rate of return, 768Ratio analysis, 394Ratio method, 405Raw time series

indicators and, 712–713Real-time models, 496–497Recovery ratio, 768

time to recovery, 769Rectangle pattern, 244–245

busted, 246trading, 246

Regression, 577–582assumptions, 582equation, 577–578, 579learning objective statements, 577multiple, 578, 580–582nonparametric regression, 582

Regression analysis, 588–594autoregressive integrated moving average,

583–589


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Scatterplot, 568–570Schabacker’s rules, 12Schultz, 218Science

functional relationships, 601knowledge and, 599–601laws versus theories, 601logic in, 601–612philosophy of, 612–629predictions, 621versus pseudoscience, 621–622restriction of, 620–621skepticism and, 614

Scientific knowledge, 599–601purpose of science, 601quantitative, 600

Scientific method, technical analysis and, 595–647

critical analysis of observed results, 631–632description of, 596Greek science and, 596–597hypothetico-deductive method, 629–631information content of scientific hypotheses,

623–626key aspects of, 632–633learning objective statements, 595objectification of subjective TA, 636–644objective reality and objective observations,

598–599observations, 646n14overview, 595philosophy of science, 612–629prediction versus observation, 597–598role of logic in science, 601–612scientific attitude and, 629scientific knowledge and, 599–601scientific revolution and, 597–598subsets of TA, 644–645technical analysis and, 633–635

Scientific Revolution, 597–598Screen trading, 392S-curve, 538–539Sector

overweights versus underweights, 505–506Secular analysis, 395–397Securities

AAA, 545mean reversion or reversal effect in, 518price behavior in an efficient market,

515–516

ROIC. See Return on invested capitalRolling calculation period, 104Rolling trend calculations, 113“Rollo Tape.” See Wyckoff, Richard D.Rounding bottoms, 258–259Rounding tops, 258–259Rouwenhorst, K. G., 406RSI. See Relative strength indexRule data mining for the S&P 500, 699–745.

See also Technical analysisanalyzed data series, 700–701average return, 701avoidance of data snooping bias, 700bias and evaluation, 699–700data input series used in case study, 722–723divergence rules, 733–742evaluation of complex rules, 701–702extreme values and transitions, 725–733learning objective statement, 699naming convention for extreme value and

transition rules, 733overview, 699parameter sets and total number of E-type

rules, 733raw time series and indicators, 712–722statistical significance level, 703statistical terms used, 702–703technical analysis themes, 701time-series operators, 705–712transforming data series into market

positions, 703–705trend rules, 724–725

Rule of seven, 60Runaway gap, 27, 28, 42, 275Run bars, 286Run days, 39Runs

distribution of, 116Russell 2000 volatility index (RVX), 384–385RVI. See Relative vigor indexRVX. See Russell 2000 volatility indexRWH. See Random walk hypothesis

S

Saliency, 544–545Salk, Jonas, 625–626Saucer, 258–259Scaling, 194Scallops, 258–259


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Sklarew, ArthurRule of Seven, 60

Slippage, 393Slope of the yield curve, 722SMA. See Simple moving averageSmith, Vernon, 556Smoothness, 769Soft assets, 395Software

user-friendly, 106Sortino ratio, 769Southern doji, 316S&P

transition from bull to bear market, 15

using Dow theory, 14–15S&P 100 volatility index (VXO)

industry weightings, 385S&P 500, 416–417

Rule data mining for the S&P 500, 699–745

S&P 500 Indexdescription of, 460

Spearman, Charles, 565coefficient, 565–566

Spikes, 28–30, 278quantifying, 29–30in volume, 200–201, 224–225

S&P indexindustry weightings, 374

Spinning top, 299, 310–311SPIVA. See Standard & Poor’s Indices vs. Active

FundsStandard deviation moving average,

111, 112, 200, 762Standard & Poor’s Indices vs. Active Funds

(SPIVA), 511STARC band, 93Star patterns, 327–328Status quo effect, 557–558Step-weighted moving average, 135–136Sterling ratio, 769Stochastic indicator, 177–182, 466, 755. See

also Channel-normalization operatorcalculating the 10-day indicator, 178comparing to momentum and RSI,

178–180creating from the RSI, 181–182double-smoothed, 191trading, 180–181

prices in an efficient market, 514returns, 518

Sellrelative strength and, 451–453signals, 118–124

Sengmueller, Paul, 524Sequences, 151–154

averaging, 152–154Setup, 268Shading, 60Shadows, 60Shark-32, 290Shark pattern, 290–291Sharpe, William F., 694n20Sharpe ratio, 691–692, 762, 769Shiller, Robert, 650, 677, 678Shleifer, Andre, 661Shooting star, 62, 300, 301, 312Short cycle indicator, 443–444Short sale, 181Short-term patterns, 241, 267–308

learning objective statements, 267overview, 267–268pattern construction and determination,

270–271traditional, 271–295

Sibbett, James, 217demand index, 217–218

SIF. See Student Investment FundSignals, 340–341

anticipating the trend, 121–122buy and sell, 118–124comparing basic trading signals, 120–121giving specific, 85–87multiple, 66progression of, 151–154for sell and buy, 21trading signals using a linear regression

model, 589–592trendlines and, 119–120

Simple moving average (SMA), 74–76, 107Single candle lines, 309–319. See also

Candlestick patterns; Multi-candle patterns

Doji line, 313–316learning objective statements, 309long real bodies, 316–319spinning tops and high wave candles,

309–313Size effect, 518


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discretionary versus nondiscretionary systems, 747–750

initial decisions for, 751–752learning objective statements, 746necessity of, 747–750optimization of, 763–772overview, 746–747pitfalls to nondiscretionary system,

749–750requirements for designing a system,

750–751special data problems for futures systems,

757–758successful, 750testing methods and tools, 758testing with clean data, 756–757test parameter ranges, 758–763types of technical systems, 752–756

System MAR, 762System Writer, 496. See also TradeStation

T

TA. See Technical analysisTaxes, 559n14Technical analysis (TA). See also Nonrandom

price motion theories; Rule data mining for the S&P 500

adoption of scientific method, 633–635elimination of meaningless forecasts, 633–635elimination of subjective TA, 633objectification of subjective TA, 636–644paradigm shift, 635popular theory of, 650–651scientific method and, 595–647subsets of, 644–645

10-day moving average rule, 13710-year bonds, 460Theories

nonrandom price motion theories, 648–698scientific, 649theory of elasticity, 42–43theory of general relativity, 627

Three black crows, 303–304, 305, 330–3313-crossover model, 146Three inside down pattern, 304–306Three inside up pattern, 304–306Three outside down pattern, 306Three outside up pattern, 306Three white soldiers, 303–304, 331–332

Stock market. See also Fab Fivebottom up analysis, 405–409diversification in, 390–391experience in, 392industry sectors of, 403–404learning objective statements, 461model, 461–495relative strength of, 405screening for favorable stocks, 409–413U. S. dollar and, 401

Stocksfrom bonds, 400choosing between futures markets and,

391–393cyclical, 504–505historical volatility of, 362performance of, 506–510ranking, 695n42returns, 424

Stop-loss order, 166–167Straddle, 351–352Strap, 351Strauss, Charles, 617–618Stretch, 294Strip, 351Student Investment Fund (SIF), 531, 532Sunk-cost bias, 550–551Supply and demand, 7

implied volatility and, 368–371Support

determining, 84Support lines, 18–20

trading rules for, 22–23Suspension gaps, 275Swings, 30–31Swing trading, 10Swiss Franc cycle, 429Syllogisms

affirming the consequent, 608categorical, 603–605conditional, 605–606invalid form of conditional, 608–610valid forms of conditional, 606–608

Symmetrical triangle, 248, 250–251System design and testing, 746–773. See also

Tradingbenefits of nondiscretionary system, 749best system, 756case study of “HAL,” 759–763,

771–772


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concepts in chart trading, 39–40costs, 391, 459cycle analysis, 427–447danger of trading double and triple tops, 47day traders, 390–391, 392diamond top pattern, 253–255double formations, 244flags, 264forecasting, 335–343frequency of, 459between futures markets and stock markets,

391–393guidelines, 342–343head-and-shoulders pattern, 259–262high-momentum, 168intermarket analysis, 401–402learning objective statements, 389liquidity, 393the MACD, 170options, 348n1overview, 389pairs, 738pennants, 264rectangle patterns, 246risks, 391RSI countertrend, 174rules for gaps, 27–28, 97rules for head and shoulders, 52–53rules for trading using trendlines, 20–21screen, 392selection, 390–393signals using a linear regression model,

589–592the stochastic indicator, 180–181strategies using ARIMA, 587–588strategies using bands and envelopes,

94–95suitability, 392swing, 390–391, 392techniques, 335–343time horizon, 392top-down analysis of, 394–404trendline rules for horizontal support and

resistance levels, 22–23triangles, 251–252volatility, 392–393volume, 393wedges, 258

Trading range, 25, 244–245Trend-following systems, 753–755

Threshold level, 168Throwbacks, 236–237Thrust oscillator (TO), 220–221Tick-to-tick prices, 239Tick volume indicator (TVI), 213–214, 229Time-based trend calculations, 99–113

accumulative average, 112drop-off effect, 113forecasting and following, 100–104geometric moving average, 111–112learning objective statements, 99moving average and, 104–111overview, 99–100price change over time, 104reset accumulative average, 113

Time intervals, 16, 117–118Time series operators, 705–712, 745n51Time stamps, 229Time-weighted average price (TWAP), 216Timing

momentum and, 163–164, 165Titman, Sheridan, 406TMA. See Triangular moving averageTO. See Thrust oscillatorTop-down analysis, 394–404, 505–510

cyclical emphasis, 397–403secular emphasis, 395–397

Topsaccumulation and distribution, 40–53calculating profit target for top formation, 58double and triple, 44–47rounded, 49–50targeting profits after, 57–60V-tops, 41–44wedges, 51

Tradeaverage trade net profit, 761“dollar down, stocks up,” 520international, 7length of average winning trade, 768maximum consecutive losing trades, 762number of, 761“risk-on, risk-off,” 520

Trade MAR, 763TradeStation, 33, 108–109, 129, 228, 496,

711, 743n19Trading, 389–414. See also System design and

testingbottom up, 405–409comparing basic trading signals, 120–121


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success of, 115–118techniques using two trendlines,

138–144three trends, 145–146timing the order, 132–133trend period, 151volatility system, 137

Trianglesascending, 36descending, 36formation of descending triangle,

36–37objectives, 59–60size of, 37standard, 247–248symmetric, 36trading, 251–252

Triangular filtering, 109Triangular moving average (TMA), 82Triangular weighting, 109–110, 436–437TRIN, 476–478Triple bottoms, 44–47, 246–247Triple tops, 44–47, 246–247Triple witching day, 204TRIX, 192, 193True strength index (TSI), 189–191Truncated moving average, 107TSI. See True strength indexTSM pivot point average, 110–111TVI. See Tick volume indicatorTWAP. See Time-weighted average priceTweezer pattern, 329–3302-bar reversal patterns, 34Two-bar breakout, 282Two-bar reversal patterns, 281–282Two-candle pattern, 321–3242-day relative strength index, 174–176

U

UDR. See Upside/downside ratioUltimate oscillator, 187–188Umbrella lines, 313Underdetermination of theories problem,

646n14Underwater curve, 769–770Uniform Prudent Investor Act (UPIA), 532UPIA. See Uniform Prudent Investor ActUpside/downside ratio (UDR), 219Utility theory, 543

Trendlines, 17–25back-adjusted data, 20creating a channel with trendlines, 23–25new trend direction, 21redrawing, 17–18rules for trading using, 20–21for signals, 119–120support and resistance lines, 18–20trading rules for horizontal support and

resistance levels, 22–23Trends, 117–118. See also Time-based trend

calculationsanticipating trend signals, 121–122classifications of, 9determining, 83–84followers of, 144, 587–588, 753indicators for, 462–463long-term versus short-term, 65–66, 115macrotrends, 154minor, 13momentum as trend indicator, 162–163persistence of, 14price and volume, 211–212price moves and, 6–7removing for analysis, 436–437in retrospect, 16–17, 64–65rules, 724–725secondary, 12–14systematic process and, 696n71time intervals and, 16volume and, 13

Trend slope method, 408Trend systems, 114–155

bands and channels, 125–134buy and sell signals, 118–124comprehensive studies, 147computer testing of, 148early exits from a trend, 154frequency of, 115learning objective statements, 114, 138moving average projected crossover, 154–155moving average sequences, 151–154multiple trends, 144–147overview, 114profit and loss distribution, 117reliability and delay compromise, 133selection of right trend method and speed,

147–151signal progression, 151–154single trend applications, 134–137


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open interest and, 202–203oscillator, 207overview, 197–198positive and negative volume index,

718–719as predictor of volatility, 205relative changes in, 231removing low-volume periods, 232removing volume associated with small

price moves, 232–233spikes, 200–201, 224–225standard interpretation of, 202–205of trading, 393trends and, 13use of, 196variance in, 200

Volume accumulator, 210–211Volume count indicator (VCI), 210Volume-weighted average price

(VWAP), 216Volume-weighted MACD (VWMACD),

214Volume-weighted RSI, 194–195V-tops, 41–44VWAP. See Volume-weighted average priceVWMACD. See Volume-weighted MACDVXO. See S&P 100 volatility index

W

Walk forward optimization, 756, 766Warrants, 351Waters, Jim, 182Wave

definition of, 437Wave analysis, 8–9, 437Wealth-Lab, 711Wedges, 38–39, 248, 255–257

characteristics of, 257performance rank of, 257top and bottom patterns, 51trading, 258

Weighted moving average, 81, 107–108Whaley, Dr. Robert, 374Whewell, William, 616–618Whipsaws

short-term, 78White’s Reality Check, 700, 702–703Whole sample optimizing, 764–765“Why Do People Trade?“, 524Wide-range bar, 291–292

V

Value Line Ranking System, 411Variable accumulation distribution, 715Variably weighted moving average (eVWMA),

215V-bottoms, 41–44VCI. See Volume count indicatorVertical charts, 412Vertical symmetry rules, 639–640VIX. See Volatility IndexVolatility

alpha versus beta returns, 504implied, 361–372patterns in, 519price and, 663reduction in, 423of trading, 392–393

Volatility bands, 126–128Volatility Index (VIX), 134, 293, 373–386,

479–480Amex QQQ, 386calculating, 375–376equity market, 381–385formula and calculations, 375–376history of, 374implied volatility and, 372learning objective statements, 373market movement and, 379–381nonmathematical approach to, 375overview, 373put-call parity and, 376–379

Volatility patterns, 291–293Volatility system, 137Volume

advancing versus declining, 217breadth indicator and, 222cumulative accumulation-distribution,

715–716cumulative on-balance, 714–715drop in, 201–202exceptions to, 204filtering low volume, 231–233futures, 198–199indicators, 205–216interpreting, 223–227learning objective statements, 197momentum and percentage change, 206–207moving averages of negative volume index, 718normalizing, 205–206on-balance, 207–210


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Wide-ranging days, 34–35Wilder, Welles, 87, 172

method, 82, 87Williams, Larry, 182, 289, 715, 753Williams’s oscillators, 182–188

linking current day with prior day, 186%R method, 187

Wilson, E. O., 520Windows, 298, 332–333“The Winner’s Game,” 523–524W intraday pattern, 199–200Woodshedder’s long-term indicator, 143Writing a covered call, 352n3

Wyckoff, Richard D., 412–413method, 412–413progression of selecting stocks, 413

Wyckoff Wave, 413

Y

Yield curve, 722

Z

Zweig, Marty, 497, 700Zweig Bond Model, 497–502

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