INDEX
- A
- Academic trading strategies, 11–12
- Actual performance, expected vs., 104–107
- AI (artificial intelligence), xii, 28–29
- Algorithmic trading, see Quantitative trading
- Algoseek, 41, 95
- Alpaca, 86, 95, 99
- Alpha decay, xii–xiii, 198
- Alternative trading systems, 85
- Amaranth Advisors, 129, 186, 193
- Annualized Sharpe ratio, 48–49
- Annualized standard deviation of returns, 49
- Anwar, Yaser, 28
- Application programming interface (API), 86, 94, 98–99
- Arbitrage pricing theory (APT), see Factor models
- Arithmetic mean, 112
- Array processing, in MATLAB, 199–203
- Artificial intelligence (AI), xii, 28–29
- assert function, MATLAB, 176–177
- Asset allocation, optimal, 189
- Augmented Dickey-Fuller test of cointegration, 149, 155
- Automated trading systems, 93–101
- Averages, ensemble vs. time series, 127, 128
- Average daily volume, 101–102
- B
- backshift function, MATLAB, 181
- Backtesting, xvii, 33–79
- of academic strategies, 11–12
- common platforms for, 34–40
- defined, 57–58
- determining optimal holding period with, 170
- execution and, 95, 100
- of half-Kelly betting, 122–123
- of high-frequency strategies, 188
- historical databases for, 40–47
- impact of survivorship bias on, 26–27
- by independent traders, 3
- of January effect, 175–179
- of mean-reverting strategies, 135
- minimum duration of, 60–61
- paper trading and, 103–104
- performance measurement for, 47–57
- pitfalls with, 57–72
- of prospective strategies, 20
- for risk management, 124
- of strategy modifications, 128–129
- strategy refinement after, 77–78
- of trader-forum strategies, 12–13
- transaction costs in, 72–77
- Backtracker, 94
- Bailey, David J., 60
- Bank of Montreal, 186
- Bankruptcy risk, 84
- BasketTrader, 96, 97
- Basket traders, 94, 96–98
- Bayes Net toolbox, MATLAB, 204
- Bear Stearns, 2
- Behavioral finance, 126–128
- Bel Fuse Inc., 102
- Benchmarks, 20–23
- Beta, 16, 188–189
- Bias. See also Data-snooping bias; Survivorship bias
- Bid-ask spread, 25, 27, 101
- bizfilings.com, 83
- Black swan events, 122
- Blogs, 12–14
- Bloomberg, 17, 41, 88
- Blueshift, 40, 94, 95, 99
- Bollinger Bands, 140
- Bright Trading, 82
- Brokerages, 85–87
- brokercheck.finra.org, 87
- Broker-dealers, 86–87
- Bugs, software, 103, 125
- Buy-and-hold strategies, 19. See also Long-only strategies
- C
- C (programming language), 188, 199, 200
- CAGR (compound annualized growth rate), 47
- Calendar effect, see Seasonal trading strategies
- Calendar spreads, 159
- Capacity, 30, 101, 194–195, 197
- Capital:
- Capital allocation:
- Capital availability:
- Capital gain, long-term, 19–20
- Cell arrays, in MATLAB, 203
- Charting, 1
- Chat with Traders, 12
- Chicago Mercantile Exchange, 18
- CNBC PRO, 88
- Coca-Cola (KO), 153–159
- Cointegrating price series, 148–153
- Cointegration, 35, 63, 147–159
- ComboTrader, 97
- Commission fees, 25, 84, 101
- Commission rate, 85
- Commodity futures markets, 183–186
- Compartmentalization, of programming work, 101
- Competition, 124, 137, 194–195
- Compound annualized growth rate (CAGR), 47
- Compustat, 163
- Computer requirements, for trading, 88
- Concatenating arrays, 201
- Conditional Parameter Optimization (CPO), xiv, 62, 138–147
- Confidentiality, 100–101
- Constraints,on institutional traders, 195
- Contemporaneous factor models, 161–163
- Continuous finance, 122
- copula (software package), 37
- Cornell University, 3
- Correlation, 154–159
- Cost of liquidity, 25
- Covid-19 selloff, 7, 169
- C++, 15, 94, 99, 200
- CPO, see Conditional Parameter Optimization
- Credit Suisse, 3
- Cross-currency stationarity, 159
- Cross-sectional factors, 161–164
- Cross-sectional mean reversion, 134–135
- CRSP.com, 41
- C#, 15, 40, 94, 99
- CSIdata.com, 41
- Currencies, 5, 16, 41, 159, 187
- Customer retention, 8
- Customer support, programming, 37, 38
- D
- Dark-pool liquidity, 85, 103
- Datafeed Toolbox, MATLAB, 204
- Data-snooping bias:
- Day only orders, 96
- DDE (dynamic data exchange) links, 94–99
- Decimalization of stock prices, 105–106, 138
- Deep Learning Toolbox, MATLAB, 204
- Deflated Sharpe ratio, 60
- Deleting arrays, 201
- Despair, 129
- Dickey-Fuller test, augmented, 149, 155
- Directional trades, 16
- Dividends, 41–44, 94
- Dollar-neutral portfolio, 16, 48
- Dollar-neutral trades, 16, 21
- Dotcom bubble, 138, 169
- Dow Jones, 41, 88
- Drawdown:
- Drawdown duration, maximum, 23–24, 53–57
- Due diligence, 33
- Duration, position, 186–187
- Dynamic data exchange (DDE) links, 94–99
- E
- Earnings, 29, 94, 135–136
- Econometrics Toolbox, MATLAB, 35, 37, 204
- The Economist, 169
- Eifert, Benn, 12
- Einstein, Albert, 3
- elitetrader.com, 87, 100
- E-mini S&P 500 future (ES), 5, 18–19, 25–26
- Emotional stability, 83
- Endowment effect, 126
- Englander, Izzy, 14
- Engle-Granger test of cointegration, 151, 153
- Ensemble average, 127, 128
- Entry signals, 77, 173–174
- epchan.blogspot.com, 12, 14, 179
- epchan.com/book, xix
- Equity curve, 22–24
- Equity markets:
- Errors, 47, 58, 98, 124, 135
- ES, see E-mini S&P 500 future
- ETFs, see GDX (gold miners ETF); GLD (gold ETF)
- Excel, xvii
- Excess returns, factor model, 161–163
- Exchange traded funds (ETFs), see GDX (gold miners ETF); GLD (gold ETF)
- Execution systems, 93–108
- actual vs. expected performance of, 104–107
- automated trading systems, 93–101
- brokerage/proprietary trading firm selection based on, 85–86, 103
- fully automated trading systems, 94, 98–100
- for high-frequency strategies, 188
- for minimizing transaction costs, 101–103
- paper trading to test, 103–104
- semiautomated trading systems, 94–98
- slippage due to, 25
- Exit orders, 77, 97
- Exit signals, 169–174
- Expected compound rate of growth of capital, 127–128
- Expected performance, actual vs., 104–107
- Experience, trader, 83
- F
- Factor exposure, 160–162
- Factor loadings, 160
- Factor models, 160–169
- Factor returns, 160, 162–164, 168–169
- FactSet, 41
- Fama-French Three-Factor Model, 160–161, 188–189
- Fat tails, 122
- Feature set, CPO, 139, 141
- Federal Reserve, 175, 196
- fGarch (software package), 37
- Financial contagion, 120–122
- Financial crisis (2007-2008), 2, 120–121
- Financial Industry Regulatory Authority (FINRA), 82, 84, 87
- Financial instruments. See also specific types
- Financial Instruments Toolbox, MATLAB, 204
- Financial Toolbox, MATLAB, 35, 204
- find function, MATLAB, 202
- FINRA, see Financial Industry Regulatory Authority
- Fixed holding period, 169–173
- Fixed-income instruments, cointegrating, 159
- Flirting with Models, 12
- Freelance programming consultants, 100
- Fully automated trading system, 94, 98–100
- Fundamental data, 1–2, 17, 123
- Fundamental factors, 168
- Fundamental valuation, 173
- Futures:
- fwdshift function, MATLAB, 177
- G
- G, see Long-term compounded growth rate
- GameStop short squeeze, 121–122
- Gasoline futures, 183–185
- Gaussian return distribution, 110, 122, 131–132, 189
- GDX (gold miners ETF):
- Gell-Mann, Murray, 127, 128
- Geometric mean, 112
- Geometric random walk, 111–112, 147
- GLD (gold ETF):
- Global Optimization Toolbox, MATLAB, 204
- Goal, strategy selection based on, 19–20
- Godot Finance, 12
- Goldman Sachs, 85, 95–96, 121
- Gold spot price, 21
- Good Till Cancel orders, 96
- Graphics library, MATLAB, 200
- Greed, 129
- greencompany.com, 85
- Growth stocks, 169
- H
- Half-Kelly betting, 112, 122–123
- Half-life, mean-reverting time series, 170–173
- “Hard to borrow” stocks, 106
- Harris, Mike, 12
- Hedge funds, 120–122, 193, 198
- Hedge portfolios, 160
- Hedge ratio, 68–69, 149, 151
- Herdlike investor behavior, 136–137
- High-beta portfolios, 188–189
- High-capital accounts, 15–19
- High data, in historical databases, 46–47
- High-frequency trading:
- High-leverage portfolios, 188–189
- High-minus-low (HML) factor, 161, 169
- High-speed internet connection, for trading, 88
- High watermark, 23
- Historical data, 29, 40–41
- Historical databases:
- HML (high-minus-low) factor, 161, 169
- Hoffstein, Corey, 12
- Holding period:
- HTTP requests, 99
- Hunter, Brian, 129
- I
- IBM, 3
- IBroker, 94
- IDEs (Integrated Development Environments), 37, 38
- Incorporation, 82–83
- Incremental execution, for large orders, 102, 136
- Independent traders:
- Industry, cointegration of stocks in same, 153
- Information ratio, 21
- Institutional traders:
- Integrated Development Environments (IDEs), 37, 38
- Interactive Brokers (IBKR), 17
- Interday positions, 16
- Internet software firm, profitability for, 9
- Intraday positions, 16, 18, 41
- Investment products, 8, 86
- ITG, 85
- L
- Lagged historical data, 58
- Large numbers, law of, 187
- Large orders, incremental execution of, 102, 136
- LastTradingDayOfMonth function, MATLAB, 180–181
- Law of large numbers, 187
- lcb1.uoregon.edu, 179
- LEAN engine, 40
- Legal requirements, for proprietary trading, 82, 84
- Legg Mason, 88
- LeSage, James, 204
- Leverage:
- in high-frequency trading, 187–188
- high-leverage portfolios, 188–189
- impact of despair and greed on, 129
- for institutional traders, 194
- Kelly formula for, 110, 112, 113
- and long-term capital gain, 19–20
- for low-capital accounts, 16
- and MAR ratio, 48
- maximum, 112, 120, 123
- optimal, 109–111, 113
- overleveraging, 5, 129, 194
- reducing, 124–125
- in retail vs. proprietary trading, 81–82, 84
- scaling up by using, 5
- Leveraged return, 22
- Liability, 82–83
- Limited liability companies (LLCs), 82–83
- Limit orders, 46
- Limit prices, 97
- Linear scales, order size and market cap, 102
- Liquidity:
- Liquidnet, 85
- LLCs (limited liability companies), 82–83
- Lo, Andrew, 72, 120, 135
- Long-only strategies, 20, 48–51, 195
- Long–short dollar-neutral strategy, 20
- Long-term capital gain, 19–20
- Long-Term Capital Management, 129, 193
- Long-term compounded growth rate (g):
- Long-term wealth, 110
- Look-ahead bias:
- Lookback period, 119–120
- Loss aversion, 126–128
- Losses:
- Low-beta stocks, 189
- Low-capital accounts, 15–19
- Low data, in historical databases, 46–47
- Low-priced stocks, 101
- M
- Machine learning, xii
- McKinney, Wes, 37
- Macroeconomic factors, 27, 168
- Magazines, trading strategies from, 12
- Manual interference, in trading, 6–7, 125–126
- Market capitalization, 102
- Market factor, 161
- Market impact, 25, 83, 101–102
- Market index, 20, 21
- Marketing, 7–8
- Market-neutral portfolio, 16, 51–53
- Market on close (MOC) orders, 46–47
- Market on open (MOO) orders, 46–47, 78
- MAR ratio, 47–48
- MASS (software package), 37
- Massachusetts Institute of Technology (MIT), 72
- Mathworks, Inc., 199
- MATLAB, xiii, xvii, 199–204
- analyzing January effect in, 175–177
- array processing in, 199–203
- avoiding look-ahead bias with, 58–59
- backtesting with, 33–36
- benefits of, 199–200, 203–204
- cointegrating pairs of stocks formed with, 149–150
- correlation testing with, 156
- evaluating transaction costs in, 73–75
- execution programs in, 96–98
- half-life of mean-reverting time series in, 171
- maximum drawdown calculation in, 54–55
- maximum drawdown duration in, 54–55
- optimal capital allocation in, 114–116
- out-of-sample testing with, 63–67
- PCA factor model using, 164–165
- Python vs., 37
- retrieving Yahoo! Finance data with, 35–36
- R vs., 38
- Sharpe ratio in, 50, 52
- year-on-year seasonal strategy in, 180–181
- Mauboussin, Michael, 88
- Maximum capital, 120
- Maximum drawdown, 23, 24, 47, 53–57
- Maximum drawdown duration, 23–24, 53–57
- Maximum leverage, 112, 120, 123
- Mean excess return, 116
- Mean-reverting regimes, 123, 126, 163
- Mean-reverting strategies:
- Mean-reverting time series, half-life of, 170–173
- Melvin Capital, 138
- “Meme” stocks, 138
- Metalabeling, xii, 29
- Micro E-mini contracts (MES), 19
- Millennium Partners, 14
- Mini gasoline futures, 184
- Minimum backtest length, 60–61
- Mini natural gas futures, 186
- MIT (Massachusetts Institute of Technology), 72
- mnormt (software package), 37
- MOC (market on close) orders, 46–47
- Model risk, 124–125
- Momentum, of factor returns, 162–163, 168–169
- Momentum regimes, 123, 126, 135–137
- Momentum strategies:
- Money management, 8
- Monitors, for trading, 89
- MOO (market on open) orders, 46–47, 78
- Morgan Stanley, 3
- Mortgage-backed securities, 2
- Moving parameter optimization, 61
- MSCI, 163
- Multidimensional arrays, in MATLAB, 202
- Multiple accounts, 87
- Murphy, Kevin, 204
- Mutiny Fund, 12
- mvregress function, MATLAB, 165
- N
- National Bureau of Economic Research, 12
- Natural disaster risk, 125
- Natural gas futures, 185–186
- NAV (net asset value), 16
- NDAs (nondisclosure agreements), 100
- Net asset value (NAV), 16
- News announcements, 123, 136
- News-driven strategies, 17
- Newsfeeds, 88
- Newspapers, trading strategies from, 12
- New York Mercantile Exchange (NYMEX), 183–185
- New York Times, 28, 136
- Noise, overfitting data to, 29
- Nominal return, 22
- Nondisclosure agreements (NDAs), 100
- Nonfarm payroll surprises, 29
- Nonreflexive targets, 29
- Nonstationary financial time series, 27
- Northwestern University, 38
- NYMEX (New York Mercantile Exchange), 183–185
- P
- Pair-trading strategy, 63–71, 77, 97, 147
- PanAgora Asset Management, 189
- Panel data, 203–204
- Paper trading, 62–63, 86, 103–104
- Parameterless trading models, 62
- Parameter optimization, 60–62, 138
- Part-time traders, 14–15
- Party at the Moontower, 12
- PEAD (post earnings announcement drift), 11, 136
- Pepsi (PEP), 153–159
- Performance:
- Personnel, reinvesting in, 197
- Peters, Ole, 127, 128
- PFGBest, 184
- Pharmaceutical stocks, 77
- Physical infrastructure, 87–89, 197
- P&L (profit and loss) data, 103–104, 204
- plotly (software package), 36
- Plus-tick rule, 106, 138
- Podcasts, strategies from, 12, 13
- Point-in-time data, 27, 44
- Portfolio managers, xv–xvi
- Portfolio margin, 16
- Portfolio size, risk management and, 129
- Posit, 85
- Position file, 59
- Position risk, 120–124
- Position size, losses/profits and, 120
- Positive correlation, 154
- Post earnings announcement drift (PEAD), 11, 136
- predictnow.ai, xix, 140, 142
- Predictors (term), 29
- Price:
- Price-to-earnings factor exposure, 161–162
- Price-to-earnings factor return, 162
- Princeton-Newport Partners, xvi
- Principal component analysis (PCA), 35, 100, 163–168
- Private liquidity needs, momentum changes due to, 136–137
- Profit:
- Profitability:
- Profit cap, as exit signal, 174
- Profit-sharing contracts, 198
- Programming consultants, 100–101
- Programming skills, strategy fit to, 15
- Proprietary trading firms:
- Prospective trading strategy(-ies):
- Psychological preparedness, 125–130, 195
- Python, xiii, xvii, 203
- analyzing January effect in, 177–178
- avoiding look-ahead bias with, 58–59
- backtesting with, 36–38
- cointegration and correlation testing with, 156–157
- evaluating impact of transaction costs in, 75–76
- forming cointegrating pairs of stocks, 150–151
- half-life of mean-reverting time series in, 171–172
- and MATLAB, 34, 36
- maximum drawdown calculation in, 56
- maximum drawdown duration in, 56
- optimal capital allocation in, 116–117
- out-of-sample testing with, 67–69
- PCA factor model using, 165–167
- on QuantConnect/Blueshift platforms, 40
- Sharpe ratio in, 51–53
- year-on-year seasonal strategy in, 181–182
- Python for Data Analytics (McKinney), 37
- Q
- Qian, Edward, 189
- QTS, 198
- Quandl, 95
- QuantConnect, 40, 94, 95, 99
- QuantInsti, 40
- Quantitative Brokers, 86
- Quantitative traders, 2–4
- Quantitative trading. See also Trading strategy(-ies)
- business case for, 4–8
- defined, 1
- effectiveness of, xi, 193–196
- exit signals in, 169–174
- factor models for, 160–169
- hedge fund losses in, 193, 198
- high-leverage vs. high-beta portfolios, 188–189
- processes for sustained profitability from, 8–9
- regime change and CPO for, 137–147
- stationarity and cointegration in, 147–159
- volume of, xv
- Quantocracy, 12
- Quantpedia, 12
- R
- R (programming language), xiii, xvii
- analyzing January effect in, 178–179
- avoiding look-ahead bias with, 58–59
- backtesting with, 38–39
- cointegrating pairs of stocks formed with, 151–153
- cointegration and correlation testing with, 157–159
- evaluating transaction costs in, 76–77
- half-life of mean-reverting time series in, 172–173
- maximum drawdown calculation in, 57
- maximum drawdown duration in, 57
- optimal capital allocation in, 118–119
- out-of-sample testing with, 69–71
- PCA factor model using, 167–168
- Python vs., 37
- Sharpe ratio in, 51, 53
- year-on-year seasonal strategy in, 182–183
- R2 statistic, of factor model, 162
- Random walk, 111–112, 134, 147
- Raviv, Eran, 12
- Real-time market data, access to, 16–17
- Reddit, 121, 138
- REDIPlus trading platform, 85–86, 96, 97
- Refco collapse, 86
- Regenstein, Jonathan, 39
- Regime, defined, 133
- Regime shifts, 198
- Regulation T, 5, 16, 81–83
- Reinvestment, 197–198
- Remote trading, 87–88
- Renaissance Institutional Equities Fund, 121
- Renaissance Technologies Corporation, 121
- Representativeness bias, 128–129
- Reproducible Finance with R (Regenstein), 39
- Reputation, of proprietary trading firm, 86–87
- Research and development, 7, 11–12
- RESTful API, 99
- Retail traders:
- Return consistency, 19–21
- Reversal strategies, 169, 174
- Reverse splits, 42
- Risk aversion, 4
- Risk-free rate, 48
- Risk management, xvi, 120–132
- “Risk Parity Portfolios” (Qian), 189
- Robinhood, 99
- Round-trip transactions, 25
- RStudio, 38
- rugarch (software package), 37
- Ruin, 110, 127
- Russell 2000 index, 21
- S
- SAC Capital Advisors, 22
- Sample size, data-snooping bias and, 60–61
- Savings, 4
- Scalability of trading business, 5
- Schiller, Robert, 136
- Scikit-learn, 36
- S corporation, 82–83
- seaborn (software package), 36
- “Seasonal Trades in Stocks” blog post, 13–14
- Seasonal trading strategies, 174–186
- Securities and Exchange Commission (SEC):
- Securities Investor Protection Corporation (SIPC), 84, 86
- Semiautomated trading systems, 94–98
- Sensitivity analysis, 71–72
- Sharadar, 18, 41, 163
- Sharpe ratio:
- Short positions, 106, 138
- Short-term income, 19
- Short-term mean reversal model, 135
- Signal Processing Toolbox, MATLAB, 204
- Simons, Jim, xvi
- Simulator accounts, 86
- Sinclair, Euan, 12
- SIPC (Securities Investor Protection Corporation), 84, 86
- Slippage, 25, 89, 102, 103
- Small businesses, 4–8
- Small-cap stocks. See also S&P 600 SmallCap Index
- Small-minus-big (SMB) factor, 161
- smartmean function, MATLAB, 74
- smartstd function, MATLAB, 74–75
- smartsum function, MATLAB, 74
- SMB (small-minus-big) factor, 161
- Social media, xiii
- Social Science Research Network, 12
- Société Générale scandal, 175, 196
- Software bugs, 103, 125
- Software risk, 125
- S&P 500 stocks:
- S&P 600 SmallCap Index, 21, 102, 164–168, 175–179
- S&P Capital IQ, 163
- Specific return, factor model, 160
- speedytradingservers.com, 89
- Split-adjusted data, 41–44
- Spreads:
- Spread_EMA, 147
- SpreadTrader, 97
- Spread traders, 94, 96–97
- Spread_VAR, 147
- SPY, see Standard & Poor's depositary receipts
- Standard deviation of returns, 49
- Standard & Poor's, 73. See also entries beginning S&P
- Standard & Poor's depositary receipts (SPY), 29, 51–53, 113, 119, 120
- Stationarity, 147, 148, 153, 159
- Statistical arbitrage trading, xviii
- Statistical factors, 163
- Statistics and Machine Learning Toolbox, MATLAB, 35, 37, 204
- Status quo bias, 126
- Sterge, Andrew, 106
- Stocks:
- Stock prices:
- Stocks, Futures and Options magazine, 12
- Stock splits, 41–44
- Stop loss orders, 123–124, 174
- Stripe Atlas, 83
- Subadvisors, 197, 198
- Subarray selection, in MATLAB, 201–202
- Survivorship bias:
- Swiss Franc unpegging, 82
- T
- T. J. Watson Research Center, 3
- Tables, MATLAB, 203
- Taleb, Nassim, 122
- Target price, 173
- Tax considerations, 84–85, 175
- Technical analysis, 1
- Technical Analysis library, Python, 141
- Technologies Corp., xvi
- Test set, 61, 71–72, 77
- Text parsing, 35–36, 200
- Thinking, Fast and Slow (Kahneman), 127
- Third-party backtesting packages, 35, 36
- Thomson Reuters, 41, 88
- Thorp, Edward, xvi, 110, 132
- Tick Data, 41
- Time commitment:
- Time constraints on backtesting, 79
- Time horizon, regime and, 134, 136–137
- Time series average, 127, 128
- Time-series factors, 162–164
- Time-series factor models, 160–161
- Time-series mean reversion, 134
- Tipping point, 137
- Trade, defined, 73
- Trader forums, 12–13
- Trade secrets, 84, 196
- TradeStation, 99–100
- Trading businesses, 81–90
- Trading capital, 15–19
- Trading frequency, 22, 197
- Trading parameters, defined, 139
- Trading strategy(-ies), 11–31
- backtesting of, 33
- effective, xi–xiii
- finding your own, xvii–xviii
- high-frequency, 186–188
- identifying suitable, 14–20
- mean-reverting vs. momentum, 134–137
- metalabeling of, xii
- modifying, after regime change, 138
- quick checks for prospective, 20–30
- refining, after backtesting, 77–78
- seasonal, 174–186
- simplicity of, 3
- sources of, 11–14
- Trading style restrictions, 84
- Trading Toolbox, MATLAB, 35, 94, 99, 204
- Traditional investment management, 33
- Training, 82, 84
- Training set, 61, 139, 141
- Transaction costs:
- Transposing arrays, in MATLAB, 202
- Trending strategies, see Momentum strategies
- Truncated data, 59
- Tuco Trading, 87
- Twitter, xiii, 12
- Two Sigma, 37
- W
- Walk Forward Optimization, 139
- Wall Street Horizon, 94
- Wealth, as objective, 4, 5
- Wealth-Lab, 13
- “What Happened to the Quants in August 2007?” (Khandani and Lo), 120–121
- “Where Have All the Stat Arb Profits Gone?” (Sterge), 106
- Windows Remote Desktop, 89
- Winners-minus-losers (WML) factor, 162
- Wittgenstein, Ludwig, 123
- Working hours, strategy fit to, 14–15
- WorldCom, 86
- Z
- Zacks, 94
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