Conditional mean, 19
Conditional variance, 19
Conservative trading, 160
Control theory, 52
Corporate events, 139
Correlation, 13
Correlogram, 15
Cost function, 133
Covariance, 12
Covariance matrix, 41–44D
Deal, 141
process, 141–142
spread, 145–147
Debt, issuing, 139
Definitive agreement, 141
Deviations from ideal conditions,
97–99
Differencing, 24–25, 76
Dinic’s algorithm, 168–170
blocking flow, 168
flow augmenting paths, 168
residual graph, 168
steps in algorithm, 168, 170
Discretization effect, 129
Distance measure, 93–94
formula, 94
interpreting, 94–97
calculating angle between two
vectors, 95–96
geometric interpretation, 96–97
Dollar neutral portfolio, 6
Dual, of a linear program, 156, 158E
Eigen portfolios, 38
Eigen value decomposition, 103
Engle, Robert F., 76, 105
Equilibrium price, 60–61
Equilibrium value, 118
Equity, issuing, 139
Ergodicity, 126–127
Error correction, 76–77
Event risk management, 185–186
Exchange offers, 140Exchange ratio, 144–146
Execution
during pricing period, 161–166
verifying, 155–160F
Factor covariance matrix, 42
Factor exposure matrix, 42
Factor models, 37–51
applications, 44–50
calculating risk on portfolio,
44–47
calculation of portfolio beta,
47–49
tracking basket design, 49–50
arbitrage pricing theory, 39–42
covariance matrix, 42–44
fundamental, 38
macroeconomic, 38
parameters, 42
sensitivity analysis, 50
statistical, 38
Fibonacci numbers, 63
Fibonacci retracements, 54
Fixed ratio stock exchange, 144
Fixed value stock exchange, 144
Forecasting, 24–25
Ford, 156
Fulkerson, 156
Fundamental factor models, 38G
Gaussian distribution, 16
Gaussian white noise, 16
Gaussian white noise series, 120
General Electric, 30
Generalized auto-regressive conditional
heteroskedascity (GARCH),
124, 125
General Re, 182–183
Geometric interpretation, 96–97
Golden mean ratio, 63
Goodness of fit vs. bias, 25–26
Granger, C.W., 76, 105
Granger representation theorem, 76
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