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PART 1: BACKGROUND MATERIAL. |
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1.2 Market Neutral Strategies. |
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2.3.2 Moving Average Process (MA). |
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2.3.3 Auto Regressive Process (AR). |
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2.3.4 The General ARMA Process. |
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2.3.5 The Random Walk Process. |
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2.5 Goodness of Fit vs. Bias. |
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2.7 Modeling Stock Prices. |
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3.2 Arbitrage Pricing Theory. |
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3.3 The Covariance Matrix. |
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3.4 APT Application: Calculating the Risk on a Protfolio. |
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3.5 Application: Calculation of Beta. |
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3.6 Tracking Basket Design. |
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3.7 Sensitivity Analysis. |
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4.3 The Scalar Kalman Filter. |
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4.4 Filtering the Random Walk. |
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4.5 Application: Example with the S&P Index. |
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PART 2: STATISTICAL ARBITRAGE PAIRS. |
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5.6 Road Map for Strategy Design. |
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6. Pairs Selection in the Equity Markets. |
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6.2 Common Trends Cointegration Model. |
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6.4 The Distance Measure. |
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6.5 Interpreting the Distance Measure. |
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6.6 Reconciling Theory and Practice. |
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7. Testing for Tradibility. |
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7.2 The Linear Relationship. |
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7.3 Estimating the Linear Relationship: The Multi-Factor Approach. |
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7.4 Estimating the Linear Relationship: The Regression Approach. |
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7.5 Testing Residual for Tradability. |
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8.2 Band Design for White Noise. |
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8.4 Non-Parametric Approach. |
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PART 3: RISK ARBITRAGE PAIRS. |
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9. Risk Arbitrage Mechanics. |
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9.7 Quantitative Aspects. |
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10.2 Specifying the Order. |
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10.3 Verifying the Execution. |
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10.4 Execution During the Pricing Period. |
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11. The Market Implied Merger Probability. |
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11.2 Implied Probabilities and Arrow – Debreu Theory. |
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11.3 The Single-Step Model. |
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11.4 The Multi-Step Model. |
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11.5 Reconciling Theory and Practice. |
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12.2 The Prediction Equation. |
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12.3 The Observation Equation. |
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12.4 Applying the Kalman Filter |
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12.6 Application to Trading. |
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