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MIT 18.S096: Topics in Mathematics with Applications in Finance →0/22
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1. Introduction, Financial Terms and Concepts

1:00:30
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2. Linear Algebra

1:12:36
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3. Probability Theory

1:18:25
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5. Stochastic Processes I

1:17:41
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6. Regression Analysis

1:22:12
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7. Value At Risk (VAR) Models

1:21:15
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8. Time Series Analysis I

1:16:19
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9. Volatility Modeling

1:21:15
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Lecture 10: Regularized Pricing and Risk Models (18.S096)

1:29:57
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Lecture 11: Time Series Analysis II (18.S096)

1:23:48
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Lecture 12: Time Series Analysis III (18.S096)

1:17:39
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Lecture 13: Commodity Models (18.S096)

1:20:45
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Lecture 14: Portfolio Theory (18.S096)

1:24:55
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Lecture 15: Factor Modeling (18.S096)

1:25:49
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Lecture 16: Portfolio Management (18.S096)

1:28:38
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Lecture 17: Stochastic Processes II (18.S096)

1:15:59
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Lecture 18: Itō Calculus (18.S096)

1:18:03
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Lecture 19: Black-Scholes Formula, Risk-neutral Valuation (18.S096)

49:52
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Lecture 20: Option Price and Probability Duality (18.S096)

1:20:29
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Lecture 21: Stochastic Differential Equations (18.S096)

56:05
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Lecture 23: Quanto Credit Hedging (18.S096)

1:37:37
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Lecture 24: HJM Model for Interest Rates and Credit (18.S096)

1:47:16

6. Regression Analysis

Peter Kempthorne, Jake Xia & Vasily StrelaMIT

MIT Mathematics & Wall Street Practitioners

1:22:12·2015·undergraduate level

MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013.

Economicsdistribution theorygauss-markov theoremgeneralized least squaresgeneralized m estimation

View the complete course: http://ocw.mit.edu/18-S096F13

Instructor: Peter Kempthorne

This lecture introduces the mathematical and statistical foundations of regression analysis, particularly linear regression.

Previous · Lecture 4

5. Stochastic Processes I

Next · Lecture 6

7. Value At Risk (VAR) Models

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