Random Walk and Mean Reversion von Edu Pristine

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Über den Vortrag

Der Vortrag „Random Walk and Mean Reversion“ von Edu Pristine ist Bestandteil des Kurses „ARCHIV Regression Analysis“. Der Vortrag ist dabei in folgende Kapitel unterteilt:

  • Regression Diagnostics
  • Residual Analysis for Linearity
  • Maximum Likelihood Estimators
  • Questions

Dozent des Vortrages Random Walk and Mean Reversion

 Edu Pristine

Edu Pristine

Trusted by Fortune 500 Companies and 10,000 Students from 40+ countries across the globe, EduPristine is one of the leading International Training providers for Finance Certifications like FRM®, CFA®, PRM®, Business Analytics, HR Analytics, Financial Modeling, Operational Risk Modeling etc. It was founded by industry professionals who have worked in the area of investment banking and private equity in organizations such as Goldman Sachs, Crisil - A Standard & Poors Company, Standard Chartered and Accenture.

EduPristine has conducted corporate training for various leading corporations and colleges like JP Morgan, Bank of America, Ernst & Young, Accenture, HSBC, IIM C, NUS Singapore etc. EduPristine has conducted more than 500,000 man-hours of quality training in finance.
http://www.edupristine.com


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Auszüge aus dem Begleitmaterial

... normally distributed 3. The error variable must have a constant variance 4. The errors must be independent of each other "How can we diagnose violations of these conditions Residual Analysis, that is, examine the differences between the actual data points and those predicted by the linear equation ...

... Knowledge Management Pristine, Purposes Examine for linearity assumption Examine for constant variance for all levels of x Evaluate normal distribution assumption Graphical ...

... is violated, we have a condition of heteroscedasticity. We can diagnose heteroscedasticity by plotting the residual against the predicted y In Regression analysis we assumed the volatility ...

... are time series, the errors often are correlated. Error terms that are correlated over time are said to be auto-correlated. We can often detect auto-correlation by graphing the resid uals against the time periods. If a pattern emerges, it is likely that the independence requirement is violated. ...

... Knowledge Management Pristine Note the runs of positive residuals, replaced by runs of negative ...

... Exchange rates and stock prices do not exhibit mean reversion. Neev Knowledge Management Pristine A process in which the full path consists of series of small random steps. Complete path is called Random Walk. Used to model many processes, including returns on stocks, economics, physics, diffusion models, etc. Close to Markov processes. Stock returns are independent and have the identical distribution. The past movement or trend ...

... of the parameters would make them Maximum likelihood estimation gives a unique and easy way to determine solution in the case of the normal distribution For a normal distribution MLE for Mean ...