mean-reversion

  1. Nicole Seaman

    P1.T4.24.6. GARCH models and implied volatility

    Learning Objectives: Apply the GARCH (1,1) model to estimate volatility. Explain and apply approaches to estimate long horizon volatility/VaR and describe the process of mean reversion according to a GARCH (1,1) model. Evaluate implied volatility as a predictor of future volatility and its...
  2. David Harper CFA FRM

    P2.T5.23.5 Cox-Ingersoll-Ross (CIR) model

    Describe the short-term rate process under a model with time-dependent volatility. Calculate the short-term rate change and determine the behavior of the standard deviation of the rate change using a model with time-dependent volatility. Assess the efficacy of time-dependent volatility models...
  3. Nicole Seaman

    P2.T5.23.4 Vasicek term structure model

    Learning objectives: Construct and describe the effectiveness of a short-term interest rate tree assuming normally distributed rates, both with and without drift. Calculate the short-term rate change and standard deviation of the rate change using a model with normally distributed rates and no...
  4. Nicole Seaman

    P1.T2.20.25 Forecasting ARMA models

    Learning objectives: Explain how forecasts are generated from ARMA models. Describe the role of mean reversion in long-horizon forecasts. Explain how seasonality is modeled in a covariance-stationary ARMA. Questions: 20.25.1. Below is plotted the monthly growth rate of a new cryptocurrency...
  5. Nicole Seaman

    YouTube T1-4 What is Autocorrelation (and how does it impact scaled volatility)?

    Autocorrelation is a correlation of variable (eg, returns) with itself over time; it is a violation of returns. Positive autocorrelation increases scaled volatility, while negative autocorrelation (aka, mean reversion) decreases scaled volatility. Here is David's XLS: http://trtl.bz/2wSpHrG
  6. Nicole Seaman

    P1.T4.804. Value at risk (VaR) estimation approaches (Allen)

    Learning objectives: Evaluate the various approaches for estimating VaR. Compare and contrast different parametric and non-parametric approaches for estimating conditional volatility ... Explain long horizon volatility/VaR and the process of mean reversion according to an AR(1) model. Calculate...
  7. Nicole Seaman

    P1.T2.704. Forecasting volatility with GARCH (Hull)

    Learning objectives: Explain mean reversion and how it is captured in the GARCH(1,1) model. Explain the weights in the EWMA and GARCH(1,1) models. Explain how GARCH models perform in volatility forecasting. Describe the volatility term structure and the impact of volatility changes. Questions...
  8. T

    Square Root Rule with Mean Reversion & AutoCorrelation - VaR & Volatility

    David, I am now thoroughly confused by the Square Root Rule and scaling the VaR under the circumstance of Mean Reversion and Auto correlation. In search of an explanation, I found this thread http://forum.bionicturtle.com/newreply/1729/ , but your link is not attached anymore. The rules for...
  9. N

    Mean reversion

    David.. I request you to to eloborate the term means reversion. What it exactly means and how it impacts VaR. Your editgrids are indeed elegant and educative. But unlike your webcasts exclusively I find it hard to follow (although I reapeatedly watch them) and learn. You indeed touch upon...
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