Blog Archives

Twinkle,twinkle little STAR

May 26, 2014
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Twinkle,twinkle little STAR

At the recent R/Finance 2014 conference in Chicago I gave a talk on Smooth Transition AR models and a new package for estimating them called twinkle. In this blog post I will provide a short outline of the models and an introduction to the package and its features. Financial markets have a strong cyclical component

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The realized GARCH model

January 2, 2014
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The realized GARCH model

The last model added to the rugarch package dealt with the modelling of intraday volatility using a multiplicative component GARCH model. The newest addition is the realized GARCH model of Hansen, Huang and Shek (2012) (henceforth HHS2012) which relates the realized volatility measure to the latent volatility using a flexible representation with asymmetric dynamics. This

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A Review of Risk Parity

December 17, 2013
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A Review of Risk Parity

What is risk parity (RP)? Simply put, it is a method of allocating equal risk shares to each asset in the portfolio. In more traditional allocation schemes, equity, being the riskiest asset (and hence providing the highest reward), has typically received the lion’s share. With RP, equalization of risk contribution means that equity and other

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A note on the co-moments in the IFACD model

December 11, 2013
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The Independent Factor Autoregressive Conditional Density (IFACD) model of Ghalanos, Rossi and Urga (2014) uniquely, in its class of parametric models, generates time varying higher co-moment forecasts, as a consequence of the ACD specification of the conditional density of the standardized innovations. In this short note I discuss in more detail the properties of the

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Direction of Change Forecasting III: One Signal, Many Markets

September 26, 2013
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Direction of Change Forecasting III: One Signal, Many Markets

In the global economic landscape, national borders have become increasingly blurred. Local economies depend on competitively priced global inputs and on well functioning and prosperous global markets for their exports. This interdependency also means that as a system, a crisis in one area quickly spreads to others areas like a ripple spreading outwards. And sometimes

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Direction of Change Forecasting II: The case of the UK

September 25, 2013
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Direction of Change Forecasting II: The case of the UK

In the previous blog article I discussed a dynamic binary model for the directional forecast of the US equity market using a select number of economic, fundamental and technical variables as predictors. A natural direction for extending that research would be to look at similar models in different countries or for other asset classes. In

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Direction of Change Forecasting using a Dynamic Binary Model

September 12, 2013
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Direction of Change Forecasting using a Dynamic Binary Model

While it is generally accepted that the returns of financial assets are almost impossible to forecast with any degree of accuracy which would provide meaningful profit1 , there is evidence that the sign of the returns is much more forecastable. Theoretically, Christoffersen and Diebold (2006) have shown how the forecastability of the sign is related

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Development Update

July 25, 2013
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This is a quick update regarding the status of my R packages on google code. Since google decided to disallow uploads from Jan-2014 for existing projects, and immediately for new ones (meaning that the tarballs and zips could not be hosted on their servers anymore), I have had no choice but to return the development

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The Fallacy of 1/N and Static Weight Allocation

June 18, 2013
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The Fallacy of 1/N and Static Weight Allocation

In the last few years there has been a increasing tendency to ignore the value of a disciplined quantitative approach to the portfolio allocation process in favor of simple and static weighting schemes such as equal weighting or some type of adjusted volatility weighting. The former simply ignores the underlying security dynamics, assuming equal risk-return,

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Time Varying Higher Moments with the racd package.

April 22, 2013
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Time Varying Higher Moments with the racd package.

The Autoregressive Conditional Density (ACD) model of Hansen (1994) extended GARCH models to include time variation in the higher moment parameters. It was a somewhat natural extension to the premise of time variation in the conditional mean and variance, though it probably raised more questions than it, or subsequent research have been able to answer.

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