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- #How create residuals after perron 1989 break test in eviews 9 how to#
- #How create residuals after perron 1989 break test in eviews 9 series#
We are certainly not restricted to "vanilla" equities. Mean reverting strategies such as this permit a wide range of instruments to create the "synthetic" stationary time series.
#How create residuals after perron 1989 break test in eviews 9 series#
Trading strategies can make use of this by longing/shorting the pair at the appropriate disruption point and betting on a longer-term reversion of the series to its mean.
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This stationary series may have short term disruptions where the value wanders far from the mean, but due to its stationarity this value will eventually return to the mean. The idea is to consider a pair of non-stationary time series, such as the random-walk like assets of MCD and BKW, and form a linear combination of each series to produce a stationary series, which has a fixed mean and variance. This is where the concept of cointegrated time series arises. To achieve this we need a robust mathematical framework for identifying pairs or baskets of assets that mean revert in the manner described above. This is the essence of the classic "pairs trade".Īs quants we are interested in carrying out mean reversion trading not solely on a pair of assets, but also baskets of assets that are separately interrelated.
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This means that a long-short trade carried out at this disruption point should become profitable as the two stocks return to their equilibrium value once the disruption is resolved. A short-term disruption to an individual in the pair, such as a supply chain disruption solely affecting McDonald's, would lead to a temporary dislocation in their relative prices. The rationale for this is that their long term share prices are likely to be in equilibrium due to the broad market factors affecting hamburger production and consumption. An example from the equities world might be to long McDonald's (NYSE:MCD) and short Burger King (NYSE:BKW - prior to the merger with Tim Horton's). The traditional idea of a mean reverting "pairs trade" is to simultaneously long and short two separate assets sharing underlying factors that affect their movements. Once we have outlined these tests we will simulate various time series in the R statistical environment and apply the tests in order to assess cointegration. This will lead us to the concept of stationarity of a linear combination of assets, ultimately leading us to cointegration and unit root tests.
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We will proceed by discussing mean reversion in the traditional "pairs trading" framework.
#How create residuals after perron 1989 break test in eviews 9 how to#
We will cover the time series theory related to cointegration here and in the next article we will show how to apply that to real trading strategies using the new open source backtesting framework: QSTrader. In this article I want to discuss a topic called cointegration, which is a time series concept that allows us to determine if we are able to form a mean reverting pair of assets. We mentioned in that article as well as other previous time series analysis articles that we would eventually be considering mean reverting trading strategies and how to construct them. A while back we considered a trading model based on the application of the ARIMA and GARCH time series models to daily S&P500 data.