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My Kalman Filter seems off??? Please help

Hello,

If you look at my code, it seems the implementation of a kalman filter in the data looks a little weird? The linear regression has a blue line nowhere near the points on the scatter plot, and the kalman filter stationary series seems to go way outside of the upper and lower bounds from the mean. Can someone tell me if the coding is off? Thank you!

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From the above two charts, you can see the intercept and slope estimation with the Kalman filter method turns out to be stable after about ten days. It means the first few estimations are not valid values in the regression analysis. The code tries to pick slope and intercept every 50 days while the first value deviates the real value. To get a chart with all the reasonable slope and intercept, you can start to plot by skipping the first 10 points. 

for i, b in enumerate(state_means[10:][::step]):
plt.plot(np.log(data[symbols[0]]), b[0] *np.log(data[symbols[0]]) + b[1], alpha=.5, lw=2, c=cm(colors_l[i]))
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All the pairs trading examples are available in our strategy tutorial library. 

https://www.quantconnect.com/tutorials/strategy-library/pairs-trading-with-country-etfshttps://www.quantconnect.com/tutorials/strategy-library/pairs-trading-copula-vs-cointegrationhttps://www.quantconnect.com/tutorials/strategy-library/pairs-trading-with-stockshttps://www.quantconnect.com/tutorials/strategy-library/intraday-dynamic-pairs-trading-using-correlation-and-cointegration-approach
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