I am using VECM model in R for stock price prediction. For prediction I used open price, closing price and high price of that day and I try to predict closing price. At first I checked if data is cointegrated.
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# Johansen-Procedure #
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Test type: maximal eigenvalue statistic (lambda max) , with linear trend
Eigenvalues (lambda):
[1] 0.189351689 0.087487739 0.002125514
Values of teststatistic and critical values of test:
test 10pct 5pct 1pct
r <= 2 | 2.64 6.50 8.18 11.65
r <= 1 | 113.71 12.91 14.90 19.19
r = 0 | 260.72 18.90 21.07 25.75
So there are two cointegration relationships. And I used "tsdyn" package to make VECM model. Prediction made by this model were quit accurate. But I am not sure if my approach is correct. So my questions are:
- Do I need to check if variables are non-stationary before making a model?
- Is this the right way to make a model or do I need to make VAR model first and then convert it into VECM ?
- Also I don't understand which equation is right in this VECM model, because I get table like this:
Full sample size: 1248 End sample size: 1241
Number of variables: 3 Number of estimated slope parameters 63
AIC -43935.64 BIC -43602.6 SSR 0.1105005
Cointegrating vector (estimated by ML):
X1 X2 X3
r1 1.000000e+00 0 -1.001445
r2 1.457168e-16 1 -1.001706
ECT1 ECT2 Intercept
Equation X1 -0.3465(0.5966) 0.0524(0.6139) -0.0039(0.0026)
Equation X2 1.0826(0.0837)*** -1.1161(0.0861)*** -0.0026(0.0004)***
Equation X3 0.9952(0.3554)** -0.7579(0.3657)* 0.0026(0.0015).
X1 -1 X2 -1 X3 -1
Equation X1 0.3506(0.5908) 0.0096(0.5576) -0.3381(0.1381)*
Equation X2 -0.0801(0.0829) 0.1134(0.0782) -0.0521(0.0194)**
Equation X3 -0.1466(0.3520) 0.5766(0.3322). -0.6551(0.0822)***
X1 -2 X2 -2 X3 -2
Equation X1 0.2849(0.5322) 0.1284(0.4969) -0.3320(0.1386)*
Equation X2 -0.0671(0.0747) 0.1095(0.0697) -0.0613(0.0195)**
Equation X3 -0.0721(0.3170) 0.5760(0.2960). -0.5673(0.0826)***
X1 -3 X2 -3 X3 -3
Equation X1 0.1235(0.4707) -0.0572(0.4328) -0.2138(0.1353)
Equation X2 -0.0716(0.0661) 0.1058(0.0607). -0.0343(0.0190).
Equation X3 -0.1478(0.2804) 0.3648(0.2579) -0.4097(0.0806)***
X1 -4 X2 -4 X3 -4
Equation X1 0.1533(0.4067) -0.1529(0.3538) -0.1084(0.1272)
Equation X2 -0.0708(0.0571) 0.0330(0.0496) -0.0332(0.0179).
Equation X3 -0.0847(0.2423) 0.1134(0.2107) -0.2806(0.0758)***
X1 -5 X2 -5 X3 -5
Equation X1 0.2247(0.3295) -0.0238(0.2539) -0.1056(0.1135)
Equation X2 -0.0023(0.0462) 0.0055(0.0356) -0.0333(0.0159)*
Equation X3 0.0981(0.1963) 0.0854(0.1513) -0.2209(0.0676)**
X1 -6 X2 -6 X3 -6
Equation X1 0.0332(0.2312) -0.0272(0.0515) 0.0937(0.0881)
Equation X2 0.0118(0.0324) 0.0007(0.0072) -0.0086(0.0124)
Best Answer
Regarding the suitability of a VECM for opening, high and closing price: