Cointegration or Correlation

Does Cointegration works for short term? After several backtests, it seems correlation works better in the shorter time frame.

Testing for Cointegration

Timeframe used: 5 mins bar chart (Over 2 months)
Steps:
1. Check for stochastic trend in the time series. Meaning, I(1) is stationary (TS is stationary after 1st differencing
2. Regress the 2 Time series, do a ACF test on the residuals.
3. A small P-Value => "Cointegration" (For hardcore stats people, "Do not accept Null Hypothesis"

I have decided to "not waste" what I learnt in school. Although she didnt teach me anything on almost anything about application, the theory is just good enough not to get lost while learning applications from somewhere.

So what "not to waste"? Time Series of course, one of my favourite module but with the worst result. (excl. French One) "Parlez Vous Anglais?"

Let's venture into the world of "Stationarity" and "Cointegration" and what not in the FX Markets.

They called it StatArb???

Stationarity - A stationary process (or strict(ly) stationary process) is a stochastic process whose joint probability distribution does not change when shifted in time or space. *

Cointegration - If two or more series are individually integrated (in the time series sense) but some linear combination of them has a lower order of integration, then the series are said to be cointegrated. *

*Source: Wikipedia ( I know it is not a good source, but I am not writing a thesis)