I've been doing this for some years now, but recently, since I started fiddling around with an old pairs trading strat of mine again, when updating the databases before running the tests, I was thinking about the prices used.
I was used to getting all adjusted close prices, dividends, splits, inplits, bonuses, etcs, and just running the strategy with those, but when eyeballing some of those time series and comparing them with the non adjusted series I get directly from the exchange (holy parsing, batman!) I noticed (the obvious) that some stocks are just way way away from their "raw", unadjusted prices and that that could lead to some really big data errors, contaminating the results.
I ran across a little white paper where the writer goes along about this issues and I exchanged some emails with some veterans in the industry. The latter told me that they just use adjusted prices for everything on the backtest procedures.
I was thinking, isn't it a little bit of a stretch to use adjusted prices for mimicking the execution of the trades?
I'm running a plain vanilla cointegrated pairs trading with some bells and whistles on top, and the difference between the two datasets, adjusted and non adjusted is just too big.
Would you consider using the adjusted series for in sample / cointegration / signal triggering, and then just using the real raw unadjusted prices at those times? (when triggering a trade, for example)
Or would you just use the adjusted ones and that's it?
The only part I'm sure here is about not using the raw series in cointegration and signal triggering analysis, too many jumps, gaps, with all the dividends, events, splits, etc.