I started my work using five indicators simultaneously, but abandoned the effort because I wasn't getting rich enough statistics for each realization of the five indicators. I guess if I was daytrading, it would be a different story. Maybe I'll revisit the multiple indicator prediction.
Volume (daily) is definitely an attribute that I can easily mine. It's certainly worth trying past volume as an indicator. On what timescales do you typically deal with volume? past day/week/month?
Since you are using indicators, these two threads have rich content:
https://www.elitetrader.com/et/threads/the-stochastic-indicator.14129/
https://www.elitetrader.com/et/thre...a-profitable-automated-trading-system.147441/
You seem to like larger timeframes and sector rotation. DryUp & First Rising Volume would be of interest to you.
Since the market is fractal, volume patterns are similar in structure regardless of timeframe. My trading fractal is the ES 5m. From what you are testing, there is noise introduced into your system whereas faster timescales filter it out. This is a minority viewpoint. An example would be the volume profile for extended session trading. Since liquidity has a functionally distinct characteristic than the price/volume relationship during regular trading hours, this introduces noise that averaging seeks to reduce. This embeds a limitation in it's approach of extracting the market's full offer even though many have relative degrees of success with it.
The above links are based in a different paradigm and will most likely not make sense to a majority of readers, nor to you unless one can embrace out-of-the-box open-minded thinking. Backtesting produces mixed results in that the assumptions generally made in a backtest do not fully incorporate a system's complete paradigm nor does it account for a tester's implied bias. This is true for most approach backtesting from an 'outside-in' perspective, using it as a way to determine the promise of a particular strategy or tactic based on an incomplete understanding of how that indicator functions on it's own as well as among it's peers.
Another approach would be to fully understand the components of a particular indicator and from an 'inside-out' perspective see which market conditions are appropriate for that particular indicator to perform well. In this way, one understands the strengths and weaknesses of any particular indicator as well as how to combine them into a something that is 'greater than the sum of it's parts.'
To use driving as an example, there are a number of different weather/road conditions, terrains, vehicle capabilities, traffic patterns and intent that determine driving conditions which inform how to best drive to get from point A to point B.
Each condition requires a slightly different skill set even though they can all be considered in the domain of driving.
All in all, where the rubber meets the road is in forward testing both as prerequisite for proof of concept and more importantly as a process as one actively trades.