A distinct trend in recent years is using multiple mentors to integrate quantitative approaches to trading with discretionary ones. A simple example occurred at a firm where I worked, where several of us developed a predictive model for trend days in the stock market. We examined days that qualified as trend days and days that did not and built a simple model based upon such variables as volume and breadth. The output from that model was then shared with traders, who integrated the results into their own trading. So, for example, a trader might focus on stocks most likely to benefit from the trend by looking at volatility, relative strength, etc. A different trader might use the model output to extend the holding time on a trade that had already hit its first target.
Yet another example of integration would be using historical studies of market tendencies to frame trade ideas. Some of those studies can be found via Quantifiable Edges and from Paststat and from InvesiQuant. Still more quant resources can be found via the excellent Quantocracy resource. Market regimes can change and what happened in history may not be mirrored in the near future, but knowing tendencies from well-constructed studies can tell you what markets *usually* do in a given set of circumstances. Some of the best discretionary trading comes from occasions when markets fail to do what they "should" be doing, as that tells us that idiosyncratic factors and flows are dominating trade.
The ability to integrate new information and styles into our trading is what keeps us learning, developing, and adapting to changing markets. It's when we don't integrate that we stagnate. The most consistent finding I've made as a trading coach is that the best traders find multiple ways to win. Those traders can be successful in multiple market regimes.
Further Reading: Identifying Trend Days in the Market
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