As a quantitative trader, it is a good practice to establish a strategy pipeline that will provide with a stream of ongoing trading ideas. We can have a framework to backtest trading ideas that can be based on any open source projects such as quantstrat from R package.
There are plenty of text-books, blog sites, forums, whitepapers and articles where we can find basic trading strategy ideas. We can start with these and then redefine them based on our own trading style and understanding of the market. It is very important to define our style before we start building a trading strategy. Some elements that require definitions are: what timeframe I would use to build a strategy, which assets I would trade, what is my risk/reward ratio, what is the maximum drawdown I can bear, etc.
We can combine fundamental and technical indicators in designing a trading strategy. We can select stocks that meet some fundamental conditions in terms of Price to Earning (P/E), Price to Book (P/B), Earning per Share (EPS), Return on Equity (ROE), among others, and secondly use technical indicators for entering into the market.
In the same way, we can select stocks that meet some criteria of volatility, or stocks that show an interesting trading pattern such as Inside Day Breakouts, Flags, Double Bottom, Double Root, Triangles among others. The volatility is related to the type of instruments for trading. The forex and cryptocurrency markets are more volatile than the stock markets for example.
The choice of asset class should be based on other considerations too, such as trading capital constraints, brokerage fees and leverage capabilities.
Reading academic papers as well as books are wonderful sources to get with new trading and investment ideas. These are great sources to understand and go deeper with the risk management side, as many papers provide tools for rebalancing and optimizing portfolios seeking the minimum variance constraint.