The only "indicators" that I believe add value in academic research are time series smoothing functions. ( I don't call them indicators because they are all lagging thus do not indicate anything into the future).
There is clear empirical evidence and a number of academic papers have been published that show that none of the common indicators (common defined maybe in pseudo-bibles such as Murphy book "Technical Analysis of the financial markets") in isolation and even in combination perform equally well throughout different cycles, market dynamics, volatility regimes, or price patterns. Thus, for many it becomes a self-fulfilling prophesy. They are very silent when such indicators do not work and point to the "technical analysis is an art" aspect and remind every last soul that indicators "just work" during regimes when, for example an RSI indicator indicated oversold conditions and price action indeed picked up.
So, yes I believe not few in the academic community already make wrong choices in the tool selection of their research efforts. Please let us not confuse "financial technical indicators" with sound statistical modeling techniques and tools. A Kalman filter is doing exactly what it is supposed to do at ALL TIMES. An RSI indicator actually very rarely does what it is supposed to do, which is to indicate "oversold" or "overbought"conditions. In fact I ran tests a long time ago and showed that a strategy which shorts the asset on which an asset's RSI reaches oversold territory for the first time as well as the reciprocal almost always outperforms a strategy in which someone uses RSI in the general prescribed way. (this incorporated "prudent" trading, meaning realistic risk-management and stop loss levels). I ran many such tests in my junior quest for the holy grail which I soon figured does not exist. Unfortunately, technical financial indicators suggest to many that they are second best thing after the holy grail.
In summary, your question can lead to the never-ending discussion of pro and cons of technical indicators. I believe they do not belong into any serious academic research for the simple reason that they can be interpreted in all sorts of ways. A research tool should be applicable to a specific approach and it should output results that can be relied on with certain margins for error that are themselves well defined.