While desktop trading platforms cannot yet be completely replaced, web based trading platforms have been getting better and better. I wanted to take give a preview of a few that I have tried recently.
This is a basic platform but supports chart trading, DOM, and options. I need explore more but could be very useful to get out of trades if TS Desktop quits working.
Overall, there are some really interesting platforms with great potential. On the other hand, it looks like platforms like Tradovate aren’t really being improved.
Please do note, this should not be taken as a definitive on these platforms but is rather meant to be a quick review. Platforms may have improved if you are reading this in the future.
Tradingview is probably the closest to offering a complete replacement. And, in select areas, the power in terms of ease-of-use, charting capability, and multi-product/multi-market analysis easily trounces legacy platforms like NinjaTrader and Tradestsation. Likewise, Tradovate’s market replay bests NinjaTrader in many respects but suffers from limited play back limits.
On the other hand, none of these platforms offer the backtesting capability of a real desktop package like Tradestation or NinjaTrader. Tradestation also has advanced scanning capability. More over, I am not a fan of the scripting language or capabilities of Tradovate. TT’s platform is interesting, and deserves closer inspection but without strategy automation it really speaks to a lack of innovation.
The major benefit for a web platform at this time is ability to place trades when desktop software has problems or for doing extensive chart analysis. There is certainly potential for something better such as advanced backtesting support, developing automated strategies and deployment in the cloud, and more– but that potential remains to be realized.
The author is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline. You can contact the author at email@example.com.
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