Is quant and machine learning useful after the test? I made a 35 minute video to showcase my latest results of this forex trading strategy. It uses the combo indicators of moving average cross, statistic number of positive daily returns, and trend. This combo of indicators can be helpful as explained in the video.

NOTE: I have scheduled a webinar to be discussed about this topic. Please find the details below. 

It seems that there is a heavy reliance on these for ‘bottoming’ process or testing of flat lining for breakout potential.

Trade like the Pros

I tried to simulate someone like NicTrades later in my video to showcase potential moves with lower trending currency pairs. In short, it seems everything is about perfect timing. You would use all the mentioned indicators as a set of tools to measure timing and historical value of the price. The idea is obviously to capture breakout opportunities for escape volatility return.

It is time to get into the mind of an institutional pro to see how they decide and filter out the trading opportunities. So the struggle continues….. I find NicTrade is a good analyst to watch to see how it is done.

Overlay with fundamentals?

Some will say the fundamentals are not useful. For instance, you could use central bank guidance and trading/econometrics forward looking date to get currency bias on certain countries. I have many scripts ready to overlay. I just need to get a predictable methodology using the technical analysis.

Is Quant and Machine Learning helpful at this point

Some may argue that quant and machine learning techniques may help in this area. I agree but when you do not have a solid foundation, you will even harder times to forecast the markets. I really don’t want to go down these paths of quant or ML is much harder to figure out.

Scheduled webinar info

Hi there,

You are invited to a Zoom webinar.
When: Mar 19, 2018 7:00 PM Eastern Time (US and Canada)
Topic: quant and machine learning useful after this trading backtest

Please click the link below to join the webinar:
https://zoom.us/j/556419907

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Webinar ID: 556 419 907
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