Thursday, May 14, 2020

Letter to Batch 13 of the Early Retirement Masterclass.

Dear Students of Batch 13,

It’s been a great honour and privilege to be able to conduct a 2-Day Early Retirement Workshop for you.

In the West, 13 is an unlucky number but to the Chinese, 13 is a number that signifies “assured growth” or “definitely vibrant.” 

This course is the hardest course ever conducted as markets has rendered previous back-tests meaningless as historical precedence does not play too well with two possible futures. A significant part of the investment community believe in the V-shaped recovery, and a large number of bears are holding back in case things get worse. If we tacked too aggressively to a market recovery, a downturn would wreak havoc in investment results. If we play a conservative game, there will be significant regrets if markets rally further.

This is the first batch to consider more than three factors in our stocks selection and factors chosen as a compromise between to scenarios. Our blue-chips, bonds and business trusts were conservative, so I expect it to hold up when the slump gets worse. Our REITs, being cheap and high-yielding may fly if markets do get better. Although I am fully invested in both, you can pick the portfolio that suits your view as to what will unfold in the future.

The unifying framework to allow multi-factor scoring is the Z-Score calculation taught for the first time in my programme after I tried teaching it in one community webinar. Covering this method would make it one of the most challenging investment training programs for retail investors. The decision to incorporate this would have been risky from a business perspective because weaker students may feel lost during our sessions and drop out after Day 1, but I am glad that drop-out rate for this class was even lower than previous batches.

This course is also seeing a lot of changes as I developed better coding skills. Thanks to my exposure to Python programming, we are now starting to be able to visualise financial markets in much more novel ways and answer questions that are different from those that we could address in the past. Imagine a small R&D lab forming within this community to get sharper insights into investment questions in the future.

You should pat yourself on the back as surviving this program is a significant personal achievement.

See you folks at the next community webinar and lab session.

Also, I look forward to your active participation in our Facebook community.

Christopher Ng Wai Chung


  1. Hi Chris, I attended your previous webinar and am intrigued with the Z-scoring method you introduced to the audience. Indeed, I am from engineering background and actually could follow the process. Would you be covering such quant methods to your future classes?

    Secondly, while the Z-scores gives you a way to systematically pick stocks with better factor attributes, is there any evidence or research that such a method works in the first place and that it can consistently yield market-beating returns over the long run ?

    Thirdly, while the Z-scores help to generate buy signals, what would then be the approach for sell signals - is it the same process whereby you simply rebalance , say maybe once a year, by always buying the stocks with top Z-scores and selling the ones whose Z-scores have weakened ?

    The approach shown is systematic but nothing has been shown on the long term performance, hence interested to hear your thoughts.
    Do you teach and apply this strategy for future classes, going forward? Or is this strategy still evolving ?


  2. Yes, the Z-Score will play an increasing role in future courses as it is getting some traction in my course. I will cover the research papers on the empirical basis of this approach in my program.

    As I am warier of short strategies, so I currently do not teach shorting stocks with the lowest Z-Score but logically this is a great way to design a market neutral fund.