Thought it would be good to share what we learnt this year, and our plans for the next year or even beyond.
For me, it would be getting over the psychological need for “perfection” or all information before i could even start, and not just in the investment context.
I joined deep value detector, investment quadrant and dividend machines courses between 2017-2018.
I have a endless load of investment books and shareholder letters waiting to be read. I had convinced myself i had to know everything Buffett or peter lynch says before i can start to do any analysis.
In the end, i can tell you buffett, howard Marks said this on this page but i cannot tell you what are e.g facebook earnings because i did not even do a single analysis.
It was only really the start of 2019 that i started to apply what i learned in the courses.
my priority for 2020 and beyond would be producing > consuming.
A few things for me:
- Many a times punting on something with not much historical information is not a good idea
- Many things are cheap for a reason, without catalysts, they might be traps
- Mispricing often occurs in low volume counters
- There’s many things beyond my control, switching to better counters may not show on your performance in 1-2 years.
Hi Hong Fu,
My learning for 2019 is moving parts. Every companies have something that will affect their revenue and profit. For instance, F&B business (In Singapore) revenue can be easily affected by raw material, rental and labour cost. Any drastic move in these three costs will affect their revenue. Whereas for Alphabet which owned Google have little moving parts except for government regulation that want to break them up which is good for investors. Google can also easily pass down their cost to their customers.
Hence, when looking at moving parts, company with more moving parts like F&B business, I want to have more margin of safety. While company like google, I am fine paying fair value for it.
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Thanks for sharing Victor. It’s interesting, i didn’t consider the “moving parts” point before in COGS.
I used to dismiss COGS and go straight for net profit, but i’m finding it more useful now to use COGS as a measure of an industry’s nature instead of just comparing it on a company basis.
e.g if a company or companies in the industry tend to have high cogs, my tendency would be to avoid them now even if they have a compelling catalyst.
if a industry has high COGS, any slight revenue misses would likely result earnings loss, EVEN WITH a margin of safely or even if there are good management, because that is the industry by nature.