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U.S TECH STOCKS: THE BIGGEST MISTAKES MADE AND FOMO

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The US technology companies such as Apple, Alphabet, Amazon, Facebook and Microsoft have become giants and have products and services that permeated throughout our lives.

We all agree that they play crucial roles in today’s society and the stock market reflected their importance – tech is the largest sector in S&P 500 currently. Any portfolio without the tech giants would have underperformed the US markets significantly – such as ours. (we fundamentally refuse to purchase expensive stocks. remember the price you pay dictates the returns you achieve.)

There’s definitely a FOMO feeling as well as the urge to get into them now. A fund manager, Vitaliy Katsenelson observed it too,

“I cannot really talk about “growth” without mentioning the FANGs (Facebook, Amazon, Netflix, Google). These companies are responsible for a very large part of the outperformance of growth. They are all terrific, well-run companies, and their products and services are incredibly popular. If you did not own these stocks over the last five years, you faced a huge headwind in your attempt to outperform the market. Due to their large market capitalizations and their weight in the index, they account for a big chunk of stock market returns).”

Vitaliy Katsenelson

But you don’t have to beat yourself to it. Even Warren Buffett couldn’t find obvious reasons to buy into Google and Amazon earlier and he acknowledged missing out on tech stocks in the Berkshire Hathaway AGM,

“I made the wrong decisions on Google and Amazon. We’ve looked at it. I made the mistake in not being able to come to a conclusion where I really felt that at the present prices that the prospects were far better than the prices indicated… I had very very very high opinion of Jeff’s [Jeff Bezos, CEO of Amazon] ability when I first him, and I underestimated him, I’ve watched Amazon from the start. I think what Jeff Bezos has done is something close to a miracle … The problem is when I think something will be a miracle, I tend not to bet on it. It would have been far better obviously if I had some insights into certain businesses.”

Warren Buffett

If you are observant, you can read deeper into Buffett’s use of ‘miracle’. He seemed to suggest it was a lot of luck to invest in Amazon in the early days as there were almost nothing that a value investor would like about the stock.

Amazon was losing money and burning cash for consecutive years and although Amazon pulled through eventually with a phenomenal gain in share price, many other companies with similar profiles had crashed and burned.

Hence, it was a lot easier to lose a hell load of money than to bet on the right one if we were to abandon the value investing principles.

Amazon is a perfect sample of survivorship bias and it only became an obviously good investment after it succeeded.


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Alvin Chow

School of Graham, Deep Value, Factor Investing, CEO of Dr Wealth

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But we believe it is too late and we do not think that the price tags are worthy to pay for at this point in time. You would be throwing away the value principles if you chase after the tech stocks now.

Don’t. FOMO. Vitaliy Katsenelson said it well again,

“I am already seeing FANGs slowly creeping into value investors’ portfolios. Maybe they are beginning to understand the value in the future growth of FANG stocks, or maybe they simply can no longer take the pain of not owning them.”

Vitaliy Katsenelson

Another common conclusion is that one should just buy the US and forget about the rest of the world. This statement is derived from the recent extrapolation of history which humans are prone to do so.

It is known as the recency effect in psychology. The US indeed has done superbly well in the stock market, the S&P 500 gained over 200% over the last 10 years while STI only managed 36% over the same period.

This led to many investors to feel that the STI ETF was a complete waste of time and they would be better off investing in the S&P 500 ETF. Some might have already done the switch.

We understand the frustrations of investors and everyone wants to make money in the fastest possible way.

Wealth is relative, gaining 36% is ok if everyone else is losing. But making 36% when there’s another instrument that made 200% is definitely not ok.

FOMO kicks in again.

The fact is that if we look a little bit further back in history, looking at the previous bull run from 2003 to 2007, one would easily have said it was a mistake not investing in Hong Kong or Singapore because the S&P 500 only gained 78% while the former gained 234% and 191% respectively.

We are so bad at learning from history and we draw all the wrong conclusions. We failed to think that a lot of investments become obvious only later on, and which is often too late to join in. Many of our biases affect our ability to think clearly – and that has a direct effect on our investment results. Here are some examples;

  • Recency effect: We draw conclusion from recent history, even though it was insufficient to draw a proper conclusion.
  • Availability bias: The stocks that get talked about in media and social circles get more attention and increase in attractiveness.
  • Survivorship bias: We give too much credit to the winning stocks and forget that the losers had similar characteristics but were forgotten because they are no longer in the market.
  • Extrapolation bias: We conveniently project history into the future. If some investible asset has gone up, we assume it will continue to go up.
  • Overconfidence bias: We know we’re right and others are wrong.
  • Self-attribution bias: We made money because we are skilful. We lost money because of bad luck.
  • The list goes on with loss aversion, endowment effect, etc.

I recommend you to read Fooled by Randomness by Nassim Taleb. Worth re-reading if you have read it.

Editor’s Notes: This is by far one of the biggest reasons why people fail at investing.

It isn’t because they are not smart enough or disciplined enough. Rather, their emotional-logical brains are incapable of self-reflection at a level that is deep enough to realise the difference between right and wrong analysis.

If you are interested to learn how we do it while eliminating all such biases without question, you can go through our live demonstration here.

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