In every preview I have conducted over the past three weeks, attendants have always contradicted themselves.
When I asked the audience where they think the STI will be at the end of 2020, I always get a consistently bearish picture, as shown below:
Half would believe that the markets will be flat. Of the remaining half, a majority believe that the index will fall below 2500, which is consistently a bearish read on the market sentiment.
However, a different picture emerges when I ask the same audience what actions they intend to take on the stock market:
The same attendees believe that even though they expect exchanges to be down at the end of the year, they intend to buy more stocks for their portfolio.
So the investment population seems to be bearish in theory but bullish in practice.
How can we explain this contradiction?
As it turns out, some of the formulas we picked up in A level maths classes can shed a lot of light and show us how to think about the stock markets. In the 18th Century, Reverend Thomas Bayes came up with Bayes Theorem, which has a fascinating application to the investing world beyond the exams posed during A-level maths classes.
The formula is as follows:
The formula looks arcane, but upon further manipulation, you will find the following:
Hidden in this formula is the secret of how investors should think about the stock market:
- We always have a certain idea of how the stock market will behave. This idea is called a prior represented by the term P(A), some sort of prior belief based on personal experience, knowledge, and history.
- Every minute, some piece of news will arrive that will, in essence, modify our belief about the stock markets represented by
(Modifier). A different piece of news will modify our prior beliefs differently.
- After incorporating this news, we now have a new belief about whether the stock market behaviour moving forward.
Imagine the stock market as thousands of market participants processing news in a real-time way and modifying their beliefs as new information arrive.
Armed with Bayes’ Theorem, how do we interpret these two contradictory surveys in a preview?
My belief is that first survey on whether the markets will fall below 2,500 represents an older interpretation of the STI. The closest graphic I have is the history of STI for the past 20 years.
The chart above shows dismal performance as it incorporates the massive drop behind COVID-19 crisis. The numbers are dismal. If you had invested in the STI for the past 20 years, your returns would only be 1.49%. Also, the recent crash has cast doubts as to whether markets would be able to sustain its current levels given that we’ve yet to see the economic damage done to businesses in Singapore.
We can represent this idea of long-term STI performance can serve as our P(A) or prior.
P(A) -> Expected STI Performance is Bearish
My opinion is that historical perspective STI performance is incomplete.
The STI had already crashed 30% from its peak in April 2019, and the market has recovered 10% from the low of 2,233 on 25 March 2020.
Some of the smarter investors are already investing based P(A|B).
P(A|B) – > Expected STI Performance given that a crash has already occurred is Bullish
A positive view emerges when we see that markets bounced back on 3 September 2009, after the Great Recession until its first peak on 1 January 2011. On a market recovery, the STI returns are quite stellar, providing annual returns of 16.9% with a low standard deviation of 113.3%.
These reflect my bullishness for the stock markets. The COVID-19 crash has been nasty but is the situation as bad as it is in March 2020?
Right now:
- China is in the middle of getting its economy back on track.
- Singapore has just unleashed a Fortitude Budget to prop up the economy.
- There are hundreds of attempts to create a vaccine for COVID-19.
- We have at least one drug that can reduce the duration of hospitalization by about a third.
- Our markets have a high equity premium (low P/E) relative to bond yields.
If you incorporate all this information into your bearish view, you will come to the same conclusion as my preview attendees – the bargain hunting must take place now before it becomes too late.
I will be conducting a webinar on many concepts, including Bayes Theorem. This webinar is free and showcases what is taught to graduates of my ERM program. Please register here: https://drwealth.com/ermintro/
