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How to Make Money from Cyclical Stocks
'Time in the market is more important than timing the market'.
This stock market adage is a cardinal rule which you would find in almost all investing books.
After all, predicting the movements of markets over the coming days or coming weeks is nothing but calculated astrology or a stroke of luck. At least that's what people think.
In fact, in my view what people call a 'luck' is nothing but statistics and sample sizing.
Over the weekend, I came across a piece from one of my favourite authors Morgan Housel who, in his blog, expressed the importance of statistics and sample size.
Here's a story he shared...
Evelyn Marie Adams won US$ 3.9 m in the New Jersey lottery in 1986. Four months later, she won again, collecting another US$ 1.4 m.
"I'm going to quit playing," she told the New York Times. "I'm going to give everyone else a chance".
It was a big story at the time, because number-crunchers put the odds of her double win at a staggering 1 in 17 trillion.
However, just three years later, two mathematicians threw cold water on the excitement. If one person plays the lottery, the odds of picking the winning numbers twice are indeed 1 in 17 trillion.
But if one hundred million people play the lottery week after week - which is the case in America - the odds that someone will win twice are actually quite good. The mathematicians calculated it was 1 in 30.
That number didn't make many headlines.
The moral of the story is clear. With a large enough sample size, any outrageous thing will eventually happen.
Let's extrapolate this to the Indian stock market.
During a bull market, we see a lot of so-called 'analysts' coming on television and talking about their trading picks. The trick for the television channel is sample sizing.
Every channel will get at least 5-7 analysts per day who will give at least 2-3 calls. That makes the sample size of 10-21 per day.
There are 4 main business news channels. That amounts to 40-84 calls a day by all the business channels put together.
This is how TV channels predict stock movements over the coming day or week. If you've ever wondered how TV channels justify trading calls, the answer is simple: sample sizing.
This is the concept of timing the market, which veterans and long-term investors disagree with.
While I agree it is speculative to predict daily or weekly movements, the whole idea of 'not timing the market' is wrong in my view.
My opinion lies in between timing the market and not being able to time the market.
Allow me to explain...
Let's take an example of the steel sector. It was the darling of investors until last year.
Let us analyse how dangerous it would have been to not time your entry and exit in steel stocks.
Steel Sector Over the Past 3 Years
Steel Sector | Demand | Debt | Steel Prices | Valuation | Action to be taken |
---|---|---|---|---|---|
2019 | Moderate | High | Moderate | Moderate | Equal Weight |
1H2020 | Weak | High | Low | Very Low | Time to buy |
2H2020 | Moderate | Moderate | High | Moderate | Time to increase weightage |
2021 | Strong | Low | High | High | Equal Weight |
2022 | Moderate | Low | High | Very High | Time to cut exposure |
2019 - The steel sector was in a steady scenario with moderate demand and steady prices. These are high debt companies.
1H2020 - Covid led to commodity prices crashing, demand vanished, and stock prices halved. This was the time to buy.
2H2020 - As the global economy started to recover due to free money doled out by central banks. Steel demand and consequently prices started firming up.
Container shortages and supply constraints from China too pushed up prices. As cash flows improved, steel companies started repaying loans. This was the time to further add to positions.
2021- Steel prices kept on rising on strong demand as well as supply constraints. Output from China declined leading to supply challenges.
Indian steel companies was in a goldilocks scenario with rising prices due to both strong demand and short supply. Exports went up due to China's internal issues.
All this led to bumper profits and strong cashflows. Companies used these cashflows to further repay debt. Some companies even became net cash free during this period. Stocks prices soared.
2022 - Demand started to moderate as interest rates went up. Steel prices corrected 20-25% from the peak (after 3x rise from the bottom). Stock prices started falling.
Unfortunately, retail investors entered at the end of 2021 when the frenzy was extremely high.
There are 3 points to understand about commodity cycles. The commodity cycle must be timed to make money.
#Factor 1 - Always buy commodity stocks when their multiples are high at the bottom of the cycle. The reason for high valuations is due to depressed earnings.
#Factor 2 - In every upcycle, there will be a point when the demand will be so robust that companies will announce expansion plans. That is the time to be cautious. It doesn't mean it's time to sell but it's time to be cautious.
#Factor 3 - When companies talk about expansion and start raising debt, it's the time to start selling commodity stocks. When you hear things like structural bull run in commodities. It's time to run away from the sector.
While I started with the fact that micro timing doesn't work, I'm ending with the fact that timing cyclical sectors is very important.
This can be extrapolated to all commodity stocks and cyclical sectors like the auto sector too. It's pertinent in investing not to have a fixed view about anything.
To sum it up, timing the market (entry and exit in cyclical stocks) and time in the market are both important. Don't ignore one of them.
Warm regards,
Aditya Vora
Research Analyst, Hidden Treasure
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