Pyramiding — The Best Investment Strategy

Amit Soni
2 min readJul 18, 2022

In the early 2000s, no one would have ever wondered that stocks like Bajaj Finance, Titan and Eicher Motors would give multibagger returns and become a part of Nifty50 today. 🤑

So how did big investors like Rakesh Jhunjhunwala sir identify such potential multibagger stocks(like Titan), hold on to it and compound their wealth?? Let’s find out! 😕

To start with, filter a few stocks(8 to 10) with the following conditions
- Small Market Capitalization — [1000, 10000] Crores
- Return on Equity(ROE) > 20% CAGR
- Revenue Growth > 20% CAGR
- Net Profit Margin > 10% CAGR
- PE Ratio at Par or Less than Industry
- Futuristic Sectors like EV, Renewable Energy, AI

The Pyramid Investing Technique ✅
This is the technique used by big investors to compound their wealth.

- After selecting let’s say 10 stocks from the above filter, invest equal amounts of money in each of these stocks.

- Keep averaging in the stocks that remain in uptrend and keep on increasing(meaning they are performing well)

- Don’t invest in stocks that are either falling/downtrend or are sideways

For eg: — Let’s say you bought 2 stocks both at a price of 100(I am assuming both are at correct valuations).
- Stock 1 moves to 150, corrected till 125 and again starts moving upwards
- Stock 2 comes down to 75 and then further down to 60

Prefer to invest in stock 1 again around the price of 125. Don’t invest in stock 2 thinking that you are getting it at a lower price.

If you keep following this technique for 5–10 years, you will realize that your portfolio has only the winning stocks(multibaggers) and very less quantity of bad performing shares. 🎉

This technique is inspired from a very famous machine learning technique called Thompson Sampling where you reward the winners and penalize the losers in every iteration(in this case, every round of investment).

#stockmarket #stockmarketeducation #multibagger #stockstobuy #machinelearning #stockanalysis #stockinvesting #reinforcementlearning

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