Masterly Inactivity: The Case for Very Long Term Passive Investments

The term 'Masterly Inactivity' was coined by Charlotte Mason in her famous book Original Homeschooling, a masterpiece on child development, parenting and education. The idea is that, parents should develop a child by 'some letting alone and some wise openings'. It's a restatement of the age-old wisdom that one should not worry about the things they can't control. I believe the idea of 'masterly inactivity' applies to investing as well.

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In the last month, NIFTY 50 has crossed the 10,500 mark and there are already talks about a deep correction in the stock market. Everyone who is making SIPs in Index Funds or other similar Mutual Funds are getting queasy. So I thought, instead of looking forward and speculating, why not look backward and interrogate? This is my argument for very long-term passive investments. Please note: When I say passive, I strictly mean Index Investing or investing in similar less-risky, blue chip Mutual Funds.

I started by downloading historical data from NSE's website. For your reference, I downloaded NIFTY 50 P/E, NIFTY 50 P/B, NIFTY 50 Dividend Yield and NIFTY 50 TRI for the past 17 years (That's almost 18,000 individual points of data) NIFTY 50 TRI is a much more logical index to look at than the NIFTY 50 alone and I benchmark my own returns with the NIFTY 50 TRI as opposed to the NIFTY 50. So don't get alarmed when you see NIFTY showing up with values above 14,000 because you would be looking at the NIFTY TRI.

A quick refresher, if you're not familiar with any of these terms: A P/E is the Price/Earnings Ratio, which tells you how much an investor is willing to pay for a company's profits. A P/B measures the Price/Book Value, which shows how much an investor is willing to pay for a company's net worth. The Dividend Yield is the amount of dividends a company pays in relation to the price at which it is trading. The 'TRI' refers to a 'Total Returns Index', whose values are calculated with the dividends re-invested. The normal NIFTY 50 ignores dividends. Finally, NIFTY itself is a composite of 50 stocks, it's an index which tracks the movement of those stocks. You can find NIFTY's composite companies here.

First, let's go for a simple visual representation of all the data I've collected. There's not much to analyze here, but observe:

(NIFTY 50 TRI with a 200-day Simple Moving Average Trendline)

What do you see in the above graph? The market always goes up. Well, not always. But if someone asks you 'Where will the NIFTY be 20 years from now?', you can confidently say 'up'. This should give you the simple wisdom that if you just invest passively in an Index Fund or similar Mutual Funds throughout your life, you would be better off than most people in terms of wealth. But can you earn more in the short term or the long term? We'll answer that question soon. For now, let's put at all the Valuation Ratios next to NIFTY 50 TRI:

(NIFTY 50 TRI Vs NIFTY 50 P/E)

(NIFTY 50 TRI Vs NIFTY 50 P/B)

(NIFTY 50 TRI Vs NIFTY 50 D/Y)

I will allow you to look through these graphs by yourself. But I would like you to notice how each of the separate valuation curves move in tandem with NIFTY. This might help you to understand how each of these Ratios are correlated with NIFTY.

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So how do you make sense of such vast amounts of data? The same way you eat a Big Mac - in small bites. Initially, I segregated all the valuation ratios into different buckets and then tried looking at how the NIFTY 50 TRI fared in terms of average returns (CAGR) in comparison to all the buckets. I used the AVERAGEIF function in excel to achieve this.

First, the P/E Ratio:

The clear consensus is that when the NIFTY is at its lower, sub-16 levels, the returns going forward will be fantastic. Unfortunately, NIFTY's current P/E is close to 23 and history tells us that below-average returns are soon going to follow. It's true that past performance is no excuse for future performance, yet I am a big believer in very long-term averages and reversions to mean. Let's step back for a moment here. Looking at the table, you would conclude that whenever NIFTY is below 16, investing in it heavily and hoping for a wonderful return in the following years makes the most sense. If it was this easy, everyone would do it. Don't you think we are missing something here?

That's why we should look at this data in relation to how much time NIFTY has spent on each of these buckets - or to put it in another way, what is the probability that you will find NIFTY below 13 P/E or 16 P/E considering the historical frame of reference? To answer this, I used the COUNTIF function in excel to pull the number of days NIFTY has spent in each of these buckets and then divided it by the total number of days for which I had collected the data (4585 days or roughly 5 days a week for 17 years). Following this, I multiplied the probability for each bucket with its corresponding set of returns, thereby finding the expected returns on the NIFTY 50 TRI for each of these buckets.

There it is. The probability of you to have caught the NIFTY in sub-16 P/E levels in the past 17 years is just about one-fifth. Indeed, NIFTY has spent most of its time in the 16-23 P/E levels - almost 63% of the time! Logically speaking, the returns have to be adjusted accordingly, yes? So that's what I did. The final row tells you how much you could expect to earn by investing passively in the NIFTY 50 and re-investing all the dividends for 1-year, 3-year, 5-year and 10-year intervals. Just to reiterate, remember that these returns are shown on a CAGR basis. So it's not that the 5-year returns is just 16.59%, it is actually (1+0.1659)^5 - 1 = 115.43% returns.

I repeated this exercise for P/B and D/Y Ratios:

Interestingly, the data for the P/B analysis looks very incoherent compared to the P/E. This is because the range for the P/B, 4, is much lesser than the range for P/E, which is 10. But we will fix this problem later. For now, let's looks at the final Ratio:

This looks even more all-over-the-place compared to the analysis for the P/B Ratio. But again, logic should tell you why. The range for the D/Y is just 2, compared to the P/B range of 4 and the P/E range of 10.

So how can we account for the data inconsistency? We can look at which data, out of the P/E, P/B and the D/Y, is more skewed and give lesser importance to it and vice versa. I used the SKEW function in excel on the entire set of 4585 data points in P/E, P/B and D/Y. A Skewness closer to 0 indicates a perfectly normal data. So, I assigned arbitrary weights in accordance to the Skewness returned by the formula (50%, 30% and 20%). Here is the final result:

A bit odd, isn't it? The 5-year return is the highest, while the 1-year return is higher than the 3-year return! That's because there's one more piece to the puzzle. Remember how I kept insisting that these returns are calculated on a CAGR basis and not on an absolute basis? It's time to remove that distinction as well, so all the 4 period's returns can be compared head-to-head.

It's common sense that as you invest longer, you gain more. But inflation, or the general rise in prices of goods and services, also catches up with you. Hence, to reconcile this, we should remove the time element from the returns. How do we do this? We calculate the cumulative returns and then discount it at an appropriate discounting rate. In finance, whenever you need a discounting rate, but you are unable to guess which one to consider, the Risk-free Rate is recommended. That is to say the return you can get on the safest investment in the country. In many countries, it is the 10-year Government Securities Yield. As I'm writing this, that rate in India is 7.29%, as reported by the RBI. Here we go:

To understand how we arrived at this, let's take the initial return for the 3-year period, which is 16.29%. To adjust for time, we will first have to convert this into a cumulative return: (1+0.1629)^3 = 1.5726. We then adjust for time by doing 1.5726/(1+0.0729)^3 - 1 = 27.33%. The procedure is the same for all the other periods, raised to the powers corresponding to the number of years.

And voila! We have a conclusion. The returns on the bottom-most row are now directly comparable. In hindsight, why do you think the 10-year period yielded such an amazing returns? It is because long-term returns are very consistent. Short term returns are double-edged swords which could make your rich or completely destroy your capital. It takes loads of research, knowledge and technical skills to dabble with short term returns. The whole idea of passive investment is that the investor lacks the time and skill to do all those. So it makes no sense for a passive investor to invest for anything else other than for the very long term.

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I initially intended to stop at this point. But since I had the data, I decided to test one more important wisdom about investments in general: Can you time the market? Without spoiling the answer, let me tell you how I went about testing this. Peter Lynch in his book 'One Up on Wall Street', answers this question elegantly. So, I stole his methodology and applied it to the Indian markets. The basic idea is to look at the extremes: periods of superior returns and crushing losses, then calculate the long-term returns from those specific points to see if there is any clearly identifiable trend.

As you can see, regardless of whether the market has currently inflated a lot or corrected a lot, the average 10-year forward return from those points is about 16-18% in all. In fact, the forward 10-year returns when the market has seen a huge rise is actually higher than the 10-year forward returns when the market has corrected a lot. Seems counter-intuitive, doesn't it? That's because there is no logic to this, no clear trend.

Look at what the Subject Matter Experts had to say about this:

"You'd be making a terrible mistake if you stay out of a game you think is going to be very good over time because you think you can pick a better time to enter." - Warren Buffet.

"I have never known anyone who could consistently time the market. In fact, I have never known someone who knows anyone who was able to consistently time the market." - Burton Malkiel.

"I can't recall ever once having seen the name of a market timer on Forbes' annual list of the richest people in the world. If it were truly possible to predict corrections, you'd think somebody would have made billions doing it." - Peter Lynch.

It's conclusive then. You cannot time the market.

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We just concluded that market timing is impossible, but don't you think that warrants at least looking at the major disastrous events in the Indian markets-- just to see what happened afterwards and if our theory holds true?

I calculated the forward returns for all the 1-Week periods when NIFTY 50 TRI had declined by 10% or more and re-ordered them by the size of impact:

Out of these 29 days, 13 of them are dominated by 2008 alone. Of course, we had the financial crisis of 2008, which is probably the worst stock market crash in the history of the world. Realistically speaking, anyone could have started investing right before 2008 and then lost a lot of their capital during the crisis. So, we should try to figure out what would be the best course of action if such a crisis every presents itself again: Should investors still hold on to their reduced positions for the very long term?

The answer is 'yes'. Interestingly, notice how the worst forward returns from 2008 have happened when the P/E, P/B were uncharacteristically high and the D/Y uncharacteristically low. It's probably just a good lesson to keep in mind in case the markets climb to such extreme highs in the future. Nothing more.

I would say both of these data sets are too small to reach any kind of proper conclusion, but it is safe to assume that our theory holds comfortably. Ben Graham was right, after all: "In the short term, the market is a voting machine and in the long term, the market is a weighing machine."

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We learned 3 important investment lessons today:

1. Consistently invest in index funds or similar Mutual Funds. The trend of the market in the long term is always 'up'.

2. Invest only for the very long term (10+ years). Short and medium term returns on stock investments are not stable and objectively not that good.

3. Do not try to time the market. You can't. The rule of thumb is 'time in the market is better than timing the market'!

Happy investing!

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If you would like to take a look at the data and analysis yourself, feel free. Here is the link to the excel. Be warned that some of the extreme cases (For ex: 10Y Returns for P/B greater than 6) have been normalized due to unavailability of data. These minor adjustments did not affect the test in any material way. The rest of the formulas are in place. Other than this, if you want me to test a specific statistic or data point from the excel for you, I would be happy to oblige. Place your request in the comments below.