Stock market always moves up in the long term but returns move up and down!

Published: August 16, 2021 at 9:09 am

The Sensex closed past 55,000 on Aug 13th for the first time, and usual trumpets from mutual fund guys blared, “stay invested! The stock market always moves up in the long term”. In this article, we present rolling SIP returns data for the Sensex (1979 to 2021)  and the S&P 500  (1900 to 2021) to illustrate while the stock market may move up in the long term, returns (even long term returns) always move up and down!

First, let us look at the journey of the Sensex price index from April 1st 1979 to Aug 13th 2021, first on a normal scale and then on a log scale. To appreciate the utility of the log scale, please see: Are you ready to climb the Sensex Staircase?!

Sensex Price Index from April 1979 to Aug 2021
Sensex Price Index from April 1979 to Aug 2021
Sensex Price Index in log scale from April 1979 to Aug 2021
Sensex Price Index in log scale from April 1979 to Aug 2021

When seen this way, it looks nice and comfy. Let us not worry about day to day volatility. The market will anyway move up, sorry I forgot “always”, move up in the long term. So there is no risk! Not so fast!

Let us now look at 15-year rolling SIP returns data. That is, starting from 3rd April 1979, we roll over a 15-year window each month as shown below.

From DateTo DateSIP XIRR
03-04-197904-04-199428.39%
02-05-197902-05-199428.06%
02-06-197901-06-199428.24%
02-07-197901-07-199428.88%
01-08-197901-08-199429.12%
04-09-197901-09-199429.61%
This gives us a total of 329 15-year SIP returns as shown below. I should say only 329 data points because of our short market history. The data is for the price index and does not include dividends. We do not have the total returns index that far back available for free.
We can safely add 1.5% to 2% returns to these returns to account for dividends but it will not change the central observation that “long term” returns have moved up and down.
15 year Rolling SIP returns of the Sensex Price Index from April 1979 to Aug 2021
15 year Rolling SIP returns of the Sensex Price Index from April 1979 to Aug 2021

In the above case, more down than up! We are unlikely to see 25%- plus returns again because the market volatility has reduced since the Harshad Mehta scandal- Sensex at 50,000 – lessons from the 42-year journey. Also see: Sensex return is 16% plus over last 41 years but half of that came from just three good years!


On 43 occasions, that is 13% of total trials, the return was less than 10%. A single-digit return after 15Y has to be considered as a “loss” at least in the past as it is not an adequate premium for the risk taken.

Please note that this 13% (or 0.13) is not a probability! It is just past performance. We cannot keep investing with hope and find out after 15 years our returns are poor. That is a risk we simply cannot afford to take.

Investing each month on the same date is not systematic investing. Regular investing and regular risk management = systematic investing. Learn more about it here:  Basics of portfolio construction: A guide for beginners.

To better appreciate why long term returns can go both up and down, we need more market history. We shall turn to the S&P 500 Total Returns index for this using the Schiller PE data.

The S&P 500 when plotted on a log scale again underpins the sentiment that the markets move up over the long term.

S and P 500 Total Returns Index in log scale from Jan 1900 to July 2021
S and P 500 Total Returns Index in log scale from Jan 1900 to July 2021

When this is plotted normally, it looks bizarrely extraordinary because it extends beyond the normal human lifespan.

S and P 500 Total Returns Index from Jan 1900 to July 2021
S and P 500 Total Returns Index from Jan 1900 to July 2021

When we look at the 15-year rolling SIP returns data – there are 1279 such data points! – it is nothing short of extraordinary! The true cyclic nature of long-term equity returns is seen.

15 year Rolling SIP returns of the S and P 500 Total Returns Index from Jan 1900 to July 2021
15-year Rolling SIP returns of the S and P 500 Total Returns Index from Jan 1900 to July 2021

We only see an arm and leg of this cyclicity in the case of the Sensex because of its short history – meaning we have to be more careful about what to expect from equity in the future. In fact, do not expect returns from mutual fund SIPs! Do this instead!

Why does this happen? Why does the index look like it is always moving up but the returns move up and down? The answer is time. The index does not move up 10% or 20% over the same period of time. Sometimes it can happen over days and sometimes over months. See for example: How can a 400% profit result only in 8% return?! Hodling to the moon Risk!

The 90% returns we say after the March 2020 crash in a year usually takes 4-5 years or even more! Volatility is both our friend and enemy. Just like fire, it is essential to beat inflation but get overconfident about it can burn you badly.

The most important takeaway is this cyclicity never goes away. These are 1099 30-year rolling SIP returns of the S&P 500 Total Return Index.  The duration has doubled from 15 to 30 years but the spread in returns have only marginally decreased!

30 year Rolling SIP returns of the S and P 500 Total Returns Index from Jan 1900 to July 2021
30-year Rolling SIP returns of the S and P 500 Total Returns Index from Jan 1900 to July 2021

Also, although we say cyclic returns, we have no idea when the returns will peak and when would start falling.  This is why both investing and risk management has to be “systematic”. If someone asks what returns can I expect from equity over the next 30 years, the honest answer is, “we do not know; we cannot know.”. The best part is, we don’t need to know!

What should investors do? We must learn to stop listening to AMC hyperbole about compounding (see: Don’t get fooled! Mutual funds have no compounding benefit!) or market rewarding the blindfolded patient in the long run – sometimes it does and sometimes not. We will have to shift our focus from returns (which can fluctuate and not in our control) to a target corpus for a specific goal (which we control better with a variable asset allocation)

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