So if you understand the whole premise of asset allocation and also understand the need to have debt in the investment portfolio, then PPF is a great option. (Try thisPPF excel calculator). But ignoring equities just because it can be volatile in short term is not wise.
Equity will go up as well as down. It is in its nature. It’s not a bank FD. But if you stick to it for long, the returns delivered are much higher than debt products.
And that is what I wanted to convince my relative about.
He seems to be convinced now. Whether he takes any action on this new found conviction is another matter.
I also shared with him the idea of investing on a monthly basis viaSIP in equity funds if he (like most people) doesn’t have lumpsum amounts to invest. He got inspired by the severalSIP success storiesthat one can easily find.
So if you too feel that someone needs a little push to consider equity for long term investments, then you can use the examples above to convince them.
Like previous years, I have once again revised the Nifty PE-Ratio & Return analysis to include fresh data (up to December 2018). Now, this analysis has data spanning from early-1999 to late-2018, i.e. full 20 years.
This analysis uses one simple valuation metric (P/E Ratio of Nifty50) and attempts to correlate it to the returns achieved across various time periods (rolling-periods ranging 3 to 10 years) when investments were made at different PE levels of the index.
The purpose of this analysis is simple.
To arrive at some sort of conclusion and see how well or not-so-well correlated are the two things – the market’s current valuation and its future returns.
This time, I have tried to make this analysis more comprehensive and have included a few additional updates that weren’t part of the previous years’ PE vs Return analysis. So even if you have read the earlier ones, I suggest you go through this one again. My guess is that you will find it incrementally useful.
But before we get to the findings, let me say this upfront that this is not a sure-shot method to make money.
Just because we can find some trends in past data doesn’t mean that the same trends will be replicated in future. Markets are dynamic and the history is no guarantee of the future. In markets, the history is known to rhyme but it is never exactly the same.
The sole purpose of this analysis is to highlight that there exists a relation between the broader market valuations and returns you can achieve.
If you buy low (valuation wise), chances of earning good returns increase and vice versa.
How to Analyse PE Vs. Returns?
What I have done is that I have calculated returns earned on investments made at all Nifty PE levels starting from the year 1999. The time periods of return calculations are 3-year, 5-year, 7-year and 10-years.
Let’s use a simple example to understand this.
Suppose you had invested money in the index Nifty50 on 24th-February-2004 when its PE was 19.97 (actual data).
Now in the next 3-year, 5-year, 7-year and 10-year period (starting from 24th February 2004), the CAGR returns would have been 29.3%, 8.5%, 17.0% and 13.0% respectively.
Using the above-described approach, I have done the return analysis for each and every trading day since 1st January 1999 (the day from which the Nifty PE data is available publically). Obviously, I had several thousand data points for each of these periods.
The days that do not have forward returns for 3-years have not been considered in the analysis of 3-year returns. Same is the case with 5, 7 and 10-year studies. For example, data for 15-July-2013 is used for calculating 3-year return (as data is available for July-2016) and 5-year return (as data is available for July-2018). But the same is not used for 7-year and 10-year returns as data is naturally not available for July-2020 or July 2023 (at the time of writing of this study).
To simplify the findings, I have been grouping Nifty PE into 5 groups earlier.
But to provide more granular data this time, I have decided to present my finding in a larger 7-grouping set.
Nifty-50 PE Ratio and Investment Returns
The findings are based on 4243 data points for 3-year analysis, 3751 data points for 5-year analysis, 3250 for 7-year analysis and 2509 for 10-year analysis.
And here is what has been found after updating the dataset:
Due to the choice of intervals in the PE range, the figures differ slightly if I revert back to the old PE-range choice. Here is the same summary on the basis of the old grouping:
Essentially, both tables tell you the same thing – when you invest at low PEs, your expected future returns are comparatively higher.
Remember, these figures are based on past data (of the last 20 years).
The trends no doubt are easily evident here. But they may or may not repeat in future. There are no guarantees that the future returns will follow similar patterns.
Markets won’t behave as you expect them to behave just because you have found its rhythm. You will not get returns just because you want them.
But the above data set and relying on a common-sense based approach to investing tells that investing at low PEs is difficult but profitable.
So let’s say if one had the courage to invest in Nifty when PE was less than 12, the average returns over the next 3, 5, 7 and 10 year periods would have been an astonishing 39%, 29%, 22% and 18% respectively! Unfortunately, it’s very rare to find days where Nifty is trading at such low valuations.
On the other hand, if investments were made when Nifty50 was trading at PE ratios of above 24 and above 27 (which are the supposed overvalued territories), the chances of earning decent returns in (atleast) near term are pretty low. This shows that if you invest in high PE markets, your chances of low (and even negative) returns increase substantially.
Investing at lower PEs can give bumper returns! But it is not easy. It takes a lot of courage, cash and common sense to invest when everybody else is selling (in times of crisis). This is what the 3 C’s of proper investing is all about too. It is very easy to sound smart and quote things like ‘be greedy when others are fearful’. Unfortunately, very few are able to be actually greedy when others aren’t.
Before we further slice and dice the dataset to find out more interesting things, let me highlight a few important points about using index data here:
The Nifty PE data is published by NSE (here) and is currently based on Standalone numbers. This means that actual earnings (that includes those from subsidiaries, etc.) in consolidated figures are higher than what the standalone numbers would suggest. And that also means that current actual PE may not be as high as that suggested by the standalone ones.
The constituents of Nifty50 keep changing. The index management committee that is responsible for maintenance of the index regularly brings in and moves out companies from the index. The Nifty composition of 2008 was quite different from that of 2018. Similarly, the index composition of 1999 might also be very different from that of 2008 and 2018. Try to understand it like this. If the index is made up primarily of companies that are low PE-types, then index at the overall level will tend to have low-PE. Whereas if the index is made up of high-PE companies, it will tend to have a high PE. So actual definition of high and low PE will be different for both type of companies, and so in turn for the index. A PE of 15 for a low-PE company might be very high whereas for a high-PE company might be very low. This is an important factor that should be kept in mind. I have addressed this to some extent in the latter part of this analysis by comparing returns while changing the periods under consideration from 20 years to 15 and 10 years.
Moving on, let’s address another important aspect here:
Risks when dealing with Average Returns
The table above gives a very clear relation between P/E and Returns.
But the above numbers are just ‘averages’. And that can be risky if you solely invest on basis of averages.
To explain this more clearly, let’s take an example.
Imagine that your height is 6 feet. Now you don’t know swimming. But you want to cross a river, whose average depth is 5 feet. Will you cross it?
You shouldn’t – because it’s the average depth that is 5 feet. At some places, the river might be 3 feet deep. At others (and unfortunately for you), it might be 10 feet.
To counter this, we need to analyze a few more things. So…
Adding More Data points to PE-Analysis
A better picture can be painted if in addition to the average returns, we also consider the following:
Maximum returns during all the periods under evaluation
Time spent in at a given valuation band
Have a look at the tables below now:
I want to spend some time here to highlight what all this means. I will also visually depict this using a small graph.
In the graph below, I have plotted PE ratios on X-axis and 3-year CAGR returns on Y-axis for all available data points in the last 20 years. As you can easily see, the trend is clear – returns are higher when investment happens towards lower PEs.
But you don’t always get the average returns that the preceding table shows. You can get anywhere between the MAX figure and MIN figure and the difference is huge.
Let me try to segregate the above chart into PE-bands to highlight this:
As you can see, within each PE band, the actual returns are all over the place.
Focus on the first green block of PE12-15 band.
The red circle is the position of average return (38.7%).
But as the two text bubbles show, the Max and Min returns are very different from the average returns. Refer to the table above and you will find that max is about 58.1% and min is about 5.9%. And all this with a standard deviation of 14.6%.
What this means is that even though the average figure might tell you something, the actual returns can vary a lot.
I hope you get the drift of what I am trying to show you here…
Let’s now see the data for 5, 7 and 10-years:
Spend some time studying the above tables.
By now, you would be clearly noticing that there are big differences between the minimum and maximum returns for almost all periods.
So even though the average return figures will tell you one thing, the fact is that the actual returns that you get will depend a lot on when exactly you enter the markets and what happens afterwards.
Two different investors entering the markets at same valuation levels (let’s say PE=17.5) but at different times would have got 7-year returns ranging from 7.7% to 26.1%. Check the table for 7-year return above and you will know how.
For a lack of better word, the difference is shocking.
What this means is that even though the average return for 7-year period in the example taken above (PE17.5) is 16.2%, the actual returns have ranged from 7.7% to 26.1%.
This is equity investing for you. Welcome!
The statement that I made a couple of paragraphs before, ‘returns that you get will depend a lot on when exactly you enter the markets’, does sound like trying to time the markets. But this is a reality. I cannot deny it. For those who can, timing the market works beautifully.
Hence even though the average returns give a good picture for long-term investors (look at the table for 10-year analysis), its still possible that you end up getting returns that are closer to the ones that are shown in minimum (10Y Returns) column and not the Avg. Returns. 🙂
This is another reason why I introduced the column for standard deviation in all tables above (see the last column of the table above).
Analyzing standard deviation tells you – how much the actual return can vary from the average returns. So higher the deviation, higher will be the variation in actual returns. For completing the scatter analysis, here are the 3 remaining scatter plots for 5, 7 and 10-year returns:
Can You Catch the Markets at Right Investible PE?
Ideally, and armed with the above insights, it makes sense to buy more when valuations are low. Isn’t it? Buy Low. That is the whole idea of investing.
But real life is not that simple.
It is very difficult to catch markets on extremes. It’s like a pendulum – it keeps oscillating between overvaluation and undervaluation. It is almost never perfectly valued.
So should you wait to only invest at low PEs? Though it might make theoretical sense to do so, it is still very difficult to wait for low PE markets. And extremely low PEs are extremely rare.
Just have a look at this 5-year table I shared earlier in this post:
Look at the column ‘Time spent by the Nifty in PE band’ at Below-PE12 levels.
It is just about 1.5% of the time since 1999 that markets spent below PE12. This is extremely rare.
For common investors, it’s almost impossible to wait for such days. In fact, such days might be spaced several years apart!
So the best bet for common people is to keep investing as much as possible, via disciplined investing (like SIP in equity mutual funds). It is not perfect (like buy low sell high) but it is your best bet given all the constraints. And once your portfolio grows in size, make sure you rebalance it periodically to adhere to proper asset allocation and manage risks appropriately.
Long-Term Investors have Better Chance of Doing Well
Another insight that this study gives is that as your investment horizon increases, the expected returns more or less are reasonably OK-ish to good enough, even when one invests at high PEs.
Have a look:
So, even if an investor puts his money in the index at PE above 24, the historical average returns are more than 8 to 10%. That’s quite ok I guess. Atleast it’s much better than being in losses.
The longer you stay invested, higher are the chances of not losing money in stock markets…even if you have entered at comparatively higher levels.
Caution – I know that’s a dangerous statement to make but to keep things simple, please read it in the right spirit and get the drift.
Now let’s compare this with someone who is thinking to invest at high PEs (above 24) for less than 3 years. Have a look at the table below:
There are un-ignorable chances that the person will not do well. Chances of losing money are fairly high if you see the average figures and Minimum returns for PE24-27 and PE>27 bands.
But let me touch upon an important point now.
Will this Result change if only the more Recent Data (and not last 20 years’) is considered?
That is no doubt an interesting and fairly valid point.
In last few years, it does seem (and I repeat ‘seem’ – may be due to our recency bias) that average PE levels are much higher than what they used to be in earlier years. The Reason for this may be many:
One of them can be that unlike earlier years, the constituents of Nifty50 are companies which in general have high PEs. So obviously there is a case for slightly higher average PE figures as the new normal.
The PE figures are based on standalone numbers of constituent companies of the index. If we consider the consolidated numbers, then chances are that the earning would be higher and lead to lower (calculated) PE figures. Earlier, the difference between standalone and consolidated figures wasn’t much as Indian companies did not have large subsidiaries that would distort the figures. But as Indian companies grow and so do their subsidiaries, the consolidated figures will be incrementally bigger than standalone ones.
To accommodate these facts, it makes sense to give more weight to consolidated figures. But NSE publishes data on the basis of standalone numbers till now. So we live with it for time being.
Another option is to reduce our period in consideration from 20 years to a more recent one – like last 10 or 15 years – where the comparative difference in the nature of index constituents in not as stark as what might be (like) 20 years ago.
Ofcourse the number of data points would reduce. But we can atleast have a slightly more relevant comparison if not a perfect one. So I wanted to try out the above analysis with different (but more recent time periods).
As a first case, let’s consider the last 10 years data, i.e. Jan-2009 to Dec-2018.
Do note that the beginning of this period coincides with the depth of the last severe bear market. So numbers will change. Let’s see:
You would agree that the trend remains the same. At higher valuations (PE), the future returns reduce.
I have not done the analysis for 7- and 10-year period as the period under consideration (i.e. 10 years) is too small to have any sufficient number of data points for the 7- and 10-year analysis.
But how does this compare with our previous analysis where period under consideration was 20 years? Let’s see:
Spend some time comparing the above 2 tables. The left one is based on the analysis of the last 10 years and the right one is based on the analysis of the last 20 years.
The basic conclusion once again is the same.
But the extent of these returns changes when we the period under consideration is changed.
Focus on the red arrows for now. The returns for PE12 case moderate from 38.7% to 23.0% (for 3-year) and from 29.2% to 18.4% (for 5-year) when we change the analysis period from 20-year to 10-year.
Now focus on the green arrows. The returns for PE18 and above (i.e. PE18 to 21 to 24 to 27 and beyond) increase somewhat for both 3-year and 5-year analysis when we change the analysis period from 20-year to 10-year.
This might be getting slightly number heavy but what I want to highlight here is that depending on the data set I chose, the return figures change to some extent (increase and reduce for different PE bands).
The overall conclusion still remains the same. But the expectations need to be revised when we give more weight to the recent past (last 10 years) than what we gave to the full last 20-year period.
You might feel that by choosing the last 10-year period, I am missing out on the Bull Run between 2004 and 2007. And rightly so.
So let’s consider a different period now:
The last 15 years (from Jan 2004 to Dec-2018).
This period takes into account the great bull run of 2004-07, the big crash of 2008-09 and the upmove since then 2009-2018.
Let’s see what the data tells here:
I may sound repetitive here – but the overall trend is still the same.
But once again, what changes though is the extent of returns in each case.
Let’s now compare 3-year and 5-year investment returns for each of the PE bands when different analysis periods of 20, 15 and 10 years are considered:
As is clearly evident, the figures moderate if we reduce the analysis period to data of the last 10 years instead of 20 years.
To be fair, there is no perfect answer as to which one should be used or which shouldn’t be. But this moderation analysis proves that we should revise our expectations to more rational levels. Due to various factors (like increasing difference between standalone and consolidated earnings and PE figures, change in index constituents and their normal valuations), we may have to keep a range of outcomes in our mind when making investment decisions. It was never black and white. It was always grey. Now it has even more shades of grey!
For the sake of completeness, I am tabulating the full findings for everything below. This includes 3-year, 5-year, 7-year and 10-year Nifty return analysis compared across various PE levels and after considering data for different sample space of 10, 15 and 20 years:
Also, note one more thing – this analysis is based on one time investing at specified PE levels.
If you are a SIP investor, then returns will obviously vary as your investment would be spread out across time and PE ranges. You cannot and should not expect to receive lumpsum-like returns on your SIP investments. The mathematical concept of average doesn’t allow that to happen.
Asking Again – Whether This Approach works in all kinds of investing?
My answer is that no one strategy can work in all conditions.
Knowing the broader market PE gives a fair idea about the valuations of the overall markets. It tells you when the market is overheating and that you should take cover (reduce equity in line with asset allocation). This, in turn, helps reduce the chances of making mistakes when investing.
Similarly, this knowledge of PE-Return Relationship also helps in identifying when markets are unnecessarily pessimist. If you are brave at such times, you can make some serious money.
And please don’t think about investing in individual stocks just because Nifty PE is low. Individual stocks have their own stories and need more in-depth analysis.
I have been doing this analysis now for several years. If you wish to access old ones done in the year 2017, 2016, 2015, 2014, 2013 and 2012, then please access the archives. But I think its best to stick with this current analysis as it’s the latest and most comprehensive one till date.
This is easier said than done but this is what really works in the market.
To sum it up…
There is a reasonable (but not guaranteed) correlation between the trailing PE and Nifty returns. And this study proves it and provides some useful insights. If we were to go by the historical data, the Nifty delivers higher return (in long-term) whenever investment is made at low PE ratios. On the other hand, it tends to deliver low to negative returns whenever investment is made at high PEs and when the investment horizon is short. You as an investor can use this insight as a backdrop to take your investments decisions.
I hope you found this detailed and comprehensive PE-Return analysis useful.
I will try to revise this study with new data points and other insights as and when practically feasible.
But still, we do get attracted to annual return figures. Isn’t it?
So as we have completed another year, I have decided to analyse annual returns of widely tracked market index Nifty50 – a widely tracked index of the Indian stock markets, which is made up of shares of 50 largest Indian companies.
Nifty50 closed 2018 with gains of about 3.2%.
After a lot of upheavals and volatility, 2018 did not turn out to be a very great year for the markets. But this comes on the back of a good 2017 – which was the best since 2014 and second best since 2009!
How does this compare with the averages?
Nifty has a CAGR of 13.4% in the last 20 years (since 1998) and 13.89% in the last 10 years (since 2008).
So below is the Nifty historical chart showing annual Nifty returns since 1996 (i.e. 2+ decades):
To see this from another perspective, have a look at the table below. It gives you the current value of Rs 1 lac invested in Nifty50 every year since 1995-96:
As already mentioned, looking at average figures has its own pitfalls. An average of 12% annual returns might sound great on paper. But it requires you to witness -30%, +20%, 5%, -15%, 13%, etc. for few years. You won’t get that 12% fixed returns, no matter how much you want it. 🙂
So obviously, the 2-decade long journey has been a volatile one. In the last 22 years, we have had:
16 years with positive returns
7 years with negative returns
You might draw out the conclusion that more often than not, markets will give positive returns.
That is true. But how much of that return will be captured in your portfolio is another matter.
So if you had invested somewhere in 2002-2003, the annual index returns after that have been 3.3%, 71.9%, 10.7%, 36.3%, 39.8%, 54.8%. And this is not normal. This was unprecedented and chances are high that such a sequence of high positive returns, might not get repeated again for many years if not decades. So do not have such expectations of multi-year high returns from stock markets.
Infact, we should be ready to face ugly years like 2008-2009 – when index itself fell by more than 50% and individual stocks crashed by 80-90%. I have said countless times that one should invest more in market crashes or when everyone else is giving your reasons to not invest. But that is easier said than done. When a crisis like the one in 2008-2009 comes, it is not easy to combine your cash with courage.
But that is what separates poor investors from good ones and, good ones from great ones.
Now we have seen Nifty’s historical annual returns for last 20+ years. But that gives us only 23 data points to look at (even though it covers Nifty returns since inception). And that is not sufficient to draw out any meaningful conclusions.
Ofcourse it is interesting to look at annual return figures. These give us a benchmark to compare our own portfolio’s performance.
But it is very important to understand what these annual figures won’t tell you. We can pick and choose data to prove almost anything – as it has been rightly said – “Torture numbers, and they’ll confess to anything.”
You might find people telling you that markets can give you 15-20% returns. And they might even show you data to prove it. But just picking one particular Nifty 5 year return period or even a 10-year period will never give you the complete picture. You need to see how markets have behaved in ‘all’ such 5-year and 10-year periods.
So when talking about annual returns, lets not just evaluate year-end figures. Instead, let’s analyse rolling 1-year returns. That will give us a better picture.
Nifty historical data is available starting from July 1990. So that is where we start.
Now to calculate one-year rolling returns, we pick every possible 1-year period between July 1990 and Dec-2017 (on a daily basis).
So we have the following:
3rd-July-1990 to 3rd-July-1991 – 1st one-year period
5th-July-1990 to 5th-July-1991 – 2nd one-year period
29th-Dec-2017 to 31st-Dec-2018 – Last one-year period
In all, there were about 6641 rolling one-year periods.
And this is what Nifty did in these several thousands of one-year periods:
And here is the graph of these returns (since 1997):
If you study the graph carefully, you will find interesting things. Some 1-year periods have seen returns of more than 100%. But there are also periods of major cuts (like the early 2000s and 2008-2009).
Now one obvious thing to note here is that when rolling returns are low for some time, then chances are high that rolling returns will increase in near future (as can be seen in sharp up moves after low returns in the above graph).
I leave it up to you to draw out your own conclusions.
Another important point to note here is that these graphs and tables are based on Nifty50 index levels. It does not reflect the impact of dividend reinvestments.
The index that captures ‘dividend reinvestments’ is called the Total Returns Index (TRI). So basically, Total Returns Index or TRI is Nifty including Dividends.
I won’t be doing the detailed annual or rolling annual return analysis of TRI here.
But to give you a perspective of how dividend reinvestment can impact your returns, I will compare the regular Nifty50 with TRI here:
As you can see, there is a decent difference in index levels (with and without dividend reinvestments). It is for this reason that one should try to reinvest the dividends as much as possible.
Now 2018 didn’t turn out to be a very good year for most market participants (after 2017 being a really good one).
But for long-term investors, a year of low returns would bring in a lot of opportunities if we are observant enough. And I am not just talking about index levels here. Even individual stocks offer various opportunities by oscillating between their 52-week highs and lows.
As for 2019, there is no point in predicting what will happen.
So let’s not rush and instead, wait for another 365 days to see how next year’s Nifty 50 annual returns turn out to be.
One of the problems in raising concerns about valuations is that you can end up looking like a party pooper. And if future markets movements do not happen in line with what you are expecting, you can even end up looking like a damn fool!
But that’s fine. I don’t intend to predict anything here.
It’s just that if you look at the data, it does trigger some concerns. I am a simple investor who wishes to buy low (and maybe occasionally sell high too). 🙂
Unfortunately, the ‘buying low’ part doesn’t seem to be easily happening these days.
For Nifty50, the valuation of the index today is in excess of PE-26.
Now historically, this is rare! And has happened very few times in the last couple of decades. In fact, there seems to be a sort of hidden upper ceiling when it comes to valuations and markets have trouble keeping above that ceiling.
Have a look at the chart below.
The blue line is actual Nifty level. The red line is hypothetical Nifty level at PE24 at that time. The green line is hypothetical Nifty level at PE12 at that time.
Clearly, Nifty seems to have trouble staying above PE24 (considered overvalued) and below PE12 (considered highly undervalued). Whenever it reaches either of these two levels, it seems to bounce off in opposite direction! (read full analysis here).
Also, a move beyond PE 25-26 has been historically rare and generally resulted in steep falls. And as can be seen from tables below, markets do not spend a lot of time on the extremes:
But does it mean a sharp fall or a full-fledged market crash is just around the corner?
I don’t know.
River water seems to be flowing above the danger mark. But will it flood the city or not is something that I cannot predict. And markets have this evil habit of surprising. So who knows they may remain at these levels for much longer.
Ofcourse every now and then, the valuations will be stretched and go where it hasn’t gone in last many years. But it’s important to consciously remember that sooner or later, the reversion towards mean happens. And this is what learning from history and identifying basic patterns helps you do.
I regularly publish index PE data and as many of you might have noticed, is showing a lot of red. Check here for the latest update in November 2017.
I have done detailed analysis earlier which shows (or seems like modestly predictive) that future returns tend to be low when investment is made at very high valuations. To summarize, it is something like this:
(Please do note that above are average figures. And depending solely on averages and ignoring the actual deviations can be catastrophic. Read about the risk of depending only on averages and please… never forget about it.) 🙂
Now interestingly, the Nifty PE has remained in and around 24 for last one and a half year. And as of now, we have been flirting with PE26 and above(s) for the last couple of months.
I did some further slicing & dicing of data to see what happens to index returns (in next 1, 2 and 3 years) when investments are made in PE24 and above zones. Here is the data cut:
It’s self-explanatory and unfortunately, paints a sorry picture.
Do note that the correlation seems very strong but the number of data points is not very high.
All these hints towards something not being right. But the party still seems to be on…
Maybe, the earnings will surprise and bring down valuations without hurting market levels. Or maybe, the constant flow from retail investors is and will support the markets for longer. Or maybe this time it is ‘really different’ and we will continue to reach newer heights on the mountain of valuations. 😉
But like all bull markets where new highs are being regularly made, it’s very easy these days to write off valuations as something of an unnecessary botheration. Everything is moving up like there is no tomorrow. Investing in IPOs is once again perceived to be a quick way to make money. But trees do not grow to skies for a reason. And valuations matter. Believe it or not.
I don’t intend to predict a big crash here.
Markets have a mind of their own and will crash when they want and not when we predict. But I feel that we should not throw caution out of the window. We should be alert. Alert to the possibility of lower future returns.
But since I have used Nifty50 PE data as a representative of the market, let’s make note of few things which should be kept in mind:
Nifty of today is much different from Nifty of earlier years. Infact, there is a regular change in index constituents. So it’s easily possible that high PE is the new normal. After all, in earlier years Nifty was made up of low-PE companies while these days it’s populated with high PE ones (read this interesting analysis).
Another aspect linked to above point is that PE data provided by NSE is based on standalone numbers of Nifty companies. It would be ideal to use consolidated numbers as many Nifty companies have subsidiaries that have a significant impact on earning numbers. This has a much larger effect now than it would have had in yesteryears. But NSE publishes Nifty PE using its own set of criterias and decisions.
For all practical purposes, one cannot wait for investing when valuations are rock-bottom (like PE 12-14). If that is the case, the investor will end up on many bull runs that begin at 15 and end at 27. 🙂
Investing in individual stocks is a different matter altogether. You can always find undervalued stocks in overvalued markets. There can be stocks that continue to command high premiums and still deliver spectacular returns year after year.
I don’t know what the so-called smart money would be doing now. But moving out of equities completely is not something that I do. Ofcourse, focusing on asset allocation with an eye on valuation and operating in preferred tolerance bands is something that should help most people.
Nothing more to add from my side here. Here is an old tweet that acts as a sort of guide 😉
Things to do in market PE>26 – Tk Holiday 26>PE>22 – Read books 22>PE>15 – Invest 15>PE>12 – Invest Heavily 12>PE – Take Loan/Steal & Invest
Updated – Nifty monthly returns data updated till October 2017.
Many people want to know the monthly returns generated by stock markets. Though these monthly returns don’t matter much to the long-term investors, it still makes for an interesting data point. Just like annual Nifty return numbers.
So if you too wish to know more about the Nifty monthly returns and how it compares with historical monthly returns data, then this post will be of interest to you.
Using publically available index data of Nifty returns since inception, you can easily find out historical monthly returns of Nifty. So below is a color-coded heat map based on Nifty’s monthly historical index data:
Nifty Monthly Returns Historical Data
So that was about returns generated by Nifty in each calendar month since 1990. But should you really care about monthly returns of the indices?
Index performance is something that many people use to know how to compare their own performances with index returns. And no doubt it’s interesting. But I think that people who are not involved in the day-to-day market movements are better off managing their money by targeting their real life financial goals and investing regularly. Keeping track of annual Nifty returns is still fine. But monthly tracking may not be of much help for most people.
But nevertheless, some people love to know things. 🙂
And just to complete the data set, I have also calculated rolling quarterly, half yearly and annual returns for Nifty too:
Nifty Quarterly Returns Historical Data
Nifty Half Yearly Returns Historical Data
Nifty Yearly Returns Historical Data
If you are more interested in Annual or yearly returns of Nifty 50, or Nifty’s performance in last 5 years or Nifty’s performance in last 10 years, then please check this post on Nifty Annual Returns.
Note – I will be updating this Nifty monthly returns post every few months.