This is the February 2018 update for the State of Indian Stock Markets and includes historical analysis and Heat Maps of Nifty50 as well as Nifty500‘s key ratios, namely P/E, P/BV ratios and Dividend Yield.
Please remember that these numbers are averages of P/E, P/BV and Dividend Yield in each month. Neither Nifty50 heat maps nor Nifty500 heat maps show the maximum or the minimum values for each month. Also, note that NSE publishes PE ratios based on standalone numbers and not consolidated numbers (Read why this may matter too).
Caution – Never make any investment decision based on just one or two ‘average’ indicators (Why?) At most, treat these heat maps as broad indicators of market sentiments and a reference of market’s historical mood swings.
Dividend Yield (on last day of February 2018): 1.13% Dividend Yield (on last day of January 2018): 1.03%
Now, to the historical analysis of Nifty500 companies…
As the name suggests, Nifty500 is made up of top 500 companies which represent about 95% of the free float market capitalization of the stocks listed on NSE (March 2017).
Nifty50 on other hand is an index of 50 of the largest and most frequently traded stocks on NSE. These represent about 63% of the free float market capitalization of the NSE listed stocks (March 2017).
So obviously, Nifty500 is comparatively a much broader index than Nifty50.
Dividend Yield (on last day of February 2018): 0.97% Dividend Yield (on last day of January 2018): 0.89%
You can read the previous month’s update here. The State of Markets section has also been updated with new Nifty heat maps (link).
For a detailed analysis of how much returns you can expect depending on when the investments have been made (at various P/E, P/BV and Dividend Yield levels), please have a look at these 3 posts:
This is the January 2018 update for the State of Indian Stock Markets and includes historical analysis and Heat Maps of Nifty50 as well as Nifty500‘s key ratios, namely P/E, P/BV ratios and Dividend Yield.
Please remember that these numbers are averages of P/E, P/BV and Dividend Yield in each month. Neither Nifty50 heat maps nor Nifty500 heat maps show the maximum or the minimum values for each month. Also, note that NSE publishes PE ratios based on standalone numbers and not consolidated numbers (Read why this may matter too).
Caution – Never make any investment decision based on just one or two ‘average’ indicators (Why?) At most, treat these heat maps as broad indicators of market sentiments and a reference of market’s historical mood swings.
Dividend Yield (on last day of January 2018): 1.03% Dividend Yield (on last day of December 2017): 1.08%
Now, to the historical analysis of Nifty500 companies…
As the name suggests, Nifty500 is made up of top 500 companies which represent about 95% of the free float market capitalization of the stocks listed on NSE (March 2017).
Nifty50 on other hand is an index of 50 of the largest and most frequently traded stocks on NSE. These represent about 63% of the free float market capitalization of the NSE listed stocks (March 2017).
So obviously, Nifty500 is comparatively a much broader index than Nifty50.
Dividend Yield (on last day of January 2018): 0.89% Dividend Yield (on last day of December 2017): 0.91%
You can read the previous month’s update here. The State of Markets section has also been updated with new Nifty heat maps (link).
For a detailed analysis of how much returns you can expect depending on when the investments have been made (at various P/E, P/BV and Dividend Yield levels), please have a look at these 3 posts:
As investors, we are generally guilty of two things:
Underestimating risks
Overestimating risks
And the result in both cases is fairly obvious:
Underestimating risks – can lead to losses (at times huge)
Overestimating risks – can lead to missing out on profits (at times huge)
Let’s talk about both aspects in some detail:
Underestimating Risk
Underestimating risk that eventually becomes a reality, can lead to losses. This is a no-brainer. For example – in late 2007, there were obvious risks to market due to various factors (like credit crisis, overvaluation, etc.). Party continued for some more time but when it ended, it had a long list of casualties. All these factors are obvious in hindsight but that’s how it is.
In investing, underestimating risk can trick investors into believing they can tolerate far more downfall than they actually can. But when the risk comes home, people panic and are psychologically arm-twisted into decisions that can cause substantial losses.
Overestimating Risk
This is common too. At times, we exaggerate and go well out of our way to avoid risks… even those with very low probability. This obviously comes at a cost, i.e. sacrificing a chance to earn decent rewards.
For example – Between 2015 and 2018, if someone was basing their decision on just one parameter like (let’s say market PE) and getting obsessed with some sort of framework induced blindness, then that would have cost them some profits. Nifty hit PE24 (considered to be pretty high) on 3rd March 2015 (Nifty was 8996 that day). A clear sign that things had begun to overheat. But what happened next? Nifty (on 29-Jan-2018) is at 11,130 at almost PE28. So had that investor who was blinded-by-the-one-factor framework decided to exit equity completely at PE 24, he would have missed out on this 25% upmove after that.
Ofcourse this episode is yet to play out fully (unlike 2007-2009 which is known to us in full).
Timing the markets is difficult if not impossible. But that’s not the topic of discussion here. What I am trying to highlight is:
We oscillate between underestimating and overestimating risks. We misunderstand it. We mistreat it. But as investors, we have to live with it.
For most people, it’s not possible to take all-in or nothing-in kind of bets in investing. Unless they are really smart investors who have insider info at multiple levels and what not… 🙂
What to Do?
Our assessment of investment risk plays a big role in helping or hindering our overall investment returns. So we need to balance and manage the risk that we take. And mind you it’s a delicate balance… more so towards the extreme ends.
Realistically speaking, we will continue to overestimate and underestimate risks. And being humans, we will always have some level of anxiety about the risk we are taking or about the risk ‘we think’ we are taking. That is a normal thing to feel.
With that said, our agenda should be to ensure that we don’t go too high or too low in our estimations. We must absolutely leave room for doubt, luck and for unprecedented (if not black swan) events.
Miscalculations to some extent are fine. But beyond those thresholds, it can cause a lot of pain – for losing out the invested capital (when underestimating risk) and losing out on possible profits (when overestimating risks).
I personally feel that ‘risk’ is a powerful ally which can help us build a lot of wealth over the long term. We need to understand and manage it. It’s a great friend if it’s working for you and a terrible enemy if working against you. And to be fair, irrespective of whether it’s a friend or an enemy, it will periodically test your patience and mental strength. 🙂
At times, we go wrong with our estimation of risk due to lack of prior knowledge about market history. And at times, due to over-analysis of data that at times may lead to statistical discoveries favoring our pre-conceived notions. We need to be aware of both these vulnerabilities when managing our portfolios.
So what exactly should be done if we cannot assess the risk perfectly or time the markets perfectly?
There is no easy answer here. But few things are pretty clear:
We need to have a proper portfolio strategy in place that is in line with our risk appetite. We need to maintain vigil. And if our skills (or advise taken from smart investment advisor) permits, we ‘may’ take tactical calls to tilt our portfolios to benefit from certain situations. This is about smart and adaptive asset allocation. I will write about this in more details some other time.
This post was more about highlighting how misjudging risks which is a common occurrence can jeopardize the health of the portfolio. This in turn can reduce investor’s ability to attain desired financial outcomes.
With markets doing well, maybe it’s a good time to look inside and contemplate about the risks you may or may not be acknowledging.
It was difficult to not make money last year (in 2017).
Infact if you did not do well last year, you should do some soul-searching as to why your boat was not lifted in a rising tide. 🙂
But jokes apart, let’s focus on something interesting:
Market Timing – something that all of us want and try to do.
I borrow a simple but brilliant example shared by Nooresh here and here:
This is the Difference between buying near the Top and buying near the bottom.
This simple data point tells that inspite of being difficult, timing can be very important to your actual returns (more so in lumpsum investing).
Being good with timing is great. Being average with timing is fine too. But being bad with timing is unpardonable from wealth creation perspective.
It is difficult and that is why there are very few good and successful investors.
Isn’t it?
Others who don’t belong to that category are better off not trying too much to time and stick with regular systematic investing via mutual fund SIPs and doing some stock picking if they know how to do it correctly.
So how can one time the markets?
Difficult to answer as I am no Buffett.
But some indicators can help – like looking at valuations and trying to intelligently gauge when things become too stretched. But beware – just considering one data point and making investment decisions is foolish. This is akin to developing a framework and then falling into a trap due to a framework-induced blindness. That can kill a portfolio.
On that note, I thought I will extend the above example a little further to show the impact of being right across years and not just between two data points.
Let’s see what happens to two investors who invested:
in end-2007 and other
in end-2008
Here is what their annual year-end CAGRs were at end of every year till 2017. This will show what both these investors had to go through:
As is evident, the investor in Nifty (at end-2007) never got a chance to see even risk-free 8% kind of CAGR! So much for investing for higher returns in a risky asset. 🙂 (For simplicity, I am ignoring movements within the year.)
On the other hand, the second investor (who began in end-2008) did very well. His CAGRs were great across years.
Both were buy-and-hold for 9-10 years. But actual returns were decided based on when they bought into the market.
This seems like market timing. Isn’t it?
So be it. This is a fact. Even if someone is not able to catch the exact top or the exact bottom.
Here is further extension and comparison.
Different investors investing at each-year ends from 2009 to 2014 went through different portfolio CAGR returns and ofcourse, mental ups and downs 😉
CAGR % of the investment made in Dec-2009 over the years:
CAGR % of the investment made in Dec-2010 over the years:
CAGR % of the investment made in Dec-2011 over the years:
CAGR % of the investment made in Dec-2012 over the years:
CAGR % of the investment made in Dec-2013 over the years:
CAGR % of the investment made in Dec-2014 over the years:
Timing is important. There is no denying it. Getting it approximately right is still fine. But don’t get it wrong big time. 😉
Most investors need to understand that (very) high valuations mean increased risk of poor returns in (atleast) near future. This is true most of the times. But this is not guaranteed.
Read the above paragraph again.
I repeat. Nothing is guaranteed in stock markets.
New all-time high doesn’t mean markets will fall off the cliff. In fact, new all-time highs generally lead to more new all-time highs. Similarly, high valuation alone may not lead to a big crash. As many people are waiting for it these days.
In investing, there has always been the search for the holy grail. 🙂 A model that works 100% of the time and in all market conditions.
Don’t get me wrong. I am not saying that one should invest at high valuations. I am just highlighting that timing can work wonders but if you know what you are getting into really correctly.
We may never have the full insight to time the markets perfectly. But we can learn some lessons by looking the past market behaviour and performance in light of things like valuations and growth prospects. We also know that markets will go up and down, will get overvalued, crash, will get undervalued and then recover to repeat the cycle.
So what to do?
Remember that most often than not, the consensus is the enemy of alpha.
But don’t take a very aggressive stance just for the sake of being contrarian. More so, if you don’t have the capacity to take such risks. And be honest with your judgement about having such a capacity. Most people overestimate their ability to accept being wrong (proof).
Take measured risks. Have the asset allocation mentality and create a smart and resilient portfolio strategy that gives cognizance to both averages and outlier extreme scenarios. And then, take small tactical calls to tilt your portfolio as and when you feel the need to (using some smart strategy / advice or both).
This is for those who have a hands-on approach towards investing. For others who want their investments to achieve their financial goals, its best to stick to goal-based investing and invest according to a financial plan.
What have been stock markets annual return given in last 1 year?
What have been Nifty returns since inception?
What have been Nifty returns in last 20 years?
What have been Nifty returns in last 10 years?
What has been Nifty CAGR or the average Nifty returns till now?
These are some questions that gain popularity as the year comes to an end.
During this time, we all have this uncontrollable urge to ‘know’ how markets have done in last one year. And how it compares to annual returns of the last few years.
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).
But that is the nature of markets. The average figures will not be achieved every year. Also for SIP investors, it is important to understand that these returns will be different from your rolling SIP returns (but we will discuss that some other day).
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.
This is the December 2017 update for the State of Indian Stock Markets and includes historical analysis and Heat Maps of Nifty50 as well as Nifty500‘s key ratios, namely P/E, P/BV ratios and Dividend Yield.
Please remember that these numbers are averages of P/E, P/BV and Dividend Yield in each month. Neither Nifty50 heat maps nor Nifty500 heat maps show the maximum or the minimum values for each month. Also note that NSE publishes PE ratios based on standalone numbers and not consolidated numbers (Read why this may matter too).
Caution – Never make any investment decision based on just one or two ‘average’ indicators (Why?) At most, treat these heat maps as broad indicators of market sentiments and a reference of market’s historical mood swings.
Dividend Yield (on last day of December 2017): 1.08% Dividend Yield (on last day of November 2017): 1.11%
Now, to the historical analysis of Nifty500 companies…
As the name suggests, Nifty500 is made up of top 500 companies which represent about 95% of the free float market capitalization of the stocks listed on NSE (March 2017).
Nifty50 on other hand is an index of 50 of the largest and most frequently traded stocks on NSE. These represent about 63% of the free float market capitalization of the NSE listed stocks (March 2017).
So obviously, Nifty500 is comparatively a much broader index than Nifty50.
Dividend Yield (on last day of December 2017): 0.91% Dividend Yield (on last day of November 2017): 0.95%
You can read the previous month’s update here. The State of Markets section has also been updated with new Nifty heat maps (link).
For a detailed analysis of how much returns you can expect depending on when the investments have been made (at various P/E, P/BV and Dividend Yield levels), please have a look at these 3 posts:
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
— StableInvestor.com (@StableInvestor) April 6, 2015
Let’s see how things pan out in near future.
Either we will make more money or learn a few new or relearn a few forgotten lessons. 🙂
This is the October 2017 update for the State of Indian Stock Markets and includes historical analysis and Heat Maps of Nifty50 as well as Nifty500‘s key ratios, namely P/E, P/BV ratios and Dividend Yield.
Please remember that these numbers are averages of P/E, P/BV and Dividend Yield in each month. Neither Nifty50 heat maps nor Nifty500 heat maps show the maximum or the minimum values for each month. Also note that NSE publishes PE ratios based on standalone numbers and not consolidated numbers.
Caution – Never make any investment decision based on just one or two ‘average’ indicators (Why?) At most, treat these heat maps as broad indicators of market sentiments and a reference of market’s historical mood swings.
Dividend Yield (on last day of October 2017): 1.08% Dividend Yield (on last day of September 2017): 1.17%
Now, to the historical analysis of Nifty500 companies…
As the name suggests, Nifty500 is made up of top 500 companies which represent about 95% of the free float market capitalization of the stocks listed on NSE (March 2017).
Nifty50 on other hand is an index of 50 of the largest and most frequently traded stocks on NSE. These represent about 63% of the free float market capitalization of the NSE listed stocks (March 2017).
So obviously, Nifty500 is comparatively a much broader index than Nifty50.
Dividend Yield (on last day of October 2017): 0.94% Dividend Yield (on last day of September 2017): 1.03%
You can read the last month’s update here. The State of Markets section has also been updated with new Nifty heat maps (link).
For a detailed analysis of how much returns you can expect depending on when the investments have been made (at various P/E, P/BV and Dividend Yield levels), please have a look at these 3 posts:
