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ValuePickr - Chintan Baithak 2019 Indian Equities Market Past Return

Turn to Look at Return

While reading CSFB Annual return studies, which provide for Global Equities and other asset class return over the years and also for individual country, I realize that they did not have any return for the Indian equities. This led to me to search for return in Indian equities over the long period. While researching on the subject, I could not get hold off any study which provides insight before 1980s. Since Sensex has base year of April 1, 1979; most of the studies in India, take Sensex return as quasi benchmark for equities return.

While that is the best indication of return over last 4 decade, I still wanted to check what Indian equity market returns were over a very long period. I started collecting data from various sources on Google. The most important support to my study came from BSE historical eBook on their website. I downloaded most of this material and studied.

Approach 1: Bottom Up

While there was no indicative Index to calculate return, 1946 Year Book (which I believe a must read for anyone interested in equity market) provided detailed financials and valuation details for many companies. I took that as a base, put all information in excel and compile first approach of aggregating return from large surviving companies during 1945-2018 period. The approach has limitation as it does not consider diversification/ merger/ demerger of divisions and companies. The other limitation was while Banks like Bank of Baroda and Central Bank have survived; they were private bank in 1940s, nationalized subsequently and have constant equity dilution over 8 decades. Nevertheless, this provided whatever indicative return information for surviving companies.

Approach 2: Market capitalisation

While working on Capital goods sector industry study, we did compile data on Indian GDP and Gross Fixed Capital Formation from RBI and CSO website. From RBI website, I realize that we can collect Indian equity market capitalisation data for various years. Hence, I tried to compare decade wise growth in Market capitalisation and compared same with Constant Price GDP growth and Current Price GDP growth. One can consider difference between current price and constant price GDP as Inflation. While I have not checked whether we have inflation data since 50s from RBI, we can improve on same if get same.

The major weakness in this approach was also same as first one. There were frequent equity infusions over the period in the company and also new companies listing/ delisting of many companies. Hence, we do not have constant sample. I tried to address this problem by partially looking at past data from RBI which provided new equity issue. What I realize that range of equity IPO was in range of 0.5-1.5% of existing market capilisation. Hence, in order to adjust increase/decrease market capilisation, I applied around 1% reduction from market capilisation growth to get indicative equity return.

Approach 3: Adjusted Equity Index

In past Economic survey data, I came across another interesting concept by name of “Index of Variable Dividend Industrial Securities” (Old Index). This was indicator used by Government then to calculate return from equity market. I tried to search of Google about same and came across a Government Gazette which provided me over two decade value (with changing base year) for this Index. Accidently, we have April 1979 value of index being 100 while Old index values were also available for 1979. I started reworking on BSE Sensex and based on the Old index and got an adjusted index and calculated return of Indian equities over the period.

There are multiple issues and weakness in this approach. Index is adjusted with Rights and Bonus in Base and also with new company entry and exit of the company. For Old index, except for value, we did not even know which companies were included while calculating same.

The objective of this study is not to provide precise calculation of Indian equity markets over 7 decades. I have neither data nor expert knowledge to claim same. However, the objective was more the get indicative return. The slide in enclosed presentation is providing my finding. PLEASE READ THE DISCLAIMER SLIDE IN PRESENTATION.

I look forward to fellow forum member’s support to take this effort forward and work on improving on the finding. Feel free to send your feedback on this thread. I would also advise fellow members to go through excel sheet which used for working summary table in presentation.
BSE Old Data about Market cap VP.xlsx (228.1 KB)
Turn to understand past Return June 2019.pptx (68.0 KB)
BSE Ebook on 1945 https://ns.mstatic.in/LS/BSE_Book.pdf (Second book in list)
CSFB Year book on Return 2019
https://www.credit-suisse.com/media/assets/corporate/docs/about-us/research/publications/csri-summary-edition-credit-suisse-global-investment-returns-yearbook-2019.pdf
India Past Economic Surverys:
https://www.indiabudget.gov.in/economicsurvey/allpes.php
RBI Data on Indian Economy
https://dbie.rbi.org.in/DBIE/dbie.rbi?site=home

16 Likes

Fantastic work @dd1474,

Your work corroborates the view that the long period average return in Indian Equities ranges from 12%-13% which is also in line with global equity returns regardless of the market, from what i have read.

Once again, thank you for all the effort put in

Best
Bheeshma

2 Likes

Good work. It also explained why many top investors have Textile and Sugar stocks in their portfolio. They have survived 7 decades and will survive future as well.

Comparsion of market capitalisaton of Top 50 in 1992 with Rank in May 2019

1992 Rank Name 31-03-1992 2019 Rank 31-05-2019 CAGR 27 years
1 State Bank of India 22,905.00 8 3,14,637.18 10%
2 TISCO 13,793.40 50 55,908.41 5%
3 ITC Ltd 9,128.04 6 3,41,586.77 14%
4 RIL 6,654.38 1 8,42,933.64 20%
5 HUL 6,369.09 4 3,86,449.46 15%
6 Tata Motor 5,287.17 58 49,806.76 9%
7 ACC 4,924.48 92 31,641.21 7%
8 Century Textile 4,003.46 209 11,466.68 4%
9 Grasim Industries 3,660.25 49 58,336.50 11%
10 Tata Tea 3,516.50 178 15,399.57 6%
11 Tata Chemical 2,986.88 171 16,077.90 6%
12 L&T 2,941.38 12 2,18,549.22 17%
13 GSFC 2,886.50 372 4,311.53 1%
14 Colgate 2,766.55 93 31,335.46 9%
15 UTI Master share 2,699.63 Merged in other scheme -100%
16 Cochin Refinery 2,619.34 Merged with BPCL -100%
17 ICICI 2,475.03 10 2,73,072.28 19%
18 Chemicals and Plastic 2,133.75 Not listed, Chemplast Sanmer was new name and same was Delisted -100%
19 Hindalco 2,104.70 68 44,148.22 12%
20 Bajaj Auto 2,069.50 34 84,647.09 15%
21 Brook Bond 2,060.10 Merged with HUL -100%
22 Indo Gulf 1,814.12 Merged with Grasim -100%
23 GNFC 1,779.40 358 4,552.25 4%
24 Jaiprakash Industries 1,779.04 694 1,179.74 -2%
25 SCICI 1,762.50 Merged with ICICI -100%
26 Bombay Dyeing 1,686.00 480 2,631.25 2%
27 Essar Gujarat 1,683.84 Delisted -100%
28 GE Shipping 1,661.72 376 4,226.28 3%
29 Tata Timken 1,530.00 331 5,106.98 5%
30 Nestle 1,501.42 25 1,10,749.36 17%
31 Castrol 1,479.00 183 14,559.88 9%
32 Century Enka 1,461.60 964 495.45 -4%
33 INDAL 1,452.50 Merged in Vedanta -100%
34 MICO 1,445.90 55 52,146.38 14%
35 Britannia 1,379.18 41 70,482.95 16%
36 Apollo Tyres 1,328.16 213 11,126.37 8%
37 Madura Coats 1,308.20 Merged in Aditya Birla Fashion -100%
38 Guj Ambuja Cement 1,160.00 62 45,798.91 14%
39 Indian Rayon 1,144.80 Merged with Grasim -100%
40 NOCIL 1,134.00 517 2,256.72 3%
41 Raymonds 1,124.72 333 5,082.33 6%
42 Birla Jute 1,120.35 336 5,027.60 6%
43 Oswal Agro 1,112.39 1,623 95.30 -9%
44 Ingersoll Rand 1,104.60 541 2,053.97 2%
45 Mazda Industries 1,095.85 Delisted -100%
46 Siemens 1,038.50 64 45,291.37 15%
47 Ashok Leyland 1,028.80 107 26,082.16 13%
48 VST Industries 1,017.25 319 5,583.18 6%
49 ITC Bhardachalam 1,003.80 Merged in ITC -100%
50 SKF Bearing 963.09 243 9,358.61 9%
6 Likes

Highest CAGR is RIL @20% and I did not see this in any of the long term, coffee can, buy and forget list.
No one seems to trust the management or ethics of the promoter or may be some other reason.

I think it is still undervalued and will continue to grow given its verticals in telecom, retail doing good and virtual monopoly in petrochemicals and ldpe-hdpe business with huge capacities which keep growing. In retail it is biggest, bigger than shoppers stop and big bazaar. Will soon foray into ecommerce.
It’s the best bet for long term and foreseeable future.

Market cap has grown 20% CAGR but has there been no dilution? We need to know by how much the share price has grown. Reliance merged RPL into itself sometime late 2000. Still it is phenomenal growth. The best share price growth was between 2002 and 2008 even considering the 50%+ fall in 2008. Since then it has given reasonable returns. I do not know before 2000 because the data is not available. Also I did not know anything about share price before 2004.

RPL shareholders got a raw deal in case of merger, but RIL shareholders benefitted. Post split RCom and Rpower was carved out of RIL but could not meet the expectations.

In due course, may be in another 5 to 7 years, retail and telecom will be listed independently.

I dont see no reason why it will not remain the most valuable company on bourses in time to come, considering inherent value that may unlock on demergers. There may be occasions when TCS or some other market favourite may overtake in mcap numbers but RIL will remain most valuable for long time to come.

I do not know what their future is. I just said while the market cap grew 20% CAGR in the last 30 odd years, did the share price grow to that extend? Were there dilutions? I feel there were dilutions because of which retail investors did not get the 20% CAGR returns.

@bheeshma, Thanks for your appreciation. I believe the range indicated is what we shall expect in very long term. There is difference between retrun in last 4 decades since 1979 when we compare from 1947 to 1979. The limited GDP growth, frequently affected by drought and war situation and higher dependency of agriculture, has kept Indian market lack luster. The real story for growth started in Mid 1980s which is still continue. Hence, my take from this presenataion, would be to estimate growth rate of around 11-12% (subject to inflation) then work with 15% growth as shown by Sensex over 4 decades coming forward.

@ChaitanyaC
While read the post, I could not understand the message. What I could gather is sensex return yearwise distributed in normal curve. However, would appreciate if you can some more insight on data. I have already given my expected return over very long term (4-5 decades).

@vku369
Textile and Sugar are cyclical sectors. Hence, both decision of entry as well as exit is important. They have survived over the years, with wealth creation has been very volatile. Hence, unless one has great understanding of timing (like Hiteshbhai), the wealth creation would not be great in buy and hold approach in these sectors in my opinion.

@Karanops and @sincyvarghese
You observation is valid and thanks for bringing that. There were many merger of group companies which market capitalisation not reveal. You have already mentioned Reliance Petroleum in the post in 2013. I do remember some name which were promoted as new companies which convertible structure. So capital employed of Reliance industries does not adversely affeced. During the 3-4 years of project implementation, the convertible portion was converted in equity, hence no interest burden on new venture. At final stage, once project has started commercial production, same get merge in RIL at valuation which is being favourable for parent company in my opinion. When studying Reliance industries, when has to give Dhirubhai credit of innnovative use of convertible instrument at right time in Indian context. Pre-1992, when new issue was controlled by CCI forumla, but acquisition was not controlled by any guideline (expect high court approvals), that was very effective way for wealth creation.

Find enlcosed companies which were merged in RIL over the year (to best of my knowledge)
Reliance Petrochemicals Limited (1992 Merger year)
Reliance Polyetheylene Limited (1995 Merger year)
Reliance Poplyprolene Limited (1995 Merger year)
Reliance Petroleum Ltd. (2002 Merger year)
Reliance Petroleum Ltd. (2009 Merger year, second company with same name)


In addition to that, RIL also marged IPCL which it acquired in disinvestment

Find enclosed interesting article on L&T takeover attemps by Reliance group and final outcome.

So there were many equity dilution in RIL, which may reduce adjusted growth rate in RIL.

However, while winner always get the most attention, what is noteworthy for me was also look at the 2-10 ranks. Secon being ICICI Ltd (now Bank, again return increased due to merger of ICICI Bank and SCICI) and L&T.

The 3-6 payers are Nestle, Britannia and Hindustan Lever (again gain from Bookbond, Lipton, Lakme, Tata Vashisht, Tata Oil and many companies over the period). So the point is, mutiple sector from Industrial good, Bank, FMCG, Metals have given good compounding returns in India. Whole IT sector which has been major wealth creator since 1995, was in cradle at that time. None except Wipro (being Edible oil businessI was listed.

My take is good valuation, growth in cahsflow (flowing from sale and profit growth with limited capex for growth) and realiable management are key ingridient for wealth creation over long term.

3 Likes

Hi Dhiraj,

I was trying to see for myself the data, though i could not get the 1992 data. So the next best thing that i could do is to see what is available and i found something which was not in line with what you have posted.

  • Britannia: Price on 31 Dec 1995 - 10.6 and price 31st may is 2936 which makes it as 290 X. resultant market cap in 1995 shall be 241 cr
  • VST Industries: Price on 30 june 2002 was 138 and 31 may 2019 was 3551 which makes it as 25 X. Resultant market cap on 30 june 2002 would have been 213 cr

I am sure you would have looked at the data very closely, however given that Sensex was much lower in 1992, and I have taken only 2 examples is there something I am missing.

attached are the data files that i had used.

BRITANNIA.NS.xlsx (26.2 KB)
VSTIND.NS.xlsx (20.9 KB)

@vishalprasad

Thanks for your efforts in attempting to get Birtannia and VST Industries price movement over the years.

I have sourced Top 50 List from BSE Book by name of The_Stock_Market_Today 1993 which is on BSE website (same link as for 1947 Ebook). Refer to schedule A-8, image of which enclosed under.

I have compiled May 2019 market capitlisation data from Screener and calculated Market capitalisation growth (without adjusting for right/new issue/buyback).

BSE Sensex data during 1992-96 is as under:

1991-92 4,285.00
1992-93 2,280.52
1993-94 3,778.99
1994-95 3,260.96

Due to Harshal Mehta, BSE March 2012 price were reached record level and same is also reflected in index at near life high of 4,285 level. During 1992-1995 only we see almost 23% decline in Sensex, which may be divergent for various companies. So one point which you have considered of Sensex being lower in 1992 is incorrect in my understanding.

I am not claiming that my findings are correct, I can just provide my source and approach.

In case of Britannia and VST, the base years are diffrent from 1992. Hence, price movmemet during the period would have impact on market capitalisation growth.

In case of Britannia, my oldest data on Market Cap was Rs 529 Cr as on March 31 1995, as compared with 1380 Cr in March 31 1992. Britannia share price (June Price Rs 2,743/-), was Rs 35 as on March 31 1992 which declined to Rs 19 per share in March 31 1995. I do not have share outstanding details during March 1992 and March 1995 to make correct assessment of market capitalisation.

In case of VST, as on March 31,1997 (Oldest date for which Data is available with me), market capilisation was 139 Cr . So increase from 1992-97 period from Rs 101 Cr in 1992 to Rs 139 Cr appear not expectional, at least to me.

Hope this clarify your concern. I have no further data to support the working. Appreciate your efforts.

2 Likes

Woking further on Indian equities return, I tried to find out Survial (1-Motrality rate) of listed corporate in BSE since 1959. The objective to was to identify Cockroach (survivor) and Dianosour (extinct) corporate on BSE over 6 decades. The earliest price list I can source was 30 March, 1959. That became my starting point.

I tried to get update about the companies which were listed in 1959 from website and other sources (mainly MRTP Report from MCA about business group in 1969). From the information collected and anylsed by me, I classified, whether the company is still surviving and listed or exinct (may be active but not listed). The objective was if someone applied coffee can approach, whether s/he would have got any value at end of 6 decade through stock exchange.

To my surprise (subject to limitation mentioned in enclosed presentation), nearly 40% of companies listed in BSE in March 1959, are still getting traded on stock exchange. This is was big learning for me as I expect very high mortality rate for Indian compannies.

In second part of series, I shall try to calculate return generated by companies over the period (since listing/ over 5 decades). Since, I have my limitation of time, the update on thread may not be regular. However, aim to work at least on 10 companies to know which has generated higher wealth/ highest return for minority investor.

Please share your feedback on the thread.
Analysis of Surival Rate of Indian Corporate 1959-2020 period.xlsx (50.3 KB) Analysis of Survival rate of Indian companies.pptx (68.7 KB)

9 Likes

Company 1, VST Industries Limited:
This is the first company I stared working to calculate return generated since IPO in April 1974. The company issued share of Rs 10 each at premium of Rs 6 per share (Total issue value: Rs 16 per share). Assuming an investor got 100 shares allotment of IPO and just hold same till date, including Bonus and Dividend, one would have got XIRR of 24.5% during April 1975-December 2019 period (~ 45 years). I was not able to get data of dividend for FY 1995 and FY1996, hence return have scope to improve marginally in case dividend are higher than nil as considred in my working.

The company was trading at dividend yield of 9.1% (Dividend of Rs 2.5 for Dec 75 year and price of Rs 27.5 in December 1976). P/E ratio as on December 76 price was 8 times.

As on December 2019, the company was trading at Dividend yield of 2.25% (Rs 95 Dividend and share price of Rs 4216) and PE of 25 times.

During 1975-2019 period (~43 years), the company net profit increased at CAGR of 12.7%.

So the growth in price, have came mainly from PE rerating. Last 10 year ROE for the company is around 36% and Dividend payout is also in upwards of 60%+ since last ten years.

I am enclosing excel sheet providing my working of XIRR for VST Industries.

Discl: VST Industries among Top 10 holding for me and I have been holding shares since 2009. It is the oldest holding in my portfolio and my view may be biased. I am not SEBI registered advisor and investors shall do their own due diligence before making any investment decision.
VST Indsutries Equity return since listing in 1975.xlsx (12.7 KB)

14 Likes

Company No. 2, Aarti Industries.

Aarti Industries did IPO in Feb 1992 at price of Rs 36 premium on Paid up value of share of Rs 10 each. Subsequent to listing, there were mutiple bonus/splits and dividend. I could not get dividend declared by the company in FY1993-95 period. The shareholder return calculated are too that extent would be lower than actual figure. Further, the cashflow returned to shareholder in form of buyback is also not included in cashflow for equity shareholder.

Assuming an investor hold original allotment of 100 shares in 1992 till 2019, XIRR for that shareholder would be 26.7% p.a. during these holding period of 27.5. I have net profit figure begining FY1996 which was around RS 10.67 cr. In FY19, the consolidated net profit increased to Rs 492 Cr, giving CAGR of 18.1% during 23 years. Hence, there has been marginal growth in wealth created resulting from PE rerating over the period.

I am enlcosing my excel calculation for Aarti Industries.
Discl: Aarti Industries is among my Top 3 holding and I have been holding the company since August 2014. Reader should take note that my view may be biased due to my investment.
Aarti Industries Equity return since listing in 1992.xlsx (11.9 KB)

5 Likes

Indian Equity Markets: A Data History

A data history of the Indian equity markets should be an ideal starting point for all who are starting the investing phase of their life. You could be investing, directly, or via an advisor, PMS, AIF, or MF and could be interested in individual equities, thematic, sectoral, strategic, ETF, Index, etc. This data history will give you a benchmark on what kind of returns to expect, what lumpiness the returns could have, the importance of investing only your patient capital into equity products, and why one needs to be careful around periods of market euphoria.

I have covered major indices based on their popularity, history, and while I could certainly add more indices given the time and resources, google sheet has a 5 mn cell limit which quickly got filled with this data. I have thus not included sectoral and thematic indices as comparing them to broad-based indices is pointless. Broad-based indices and their historical returns should be directly comparable to most diversified portfolios. However, I have included two strategy based indices into the comparison, they are the simplest form of factor-based investing.

I have included comparable indices from both NSE and BSE as I wanted to focus on the value-add if any provided towards the indices’ returns by these two major exchanges and whether we could identify a clear loser and winner.

Indices

I have included the following indices in this comparison:

  1. NIFTY 50
  2. SENSEX
  3. NSE 100
  4. BSE 100
  5. NSE 200
  6. BSE 200
  7. NSE 500
  8. BSE 500
  9. NSE MIDCAP
  10. BSE MIDCAP
  11. NSE SMALLCAP
  12. BSE SMALLCAP
  13. NSE MIDSMALLCAP
  14. BSE MIDSMALLCAP
  15. NSE ALPHA 50
  16. BSE MOMENTUM

The data for the above indices is available from different time periods, I could have cleaned the comparable indices data to avoid any outliers which may have crept due to differing market cycle in the longer time periods but I wanted to include the oldest data points I could find. I will call out such outliers in the data and not consider them for comparison.

Indices Dates

Dates

Rolling Returns

To start with let us pick up the rolling return charts of different indices. If you do not know what rolling returns are, what you need to know is that rolling returns are an attempt to protect ourselves from the bias of picking arbitrary starting and ending points in any time data series.

You all must have heard the stories from someone highlighting that XYZ asset class or instrument gave ABC returns between timestamp 1 and 2. What this ignores is that we have no idea what the returns were between or outside these timestamps. This technique is used by both bear and bull camps to reinforce their bias or view.

So instead we look at rolling returns on a daily price data where we calculate returns from a date “t” to date “t+250” and then we take “t+1” and “t+251” for the next rolling period and so on until the end of the dataset.

As humans, it is impossible to completely remove our biases, and in the rolling return charts below I have included my human bias of choosing arbitrary time periods of 1 month, 1, 3, 5, 7 and 10 year periods. This is a civilization/planet-based bias that we all have. Suppose if we were on a different planet in our or different solar system (hopefully in the goldilocks zone), or Earth took a different time period to revolve around the Sun we would be using different time periods to measure performance (same goes for measuring company/investment performance on a quarterly or financial year basis. Do not dismay if a company does not perform in these arbitrary time periods, each company’s business model is different and it takes different time periods for each one to grow their dominance. However, for now, we are stuck with the time period our civilization uses.

I have assumed approximately 250 trading days in a year. The monthly and 1-year return figures are absolute, while the longer timeframe figures are in CAGR.

The average performance of both NSE and BSE indices in a 1-year rolling timeframe are mostly similar. The mid-cap indices have given 17-20% yearly returns, while small-cap indices have given 20-23%. The 50, 100, 200, & 500 constituent indices which have a heavy skew towards large-caps are not far behind in average performance.

Averages have a way of hiding the outliers if we compare the maximum of 1-year rolling returns, we see surprising outliers from the pre-2000 indices. The maximum returns are almost 2x of the indices which started post-2000. This tells us just how undervalued, underresearched the markets were back then and the market euphoria post-2000 was a mere shadow of what our elders have witnessed before us.

In terms of minimum returns, the returns only the unluckiest investor could get, the data is more comparable across all indices, perhaps this is telling us that the markets do not distinguish between any instrument when panic sets in and everyone wants to get out of everything and that this ability of the market to sell indiscriminately in panic has not weakened with time.

We can ignore the outlier that is the BSE Momentum Index, the index has not seen a full-blown market panic in its lifetime, its older cousin or daddy (whatever you may prefer) the NIFTY ALPHA 50, should be an appropriate benchmark for the fall, momentum strategies can see during tough times.

Indices 1 yr Returns

1 Year

BSE vs NSE – We can ignore the small win for BSE in the Small-Cap indices, BSE’s index was started 8 months before the NSE, BSE captured a lot of the up move in the market and NSE did not. We should also ignore BSE’s win in the 100 & 200 constituents indices as NSE started much after BSE. The 500 constituents indices started around the same time with a difference of 5 months. The 24% outperformance by BSE over NSE was all the result of market direction. Similar story in SENSEX vs NIFTY 50 due to differing time periods.

Amalgamating the above data in the chart below, we can ignore the maximum figure until we reconcile the differing time periods, however, we see small outperformance and underperformance by BSE in average and minimum returns respectively.

NSEvsBSE 1 yr

1 yr

Moving on to the 3-year rolling return data, here, the pre-2000 outliers of the 1-year returns disappear, which tells us that market euphoria or climb does not continue for long, i.e., markets do not keep going up year after year.

What all market participants should notice is that while the maximum and average returns have mellowed down with an extended timeframe, even the minimum returns of the unluckiest investor have reduced. In fact, while the average of maximums has halved, the amalgamation of averages have reduced a few percentage points, the minimums are the real champs here, the averages of minimums have reduced to 1/3rd.

All market participants are getting a lot more wins and a lot fewer losses by just extending their timeframes.

Indices 3 yr Returns

3 Years

BSE vs NSE – We see a similar outcome between the exchanges as above, however, the average of minimum returns have fallen significantly for BSE against NSE. The bulk of this outperformance by NSE is from the 100 and 200 constituents indices and some from the small-cap indices. The first 4 of 100 and 200 indices have decades between them, while the small-cap indices do not. As a counter-argument to time differences leading to lower minimums, the SENSEX and NIFTY50 also have a decade between them but do not see much difference in minimums.

What is happening here is that we are missing the forest for the trees, we are focusing on one time period of maximum and minimum returns. The ideal way to compare the rolling returns would be the average of all these periods. Which smoothens out the effects of outliers. If you feel that averages obfuscate the data, we can compare the average of the highest and lowest (1%, 2%, 5%, 10%, 20%) of a particular set of returns. This is like looking at a part of the forest which is a middle ground between looking at the entire forest and a single tree.

I have calculated the figures for different %s of data to look at and found that directionally, the results are not different from the picture we get from looking at the average dataset.

NSEvsBSE 3 yr

3 yr

Similar story continues for the 5, 7, 10-year timeframes. The minimum returns that any investor can get at even the unluckiest of times, turns positive as the time period extends.

Indices 5 yr Returns

5 Years

NSEvsBSE 5 yr

5 yr

Indices 7 yr Returns

7 Years

NSEvsBSE 7 yr

7 yr

Indices 10 yr Returns

10 Years

NSEvsBSE 10 yr

10 yr

The amalgamated average rolling return data shows that BSE is a clear winner against NSE in all timeframes of monthly, 1, 3, 5, 7 and 10 years. A lot of this outperformance is due to the difference in performance between SENSEX and NIFTY50 which is mostly due to the difference in the length of history. Even when we remove these two main indices in our amalgamation, BSE’s lead over NSE continues in terms of average rolling period returns.

The only indices where BSE loses to NSE is, in the longer periods (5, 7, 10 years) of their respective Mid-Cap indices, and all the periods of their SmallMid-Cap indices.

Indices Monthly Returns

Monthly

The last of the rolling returns graph is for the monthly period, investors should never judge their portfolio returns on a monthly basis, it is too short a timeframe. The only strategies which necessitate a monthly vigil are the momentum-based strategy, which requires frequent rebalancing, even then the investor in those strategies look at the bigger longer picture and knows that monthly outcomes can be negative for some time.

I include this chart just to show how wildly the market can move in a short span of time, any investor needs to be emotionally, mentally ready to see such falls once in a decade on average.

For some reason, on an amalgamated monthly basis, BSE outperforms NSE with its indices but the outperformance is not significant.

NSE vs BSE Monthly

Monthly

Buy & Hold Returns

Below are the charts which depict, the absolute and CAGR returns of these indices since inception. SENSEX is the obvious winner here because of its relatively longer history.

NIFTY ALPHA50 is an interesting candidate here, it has similar inception date to BSE Mid Cap, NSE & BSE Small Cap, NSE 100, & NSE 200 indices. With the exceptions of BSE Mid Cap and BSE Small-Cap indices, the ALPHA50 has outperformed the other with its simple factor-based strategy and concentrated design.

Amongst the Small Cap indices, the BSE clearly outperforms the NSE by 3x even though the difference in their inception dates is only 8 months. This difference in such a short amount of time is a testament to the fact that different starting/ending period of a time series can yield different results.

Indices ABS Returns

Absolute Return

In terms of CAGR returns since inception, the two momentum strategies are clearly giving ample competition to all the other indices. The underperformance of some Midcap & Smallcap indices relative to their larger-cap peers is puzzling, over such long timeframes they should have clearly outperformed. The reason for the underperformance could be the different length of histories, and that, today’s large caps were actually the small caps at the time of inception.

Indices CAGR Returns

CAGR Return

Drawdowns

Below is a graph of the maximum drawdown days for different indices. What these represent is the highest number of days an investor’s investment was below the previous all-time high. This graph throws caution to the buy and hold strategy for the really long term, or adding fresh investments at the market tops. These are just the maximum figures, I have included the individual detailed Drawdown graph for each of the indices in the data folder linked at the end of the post.

Indices Max DD Days

Max Drawdown Days

While the above graph tests the patience of any investor, the one below which charts the maximum drawdowns one could suffer from peak to trough, tests the nerves of even the most experienced investors. Massive erosion of capital in a very short amount of time is a real risk in the market when one is investing near market peaks. Although these drawdowns can often have a V-shaped recovery and one only suffers paper losses, there is something to be said about the lost opportunity cost if one does not keep aside cash in the portfolio for such opportune times.

Indices Max DD

Max Draw Down

Not much to read here, given the magnitude of the drawdowns in both NSE & BSE indices a few days fewer of drawdowns and 6% lesser drawdown would bring a little comfort to the investor who had suffered so much.

NSEvsBSE Max DD Days

DD Days

NSEvsBSE Max DD

Max DD

SENSEX Data Charts Sample

I have included the following charts for each of the indices in the data folder linked at the end. For the rolling returns charts, the return corresponds to the purchase date. The longer the time horizon of the investor, the lower are their chances of a negative outcome in their investment.

The drawdown and drawdown days charts will help familiarise the investors with the fact that equity as an asset class spends most of its time below some previous all-time high. It is impossible to successfully/perfectly time the entry and exit in equity markets. You will never know beforehand what was the peak and trough.

The ST rolling returns chart is a perfect example of randomness, this is why it is hard to be profitable in trading.

The last chart is of the local price peaks, in equity markets it can take years for the previous peak to be conquered.

chart

LT Rolling Returns

Close vs. Date

Index with SMAs

Days in DD

Drawdown Days

DD

Drawdown

Monthly Return vs. Yearly Return

ST Rolling Returns

Peak

Peaks

I would like to end this post, with a phenomenon I have noticed in my limited time in the markets. The life of an investor is always at the edge of regret, sometime you will regret buying/not buying, selling/not selling, someone will always be making more money faster than you, your portfolio may not grow as fast as you want it to. It is also difficult to be satisfied in equity markets, the ones who made 20% returns are looking to double their money, the doubles wants a 5 bagger, the 10 bagger wants 100. Even the 100 baggers won’t rest and want to achieve this feat again and again.

You will notice that market performance is not much different from life, life also has its ups and downs, rarely are people satisfied in their life, most of the successful people in both life and markets follow a structure in their efforts towards improvement, if one does that, they can position themselves on the right side of luck.

Happy Investing.

Data:

  1. Indices Data – https://www.dropbox.com/sh/pj0as504lt4382f/AAAEavzYP-7C0i3WCqsxpduVa?dl=0
  2. Indices Data Sheet – https://docs.google.com/spreadsheets/d/1gG8X5ByujwWKZYyubC1NpuUjDtvkfPqI31YtcPGbcag/edit?usp=sharing
  3. Momentum Indices Data Sheet – https://docs.google.com/spreadsheets/d/1VbI7ns_yrZAiO5q_-0szKCT0TR6JFL_wGCTyDoGXYU0/edit?usp=sharing
  4. ITC Price Data Sheet – https://docs.google.com/spreadsheets/d/1IFGgyLBNzzxed7Xva2JYyIgmWtKSmSiAD6irY5arpXI/edit?usp=sharing
  5. ITC Data Charts – https://www.dropbox.com/sh/mynbr45it5lbr25/AAA1-kiqMuPZQYUwiNSw23kPa?dl=0

Blogpost: https://oldschoolfinance.wordpress.com/2020/02/06/indian-equity-markets-a-data-history/

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@hack2abi

Appreciate your efforts, but I am not able to summary for this message. Can you please summarise your understanding from the data? I find it difficult to comprehend all these data points and chart. Something which is learnt from the chart. Please note that this is my limitation to understand and by no way, shall undermine your efforts. Thanks and happy investing

Hi Dhiraj ji,

The message of this history is mainly for new investors, ones who haven’t seen a complete market cycle.

I did not get into the statistical distribution of the rolling returns as the excel was getting heavy, perhaps that would have got the point across better but to summarize the rolling returns data, one can see that the longer timeframes result in more positive returns than negative returns. So enter equity with long investment period in mind.

The drawdown % and drawdown days show the perils of investing at market tops, lump-sum investment or being fully invested at market tops can be harmful to one’s portfolio. Using this data with the rolling returns data one can see the return volatility during different market times. So there is a case to be made for benefits of market timing, having a cash allocation in portfolio to be deployed at the opportune time.

Yes, no one will get the perfect entry and exit times, but that doesn’t mean one should be discouraged from trying to exit/enter part of the portfolio as per market valuations.

I included the momentum indexes to show that one can perform better than benchmark indices in the long term with factor based investing.

Included ITC data, since it is the latest victim of market infancy and the current drawdown days and % are even worse than the last market downturn of 2008. One can compare the individual stock data with the well diversified indices and find that diversification is not the cure for volatility in rolling returns, nor does it reduce the drawdowns.

This is sort of a primer for new investors of what to expect in equity investing. Seasoned investors would already be familiar with all of the above.

1 Like

Great, Excellent working. Just one more thought, any way from Momentum index or some other benchmark/indicator which can measure market is at exreme pessimsim or optimism. That would be really useful for everyone in general and me in particular. Appreciate your hard work.:slightly_smiling_face:

hi @dd1474

@Yogesh_s in one of his posts had shared a google sheet to measure optimism and pessimism in the market

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