I am planning to start a 10 stock low volatility portfolio from an underlying index of Nifty 100 or Nifty 200. I have seen some articles and videos on how low volatility stocks perform well in both, bear and bull markets. Want to evaluate the same.

The idea is to identify stocks with low Standard deviation of log of daily returns. Arrange them in the order of increase SD and select the top 10. They come with two other conditions,
a. 6 months return must be positive (or 1 year)
b. Current market price must be > its 200 DMA.

Portfolio will be rebalanced once a month. But, I expect the churn to be very low.

As the stocks are selected on the basis of SD of daily returns, I don’t think there is any use in looking at smallcaps or microcaps. Hence, my universe will be Nifty 100 or Nifty 200.

I will create a notional pf and monitor for couple of months, before I start really investing.

@ChaitanyaC Thank you. After you pointed out, I had a look at these indices.
Nifty 100 Low Volatility 30 is similar to what I had in mind except that this index has 30 stocks and my plan was 10.
Nifty Alpha Low Volatility 30 includes an alpha element with a 50% weightage. I am not planning to add any alpha element. Just want to remain with low volatility and see what happens.

I went through the short thread. Very interesting.

@Viraj_Kawatkar has not defined the universe. He talks about doing both large caps and others; therefore, I guess he has used the entire universe (N750). My plan is to use N200 which is a mix of large and midcaps (Nifty 50 + Nifty Next 50 + Midcap 100).

He stopped in a few months and shifted completely to Momentum. Don’t know what his experience was. I have been doing DIY momentum for the last 18 months and looking to add this low volatility pf.

He talks about adding a touch of momentum by considering stocks that are close to their 3 year highs (2nd layer of short listing). This is a good suggestion and I might try and use it. I had already planned for 1 year positive change and CMP > 200 DMA.

Don’t know if @manojh is still continuing with this methodology. If yes, would like to hear his experience.

I had done a trial by investing in ICICI Prudential Nifty 100 Low Volatility 30 ETF. After remaining invested for 2 years , I exited last year as my return was only 15% per annum , though my return from flexi cap and multi cap fund was 30-40% during the same period.

However, the same ETF seems to have given a descent return this year with 29%, though some multi cap/.flexi cap funds have given 50% + this year. ( kotak multicap , quant flexi cap)
the portfolio of icici LV390 ETF is given below.

Addition of a secondary parameter like close to 52w high could improve the returns.

Also, if we did this exercise over Nifty 200, we could possibly get better performance. Will have to wait and see.

Additionally, two other reasons could help us vis-a-vis LV ETF.
a. I am planning my pf over 10 stocks and not 30.
b. Will rebalance every month instead of every quarter.

@ChaitanyaC Thanks. This article, among some of the others, prompted me to look at low volatility investments. The author makes a strong case for low volatility. Let us see how it works for us.

The factors of quality, low volatility, momentum and small cap outperform the index but not at the same time. There are periods where each one is more likely to outperform.
Momentum performs best during bull market, quality in bear market and low volatility in sideways market.
It is not possible to correctly time the market so one will have to face poor performance when the factor is not working to benefit from it when their time comes.

@akash_das Totally agree with you, that is why I want to have an additional investment methodology. I am doing momentum now with different underlying indices. Want to add low volatility as a complementary strategy.

It is also possible that we get some quality stocks, value stocks in our momentum search results, in a falling market, if the search criteria is not too restricted. When the market is buoyant, may be Nifty 500 or go by market cap, and when market is not conducive, stick to Nifty 100 or so.

Just an idea, I am yet to experience this, as we are still in a bull market.

Since @virajkhatavkar stopped his experiment and shifted to momentum, I presume his experience was not satisfactory. @1957 's experience above also confirms the same. I think there are many reasons for this.

Firstly, while lower volatility is a desirable characteristic, it may not be a good starting filter to pick stocks. Business fundamentals are more important. Secondly, I have mentioned in the above thread that portfolio volatility is what one should be concerned about, not stock volatility. And lower portfolio volatility can be achieved even with individual stocks having higher volatility. Thirdly, standard deviation may not be the best measure of volatility, though it is the most commonly used. There are other better metrics.

I guess what you are saying about @virajkhatavkar and @1957’s experiences are valid. However, we are going through a bull phase and that is why low vol pfs are not good enough. I suppose if we went through multiple cycles, we might see something different.

I read what you wrote about pf volatility vs stock volatility. Your point was to add defensive stocks and you should end up with a low volatility. I am trying to come up with a system where entries and exits are clearly defined. There should be no room for discretion or judgement on companies performance.

You have said that SD may not be the best measure of volatility. What are the other better metrics that you can think of? I am interested to know and will implement if feasible.

I went through with the exercise of identifying top 10 stocks based on low volatility (with the condition that CMP > 200 DMA and 1 yr +ve returns). I ended up with the following stocks (1 yr returns given alongside).

ICICIBANK

23%

BRITANNIA

3%

ITC

2%

SUNPHARMA

56%

TITAN

29%

NESTLEIND

12%

DABUR

5%

BHARTIARTL

62%

MRF

30%

ULTRACEMCO

29%

Average for this pf is 25%.

When I added the additional parameter of closeness to 52w high and then ranked them, I came up with the following list ( 1y returns alongside).

ICICIBANK

23%

AXISBANK

32%

BHARTIARTL

62%

SBIN

44%

PIDILITIND

19%

RELIANCE

17%

GRASIM

42%

DIVISLAB

13%

SRF

2%

ICICIGI

56%

Average returns is around 31%
I know that this is not perfect as we are selecting today and checking how they have done in the past one year. I am aware that past returns cannot be extrapolated to the future, but was just trying to see what sort of returns of these stocks provide.

If you consider standalone these returns are not bad. In a bull market, when all stocks are doing well, this might seem insufficient.

I am not suggesting to add defensive stocks. On the contrary, I am saying with your approach you will end up with defensive stocks. The objective should be lower volatility at a portfolio level and that can be achieved even by including cyclicals, if the portfolio stocks are uncorrelated or negatively correlated with each other.

On measure of volatility, I will try to write sometime later this week. Meanwhile you can look at a metric called Average True Range (ATR) until then.

Read a little about ATR. How can we use ATR to compare across stocks? ATR is expressed as a number (not %) and hence a stock with lower stock price will have a lower ATR while a stock with higher price will have higher ATR.

Finance textbooks use Standard Deviation (SD) as a measure of volatility, a practice which has been carried forward by industry as well. SD uses Closing Price to measure volatility. Average True Range (ATR) uses more inputs as it also considers High and Low price for the period, besides Close. This makes ATR a conceptually better metric than SD. ATR is an absolute measure of volatility, but it can be easily converted into percentage by dividing the True Range (TR) by previous closing price.

For example, look at the following calculation of Maruti Suzuki, which had a TR of Rs.343.60 on 17-May-2024. This can be easily converted into a percentage by dividing it by the previous closing price of Rs.12,497.65 (i.e. 343.60 / 12,497.65 = 2.75%)

On the other hand, see the same for Motherson Sumi Wiring (an auto ancillary which caters to most of India’s top car manufacturers with Maruti as its largest customer):

On 17-May-2024, it had a TR of Rs.2.65 which is 3.81 % of the previous closing price of Rs.69.50. Conversion of absolute values into percentages this way makes volatility of the two stocks with widely differing absolute values comparable.

One can calculate TR & ATR anytime just by downloading the stock price history from NSE website and copy paste it onto an excel, once the basic formulas are input into the excel.

Technical analysis textbooks take 14-day average to calculate ATR, but this is at our discretion. One can choose what one wants. As a long-term measure, I sometimes look at 1 year average or 1-year median TR (instead of just the 14-day average which is more short-term). However, this is just for added insight into the stock I am looking at, not as a selection criterion for reasons explained earlier.

I like the idea of 1 year ATR instead of 14 day. Also, the suggestion on how to convert TR to %. Here, I have a doubt. Should the calculation for % be on the previous closing price or current day’s closing price? Any reason why it should be on the previous closing price?

Any idea on how we can integrate mathematically the 2nd layer of filtering, ie closeness to 52w high or any other price action that shows momentum?

Calculation should be on the previous Closing Price because we are essentially measuring the volatility vis-à-vis previous closing price (see the formula for R2 & R3).

However, one further refinement that is possible is to use Last Traded Price (LTP) instead of previous Closing Price in the entire calculation. After all, LTP is an actual price at which the final trade for the day took place while Closing Price is just a fictional price arrived at as Weighted Average Price of the last 30 minutes of trade. I think using LTP will make the calculation truly perfect, capturing volatility in its true essence. Though in practice the results may not be very different from using Closing Price as I have done above.

I guess any standard momentum indicator such as Relative Strength or RSI would be good enough, I haven’t thought much about it.