Why I was not a value investor

As an introduction to value investing, the course on Safal Niveshak recommends keeping an investment diary to note down learnings from value investing. These may be instructions of some sort, like a checklist before making investment decisions or just notes on companies. The idea is simple. As Neeraj Marathe elegantly put it, you cannot hide from your own written words. By maintaining a diary, you keep checks and balances on yourself and ensure that your theoretical understanding of concepts in enforced in practice. It's also an excellent way to rejig your memory about past decisions and alter future course of action if need be.

One of the first things to increase self awareness as a value investor includes the understanding of why you have not used value investing principles to make decisions yet. I wrote the following down as I mulled over this issue:

I have not been a value investor because...

I am fairly new to investing in general (less than a year). I was not introduced to value investing directly. Initially I started with William O' Neil's CANSLIM methodology of stock picking. I dabbled in some stocks. I remember my first bet - Symphony Ltd. It was nearing the end of it's meteoric rise and was trading at 40x PE around April 2015. Without a sound background in accounting, I took CANSLIM to heart and dived headlong in. In hindsight, I was a victim to availability bias. Without sufficient reading and exposure, I naturally assumed CANSLIM to be the definitive method for successful investing. The methodology did not talk about valuations at all and I mistook 'good companies' as 'good investments'.

Despite my losses, I was not demotivated. Even though CANSLIM is largely a momentum based approach, at its heart it looks for stocks with proven track records of long term profitability and performance. The other aspect of it is based on technicals which are largely driven by institutional forces. While William O' Neil gives numerous examples in his book and his methodology is considered successful in US market, I wondered if it was truly replicable in the Indian context. A quantitative study of this methodology in the Indian context remains unfinished and I will be very glad to discuss the experiences of Indian investors who may have tried such an approach. Coming from a coding background, I've always been excited about using algorithms to help make investing decisions. From an academic point of view, this is work in progress.

I apologise for digressing from value investing. But I feel my losses have been instrumental in understanding the importance of valuations and consequently 'margin of safety'. I think investing is inherently risky. Whether you consider risk in the academic sense of volatility or permanent loss of capital, risk comes from uncertainty about the future of any business. Value investing trumps other investing methodologies because it minimises speculative value and focuses on intrinsic value arising from an existing business in its existing competitive environment. Focusing on intrinsic value and applying a margin of safety minimises the chance of 'permanent' loss of capital. However, 'short term' loss of capital in terms of paper losses (affected by volatility in prices) cannot be eliminated. This proves for longer time horizons in value investing. I now understand the importance of taking rational decisions for long term wealth creation and am very excited about training myself to be a value investor.

Qualitative v/s Quantitative

Quantitative Value talks about how you can use numbers directly and run them through a sieve to separate good and bad companies. The authors have gone to great lengths to prove how a purely Buffett style of value investing can be combined with an Ed Thorp inspired quantitative model to gain advantage in stock picking. In the American context, they've used Enron and WorldCom as examples to show the power of their models. What is likable about the book is that they've not laid claim to these methods and only tried to enhance them by bringing various tools together. But the question really is whether it's so simple. Surely algorithm based accounting methodologies cannot give the best answers always. Even if the book tries to argue its case for US market, I am not aware of any case studies in the Indian context.

Then again you have Mr. Greenblatt who professes that Magic Formula beats the market and that his methodology has worked year on year without market timing. The authors of Quantitative Value have also used it for their case study in their book. At the heart of it, Magic Formula boils down to very simple value investing principles - i.e. buying companies with good returns on capital at cheap prices. In that sense there is much merit in keeping things simple and boiling it down to a few simple ideas in the end.

Einstein said, "Make things as simple as possible but not simpler". So losing out essential details by focusing far too much on simplicity can be harmful. With respect to Indian markets especially corporate governance is probably one key variable which cannot be measured through numbers directly. Rahul Saraogi makes this point very clearly in the video below (for a general sense of how professional investment managers invest with a value investing perspective in India, this is a wonderful interview). With this perspective in mind, qualitative assessment is probably as crucial as quantitative valuation.

To boil it down, I think there's merit in both qualitative and quantitative methods. In the Indian context, I'm unaware of any methodological study of Magic formula investing or the other quantitative methods extolled by foreign investors. Without access to a database of past financial accounting information on Indian firms, testing would be not be possible for the layman investor. Nonetheless, I would definitely suggest the book Quantitative Value to fellow investors. Even without being able to test methods, the ideas behind financial metrics explained in the book have merit and can be key to making sound investment decisions.

P.S. For Indian investors who would like to use quantitative filters to search for stocks, I recommend screener.in. We'll be ever grateful to Ayush Mittal for this. :)

Musings about social media and validity bias

The craving for action is always high; especially when you tune into any of the business channels. The hulabaloo surrounding corporate stories and constant chatter by market experts makes you feel uneasy during both bull and bear markets. In the first case you're scared that the ship might sail off without you and in the latter you're scared the ship will sink taking you down with it. Independent analysis based on rationality can take a serious hit in such cases.

I want to take this further and recount from my experience with social media. Recently, I decided to follow some 'value investors' from India on my twitter page. Needless to say I was hooked onto their tweets and looked forward to their pearls of wisdom. Initially, I did well to chant their mantras (and make mental notes for the future). However, in any discipline there are only a few main ideas. I like this quote I heard somewhere - "Everything that has to be said has already been said." Usually people are only giving their own twists and turns to old ideas. This is not without merit of course, for different people respond differently to different story tellings and most often the most lasting impact of a moral story is when you fail to learn from the core message and it happens to yourself. Experience is the best teacher. But Munger also says that it's better to learn from the history of other people and that this can speed up your learning curve exponentially. This was the sole aim of joining twitter.

But my point in outlining the role of the twitterati is also to suggest that because some people have a lot to say, it can make you feel unaccomplished. This is especially true for twitter. Most people I know make twitter accounts and find it extremely difficult to come up with intelligent things to say in 140 words. More often than not, most of their accounts remain dummies for most periods of time. So taking to twitter with the single minded goal of following people with similar interests and contributing to that circle of interest can be daunting if you don't have much to say yourself, especially when you'd like to grow to become like some of the people you are following.

My feed, for example, is often abuzz with stock ideas from some 'value investors' and although I have no reason to doubt their skill in picking good stock picks (until now at least), I usually feel rather unaccomplished seeing the multitude of companies on which they have things to say. This makes me question my own capacity to evaluate companies on my own.

I think this bias is close to the kind you face when you view business channels. The goal is then to focus more on your own study of annual reports; even if you're a newbie and it takes you more than a couple of days to try and understand a single company. Surely the gurus out there were not nearly as good as they are now. There is value in focusing on your own strengths and waiting for your own 'aha' moment. That's when you must strike with all your might.