October 6, 2018

Dont worry, there will be pain

A comment made to subscribers when adding to the portfolio:


I am not calling out the bottom of the market or anything of the sort by making the above transactions. As I have repeated often in the past, no one other than liars and self-delusional people can predict what the market will do in the short term.

The best approach always is to look at each individual company closely and evaluate how it will do in the next 3-5 years including under stressful macro conditions.

As we add to the model portfolio, a few positions will not work out – that is a given. The key is to ensure that we do well on an aggregate basis and the returns are above average over time. This approach has worked for me over the last 20 years and I think is still the best approach to follow.

Although we are analyzing as rationally as possible and making a tough decision to start adding to the portfolio, it will be painful to watch the portfolio drop almost on a daily basis. After all these years in the stock market, it is equally painful for me. The key is to focus on the long-term prospects of the companies and their intrinsic value and not react to emotions which will lead you to the wrong decisions.
 

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Stocks discussed in this post are for educational purpose only and not recommendations to buy or sell. Please contact a certified investment adviser for your investment decisions. Please read disclaimer towards the end of blog.

September 26, 2018

Blood on the streets


I sent out this note to the subscribers over the weekend. Reproduced below with edits

I am not going to talk about risk again. I have been speaking about it for the last 12-18 months. The time to prepare for the storm was when the skies were clear. We have a full storm now.

We started reducing some of the fully valued positions last year and raised our cash levels to almost 30% of the portfolio. We were at 29.1% of the portfolio in cash at the start of the year. We now have 33.3% of the portfolio in cash as of last week. In effect, we have shuffled between the existing positions, but have not changed the net cash position much since the start of the year.
 
There is no grand strategy or deep macro reasoning behind all of this. We have been exiting some of the positions which seemed overvalued and started positions in a few others with good long-term prospects. As I have shared in the past, I don’t invest based on macro factors such as interest rate changes, currency or inflation rate. I also ignore short term panics and euphoria in the market other than making decisions at a company level based on the valuations in each case.

My preferred approach is look at the long-term prospects of a company and invest in those cases where the we can make above average returns in the long run. In all these cases, the objective is to make multiples of the invested amount.

Why am I repeating this again? I am making this point because I have no plans to play the current panic for some quick gains. There are a lot of investors and traders who can jump in during intraday lows and make a good gain out of it. There are a handful who can even do this on a consistent basis.

I am not one of those. I know my temperament. I have a tendency to buy and hold to the point of overstaying in a position. In some of these cases, it would have been better to have exited earlier. However, on average I have found that, being patient and holding on has worked out better in the long run.

If you agree with my philosophy, then you will understand the reason why I have not reacted much in the last few months to the noise in the market. As always, I continue to analyze the current and new positions and will make buy or sell decisions slowly over time. I see no reason to speed up the decision making process unless the current events change the thesis for the existing or new positions.

This bring us to the events around the NBFC space.
An obscure term – ALM
There is an obscure or rarely discussed term – asset liability management in the case of all NBFCs. This is a critical part of managing the operations of a financial institution but is rarely discussed as it works smoothly most of the time.

What is ALM?

I will not get technical on this and will try to simplify the explanation as much as I can. Any financial institution borrows money to lend it onwards to its customers. This borrowing is done via commercial paper, Bank borrowings, Mutual funds, Bonds etc. These instruments have varying durations between a few days to years. 

On the asset side, the lending instruments also have varying durations depending on the nature of the loan and the time left on it. At one end of the spectrum are gold loans with a duration of 2-3 months  and at the other end are the long dated loans such as infrastructure loans with a duration of 5-15 years (as in case of ILFS which is in the center of the current storm).

If you layout all the borrowings on a graph with amount on the y – axis and duration on X axis, you will get the liability profile of the company. A similar curve can be generated for the assets too. A well managed ALM operation tries to match these two profiles as close as possible. This makes intuitive sense. You want the short term assets to be funded by short term borrowings and vice a versa

I have pasted below the ALM chart as an example below. As you can see the ALM profiles are reasonably matched.

ALM mismatch and funding issues
As a financial institution has a mix of long and short-term debt, it has to renew its debt on a regular basis. This means that if the company cannot renew its debt, it has no way of repaying it via the cash flow from assets, especially if the assets are long dated in nature.
Let’s look at the case of ILFS 

The company has a short term borrowing of around 25000 Crs out of total borrowing of 91000 Crs. This means that the company has renew to this borrowing on a regular basis.
The company does not break out the asset side duration, but if you look at the balance sheet almost 80% of the assets are long dated in the form of infrastructure assets and receivable claims etc.

This kind of a balance sheet works till the financial institution can refinance its debt on a regular basis. In the case of ILFS, they have been facing cash flow issues and losses due to various projects being stuck at different stages of completion with claims pending with the government. At the same time, the short term debt and interest has to be paid when it comes due. 

In the recent months, the company started facing liquidity issues and has not been able to make payment on its interest obligations as it cannot liquidate its assets quickly to make these payment (keep in mind the nature of assets such as roads and bridges which cannot be sold quickly).

As the company defaulted in the last few weeks, the debt held by mutual funds and other lenders had to be marked down. This has led to a cascade effect where these funds have had to liquidate other instruments to meet their liquidity requirements.

This is a classic run on the bank. ILFS may not have a solvency issue (I don’t have an insight on that) but has a liquidity issues which is now spilling over to the wider market. These liquidity issues mean that all other financial institutions, especially NBFCs which are funded via a mix of short and long-term debt could face a similar risk if the situation escalates.

The parallel with Lehman
There is a fear that this is similar to the Lehman crisis from 2008. There are similarities, but it is not identical. In the Lehman crisis, the company had leveraged up to around 100:1 and funded the derivative assets with short term funding.

When the housing market collapsed, the company had to write down its assets and as it was so highly leveraged, its net worth vaporized in an instant. As Lehman was bankrupt, the counterparties refused to extend credit and hence the liquidity dried up. The only way to save Lehman was to recapitalize it.

In the case of most financial institutions in India, we do not have an asset side problem and hence they don’t have a solvency issue. What we are seeing is a liquidity concern and hence if the government steps in and provides liquidity, the situation could normalize.

Position risks <edited out from this post>
Let’s review the risk at the individual company level now in terms of ALM and liquidity levels

Portfolio risk
Let’s look at the portfolio level risk. For starters, I have kept position size at 5-7% (at cost) and the sector level cap at around 15-20%. This is to ensure that we reduce the risk from an implosion in a company or sector at any point of time. 

This however does not eliminate some risks completely. I have focused on the company level and portfolio risks but cannot eliminate the second or third order effects. For example, the recent drop has been due to the problems at IL&FS, but as the liquidity concerns spread, it has started impacting the overall markets now. We saw midcap and small caps drop as a result of the fear last week.

There is a lot of commentary around what will happen. A lot of commentators feel that the market has over-reacted and we will back to normal soon. Anytime, I hear people prognosticate about the market, I am reminded of a simple fact – No one cannot predict what will happen next. If someone can, they will not share it with you as they will use that insight to make money in the market.

The reality of the situation is that we do have a serious situation with IL&FS which is a SIFI (systematically important financial institution). In simple words it means, that the company is so large that if it goes down, there will be a domino effect which will affect the entire financial sector.

As this is a private company, we have not seen any action from the government on it. However, we are now at a point where the contagion has started spreading and sooner or later there will be a bailout (government will have to back the company). If this happens soon, then fall out will be contained. However, if the government delays taking action due to political compulsion, then we have lots of turbulence ahead.

The first order impact would be in the financial services sector, but it will spread to all the other stocks as we are already seeing now.

Action plan
I don’t have to give false hope to anyone. The reality is that no one knows yet how this situation will evolve. If the government steps in quickly, further panic will be avoided. If, however, we do not see a firm action, then we need to ready for some tough times.

As I have shared in the past, I do not manage the portfolio with an eye on reducing the short term swings in the portfolio. I am always concerned with the long term intrinsic value of the companies we hold. In sharing the above analysis, I have tried to evaluate the impact of a liquidity squeeze on some of our holdings in the long run. Inspite of the logical analysis here, it does not mean that our other positions will not be affected if panic spreads in the market.

This is similar to the analysis I shared after the demonetization even in Nov 2016, when our portfolio dropped by more than 10% in a few weeks. The risk at that time was much more wide spread and was mainly on the asset side of the business (loans going bad). This time around a liquidity crunch will not have a direct impact on the asset side and is more of an issue from the liability side of the balance sheet.

If you are invested the same as the model portfolio, then you should not try to average down if you already have an allocation which matches with the recommended percentage. If however, you have not purchased any particular stock, then you should buy slowly over time keeping in mind the recommended percentage.

Although I don’t react to the day to day movements in the market, I do have an eye on it. I will update all of you if there is any change in my views. For now, we have to be prepared for some tough times
 

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Stocks discussed in this post are for educational purpose only and not recommendations to buy or sell. Please contact a certified investment adviser for your investment decisions. Please read disclaimer towards the end of blog.

August 1, 2018

Evaluating management: Bayesian reasoning and fallacy of obviousness


When I invest in companies, I don’t vouch for or give a character certificate to management. I look at the past and current behavior and then try to arrive at a judgement. In majority of the cases, past behavior is a good indicator, but we do get surprises from time to time.

If new developments make me change my view, I will not try to defend my past decision which was made on a different set of facts. The key is to rationality is to evaluate new facts appropriately and move on from there. As John Maynard Keynes said a long time ago – when facts change, I change my mind. What do you do sir?

Let’s move to the point of how to evaluate management quality in light of poor behavior? For starter, there is no formulae which will give the answer. The best analogy to judge management quality comes from the court system in passing verdict on defendants. A defendant is assumed innocent till proven guilty.

I personally try to look at management with a neutral view when I start analyzing a company. They are neither good nor bad. This is a very important point. I have seen majority of investors start with a presumption of a good or bad management and then collect evidence to prove it. It is very easy to make an assumption and gather enough evidence to prove your point.

The fallacy of obviousness
See this wonderful article which makes the same point. I would highly recommend reading this article. Some excerpts -

So, given the problem of too much evidence – again, think of all the things that are evident in the gorilla clip – humans try to hone in on what might be relevant for answering particular questions. We attend to what might be meaningful and useful

However, computers and algorithms – even the most sophisticated ones – cannot address the fallacy of obviousness. Put differently, they can never know what might be relevant. Some of the early proponents of AI recognised this limitation (for example, the computer scientists John McCarthy and Patrick Hayes in their 1969 paper, which discusses ‘representation’ and the frame problem).

In short, as Albert Einstein put it in 1926: ‘Whether you can observe a thing or not depends on the theory which you use. It is the theory which decides what can be observed.’ The same applies whether we are talking about chest-thumping gorillas or efforts to probe the very nature of reality

Equal priors
The key is to start without an assumption (50-50 probability for both scenarios or equal priors) and look at the meaningful (and not trivial) evidence to come to a conclusion. Once you have done that, your conclusion should not be set in stone, but treated as a hypothesis which can change based on new evidence.

If the management continues to behave well, your confidence is increased. If you start seeing negative behavior, your confidence goes down and at some point (which cannot be mathematically defined), you may lose faith in the management and exit the position.

The above approach is fancifully also called Bayesian reasoning.

One should think probabilistically when evaluating management and not consider these issues as black or white. That’s the essence of Bayesian reasoning.

The central point of this approach is to look at new evidence in light of your prior conclusion and change it in proportion to the evidence. In some case, the new episode may be a small one and will cause you to reduce your level of confidence a bit. In other cases, either the episode or series of episodes will be so awful, that you will be forced to change your mind completely.

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Stocks discussed in this post are for educational purpose only and not recommendations to buy or sell. Please contact a certified investment adviser for your investment decisions. Please read disclaimer towards the end of blog.