CategoryGeneral thoughts

Can we time it better?

C
We talk more about losses than winners with our subscribers. Winners take care of themselves and show up in the portfolio returns. Losses, especially in markets like now, are painful and take effort to manage.
Following note was published to our subscribers

We recently sold Company A (name withheld due to regulations) after 40% drop from the all-time highs. We got queries asking if we could have timed it better

Let’s break down the transaction in terms of how it played out rather than ‘anchoring’ to the all-time high

We invested close to 4% of the portfolio in several tranches. The exact price will vary for you based on when the transaction was executed. On average, the loss would be between 15-25% for most subscribers. This translates into a portfolio loss of 0.6% to 1%. Even in the extreme case of someone buying at the top, this amounts to 1.5% loss at the portfolio level

This is within the bounds of our risk management for individual positions. We try to keep our max loss between 20-25% of buy price and total risk at portfolio level at around 1-1.5% on cost basis. Based on historical data, this gives us a 3:1 to risk reward ratio and with a 55-60% win rate, our returns over the long run are above average

Hopefully the above live example shows how we think mathematically about individual positions and that Company A played out within our set parameters

Managing risk from all time high

We do not manage risk from all-time high for any stock

Doing so is valid for swing trades with shorter time horizons. We have done this partially with our position trades in the MA accounts, but Company A was not such a position

For our time horizon, selling a stock when it drops from all-time high, will result in jumping in and out of positions, especially in choppy markets such as now.

Trying to manage this type of risk brings up the following questions

  • At what level should one exit? 20%, 30%?
  • Do we re-enter if the stock drops 20% and resumes the journey upwards?
  • Is there a fundamental criterion to exit? Keep in mind prices react before the fundamentals
  • How about bear markets versus bull markets? In bear markets, a small miss can cause the stock to drop more than 20%

It is always easy to look at the stock price in hindsight and ‘know’ the right decision

Risk is managed probabilistically

The answer to the above questions is that ‘it depends’ and there is no perfect answer.

We aim to lose less when we are wrong but gain more when we are right. If we do this consistently over the long run, our portfolio returns will be good (as they have been for the last 15 years)

We will continue to exit positions which have not worked out, and it will be painful during bear markets. Exiting a position, even at a loss, does not mean we will not revisit it. We have made this mistake in the past and missed a 50 bagger

PS: There is a lot of nuance on this topic. We plan to publish a video post on it soon to explore it further

 

 

 

Timing the market

T

We have had several meetups with subscribers in the last 2 years. One of the most common question is ‘what do you think about the market’ ?

It is important to unpack this question and on why people ask this question

Most people want to know if the stock market is overvalued (so that they can sell) or undervalued (so that they buy). The other reason is that they are concerned the market will crash and lead to losses

The above concerns are valid, but this is the wrong question to ask. If you are a bottom up investor, market levels make no difference. If the companies you hold are undervalued, then you should buy or hold irrespective of what happens to the market in the short term

The other concern is losing money at the portfolio level when the market crashes. This will happen even if your stocks are undervalued. The first change in mindset is to get comfortable with losing at the portfolio level when the market drops. There is no way to get around it and this is the price we pay to make above average returns

If you get upset when your net worth drops substantially during market corrections, review the asset allocation of your portfolio. Let’s say 80% of your portfolio is allocated to equities. If your portfolio drops by 25%, will you get upset and sell your stocks in a panic ? If yes then reduce the equity allocation to the point where you will not lose sleep over it

The right question to ask is not what will happen to the market in the near term. Instead, figure out the  asset allocation where you will not lose sleep if the market drops. This action is under your control where as no one knows what will happen to market.

Is it the right time?

I

This is the most common question we get from our new subscribers when they enquire about our service. The second question most frequent question is – what do you think about the market?

Both the questions are linked. Let’s explore the assumptions behind these questions.

The investor is trying to time their entry in the market to maximize their return. If they can time the market more precisely, the portfolio returns should improve. That is the theory.

The Time angle

Let’s explore this question first from the time horizon of the individual. For the sake of argument, lets look at the two extremes – one is a swing trader, and the other is a buy and hold investor with 10+ year horizon.

The swing trader has a holding period of 3-6 months and for this person, the near-term direction of the market makes a lot of difference. At the other extreme, the buy and hold investor could care less about what happens in the next 6 months. As long as the long-term economics of the company is intact, he does not care.

We have a time horizon between 2-5 years. For us the near-term direction of the market has some implication, but not a lot. Let me expand on this.

We watch the overall market to look for the extremes. If the market is too frothy and so are our stocks, we start reducing our exposure progressively as we have done in the past. At the other end, when the market gets cheap, we reduce our cash and raise our exposure.

This range is wide and most times we ignore the state of the market. We are focused on the prospects of individual stocks and follow a bottoms up approach.

Asset allocation

This gets to the second element of our process – asset allocation. Although we do not manage this for our clients, we follow a simple approach for our money. We have a pre-decided allocation for equity, debt, real estate and so on. As the markets rise, we rebalance the portfolio to get the allocations back to target.

For example, if the target equity allocation is 70% of our asset mix, we reduce our exposure to achieve the target when markets get overvalued. Selling some of the overvalued stocks and raising the cash levels allows us to reduce risk in the portfolio and achieve the target allocation at the same time.

 

Combining the two

As long-term investors, we cannot swing from 0% to targeted equity allocation in your portfolio based on market levels. We follow a graded approach of working within a band where we reduce risk to our equity portfolio when valuations get out of whack. That also achieves the asset allocation targets.

Instead of asking whether this is a good time to invest, the better questions to ask are

  • Am I below or over my equity allocation in my portfolio? If below I can allocate more capital to it
  • Are there opportunities which will do well over 2-3 years and are reasonably priced. If yes, then I can add to them subject to the limits from previous point.

Unless you are a swing trader or position trader, there is no need to agonize over the precise market level. It makes sense to slowly raise or reduce your allocations based on the above two factors.

The new Superpower

T

Last week, i posted a note on the paradigm shift in white collar work. i have been exploring the new LLM-based tools such as ChatGPT, especially the deep research option, to improve the quality of my analysis and productivity.

Let me explain how –

I search for new ideas using various screens, charts and through general reading. I then review the charts and read a few annual reports and conference call transcripts. At this stage I have a rough idea about the company and know enough to ask the right questions.

Research plan and Autonomous agents

This is a good point for me to create a research plan. This plan has the usual elements of company details, its industry, competitors, management and so on. The nuance is adding company specific questions which are relevant to the idea. For example – when analyzing a bank i would like to compare it with other banks various metrics such provisions, NPA trends, Loan books etc

I feed this research plan into multiple LLM tools – Chatgpt, Grok and Gemini etc . I can add all the annual reports, conference call ppt and transcripts to the chat too. The deep research tool uses these uploaded documents as the primary source to generate a detailed report. The beauty of these tools is that if it cannot find the answer, it does extensive search on the web and provides those details with references

The latest reasoning models can understand your questions and reason through the best approach on answering them. It can also figure out which tools to use such as Search, code interpreter and so on. In other words, it is acting as an autonomous agent

The result is often a 30–40-page detailed report tailored to my questions. This report then sparks more questions which i can google or ask the LLM to find answers

In summary, these tools are like 24/7 analysts, improving at an exponential rate. The analyst is not smart enough to ask the right questions or decide on which companies to research. That is my job.

Are these tools perfect? Of course not. They often get the numbers wrong but by knowing enough beforehand, i find the errors and correct them. As these tools evolve, i expect to use them in more creative ways

Asking the right questions

A

The basis of white collar work is changing rapidly

In the early 2000, with the internet and google, the grunt work around finding information was removed. Value add for any type of work shifted to putting together this information in a valuable format

For investors, this meant that bulk of your effort shifted from finding information to synthesizing it to arrive at an investment decision. The front end of the workflow – Finding annual reports, data points which used to be manual was now available at the click of button.

In the same manner, for jobs like coding, we have repositories for a lot of the boiler plate code. A significant part of such jobs is now is in glueing these components together to achieve the desired outcome

Paradigm shift

The launch of LLMs in 2022 is changing the core of all white collar jobs again. The difference this time is that it is faster and moving up the value chain at the same time

I was initially curious about these new tools and started experimenting with them in early 2023, as I did with the internet and google in the past. For those who saw the early internet, these tools felt like the dial up connection of the late 90s – slow, clunky with limited usage

Google and broadband in the early 2000s made the internet what it is today – cheap, easy to use, ubiquitous. I am seeing the same transformation in the LLMs, but at 10X the speed

The early chatgpt was Realtime and good at answering questions for which the answers already exist on the internet (and thus part of its pre-training). With the launch of the O1 and now O3/O4 models, we have reasoning models which can ‘understand’ your questions, plan the tasks and decide which tools to use to best answer these questions

This is a paradigm shift on how computers work

All other software tools follow a fixed information flow via logic embedded by the developers and system designers. In contrast these tools operate more like us, than traditional systems. They are becoming autonomous agents

Burying head in the sand

There is a lot of chatter around the implications of these tools on the future of work. I will not get into which jobs will or will not get replaced. Time will tell

A few things are, however, clear based on the current state of these tools

  • The base models continue to improve rapidly based on new algorithms and more compute
  • We have new reasoning models which continue to improve based on reinforcement learning techniques
  • The cost of these tools continue to drop exponentially (almost 90% per year)

This means that the cost of performing routine tasks and synthesizing information is dropping rapidly. If the major part of your job is to use existing information and put it together in a different format, you face competition from these tools which can do a good enough job at 5% of the price (and dropping)

This does not mean we are doomed to irrelevance as the tools get better. However it does mean that we need to re-think what is our value add (to get paid well)

This is similar to waves of automations in the past – Farm and factory workers were not happy when machines replaced human labor. They fought this change tooth and nail. We will see the same happen with white collar work.

A lot of pushback is on the following lines

  • The work quality of these tools is poor (same as weavers complaining about the quality of hand-woven cloth versus the machines)
  • They are taking work away from hard working people
  • It is unfair

I am not denying the pain these tools will cause in the workforce, but burying our head in the sand is not going to change reality.

Change your workflow

I personally think we should all take these new tools seriously and start learning as much as we can on how to use them. The next step is to breakdown your own workflow into what can now be done more efficiently using these tools.

Let me take investing as an example

The job of portfolio managers/Investors/Research analyst shifted from finding information to synthesizing it in the last few years. There are screening tools, financial websites, charting tools available where we can get all the necessary information in a few minutes (which used to take hours and days in the past)

The main job for us was to put synthesize all this information and arrive at the final decision – should I buy the stock, how much of it and at what price ?

As an investor, we get paid for our decision, not for the effort we put it. If we can reach a high-quality decision in a few hours versus days then it’s even better. In such a case, these new tools are a great benefit to us. We need to drop the mindset from our school days: grade = amount of homework. In markets, it is always quality over quantity

In the past I would read up a lot of documents and think of questions to answer. I would then dig further for the answers, but generate new questions at the same time.  Invariably there would be a point of diminishing returns after which I would decide with 70-80% of the information

I am no longer constrained

My job as an investor is to read the necessary documents as a starting point and come up with a list of questions. I can feed these questions to one of the LLM tools and  get a detailed answer. I can dig into this output, push my understanding forward and generate a new set of questions

The result is that I can have a better understanding of the company and its industry in a much shorter period of time. What can be better than that?

I will dig deeper in my next post into how I have changed my workflow and incorporated these tools.

The most important change for all of us, including investors, is now to come up with high quality questions. We are getting to the point where our computers will generate better answers than most humans

Agency and Fun

A

I came across this word recently and resonated with me. On reading about it, I realized that I have always admired this behavior and strived for it. So what is agency?

As per google,

In a person, “agency” refers to the capacity to act independently, make free choices, and exert power to shape one’s own life and experiences. It’s about having control and influence over one’s actions and the outcomes they produce

In India, we call this jugaad

As I look back on my own life and those around me who have done well, I find almost all have had high agency – a drive to improve their life

In my generation, India had started opening up and we experienced the first technology revolution – Internet. A lot of young people in the late 90s joined IT services companies (making switches from other careers), some started online businesses, some moved to the US and some like me started a blog on investing on a whim

I enjoyed reading and investing. Pre-internet it meant getting annual reports from brokers and reading the newspaper. There were no Indian blogs (only US based such as the Motley fool bulletin boards). When I found this new medium, I started writing my own thoughts for no particular reason

Today its called content marketing, but then it felt like writing to myself with no one reading it

One thing led to another – I eventually started an advisory with my friend – Kedar which we have been running for 12 years. I still get surprised to hear from people that they have followed me for years and were reading what I was writing. I never realized that this would happen

The new revolution

We now have another shift in the making – Artificial intelligence. I am equally excited about it. As in the late 90s I get the same tingly Spidey sense of something exciting.

How will it evolve and where will it lead us?

I don’t know, but as I did earlier, I am learning about it and playing with it

I am sure it will be an exciting and fun journey as it happened with the internet. I keep saying to anyone willing to listen to do the same but be less timid

The wrong questions

T

We wrote the following to our subscribers


When and at what level will the market bottom?

what should be the cash level in the portfolio to ride out the bear market?

These are wrong questions to ask. Let me explain –

I wrote about preparing for a downturn in my prior note. We have developed a process based on the study of the past bear markets and our failures. The key point is that we ignored some risks in the past which hurt us when the market cycle turned.

We have identified the following risks and managed them as they intensified towards the second half of 2024

  1. Valuation risk: We exited/trimmed several positions in tranches as stocks went from under-valued to fairly and then overvalued. We did not exit these positions in one shot as we wanted to take advantage of the momentum
  2. Position size risk: There are positions we want to hold through the cycle. However, this poses the risk of opportunity loss if the size is too large. We trimmed some of these positions so that we can hold the balance with less stress
  3. Sector concentration: we reduced positions if they were based on the same theme and sector. When a sector goes out of favor, it can impact the stock for a long time
  4. Poor performance: In some cases, the performance of the company was weakening and we exited as the risk reward was no longer attractive

One additional element this time was to review the indices and breadth to gauge the market cycle. As the cycle weakened in Q4, we actively reduced our risk.

In summary, we were focused on managing risk and not predicting what will happen to the market.

Half the battle

We are now at 45%+ cash level which is the highest ever and it is NOT burning a hole in our pocket. This cash level is an outcome of the process

It is easy to feel smug at this point. However, this is only half the battle. Equally important is to re-enter the market and not get locked into a bearish outlook.

We will not depend on market forecast or expert views for it. We have looked at this phase of the market too in the past cycles and have a process of initiating or raising our positions. Some of you have asked how long will it take?

We don’t know. That can only be known if you can predict the market (We can’t)

Graded entry and exit

We had a gradual exit out of several positions to reduce the aggregate risk as the market weakened.  We will re-enter in a gradual manner too driven by our buy process

The buy process for a stock will be based on its fundamentals and risk reward equation. It does not require for us to forecast when and at what level the market will bottom. Fixating on the market level is a waste of time. We are focused on refining and executing our process of finding and entering new positions

This time around, the cash level will also be a result of executing this process

Preparing for a downturn

P

We published this note to all our subscribers today


I have been doing a detailed analysis of the past bear markets of 2008, 2016, 2018, 2020 and 2022. I looked at the indices, individual stocks and our past holdings during this period. It has allowed to me understand context of the market and mistakes I made during these periods.

I am listing a few learnings from this study. This should give you a context of our actions in the recent months during which our cash levels rose from 6% to 33% now

The current market reminds me most of the 2007/early 2008 and 2017/early 2018 period. It does not mean that we will have a financial crisis later this year. Please keep in mind that it is about similarities with these periods, but you cannot use it to forecast the market

A few learnings

No one can predict the market but often there are signs of froth, and it makes sense to become cautious. One can guess ‘what’ may happen, even if you cannot figure out when it will happen

  • Valuation extremes: In the past, when valuations hit the extremes, it took months for the excesses to be wrung out of the system. Valuations are now at their 10+ year high in the small cap/mid cap space. Promoters have been launching IPO/QIP etc to raise capital when it is cheap
  • Deep corrections: Theme stocks of the current cycle, no matter how good the prospects, get hit the most and can easily drop 50% or more. Other stocks will not be spared as indices drop 10-30% from peak to trough
  • Nowhere to hide: During deep corrections, there is no place to hide, and all stocks will be impacted. The key is to remain invested in those companies with a robust business model and good growth prospects for the next 2-3 years

Mistakes from the past

We made the following mistakes which I am trying to avoid now

  • We were concentrated in a few sectors/ stocks in the previous downcycle. When these stocks were hit, our portfolio had a big impact
  • We kept buying or held on to stocks which were in continuous down trend. A lot of these companies did not recover for another 2-3 years
  • Heavy losses made us risk averse and we were not prepared enough when the market turned

Some recent actions

  1. Reduce valuation risk – We have reduced or eliminated positions where the valuation was much higher than the median. This was to reduce the valuation risk in the portfolio
  2. Reduce concentration risk – We have reduced the size of some positions which are fairly valued. This was done to reduce the concentration risk
  3. Exit weak sectors – We have exited some stocks where the stock and the sector seem to be topping off and growth is slowing such as the FMCG space

Go forward plan

We have not started a new position for some time.  As we have shared in the past, we will not invest to show activity from our side and justify our fees. We will act only when the risk reward is favorable

Just because the market is down 10% does not mean that it’s a good time to buy. If you expect steady stream of ideas, you will be disappointed as markets don’t work that way. There are times to be active and then times to just wait and prepare

We continue to monitor all our positions and will not hesitate to exit or reduce some of them if the risk reward is not great. Just because a stock is already down, or a turnaround is around the corner is not the right way to make decision.

Experience in prior bear market has taught us that hope is a bad strategy. Take your hits, clean the slate and conserve your financial and mental capital. We will be ready whenever the market turns

Learning and feeling dumb

L

I started my career in Marketing and switched to IT (consulting). The pay was 2X and the stress was half of that. I had also come to the realization that I did not enjoy sales/marketing. Reading and learning was the thing I loved, and IT provided a great opportunity for that. Investing was the other area where I could the same and earn at the same time

I joined one of the Large IT services companies and was deployed on an ERP project. I had no clue about the technology. I tackled the problem the same way I had handled it as an investor

I went online, downloaded the implementation guides, manuals, notes – whatever I could find and started reading them. At first, they made no sense. However, by the third reading (cover to cover), I started getting a hang of it

The next step was to get into the software and practice. I became good at it within a year.

On the next project, I had some juniors working with me who were in the same place, I was a year back. To my surprise, when I asked them to read all the material, cover to cover, they balked at it. Till the end of the project, they kept reaching out to me for help and just coasted along

Most people avoid lifelong learning

At the end of this episode and a few years later, I realized a couple of things

  • These colleagues did reasonably well in other companies and moved into managerial roles. It just showed that learning was not key in moving up the ladder and most companies did not care for it.
  • There is a perverse system where a lot of IT service companies do not reward for deep expertise. As a result, they end up with a layer of management who have outdated technology skills. It is not their loss though as they tend to fire such resources when they get bloated
  • Curiosity and drive to learn is not as common as I thought. Most of the people I know would rather coast along without pushing themselves

Why people avoid learning

Initially I was puzzled why people avoided learning when it was fun, and you were better off in the end

I realized that the process of learning makes you feel stupid. I recently went through this phase when I was learning technical analysis and poker a few years back. Even now, I get the same feeling on a regular basis. This is not a question of intelligence. No one likes to feel dumb and as a result people avoid learning new things

This will be a major hurdle in the future for a lot of people as new AI based technologies go mainstream. I have gone down that rabbit hole in the last 2 years and can see massive changes on the horizon.

Unfortunately, a lot of people will complain and find reasons to avoid the discomfort of learning. I am lucky that I am comfortable with feeling lost and stupid most of the time. I have 25 years of practice in it

Here we go again

H

A recent post to our subscribers on the current market situation. Hope you find it useful


We have experienced 13 drops of more than 10% in the last 14 years of our advisory. A few have been more than 20% and the one in 2020 was 30%+

If you have been in the equity market for a long time, this is not a surprise. Even a cursory study of market history, shows the same. Yet, a lot of people get shocked by such drops.

The recent drop is being explained with a new set of reasons whereas just a few months back, India was being touted as a miracle economy. If you really need a reason, how about this? – The markets fell as it often has in the past and will do so from time to time in the future

A study of the past

I recently did a talk about past cycles of manias and booms & busts. You can watch the recording here. Some of the key lessons are

  • Manias and crashes are driven by human nature. They will always be there as long as people are trading in the markets
  • There is a plausible, kernel of truth which gets stretched to excess
  • No one can predict when/where a bubble will start and when it will end
  • Media always acts as a cheer leader of Bubbles (Story/Attention Bias)

As part of this study, we also reviewed the past 25 years of the Indian market. We have incorporated the learnings in a new process, where we review the market on a monthly basis to gauge its trend, breadth and sectors which are doing well and ones that are slowing down

As a result of this review and rising valuations, we started exiting some positions and are now at 25% cash levels

Did I foresee that the market would drop? No amount of market analysis can help you forecast the future. What we did realize was that some companies in our portfolio were stretched and so we started pulling back. We also exited positions where the performance was poor and the stock was weakening

In a nutshell, we raised our cash level as the risk reward ratio in our portfolio dropped

So what about the cash?

The next set of questions, we invariably get after every drop, is when we plan to invest the cash. For starters, we are not swing traders who are trying to catch the swing low to make a 20% gain on the next bounce

Our focus is to buy stocks with a 2-3 yr window and a 10% drop is not enough. Several stocks have dropped from a PE of 100 to 70. That is not cheap

We are constantly searching for new ideas and that process continues independent of the market condition. A bear market turns up more ideas for consideration, but we are not in a hurry. We have slept well and made reasonable returns inspite of holding high cash from time to time. We will continue in the same manner

Subscription

Enter your email address if you would like to be notified when a new post is posted:

I agree to be emailed to confirm my subscription to this list

Recent Posts

Select category to filter posts

Archives