A guide to navigating quarterly noise-flow
It's hard to read a long form essay amidst frenzy of quarterly earnings season. Then again, that frenzy is why this essay on separating signal-from-noise in quarterly results is required.
(If you prefer to read 3000-word essays on paper, here is a printable pdf version of the same)
The most reliable path to adequate returns over the long run involves (1) buying into good businesses at prudent valuations and (2) holding onto the same for long. Doing this is analytically simple but psychologically difficult. First part of doing the sensible is hard but doable. Second part of doing nothing thereafter is way harder, possibly undoable.
Our propensity to overreact to bad news lies at the heart of premature evacuation out of fine businesses. Our overreaction is in turn driven by nature of stock-markets, particularly short-termism and high noise-to-signal ratio. This is best reflected in our silly rituals around the routine event of companies releasing quarterly financials. We have created an entire charade around it – guidance & estimates, earnings previews, big miss or big beat, anal scrutiny of mundane line items & innocuous comments, revised guidance & estimates, upgrades & downgrades, upper & lower circuits. Earth completing a quarter revolution around Sun has gone from seasonal to sensational. We overanalyse and overreact to normal fluctuations around a generally upward trend, making many of us sell good businesses caught up in the frenzy around transient weakness.
Over the past seventeen years, Nalanda has held over twenty businesses for longer than a decade. With hindsight, inaction after purchasing these businesses has done us way more good than any conceivable action. Not one of these businesses had a smooth ride over the decade. Most businesses went through at least one horrible phase, accompanied by panicky market reactions. So, what allowed us to stay put, despite being unsure, feeling scared and looking stupid?
That’s what this lengthy essay is about – developing a detached attitude to quarterly noise-flow, without losing sight of any meaningful signal embedded within the same.
Decadal business history is our guide, not recent analyst estimates.
Let’s start with a picture or two. I took quarterly Profit After Tax (PAT) of one of our businesses, for the decade over which we owned it. It’s a representative business, in an industry perceived as neither particularly cyclical nor acylical (separately, all businesses are cyclical). I then plotted the same data two ways, showing: (1) year-on-year growth in PAT and (2) absolute number for PAT (with starting quarter PAT indexed as 100). I used 11 years of data, 44 data points, so that I can show a decade of growth rates.
The first picture is how analysts and commentators saw it as it happened.
Looking at this, you can build a case for extreme euphoria or extreme panic, almost every single year. If you’re the kind who also plots quarter-on-quarter growth (a medical condition named ITAnalystitis), you can even experience euphoria and panic simultaneously. Had I obsessed over this metric, I would have lost both the business and my hair.
The second picture is how I looked back on the business after owning it for a decade.
If a genie assured me that profits would grow 6x in a decade and stock price would fare even better, I would hold onto that business like how Washington Post holds on to its prejudices. Luckily for us, despite lacking hindsight genie and living through a rollercoaster ride, we didn’t let go of this business over that decade. I still lost hair though.
I encourage you to repeat the above exercise with any decent business that you have owned or tracked for over a decade. And ask yourself the question: “How do I not lose sight of the second picture over ten years, while living through the first picture every three months?”.
Answer starts with making such pictures, so as to internalise inherent lumpiness of long-run trajectories of good businesses. And then incorporate the same into short-run expectations. Use business history, rather than strangers’ estimates, as our guide to analysis of quarterly financials. Realize that that even the act of producing precise quarterly estimates is as arrogant as it is futile. Over the long run, good business invariably do fine, while following a path that is assuredly and extremely volatile. To borrow Pulak’s quote, “Nothing goes up in a straight line”.
If you appreciate this, you can stop reading now. Rest of the essay merely elaborates on how we incorporate this timeless truth into our process.
View each quarter as one more datapoint in a continuing trajectory, not in isolation.
Look at the first picture again. You might ask me what happened in Q3 of FY10?. Or Q1 of FY13? Or Q1 of FY18? Answer is, I don’t remember. If you push me, I might make up some plausible explanation to seem smarter that I am. But the truth is, I neither know nor care. Given that these were extreme quarters, they must have been a big deal back then. Yet today, they are forgotten blips on a satisfactory decadal trajectory.
As you pore over quarterly results over the next few weeks, remember that some years from now, Q3 of FY24 will almost surely be a blip. Whatever narrative seems all-consuming now will be neither relevant nor remembered. I am not suggesting ignoring any quarter. I am suggesting placing it into proper perspective. Each new quarter is additional datapoint in a long series, to be seen in the context of the entire series, its long-run trajectory and inevitable fluctuations around the same. Don’t let recency bias and market chatter make most recent quarter seem larger than life.
Since all trajectories are bumpy, keep wide bands.
Awareness of long-run trajectory makes a compelling case for banning ‘basis points’ as unit of financial analysis. Plus or minus 25% swings in typically tracked metrics (revenue growth, EBITDA margin %) are a feature not a bug. For a company with 15% long-run average margin, a 12% or 18% quarter is normal, not exceptional. Ditto for revenue growth or working capital intensity. Explanations for deviations sound plausible but are actually made-up, usually to fob off pesky questioners on conference calls.
Approach financial results with wide error bands around a general long-term trend. Swings within this band generally merit a shrug of the shoulders, not activation of neurons.
Focus on controllables: relative over absolute performance, balance sheet over P&L.
Companies have little control over the metrics we obsess over – revenue and profit growth – at least over the short run. These are determined by industry growth, stage of business cycle, commodity inflation, exchange rates and base-period. Often, these effects are extreme.
What companies actually control is how they do relative to their industry context. And whether they respond to that context prudently and competently. These are better reflected in relative performance (e.g. market share, by segment) and balance sheet metrics. Strengthening competitive position by outdoing peers matters more to long-term investors than absolute growth. Likewise, responding to an adverse environment without compromising on working capital discipline is a measure of business health and management quality.
Over the short-run, overrated P&L metrics can be more noise than signal. Underrated metrics pertaining to balance sheet and relative performance are a better measure of how the business is actually faring.
Factor in context, leads & lags. Be reasonable and pragmatic.
Good businesses take graded price increases, spread out over time, even amidst high inflation. Any other path messes up channel relationships and health. Businesses also avoid price cuts as this complicates inventory already held by channel. No point overreacting at both ends to ultra-high inflation that is usually transient. Then, there are second-order effects of channel stocking and destocking in anticipation of price changes. A part of cost-base being fixed in nature also exaggerates profit swings. Underlying all of these is the industry’s settled competitive equilibrium and company’s pricing power, which ensure that reasonable economics are sustained across a cycle.
Most analysts are aware of this business reality. And that it leads to margins being volatile in short-run, yet stable in long-run. Extent of swing and timing for mean reversion are unknowable. They are also immaterial to what the business is worth since it will all average out in long-term cashflows. Our industry’s problem is that we lose sight of this realistic picture in our unrealistic attempt to predict the exact path that margin fluctuations will follow.
Best approach to quarterly analysis is to incorporate context, assess what directional impact it could have and just accept resulting swings. We are better off being business analysts than mere financial analysts.
Don’t over analyse micro line items, stick to a few broad metrics that matter.
Business is hard to do, but not that hard to analyse. In the denominator, there’s fixed assets and working capital. In the numerator, there’s revenue and cost (except for unicorns, which also have ‘adjusted’ versions of everything). All XL jugglery is basic arithmetic performed on four metrics. Since we are group that has cleared entrance exams only to do my 9-year old’s maths, there is a lot of cognitive dissonance. So, we feel compelled to get anal details of gross margins, contribution profit, GOV, order book, volume-vs-value etc and somehow infer meaning in them. Much of this is also dubious. It’s unclear how to interpret gross margin in a business whose make-vs-buy mix is constantly shifting. Or how volume growth is meaningful amidst significant mix changes across 1000s of SKUs.
If broader metrics are known to swing wildly, God help us on narrower metrics. We simply cannot separate signal from noise at a micro level. Our domain is about being roughly right, not precisely wrong. It is better to focus on a handful of important metrics, after developing a sound historical reference on these.
Trigger for worry is a pattern to bad news, not one bad quarter.
Clearly, any company can have a disastrous quarterly print simply because uncontrollable factors lined up adversely. It need not be a cause for worry as it is neither here nor there. We cannot draw a line of best fit with only one datapoint. So, when do we start worrying that quarterly bad news is reflective of deeper problems?
My threshold for worrying isn’t a bad quarter but a pattern to bad news. Persistently growing slower than competitors is a problem. So is systematic worsening of working capital. Both could be signs of a weakening franchise. Core business slipping up after getting distracted by M&A is a worrying pattern. Entering unrelated areas shortly after a generational transition is another. An added advantage of our focus on business history is that we get better at spotting ruinous patterns.
Keep an eye out for anomalous developments, outside of the numbers.
As the adage goes – not everything that counts can be counted. Real damage often shows up outside of quarterly numbers. Keep an eye out for announcements or actions that make us go “Hmm, that’s odd” or “I don’t like the sound of this”. These come in many forms: entry into unrelated area, big acquisition, series of small acquisitions, entry into a lower-quality business segment, pattern of senior resignations, employment generation for family members via vanity projects, consistent disconnect between what they say and what they do, management seeming in denial about business problems or making one excuse after another for the same. There isn’t a precise science to it, but studying history leaves us with some recurring themes to watch out for. One useful outcome of in-person meetings with management is to get a sense of how comfortable we are with management’s thinking on such matters. A fuzzy feeling of discomfort on one of the aforementioned issues is often a bigger red-flag than an earnings miss.
For a business with long history of good and short period of bad, our bias is to give benefit of doubt and time.
So, we have waited several quarters, established a pattern to bad news. We are sure that there is a material business problem. Now what? And remember that we only have two actionable choices: hold or sell. Everything else is just words. Do we hold and risk a bad outcome should problems persist? Do we sell and risk losing out on a good outcome should problems get fixed? That’s the universal trade-off at the heart of investing: capital loss vs opportunity loss.
This is a tricky one. Every situation is unique. Answer is case-specific and a subjective judgment call. I describe our experience with such situations, without prescribing what should be done in all circumstances.
Over the last seventeen years, we have seen severe problems at least once in a majority of our companies. A couple of businesses teetered on edge of bankruptcy. Few witnessed disruptive changes within promoter group. Some suffered a vicious downturn that lasted as long as a decade. Few saw a dramatic change in business profile, as a large business segment either stagnated or disappeared. M&A blew up in the face of many. Distraction from M&A led to core business slipping up. In every case, problem persisted for years, not quarters. As we lived through these, we were far from certain whether the problems were fixable.
So, what did we do in these situations? Mostly nothing. Out of roughly thirty businesses that I base the previous paragraph on, we continue to own roughly twenty five. After it was clear that there was a problem, our approach was simply to wait & watch. We did watch it more carefully than usual. We did our periodic due diligence (a fancy word for talking to industry people) more frequently than usual. We paid careful attention to what management said and did. However, all of these constitute activity, not action. In terms of hold vs sell, we simply held. And waited. And hoped.
How did we fare with this approach of giving benefit of doubt and time? Quite well. Nearly all of the companies overcame business problems and returned to prior glory. In 80% of the cases, we ended up with a good investment outcome. By ‘good’, I mean had we sold out prematurely, I would have been filled with soul-crushing regret. In the remaining 20%, none had a disastrous outcome. Even the cases with modest outcomes weren’t necessarily because of business problems. All things considered, that’s a pretty healthy RoI (Return on Inactivity).
Why did “do nothing” work so well? Because of innate resilience of good businesses. We perceive businesses based on where they end up, not how they got there. If we return to history, every business that we perceive as good today went through many prior challenging phases. They are good today because of a long history of overcoming bad. While a rough period may be new to us, it wasn’t new to these companies. Our giving benefit of doubt is simply a recognition of historical odds. Good businesses will, more likely than not, overcome problems. It is why they turned out good to begin with.
Sell only if convinced that damage to business quality is irredeemable.
We did exit in some cases. We did so, after giving enough time, when we were convinced that damage to business quality was irredeemable. Again, there are no universal standards for gauging when this is so. This is also one of those “I know it when I see it” things that cannot be dissected too much. Again, here is some description of our thinking in such cases, with no prescription.
We tend to give more time if damage is only in P&L. These are cases where company seems to be lagging its peers, but working capital hasn’t deteriorated and return on capital is still healthy. Maybe it is an execution slip-up, but not an erosion of franchise. If balance sheet, especially working capital, starts ballooning, we gave a much shorter rope. Ditto in cases involving acquisitions, especially if management shows no signs of slowing down on this ruinous pursuit. Or with egregious capital misallocation, such as entering a completely unrelated area. Our shortest rope is if bad governance comes to light.
As a long-term investor, we wish to form an updated perspective on businesses we own, without distortion from the frenzy that surrounds quarterly results. We wish to stay alert to important signals, without overreacting to transient noise. We wish to avoid our biggest sin – needlessly selling out of a good business. To achieve this, we incorporate the following tenets into our process for analysing quarterly performance:
1. Decadal business history is our guide, not recent analyst estimates.
2. View each quarter as one more datapoint in a continuing trajectory, not in isolation.
3. Since all trajectories are bumpy, keep wide bands.
4. Focus on controllables: relative over absolute performance, balance sheet over P&L.
5. Factor in context, leads & lags. Be reasonable and pragmatic.
6. Don’t over analyse micro line items, stick to a few broad metrics that matter.
7. Trigger for worry is a pattern to bad news, not one bad quarter.
8. Keep an eye out for anomalous developments, outside of the numbers.
9. For a business with long history of good and short period of bad, our bias is to give benefit of doubt and time.
10. Sell only if convinced that damage to business quality is irredeemable.
As always, what we do is a function of our specific context. In discussing the risk of prematurely selling out of a business on bad news, I made a few contextual assumptions. Like a tendency to only buy into decent businesses with long track record. Or a time horizon long enough to wait out problems. Or access to informational resources that a retail investor may not have. I also ignored the separate topic of selling on valuation for the purpose of keeping this essay focused. What I write is best viewed as one perspective, with some kernel of it applicable to your context.