Wheels of the bus went swimming one day

One story I like to tell is about how Mozart charged so much for setting Twinkle Twinkle to tune (if he did set it to tune, that is) that propagators of nursery rhymes decided to use the same tune for several other popular songs – most prominently for ABCDEFG and with a small variation for Ba Ba Black Sheep.

It’s confusing, not just for kids but also for the parents. I’d written here a month or so back about how I would play tunes on the keyboard and Berry would try to guess the song and sing along. As someone who sets quizzes occasionally, the lack of “a unique answer” drives me nuts. And it possibly drives Berry nuts as well, since she changes from twinkle twinkle to ABCD within the course of one stanza.

I wonder why this is the case. Using my one data point (Berry) kids can catch on to tunes pretty quickly (she was barely a year old when she started humming the tune of Black Sabbath’s Iron Man. Now she knows the full lyrics). And having unique tunes for songs means that kids are able to make easy associations between music and words – always a desirable thing.

And the lack of one-to-one correspondence doesn’t just run one way – sometimes there are multiple ways in which the same song can be sung. For some songs, such as Happy Birthday, this is due to copyright issues. I’m not sure why other songs are sung in different tunes.

For example, there are two clearly different ways in which the third line of itsy-bitsy/incy-wincy (depending on which side of the pond you’re on) spider is sung, and it gets especially confusing when I’m playing on the keyboard, since I don’t know which version Berry is expecting ( we invariably sing/play the “other” way).

The usage of voice controlled players has made things worse. In fact, the first time I appreciated Siri on my phone was when Berry was just born, and I needed both hands to hold her and put her to sleep, and then someone turn on a lullaby (“Hey Siri, play iron man by rockabye baby”). Now, the problem with voice-controlled playing is that when there are multiple versions of the same song you don’t know which one will get played.

An extreme case is like earlier today we asked Alexa to use Amazon Unlimited (we have a 3-month free trial, possibly because of my Prime membership) to play “london bridge”. It belted out some dhinchak EDM song! Within the realms of nursery rhymes itself there are songs that are sung to completely new tunes (like I had never expected that there exists a version of Jack and Jill sung to the tune of Yankee Doodle. It is most annoying). It is extremely disorienting for me – and I guess it is for kids as well, for I’m told they like predictability.

I don’t know what can be done to restore the sanity of one-song-one-tune.  Yes, I can record a set of songs in unique and popular tunes, but there is no guarantee that it will take off. And with the increase of voice controlled music playing, there is no guarantee that the “bad tunes” won’t get any air time.

The title, for those that didn’t get it, is a portmanteau of two songs that share a name. I must mention I have no intention of popularising these two precise renditions of these songs – they were simply on top of the search engine results.

Mommy duck said quack quack quack, all day long!

PS: There are differing versions in lyrics as well. One version says “all day long”; another says “all the way to town”. As Aditya Narayan sang in Rangeela Re 23 years ago, it’s complicated being a kid.

Programming Languages

I take this opportunity to apologise for my prior belief that all that matters is thinking algorithmically, and language in which the ideas are expressed doesn’t matter.

About a decade ago, I used to make fun of information technology company that hired developers based on the language they coded in. My contention was that writing code is a skill that you either have or you don’t, and what a potential employer needs to look for is the ability to think algorithmically, and then render ideas in code. 

While I’ve never worked as a software engineer I find myself writing more and more code over the years as a part of doing data analysis. The primary tool I use is R, where coding doesn’t really feel like coding, since it is a rather high level language. However, I’m occasionally asked to show code in Python, since some clients are more proficient in that, and the one thing that has done is to teach me the value of domain knowledge of a programming language. 

I take this opportunity to apologise for my prior belief that all that matters is thinking algorithmically, and language in which the ideas are expressed doesn’t matter. 

This is because the language you usually program in subtly nudges you towards thinking in a particular way. Having mostly used R over the last decade, I think in terms of tables and data frames, and after having learnt tidyverse earlier this year, my way of thinking algorithmically has become in a weird way “object oriented” (no, this has nothing to do with classes). I take an “object” (a data frame) and then manipulate it in various ways, changing it, summarising stuff, calculating things on the fly and aggregating, until the point where the result comes out in an elegant manner. 

And while Pandas allows chaining (in fact, it is from Pandas that I suspect the tidyverse guys got the idea for the “%>%” chaining operator), it is by no means as complete in its treatment of chaining as R, and that that makes things tricky. 

Moreover, being proficient in R makes you think in terms of vectorised operations, and when you see that python doesn’t necessarily offer that, and and operations that were once simple in R are now rather complicated in Python, using list comprehension and what not. 

Putting it another way, thinking algorithmically in the framework offered by one programming language makes it rather stressful to express these thoughts in another language where the way of algorithmic thinking is rather different. 

For example, I’ve never got the point of the index in pandas dataframes, and I only find myself “resetting” it constantly so that my way of addressing isn’t mangled. Compared to the intuitive syntax in R, which is first and foremost a data analysis tool, and where the data frame is “native”, the programming language approach of python with its locs and ilocs is again irritating. 

I can go on… 

And I’m guessing this feeling is mutual – someone used to doing things the python way would find R’s syntax and way of doing things rather irritating. R’s machine learning toolkit for example is nowhere as easy as scikit learn is in python (this doesn’t affect me since I seldom need to use machine learning. For example, I use regression less than 5% of the time in my work). 

The next time I see a job opening for a “java developer” I will not laugh like I used to ten years ago. I know that this posting is looking for a developer who can not only think algorithmically, but also algorithmically in the way that is most convenient to express in Java. And unlearning one way of algorithmic thinking and learning another isn’t particularly easy. 

The Crane-Mongoose Theory of Public Policy

I have several favourite stories from the Panchatantra (which perhaps explains my lack of appreciation of modern children’s fiction). One of them involves a crane and a mongoose. And I think it is a good lesson on when and where to call for regulation, and government or legal intervention.

So the story goes like this. A snake lives at the bottom of the tree where a crane has built its nest. Each time the crane lays eggs, the snake slithers up the tree and devours them. And the crane doesn’t know what to do. Ultimately it receives some “brilliant advice”.

There is a mongoose living somewhere nearby, and the crane lays out a Hansel-and-Gretel like path of fish from the mongoose’s house to the snake’s house. The mongoose duly follows the trail of fish and finishes off the snake. The next day, the mongoose is hungry again, and it climbs up the tree and devours the crane’s eggs.

It is common political discourse nowadays to call for the government’s or court’s intervention to solve what seems to be private problems. The governments and courts are of course happy to oblige – any new source for intervention and rent-seeking are good news for the people involved. And then you get a solution that temporarily solves the problem (slaughtering the snake). And then in the long term, what you get is a bigger problem (mongoose eating the crane’s eggs). The only difference is that in real life it is not just the crane that gets negatively affected – the regulations hurt everyone.

The examples that come to my mind at this point in time are all “local”. Some residents in Indiranagar in Bangalore weren’t happy about the noise from nearby pubs. They asked the government to “do something”. And the government “did something” – it banned the playing of live music in restaurants, killing off what was then a budding industry in Bangalore.

Some other residents somewhere else in Bangalore were unhappy that their neighbours had dogs that barked. They asked the government to do something. The government did something – coming up with an elaborate document to regulate dogs that people can own.

And there are more involved (and dangerous) examples of this as well.

Don’t be like the crane.

Investing in ETFs

So I put some money in an ETF today. This isn’t the first time I invested in one. A long time back, before my then employer had bought and essentially killed Benchmark, I had invested in a couple of their ETFs – the Nifty ETF to get invest in the broad Indian market, and GoldBees to hedge against increase in the price of gold as I was planning my wedding.

I had some Rupees lying around in my bank account for a long time, and given that the Indian markets have tanked, I thought this is a good time to get invested. In fact, this isn’t the first time in recent times I’m having such a thought – about a month back I had put in more money into the Indian markets, but had then chosen a low cost index tracking mutual fund (and I’m not tracking how my investment is doing).

Anyway, today I decided to invest in ETFs since the transaction costs (in terms of both trading, and annual expenses) are much lower. A quick chat with a friend currently trading the Indian markets revealed that the SBI Nifty ETF is the best option to go with, and I was left with the small matter of just making the investment.

I’m generally happy with ICICI Direct as my broker, since in general the interface and app are pretty nice. Last month, the purchase of the mutual fund through the same app had been pretty simple. And I imagined buying the ETF will be easy as well. It wasn’t. And if I, as a professional investor with considerable capital markets experience, find it hard to invest in ETFs, I can only imagine how hard it might be for mango people to invest in them.

So the points of pain, in order, that prevent people from investing in ETFs:

  1. Knowing that indexing exists. Most people seem to think that the only ways to invest are by researching the stocks themselves, or by paying an asset manager fairly hefty fees.
  2. Once you know you can index, the fact that you can do it through an ETF. ETFs are again not well known, and not really marketed broadly since their fees are low (with Benchmark’s demise, we don’t really have ETF-first fund houses in India, like we have Vanguard in the US).
    1. Related, even some of the more popular robo advisory funds in India largely use mutual funds, rather than ETFs.
  3. Once you know you can index, and do so through an ETF, the next task is to find out which ETF you should invest in. Literature exists, but is not easy to find. My friend sent me this page, and asked me to select the fund with highest market size. Knowing that I want to invest in the broad market, and in large caps, the choice of SBI Nifty ETF was easy for me.
    1. But it’s not so intuitive for a less sophisticated investor. For example, correlating asset size with liquidity isn’t exactly intuitive.
    2. Different ETFs track different indices, and knowing which one to invest in is again not a trivial task.
  4. Having selected an ETF to invest in, you go to your broker’s site or app (I used the app). And you need to know that ETFs are clubbed with equities, and not with mutual funds (not an intuitive classification for most people)
  5. So I go to ICICI Direct’s Equities page, allocate funds to it (from my bank account, also with ICICI), and hit “buy”. There’s a text box where I need to enter what I’m looking for, and then there’s a dropdown that pops up.

    I type “SBI”, and the first thing it shows is the SBI Bank Nifty tracker. This is followed by lots of bonds. I don’t know if it’s clever nudging on ICICI’s part to get you to invest in the Bank Nifty, since that has a significant exposure to ICICI, or if it’s something as mundane as alphabetical sorting. The latter is more likely.

  6. Scrolling down the list past all the bonds, it’s not easy to know which is the SBI Nifty ETF. Because there’s a “SBI Nifty Next 50 ETF” (smaller caps, so more volatile, not something I want), and a few others with confusing names.
  7. Then you need to enter the number of units you need to purchase. This is unlike in mutual funds where you just enter the amount you want to invest. Here I had to pull up a calculator to know exactly how many units I had to buy.
  8. I hit “market order”, and then on the next screen I got a warning that since this wasn’t a particularly liquid instrument I was only allowed to post limit orders. So I had to guess what was a reasonable spread I was willing to pay, and put that. Thankfully the ETF was fairly liquid, and I got execution close to mid.

Honestly, I felt rather daunted at the end of the exercise, and I’m what most people would classify as a sophisticated investor. So there is no wonder that more people aren’t investing in ETFs.

The advantage of ETFs is extremely low fees (the fund I purchased today charges 7 basis points a year), and one downside of it is that it doesn’t allow for more marketing budget.

I’m beginning to think that the way to “solve” this market is by having a bundled ETF and robo advisory offering. Perhaps more on that later.

 

 

Acceptable forms of help

I was reading this note by Kunal Bahl, CEO and co-founder of Snapdeal on the company’s turnaround after the failed acquisition by Flipkart last year. It’s a very interesting note – while I’ve never been a fan of the company (never considered buying from them), this story seems rather interesting, especially given the deep shit it was in a year ago.

What caught my eye is this little note about getting help from a small network of mentors. Bahl writes:

I was able to get the guidance and counsel from some of the most respected and leading business persons in the country. […] In our time of need, it was those who had the least to gain, and most to give, that came to our help. Not with money. But with their wisdom and encouragement. I recall sitting in the room with one of the above persons in August 2017, staring down the barrel with only months of money left in the bank. The gentleman, probably seeing how dire our situation was, picked up the phone and called six of the top business people in the country in quick succession explaining our situation to them – that we were good guys stuck in a bad situation – and requesting them to meet me to see if there were any synergies with their businesses[…]

(emphasis added)

What this got me thinking was about why it’s considered okay to give or take help in the form of intangibles, but not in terms of money. It’s rather common that people help each other out by way of providing advice, making introductions and sometimes just hearing them out. It’s not that common, though, that people help each other out with money.

To take a personal example, if someone asks to talk to me to get some advice, or asks for some connections, it’s very likely that I’ll help them out. On the other hand, if someone were to ask me for money I’ll start seeing them suspiciously.

One quick reason as to why intangibles is okay is that it is sometimes “cheap”. Making introductions doesn’t cost you much as long as you think it’s mutually beneficial for both parties (and in that, it seriously helps if you do double consent introductions – talk to both parties independently before introducing). Advice costs you maybe half an hour or an hour of your time, and if you feel like your time is being wasted, it’s not hard to cut losses. And the value that the recipient gets from this can far exceed the cost incurred by the “giver”.

Another reason is that intangibles are intangible – they’re hard to measure. And by that measure, you don’t rack up some sort of debt. If I take money from you, then what I owe you becomes precisely measurable. And until I repay you, things between us can be awkward. Introductions or advice, on the other hand, keep the value of the “debt” fuzzy, and in most case it gets “written off” any way, permitting the two parties to continue their relationship normally.

Anything else that I might have missed out?

Teacher abuse

Historically, it has been acceptable, indeed desirable, for the teacher to abuse students. Our epics are full of stories where the teacher plays elusive, challenging students to “prove themselves worthy” before being imparted learnings.

The most famous example, of course, comes from the Hindu myth story of Ekalavya who gave a finger to his non-teaching Guru Dronacharya. Elsewhere in the Mahabharata, we had Parashurama cursing his student Karna after discovering that the latter was not a Brahmin.

It is not just Hindu mythology that has such stories (just that I’m most familiar with this). In Quentin Tarantino’s Kill Bill, for example, Pai Mei abuses his pupils, making them carry water up the hill and serve him otherwise until he teaches them the five point exploding heart technique. He drives his students to such a rage that one of them (Elle Driver) ends up killing him.

And this privileged attitude of the teacher (“acharya devo bhava“) extends to modern universities as well. It is common for advisors to endlessly push graduate students before they permit them to graduate, or to take credit for graduate students’ work (check out PhD comics.). In IIT Madras, where I did my undergrad, it is reportedly common for professors to endlessly flunk students who have pissed them off (I played it safe, so no first hand experience in this). Schoolteachers hand out corporal punishment, which is only recently making its exit from the classroom.

As part of my portfolio life over the last seven years, I’ve done several teaching jobs. I’ve taught at IIM Bangalore as an Adjunct Professor. I’ve conducted Data Journalism workshops for journalists and PR executives. I’ve done corporate training workshops.

In the initial days, I would sometimes act like a “typical teacher”, getting annoyed with students with this or that, or abusing my position of privilege in the classroom. Over time, though, I’ve come to see my students as clients – after all, they’re paying me (directly or indirectly) to teach them. And I’ve come to understand that they need to be treated like I treat my other clients – with respect.

If the fact that students are teachers’ clients is this intuitive, why is it that teachers everywhere (both in history and contemporarily) have found it acceptable to abuse students? Is it because teachers are sometimes able to hide behind the brands of sought-after schools and universities? Is it due to the concept of tenure, where professors are recruited for research prowess, and student feedback doesn’t really matter?

Or is it just a self-fulfilling prophecy? Once upon a time, teachers were scarce, and could hence put up their price, and chose to extract it not in cash but in other means. And so the image of “teacher is god” got formed, and perpetuated since most students decided to adhere to it (at least when the teacher is around). To add to this, over time we’ve created institutions such as university rankings which continue to push up artificial scarcity of teachers.

Do you have any idea on why teachers abuse their clients?

Speaking of yellow

Last night, we needed to distract the daughter from the play-doh she was playing with so that she could have dinner. So I set up a diversionary tactic by feeding her M&Ms while her mother hurriedly put away the play-doh.

Soon we figured we needed a diversionary tactic from the diversionary tactic, for the daughter wanted to continuously eat M&Ms rather than have dinner. I tried being the “bad dad” by just refusing to give her any more M&Ms but that didn’t work. So another diversion was set up where the put on TV, and in that little moment of distraction, I put away the yellow packet of M&Ms behind some boxes in its shelf.

Evidently, it wasn’t enough of a distraction, as the daughter quickly remembered the M&Ms and started asking for it. I told her it’s “gone” (a word she uses to describe my aunt who passed away recently), but she wouldn’t believe it. Soon she demanded to inspect the shelf by herself.

Her mother held her high, and she surveyed all three shelves in the cupboard. I hadn’t done a particularly great job of hiding the M&M packet, but thankfully she didn’t spot the yellow top of the packet from behind the masala box.

Instead, her eyes went up to the top shelf of the same cupboard where there was the only visible yellow thing – a bright yellow packet of coffee powder (from Electric Coffee). She demanded to inspect it.

Both of us told her it was coffee powder, but she simply wouldn’t listen. I opened the packet to make her smell it, and see the brown powder inside (we get our coffee ground at the shop since we don’t have a grinder at home, else it’s likely she might have mistaken a bean for a brown M&M). She still wasn’t convinced.

She put her hand right in and pulled out a tiny fistful of coffee powder, which she proceeded to ingest. Soon enough, she was making funny faces, though to her credit she ate all the coffee. It seems the high was enough to make her forget the M&Ms. And suddenly she started running around well-at-a-faster-rate. Fast enough to go bang her head to the wall a minute later – I suspect the caffeine had begun to act.

By the time she had finished crying and recovering from the head-bang, she was ready to belt curd-rice with lime pickle.

And if you want to ask, she fell asleep an hour later. Unlike us oldies, caffeine doesn’t seem to interfere with her sleep!

PS: The title of this post is a dedication to Sanjeev Naik, for reasons that cannot be described here.