US banking crisis, AI, Demonetization, data on Indian economy, CAMS report on millennials and more
#Issue 26
This is the latest issue of Markets and Macros by TradingQnA written by Abhinav.
TradingQnA is India’s most active stock market forum. It’s the go-to place if you are looking for answers relating to trading, investing, personal finance, or anything markets.
The US banking crisis
It seems that the Silicon Valley Bank collapse set off a chain reaction that resulted in the subsequent collapses of Signature Bank, Credit Suisse in April 2023 and First Republic last week.
What are the reasons behind this? We have previously covered the SVB collapse.
In this substack post, Professor Damodaran writes about the current crisis and more. He explains the banking model and how banking regulations came into being. If you are new to this, the first half of the piece is a must read. I haven't come across a simpler explanation of the banking system.
The way he concludes that stickiness of deposits is the major factor behind the recent crashes is very interesting.
You can also watch him talk about this topic:
Ambrose Evans Pritchard has an interesting take on the US banking crisis. He starts out by saying that we are in the beginning of a credit crunch as half of America’s banks are insolvent at the moment.
Talking about the First Republic Bank, he mentions how it collapsed due to a slump in commercial real estate. It is expected that commercial real estate prices will correct more (Morgan Stanley predicts a 40% correction) and the problem will hit other banks too, especially regional banks, which account for 70% of commercial real estate financing. You can read more on this here.
On SVB, he says
Its sin was to park excess deposits in what is supposed to be the safest financial asset in the world: US treasuries. It was encouraged to do so under the risk-weighting rules of the Basel regulators.
The US authorities say the bank should have hedged this Treasury debt with interest rate derivatives. But hedging merely transfers losses from one bank to another bank. The counterparty that underwrites the hedge contract takes the hit instead.
The root cause of this bond and banking crisis lies in the erratic behaviour and perverse incentives created by the Fed and the US Treasury over many years, culminating in the violent lurch from ultra-easy money to ultra-tight money now underway. They first created “interest rate risk” on a galactic scale: now they are detonating the delayed timebomb of their own creation.
He pins the blame on the Fed’s policies and excessive open market interventions in the last few years.
The horrible truth is that the world’s superpower central bank has made such a mess of affairs that it has to pick between two poisons: either it capitulates on inflation; or it lets a banking crisis reach systemic proportions. It has chosen a banking crisis.
Getting ready for a world with AI
I recently came across this piece titled: Will A.I. Become the New McKinsey? It is very well written and explores how AI could change the world, both for the better and for the worse, and how we might need a fresh look at AI.
The writer criticises capitalism not on its first principles but how capitalism is practised today in that it pushes for inequality and concentration of wealth. He says that AI also poses the same risks.
If we cannot come up with ways for AI to reduce the concentration of wealth, then I’d say it’s hard to argue that AI is a neutral technology, let alone a beneficial one.
How will AI change the world? Do we need to regulate it? Are the risks too high?
That’s a question we can just speculate on given how fast things are evolving in this space. One approach to dealing with AI is letting AI run its course. This idea comes from the concept of accelerationism in political philosophy.
Accelerationism says that it’s futile to try to oppose or reform capitalism; instead, we have to exacerbate capitalism’s worst tendencies until the entire system breaks down. The only way to move beyond capitalism is to stomp on the gas pedal of neoliberalism until the engine explodes.
But are we ready to take this risk? Has it really worked in the past? Well not really.
Looking at the industrial revolution or the internet I am not too sure about this. True that they have changed the world and increased our per capita GDP, but at the same time housing, education and healthcare have become terribly expensive making one question if the quality of life has gone up for all of us? If you are on the right side and have accumulated some wealth, then your quality of life has increased for sure, but what about the rest? This is precisely what's scary about AI. More concentration of wealth and increase in quality of life for a few at the expense of others.
This brings us to the other approach, an approach guided by a sense of economic justice. Technology can enhance the quality of life only when accompanied by economic measures that ensure fair distribution of its benefits.
The conversations and debates around AI are picking up pace and governments have also started looking at it.
The white house has told Big Tech that they need to protect the public from AI risks. Kamala Harris cautioned the chief executives of major companies, including Google, Microsoft, Anthropic, and OpenAI, that the government might consider regulating the industry due to the emergence of generative AI.
The European Union has proposed new AI regulations pertaining to copyrights, and the UK’s competition watchdog is evaluating whether to intervene.
Will AI mean we will have to work less?
Many have predicted that AI could liberate us from doing mundane tasks and free up time leading to us working less and fulfilling other endeavours in life. Will that really be the case?
This article explores this question.
Today, many fears around AI focus on its potential to replace human workers—whether teachers, lawyers, doctors, artists, or writers. In a 1930 essay, the economist John Maynard Keynes made similar predictions, coining the term “technological unemployment” to refer to “unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.” For Keynes, this was proof positive that “mankind is solving its economic problem.” He predicted that his grandchildren would work fifteen-hour weeks, liberated from economic necessity.
But the recent Global Innovation Index suggests otherwise, raising concerns that “considerable investments in technology, innovation, and entrepreneurship [are] failing to deliver the kind of productivity improvements that improve the lot of people across society.” Indeed, the history of “technological revolutions” paints a different story than the one Keynes anticipated about the benefits of technology-related productivity gains.
Implementation of new technologies, which lead to improved efficiency and productivity, usually fail to free up the already overloaded members of society. Rather, these advancements typically create new standards and expectations, resulting in an increased workload to meet these expectations. This phenomenon is known as Parkinson's law, which asserts that work will fill up the time allotted for its completion. So in a way not only does new tech often result in more work for people but it also introduces additional kinds of work
While we are on the topic of AI, I’ll leave you with this list of 10 AI companies to watch out for.
A look at demonetization
I came across this very interesting paper that analyses the medium term effects of 2016s demonetisation.
The findings in this study are contrary to the popular narrative around demonetisation and the way the researchers arrived at this conclusion is interesting. It also teaches you a little bit about parameters such as headcount ratio and nightlight data.
This paper states that both economically deprived regions and households witnessed notable advancements in their financial standing over a period of 18 months. An analysis of the monthly night-light data reveals that the poorest districts experienced an 11% higher increase in GDP per capita compared to the wealthiest districts.
In addition, an analysis of a survey of over 140,000 households, tracking their expenses and incomes over time, reveals that the poorest quintiles experienced a 35% increase in expenditures and an 18% increase in incomes relative to their previous financial status over the same eighteen-month period.
The researchers’ theory that an unintentional redistribution occurred can explain the observation that almost all of the money (99%) was recovered, suggesting that little overall wealth was lost. Furthermore, any adverse effects on GDP were mild and temporary, and the ruling party (BJP) did not suffer any political consequences. In fact, the party's popularity even increased.
Data can be interpreted to say India is doing well, is it?
This is a very interesting article which lays bare the push to interpret data in a way to make India look like it's doing way better than it actually is. For example every month an increase in GST collection data is hyped up to show that the economy is doing well, well the author demolishes this when he says
First, GST collections are always a certain percentage of price. If prices go up, GST collections go up. This is a no-brainer. Wholesale inflation was 13% in 2021-22 and 9.4% in 2022-23. So, once prices have gone up, GST collections continue to remain high in nominal terms.
Second, every year the population also grows 1-1.5% and that adds to the GST collections.
Third, in the last few years, there has been a crackdown over GST evasion, leading to higher GST collections. Kudos to the government for this. But this doesn’t mean higher economic activity. It just means that economic activity that wasn’t being taxed earlier is now being taxed. And this reality will gradually start showing up in GST data.
Fourth, there has been an increase in the consumption of higher-priced goods and services post the pandemic, leading to higher collections.
Similarly, he also talks about data regarding air travel, monthly UPI transactions and domestic passenger vehicle sales.
We had talked about the need for clean data and for insightful interpretation of it in our previous newsletter as well when we discussed the debate around poverty which was shrouded in controversy due to the data used for it.
CAMS report on millennials
CAMS recently shared a report on new millennial investors titled “The emerging force of millennial investors is here to stay & grow”. Meher Smaran has gone through it and shared the highlights from this report on TradingQ&A.
How to win at cards and at life
Daniel Cates is one of the most successful poker players in the world. This article merges insights from his life and his game to give you a perspective on winning at cards and life. It's a nice light read for anyone interested in poker.
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