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DDIntel - Market Relocation in Progress

DDIntel - Market Relocation in Progress
By DataDrivenInvestor • Issue #40 • View online

On January 4th, 2022, the S&P 500 peaked just over 4800. Back then, the VIX sat under 18. Bitcoin was trading above $45k, while crude oil was trading at ~$80/barrel. 1 US Dollar ($) was worth 115 Japanese Yen (¥). The 10 year US Treasury traded around 1.6%.
As of Wednesday, June 22nd, 2022, the S&P 500 closed more than 1000 points lower than the year’s peak at 3755, marking a decline from peak of ~22%. Vix closed at 29 (+60%), BTC traded at $20k (-55%), crude 107 (+33%), and Yen (¥) 136/$ (-15%). The 10 year US Treasury is now at 3.2%, a whopping increase of 100% YTD!
Crypto markets are experiencing a liquidity crisis, the likes of which it has truly never experienced before. From the de-pegging of Terra Luna to Celsius’s blocking of withdrawals, from Microstrategy’s potential margin call to Three Arrows Capital’s call for a bailout, crypto is experiencing its “2008” moment.
Inflation is still running hot in Europe (8.1%) and Japan (2.5%), the UK (9.1%) and the US (8.6%). It seems no asset class, not even energy, is safe from potential stagflation and geopolitical risks. But with over 80% of investors bearish on the stock market, perhaps the contrarian call is that recession risks are overblown and the Fed actually will execute a soft landing.
Nevertheless, the 2 year 10 year yield curve inverted a couple of months ago and again last week, a worrisome recession indicator (with a lag of 9–24 months) that suggests the Fed may be “ahead” of the curve (for once). As the central bank raises interest rates and attempts to offload its $10 trillion balance sheet, many investors are asking, who’s buying?
This unprecedented round of quantitative tightening may prove to push the world economy into recession territory, but what is certain is that this is one of the most massive market relocations in human history, not only in aggregate nominal value (>$10 trillion lost YTD), but in relative terms as well.
As such, we thought now would be the time to pause and reflect on DDI’s past, present, future and core mission. DataDrivenInvestor started in 2018 with the goal of helping investors be data driven. This may seem counterintuitive; after all, aren’t all investors data driven? Actually, at DDI, we believe most investors are dogma driven, not data driven.
Most investors, especially fund managers, follow a few popular mantras they were taught in their graduate level economics courses (markets are efficient, passive investing is the only way, etc.) and collect their fees. Assuming market efficiency, most financial market thinkers ignore how information gets into prices. Using strong assumptions to arrive at elegant formula, which do nothing other than impressing investors, lazy intellectuals, or whoever that doesn’t see through magic. No wonder the well respected Benoit Mandelbrot, in his famous book The MisBehavior of Markets, ridiculed our whole understanding of financial markets as merely a huge castle “built on sand”.
Building on sand is fine, at most our knowledge institution just collapses without hurting anyone. But Noop! As ignorance gets piled up that also affects how massive capital flows through markets. The collective market behavior built on dogmatic beliefs and faulty assumptions cause prices to be perpetually distorted in the face of changing information. The academics didn’t do the job of getting to the root of the matter. It is a topic that deserves special attention.
Being data-driven doesn’t just mean statistics and no theory. In fact, the Latin origin of the word data means “thing given”. In keeping with Greek tradition, at DDI, we believe in empiricism, or the philosophical position that suggests discovering “contingent” facts is supreme. As opposed to rationalism where reason is the source of knowledge, empiricism believes that experience is the source of knowledge.
This is not to say that theory is not important; in fact, it is equally important. At DDI, we believe investors should be scientists, and our data driven “tools” will make them so.
To date, DataDrivenInvestor has been operating globally as a network of like-minded people, starting from its origin in Singapore, its development team in India and Russia, contacts in Hong Kong and Taiwan, and a global community of hundreds of writers and tens of thousands of readers. Today we are excited to announce that DDI has opened its new US office in Buffalo, New York.
We are in the process of raising funds to develop a suite of data-driven applications for investors and entrepreneurs.
Our long term vision at DDI is to efficientize financial markets with data, knowledge, and domain expertise. It is the gap between information-based and equilibrium-based perspectives of financial markets. Whether that’s through
  • topic discovery through content;
  • signal creation and subscription service;
  • marketplace for expertise;
DDI will be a place that inspires a new generation of decision makers (which include investors).
This week’s Intel graphic, designed by the talented Ritik Jain, portrays the classic evolution graph - from monkey to man, but with a twist: evolution does not always mean upward!
Here, we humans have evolved to drive cars and access incredible technology, but we are ultimately still just cavepeople, following the crowd, mindlessly driving a car whose steering wheel doesn’t work, and without a roof.
Coincidentally, the mountain peaks in the background form the recent market’s movements, headed downhill, but with clouds in sight blocking our view.
Who really knows where the market is going?
This week’s DDIntel highlights 8 top DDI articles, covering topics ranging from bubbles, global investing, crypto, coding, to why Information Overload is a Choice. Be sure to subscribeforward this to others who might like it, and check out our previous issues. You may also want to learn about how to work with DDI here.
Information Overload is a Choice | by Marcus Glowasz | Medium | DataDrivenInvestor
Futurist Marcus Glowasz argues convincingly that information overload is a choice. Often economists assume that information is free and readily available, when in reality we know that information is costly. This leads some to conclude that too much information results in overload; however, Glowasz contends this is our choice.
History and Modernity of Algorithmic Trading | DataDrivenInvestor
Algorithmic trading often gets a bad rep, especially due to the 2011 Flash Crash, but the industry is expected to grow from $12 billion in 2020 to $31 billion by 2030, so it’s important to understand the history and modern approaches to algo-trading. Check out finance and technology writer Anastasia Shcherbina’s article for a refreshingly simple intro to the space.
Real-World Data Science Use Cases in the Insurance Industry | by Kenneth Leung | Jun, 2022 | DataDrivenInvestor
For an excellent deep dive into data science uses cases in the insurance industry, we had to highlight data scientist Kenneth Leung’s recent article. Leung begins by describing the insurance value chain, covering everything from behavioral economics in product development to fraud detection and claims management. By the end, you’ll feel like you are an expert both in data science and insurance economics!
Cryptocurrency Regulation Is Unavoidable & Not Necessarily a Bad Thing for Investors | by Stephen Dalton | Jun, 2022 | DataDrivenInvestor
While crypto originally attracted many due to its unregulated nature, its growing up as an industry, and as such it is fair to ask if it is time for regulation. Many insiders don’t fear regulation; in fact, they embrace it!
Stephen Dalton is a retired US Army First Sergeant with a degree in journalism from the University of Maryland. Be sure to read his excellent overview of the problems facing the industry, and how, ironically, the government may be the answer.
Recommendation Engines: Making Better Choices | DataDrivenInvestor
Recommendation engines may seem like a rather boring application of machine learning, yet they have actually driven a lot of technical innovation on the underlying algorithms. Recommendation engines not only face statistical bias problems, but can also be manipulated. Importantly, they can help with decision making across the board.
How to Use Python to Build Your Own Value Investing Stock Screener in 10 Minutes | DataDrivenInvestor
Stock screeners are used for filtering out top stocks of interest for investors. Different investors will look for different things. Value investors, for example, are looking for strong companies that are currently undervalued by the market. Here, Australian investor Jason Huynh breaks down how to create a stock screener using Python Pandas, a powerful framework for handling data frames.
Here is What Investors Need to Know about Equity Index Investing and Country Selections | by Marianne O | Jun, 2022 | DataDrivenInvestor
This isn’t just an article on passive versus active investor. It’s also not just about macro and market structure, or emerging markets, policy, and debt. Investment manager and fintech founder, Marianne O. covers all that and more!
Jeremy Grantham Is Warning Of A “Super Bubble” In US Markets | by Thomas Herold | Jun, 2022 | DataDrivenInvestor
Famed investor Jeremy Grantham has successfully predicted 3 major bubbles and is claiming that we are possibly in a “super bubble”. This has a precise technical definition. If we are in a super bubble, it’s possible assets have 50% more to fall. But bear in mind that even if we are in a super bubble, the market can stay irrational a lot longer than you can stay solvent.
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