Market Commentary

The recent shutdown has brought light to the disparity between markets and economics, and also served to widen the relationship. 

In high school, most of us were taught basic supply and demand. Some probably took a macroeconomics course, fewer got an MBA, and I know some of you reading this are actual economists or traders. 

Yet, most people (even some economists) misunderstand what drives financial markets. 

In theory, share price is supposed to be the net present value of the future earnings stream.  This is a "weighing" mechanism that also balances positives and negatives, short-term and long-term issues, industry cycles, fundamental data, and a host of other issues.

The markets represented the collective fear and greed of a population.  A trader doesn't need to guess what someone specific is going to do … their calculus is more about the law of large numbers.  How will most people respond to a sudden move up or a sudden move down?  Will they see it as a danger or an opportunity?

In a sense, markets operate like an actuary for an insurance company.  Actuaries don't need to know when you will die, specifically, but rather if they insure 10,000 people like you, how many are likely to die this year (and what premium can they charge to cover the death benefits to be paid, the cost of operations, plus their intended profit margin.

In the basics of economics, markets and their consumers play a sort of tug-of-war until an equilibrium is set. Price represents the amount of money a consumer is willing to pay for this good (or a comparable good) and the amount of money a seller is willing to sell it for taking into account overhead, manufacturing, time-value, etc. 

It's not necessarily the maximum cost a consumer would pay and minimum a seller would sell, but for the sake of this discussion, that nuance isn't overly important. 

The markets were an important price discovery tool using "open outcry" as a way to see at what price others were willing to buy or sell.

As markets got faster and transactions stopped being generated solely by people trading with people, the pricing mechanism changed.  I think of it as a fair value range surrounded by a fair speculation buffer.  As markets get faster, noisier, and more volatile, the fair speculation range expands.  That means pricing is more dynamic and edges decay faster than ever.

This also means that less of the price is based on simple things, like whether the economy is improving or declining.  As we've seen, markets can soar even when economies face serious existential threats.

Market structure, today, involves many more players investing for many different reasons. Gone are the days when the market waited with bated breath for Fed conferences, earnings reports, and presidential updates. Instead, you have speculators, passive investors, fundamental investors, quantitative investors, companies trying to hedge bets, market makers, manipulative algorithms, governments, and more … all involved in trench warfare seeking an edge. 

They trade for different reasons – some may make sense logically to you, others are executing part of a strategy you may never figure out. But, together, they form the engine that powers the market.  Markets really are a collection of forces all focused on trading.

Simplifying, you can look at the decline in the economy compared to the relative stability of the stock market (in light of the world shutting down), as proof of this. Economic stimulus played a massive role in propping up the market, but so did the comparative variety in why market participants trade. It's why you still see liquidity in the markets despite the decrease in consumer confidence and economic activity.  

Sure, the government created increased liquidity, stimulated markets, and even participated directly (and indirectly) at plunge protection.  But that is the playing field all traders have to play on right now.  It doesn't matter if it reflects the realities you see in the economy or the world.

Today's markets are much more complicated than before.  Moreover, the vast amount of information available (whether true, false, relevant, irrelevant, clarifying, or misleading) creates a vast signal-to-noise ratio challenge.  Meanwhile, many market participants (like many day-traders) have simply ridden the wave here, though it's unlikely that a vast majority of them truly understand what they're doing. Think of this as the "Smart Money" versus "Dumb Money" … and it doesn't usually end well for one of them.

VisualCapitalist put together a great infographic looking at the difference in response to the shutdown via economic activity and the S&P 500 as of July 17th. 

Take a look. 

via visualcapitalist

The chart makes the valid point that the S&P 500 is not an equally-weighted index and is currently driven primarily by the tech giants, even with other industries struggling. 

Consumer sentiment is still a factor, and news cycles can absolutely still impact stocks, as evidenced by Kodak's meteoric growth (and subsequent decline) last week. 

All-in-all, there are lots of things influencing markets besides the economy. It is a lot to take in (especially for us humans who can only process seven things plus or minus two at any one time.

It is no wonder that Smart Money is relying more on exponential technologies (like AI and Big Data).

Be safe!

Onwards! 

Last year, around this time I shared an article on data as the new precious commodity. In case you missed it, I thought it was worth revisiting. The closing feels even more relevant today than when I wrote it. Below is the article in its entirety

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Data is becoming a precious commodity.

A staggering 90% of all the world’s data (2.5 quintillion bytes per day) has been created in the past two years alone … and its value is rapidly rising.

With IoT growing from 2 billion devices in 2006 to a projected 200 billion by 2020 you can expect to see that growth continue to explode.

Data is today’s “wild west” and the battlefield of today’s tech titans. 

Alphabet, Amazon, Apple, Facebook, and Microsoft all have an unprecedented amount of data (and power).

Rapid growth means little time to create adequate rules. Everyone’s jumping to own more data than the next and to protect their own data from prying eyes.

I see it in trading, but it’s pervasive in every industry and in our personal lives. 

Having basic data and basic analytics used to be enough, but the game is changing. Traders used to focus on price data, but now you’re seeing an influx of firms using alternative data sets to find an edge. If you’re using the same data sources as your competitors and competing on the same set of beliefs, it’s hard to find a sustainable edge. Understanding the game they’re playing, and their rules are important, but that’s table stakes.

Figuring out where you can find extra insight, or where you can make the invisible visible, creates a moat between you and your competition, and it lets you play your own game.

I shot a video where I talk high-level about Data as fuel for your business. Check it out.

 

It is interesting to think about what’s driving the new world (of trading, of technology, of AI, etc.) and that often involves identifying what drove the old world. History has a way of repeating itself.

Before e-mails, fax machines were amazing. Before cars, you were really happy with a horse and buggy.

It’s in these comparisons that I think we can help explain the importance of data in today’s new world economics.

via gapingvoid

Data as the New Oil

Petroleum has played a pivotal role in human advancement since the industrial revolution; it fueled (and still fuels) our creativity, technology advancements, and a variety of derivative products. There are direct competitors to fossil fuels that are gaining steam, but I think it’s more interesting to compare petroleum to data due to their parallels in effect on innovation.

The process of pumping crude oil out of the ground and transforming it into a finished product is far from simple, but anyone can understand the process at a high-level. You have to locate a reservoir, drill, capture the resource, and then refine it to the desired product – heating oil, gasoline, asphalt, plastics, etc. 

The same is true for data.

You've got to figure out what data you might have, how it might be useful, you have to figure out how to refine it, clean it, fix it, curate it, transform it into something useful, and then how to deliver it to the people that need it in their business. And even if you've done this, you then have to make people aware that it's there, that it's changing, or how they might use it. For people who do it well, it's an incredible edge. – Howard Getson

Data can be seen as the fuel to the information economy and oil to the industrial economy. The amount of power someone has can be correlated to their control of and access to these resources … and, leaking of these resources can lead to extreme consequences.

Why Data Is Better Than Oil

The analogy works, but it’s just that, an analogy, and the more you analyze it, the more it falls apart. Unlike the finite resource that is oil, data is all around us and increasing at an exponential rate, so the game is a little different:

• Data is a renewable resource. It’s durable, it’s reusable, and it’s being produced faster than we can process it.
• Because it’s not a scarce resource, there’s no urge to hoard it – you can use it, transform it, and share it knowing that it won’t diminish.
• Data is more useful the more you use it.
• As the world’s oil reserves dwindle, and renewable resources grow in popularity and effectiveness, the relative value of oil drops. It’s unlikely that will happen to data.
• Also, while data transport is important, it’s not expensive the way oil is. It can be transported and replicated at light speed.

Using alternative data gives traders an advantage, but it doesn’t always have to be confidential or hard to find information. Traders now have access to vast amounts of structured and unstructured data. An important source that many overlook is the data produced through their own process or the metadata from their own trades or transactions.

In the very near future, I expect these systems to be able to go out and search for different sources of information. It's almost like the algorithm becomes an omnivore. Instead of simply looking at market data or transactional data, or even metadata, it starts to look for connections or feedback loops that are profitable in sources of data that the human would never have thought of. – Howard Getson

In a word of caution, there are two common mistakes people make when making data-driven decisions. First, people often end up slaves to the data, losing focus on the bigger picture. Second, even the most insightful data can’t predict black swans. It’s important to exercise caution.

The future of data is bright, but it’s also littered with potential challenges. Privacy concerns and misuse of data have been hot button topics, as have fake news and the ability of systems to generate misleading data. In addition, as we gain access to more data, our ability to separate signal from noise becomes more important.

The question becomes, how do you capitalize on data, without becoming a victim to it? 

Food for thought!