I think most data scientists or traders would agree that some charts are just prettier than others.
Whether it's due to the artistry of the creator, the results shown, or an insight or perspective illuminated ... I am sometimes surprised by the beauty of a chart.
After looking at thousands of charts, some really do look "pretty" and others look "ugly" to the trader. Perhaps this stems from an intuition honed through many trials of separating luck from skill?
Taking a different approach is Stoxart, created by a visual designer at Nike named Gladys Orteza. She has been turning stock charts into landscape artworks related to the company they reference. All that's missing is the warning that past performance doesn't guarantee future results.
Here is an example of her art inspired by Ford's performance in the last year. Maybe she should have titled it "Sunset".
I recently had the chance to speak at a wealth summit helping to educate family offices on the different opportunities available to them. Because of my work around the hedge fund space - and with emerging technologies like AI - I was brought in to focus on both topics for their audience.
The financial industry is intimidating - especially to newcomers - and while this summit is targeted towards family offices with $5MM+ in liquid assets, the lessons are accessible to any level of wealth.
The presentation was somewhat of a departure from my normal talking points because it was more focused on the basics of hedge funds & trading in general. Nonetheless, I think it's worth watching. This clip shows my response to the moderator's previous presentation. The presentation provides an introduction to hedge funds and alpha generation now and into the future. We also talk about Madoff, performance fees, the 2008 crash, "why a hedge fund?" and a lot more.
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.
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.
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).
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
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.
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.
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?
Back in June, I participated in a series of webinars for IBM. The focus was on building smart and secure financial services. My talk, specifically, was on advanced computing and the new world of trading. Challenging times drive advancement - and what better time to talk about advancements in technology (and their applications) than in the midst of a global pandemic.
You can watch a replay of the Fintech webinar here. There are several interesting presentations. If you just want to watch my presentation, it starts at the 5:16 mark.
In addition, I've uploaded a different version of just my talk that you can watch directly here.
In the past. trading used to be about people trading with people. Markets represented the collective fear and greed of populations. So price patterns and other technical analysis measures really represented the collective fear and greed of a population. If you could capture that data and figure out certain statistical probabilities, you might have had an edge. The keywords is "might have".
If you had more information than your competitors - an information asymmetry - you had an amazing edge. At one time that was being able to print out reports on stocks from that new-fangled technology called the internet. As time passed, it became harder and harder to gain an asymmetric information advantage.
The rules, the players, and the game have all changed. Today, technological asymmetry is a major factor, and your edges come from things like bigger and faster servers and low latency connections to markets.
In the future, I see those edges combining as artificial intelligence starts to leverage exponential technologies and new data sources (like alternative data and metadata feedback loops). It is easy to imagine a time when information is the fuel, but your ability to digest and parse that information is the engine.
I talk about much more in the video but boiling down the main points, ask yourself (in business, in trading, in life) are you separating the signal from the noise?
A technological advantage doesn't mean anything if you're plugging in inaccurate or biased data into it.
We've talked about it over the past few weeks with the never-ending news cycle - but it's a lesson that's infinitely applicable.
We're now two days into August. U.S. GDP is down 33% on an annualized basis, the largest quarterly decline since the series began in 1947. For context, 1% is a recession, "The Great Recession" peaked with 8.4% in December 2008, and 15% was The Great Depression.
Adding insult to injury, approximately 40% of renter households are at risk of eviction. On Friday, the federal moratorium on evictions expired. Consequently, 25 million Americans have stopped receiving their $600 weekly unemployment checks. Many states have stopped or are rolling back their reopening plans.
Jobless rates, which have been trending downward since March, and credit card spending, which had been trending upward, have both reversed. The corrections weren't nearly as pronounced as the initial shocks.
So there's the bad news, but let's try and find some silver linings:
First, the prediction for the contraction was 35%, so we're below that number, and job creation in May and June surpassed expectations by almost 12 million.
Compared to previous contractions, we entered it on a much stronger footing as a result of the long-term expansion.
As well, remember that 33% number is based on an annualized rate (which assumes the trend will continue, meaning the economy is really only about 10% smaller than in the first quarter).
Many states are still reopening, and the rest have various recovery efforts underway.
The economic consequences of the public health crisis and the measures taken in response will continue to affect the course of the economy for a long time. The recovery will be protracted. But, we're resilient, and we know how to dig ourselves out of this hole. In addition, the whole world is going through a similar crisis. For the most part, I'd rather be here than almost anywhere else. My sense is that people with capital feel the same way, and that is a very positive indicator of why our economy will suffer less and recover faster than other economies.
As I've mentioned before, fear plays as much a role in the recovery as other factors. If people believe in the future, their habits affect the economy differently than if they're at home, hoarding what they have left.
Personally, I believe we're about to see a tough time, with increased volatility and a lot of noise. It is increasingly likely that we will see another push downwards in the markets. I believe that America is well-positioned to adapt and recover. As a company, my sense is the strongest are not the most likely to survive and thrive in times like these. This is a time where adapting and responding to new opportunities and threats will separate the winners from the losers.
Jeff Bezos is officially worth ~$172 Billion dollars; more than he was worth before his divorce.
Everyone on earth is closer to being a millionaire than he is. Think about that. He has so much more than $1 million dollars that the homeless person willing to work for food is closer to being merely a millionaire than Bezos. The med school graduate with $100K+ in debt? Closer to being a millionaire than Bezos. Obvious at one level ... but crazy to think about on another level, right?
Humans are notoriously bad at large numbers, so it's hard to wrap our minds around something of that scale.
I've recently seen a couple of good visualizations of the difference between a million and a billion dollars.
If you have an hour to "waste," this comprehensive video by Tom Scott shares a couple of different ways to look at it, and he literally goes on a road trip to show the difference.
One good example from the video is "It would take almost 12 days for a million seconds to elapse and 31.7 years for a billion seconds." A billion seconds from today would be 1988.
Another:
1 dollar
0.0043 inches or 0.00010922 meters (thickness)
1B dollars
1B x 0.0043 inches → 4.3M inches → 68 miles
1B x 0.00010922 meters → 109K meters → 109 kilometers
Now multiply that by 172.
In distance, Bezos's net worth is a hair under half the equatorial circumference of the Earth.
Here's a link to specifically understanding Bezos's net worth - https://mkorostoff.github.io/1-pixel-wealth. If you were to spend a dollar every second for an entire day, you would spend $86,400 per day. If you have a million dollars, you can do that for approximately twelve days. With a billion dollars, you can do that for over 31 years. Ignoring the difference between net worth and cash, Jeff Bezos could spend over $9M per day for over 31 years.
Lastly, here's a shorter video visualizing the $10 Trillion in economic stimulus the U.S. government has been undertaking.
Even with these depictions, it's hard to understand. We're wired to think locally and linearly, not exponentially (it's one of the reasons I love AI so much).
There is nothing wrong with your television. We will control all that you see and hear. We can deluge you with a thousand channels or expand one single image to crystal clarity and beyond. We can shape your vision to anything our imagination can conceive. Enjoy ....
There is nothing wrong with your television set. Do not attempt to adjust the picture. We are controlling transmission. If we wish to make it louder, we will bring up the volume. If we wish to make it softer, we will tune it to a whisper. We will control the horizontal. We will control the vertical. We can roll the image; make it flutter. We can change the focus to a soft blur or sharpen it to crystal clarity. For the next hour, sit quietly and we will control all that you see and hear. We repeat: there is nothing wrong with your television set. You are about to participate in a great adventure. You are about to experience the awe and mystery which reaches from the inner mind to the outer limits.
We believe what we want to believe, so it can be very hard to change a belief, even in the face of contrary evidence.
Recently, we've seen a massive uptick in distrust toward news agencies, big companies, the government, and basically anyone with a particularly large reach.
To a certain degree, this is understandable and justified. Here is an example of the power of the media focused on a message. Click to watch.
Propaganda has always been an issue, and almost everyone does it; governments, companies, etc. Luckily, it's easier to see today than in the past, but unluckily it's also more pervasive and insidious than before.
It's to the point where if you watch the news you're misinformed, and if you don't watch the news you're uninformed.
The above segment portrays a rosy picture of Amazon's efforts to protect its workers while delivering essentials to the struggling homebound masses. This comes while Amazon has come under massive fire for removing some of its protections.
Honestly, I use Amazon and, in my opinion, this isn't a massive breach of trust. News stations have a lot of time to fill, they often have sponsored content.
That being said, it's something to be cognizant of - not necessarily offended by.
Personally, I believe I am reasonably aware and somewhat immune from propaganda. That probably isn't as true as I'd like to believe.
It used to be true that winners wrote history (think empires, wars, etc.). Now, the one that delivers the most broadcast narratives shapes the emotional and seemingly logical responses to what we perceive to be happening around us.
The result impacts elections, financial markets, buying choices, and countless other areas of our life.
As A.I., Bots, and social media grow, our ability to discern truth from 'truthiness' weakens.
It's a great reminder that what you're seeing and hearing is carefully manufactured, and hopefully, it encourages you to get outside your bubble.
In response to COVID-19, the U.S. Government has tried numerous things to bolster the economy.
In Q2 alone, the U.S. Treasury borrowed a record $3 trillion dollars for coronavirus relief. It's already the largest-ever borrowing for any fiscal year, and it brings our total above $26 Trillion (over $80,000 per citizen).
The concept of "Debt" can be confusing to a layman. Most people understand what it means to take on debt with a local bank, but it can be harder to understand the role debt plays in global economics. Debt often enables governments to run smoothly. But sometimes you can have too much of a good thing.
Many worry that our "excessive" government debt levels impact economic stability, the strength of our currency, and unemployment. For all the potential, it's certain that our debt with a country affects the relationship. So who "owns" most of our debt?
Japan holds more U.S. debt than any other country but is followed closely by China. Both countries hold more than 6% of total foreign-held debt.
The chart focuses on foreign debt - but only about 30% of the national debt is held by foreign countries. The rest is held by investors, the Federal Reserve, and the government.
Taking a step back, how does our debt compare on the world stage? An important metric of debt is the debt-to-GDP ratio. It is a key indicator of the sustainability of government finance.
Ultimately, we're in the highest bracket, but also have a historically strong GDP to back it. It's also worth noting that lower debt levels don't necessarily translate to safety on a global scale. Yugoslavia had very low government debt until its breakup.
In some ways, it seems like paying-off our debts seems insurmountable. Yet, our economy is reliable so we're allowed to continue borrowing. Debt is also an important part of the economic machine - it can be argued that we wouldn't have money without debt.
While this doesn't mean we can go on borrowing forever, it does mean we have options.
If you want to see an updated, interactive version of the U.S. Debt Clock, just click here. It is worth spending a little time watching the pace the numbers turn.
There are many different methods of investing - and I've experimented with quite a few of them (fundamental, technical, statistical, quantitative, machine learning, etc.).
Ultimately, I believe most trading techniques work until they don't.
I don't believe that any technique always works ... but I do believe that there is always something that works.
Likewise, I believe that there is always a bestnext step.
Evolutionarily, the strongest or smartest doesn't necessarily survive ... The quickest to adapt and adjust to its changing environment is the one that gains advantage.
Consequently, it makes sense to be on the lookout for sources of new learning (even if they are old).
In the same way that reading news from an opposing slant can inform your decision - studying other beliefs may help you find the underlying truths (or spark the insight you needed).
Warren Buffet is a famous value investor. He does immense research on companies, attempts to buy them at a discount and then hold on to them for long periods of time. On some levels, our approach to the markets is radically different. On the other hand, it would be crazy to ignore the brilliance of what he "knows" and what he does.
One of his favorite books on investing is titled The Intelligent Investor by Benjamin Graham. It's a great introduction to the basics of value investing (versus speculating) and the role of inflation, margin of safety, etc.
It's worth a read ... but if you want to watch a good summary, here's a six-minute video.
Data Really Is Beautiful
I think most data scientists or traders would agree that some charts are just prettier than others.
Whether it's due to the artistry of the creator, the results shown, or an insight or perspective illuminated ... I am sometimes surprised by the beauty of a chart.
After looking at thousands of charts, some really do look "pretty" and others look "ugly" to the trader. Perhaps this stems from an intuition honed through many trials of separating luck from skill?
Taking a different approach is Stoxart, created by a visual designer at Nike named Gladys Orteza. She has been turning stock charts into landscape artworks related to the company they reference. All that's missing is the warning that past performance doesn't guarantee future results.
Here is an example of her art inspired by Ford's performance in the last year. Maybe she should have titled it "Sunset".
Another fun one is a year of Tesla performance.
Here's a link to see more Stoxart.
Posted at 07:18 PM in Art, Business, Current Affairs, Just for Fun, Market Commentary, Trading | Permalink | Comments (0)
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