The latest “bubble indicator” readings.
As you know, I like to turn my intuition into decision rules (principles) that can be back-tested and automated to create a portfolio of alpha bets. I use one for bubbles. Having seen many bubbles in my 50+ years of investing, I described what makes a bubble and how to identify them in markets—not just stocks.
A bubble market has a high degree of the following:
- High prices compared to traditional values (e.g., by taking the present value of their cash flows for the duration of the asset and comparing it with their interest rates).
- Conditons incompatible with long-term growth (e.g., extrapolating past revenue and earnings growth rates late in the cycle).
- Many new and inexperienced buyers were drawn in by the perceived hot market.
- Broad bullish sentiment.
- Debt financing a large portion of purchases.
- Lots of forward and speculative purchases to profit from price rises (e.g., inventories that are more than needed, contracted forward purchases, etc.).
I use these criteria to assess all markets for bubbles. I have periodically shown you these for stocks and the stock market.
What Was Shown in January Versus Now
I will first describe the picture in words, then show it in charts, and compare it to the last update in January.
As of January, the bubble indicator showed that a) the US equity market was in a moderate bubble, but not an extreme one (ie., 70 percent of way toward the highest bubble, which occurred in the late 1990s and late 1920s), and b) the emerging tech companies (ie. As well, the unprecedented flood of liquidity post-COVID financed other bubbly behavior (e.g. SPACs, IPO boom, big pickup in options activity), making things bubbly. I showed which stocks were in bubbles and created an index of those stocks, which I call “bubble stocks.”
Those bubble stocks have popped. They fell by a third last year, while the S&P 500 remained flat. In light of these and other market developments, it is not necessarily true that now is a good time to buy emerging tech stocks.
The fact that they aren't at a bubble extreme doesn't mean they are safe or that it's a good time to get long. Our metrics still show that US stocks are overvalued. Once popped, bubbles tend to overcorrect to the downside rather than settle at “normal” prices.
The following charts paint the picture. The first shows the US equity market bubble gauge/indicator going back to 1900, currently at the 40% percentile. The charts also zoom in on the gauge in recent years, as well as the late 1920s and late 1990s bubbles (during both of these cases the gauge reached 100 percent ).
The chart below depicts the average bubble gauge for the most bubbly companies in 2020. Those readings are down significantly.
The charts below compare the performance of a basket of emerging tech bubble stocks to the S&P 500. Prices have fallen noticeably, giving up most of their post-COVID gains.
The following charts show the price action of the bubble slice today and in the 1920s and 1990s. These charts show the same market dynamics and two key indicators. These are just two examples of how a lot of debt financing stock ownership coupled with a tightening typically leads to a bubble popping.
Everything driving the bubbles in this market segment is classic—the same drivers that drove the 1920s bubble and the 1990s bubble. For instance, in the last couple months, it was how tightening can act to prick the bubble. Review this case study of the 1920s stock bubble (starting on page 49) from my book Principles for Navigating Big Debt Crises to grasp these dynamics.
The following charts show the components of the US stock market bubble gauge. Since this is a proprietary indicator, I will only show you some of the sub-aggregate readings and some indicators.
Each of these six influences is measured using a number of stats. This is how I approach the stock market. These gauges are combined into aggregate indices by security and then for the market as a whole. The table below shows the current readings of these US equity market indicators. It compares current conditions for US equities to historical conditions. These readings suggest that we’re out of a bubble.
1. How High Are Prices Relatively?
This price gauge for US equities is currently around the 50th percentile.
2. Is price reduction unsustainable?
This measure calculates the earnings growth rate required to outperform bonds. This is calculated by adding up the readings of individual securities. This indicator is currently near the 60th percentile for the overall market, higher than some of our other readings. Profit growth discounted in stocks remains high.
Even more so in the US software sector. Analysts' earnings growth expectations for this sector have slowed, but remain high historically. P/Es have reversed COVID gains but remain high historical.
3. How many new buyers (i.e., non-existing buyers) entered the market?
Expansion of new entrants is often indicative of a bubble. According to historical accounts, this was true in the 1990s equity bubble and the 1929 bubble (though our data for this and other gauges doesn't go back that far). A flood of new retail investors into popular stocks, which by other measures appeared to be in a bubble, pushed this gauge above the 90% mark in 2020. The pace of retail activity in the markets has recently slowed to pre-COVID levels.
4. How Broadly Bullish Is Sentiment?
The more people who have invested, the less resources they have to keep investing, and the more likely they are to sell. Market sentiment is now significantly negative.
5. Are Purchases Being Financed by High Leverage?
Leveraged purchases weaken the buying foundation and expose it to forced selling in a downturn. The leverage gauge, which considers option positions as a form of leverage, is now around the 50% mark.
6. To What Extent Have Buyers Made Exceptionally Extended Forward Purchases?
Looking at future purchases can help assess whether expectations have become overly optimistic. This indicator is particularly useful in commodity and real estate markets, where forward purchases are most obvious. In the equity markets, I look at indicators like capital expenditure, or how much businesses (and governments) invest in infrastructure, factories, etc. It reflects whether businesses are projecting future demand growth. Like other gauges, this one is at the 40th percentile.
What one does with it is a tactical choice. While the reversal has been significant, future earnings discounting remains high historically. In either case, bubbles tend to overcorrect (sell off more than the fundamentals suggest) rather than simply deflate. But I wanted to share these updated readings with you in light of recent market activity.
More on Economics & Investing
Cody Collins
3 years ago
The direction of the economy is as follows.
What quarterly bank earnings reveal
Big banks know the economy best. Unless we’re talking about a housing crisis in 2007…
Banks are crucial to the U.S. economy. The Fed, communities, and investments exchange money.
An economy depends on money flow. Banks' views on the economy can affect their decision-making.
Most large banks released quarterly earnings and forward guidance last week. Others were pessimistic about the future.
What Makes Banks Confident
Bank of America's profit decreased 30% year-over-year, but they're optimistic about the economy. Comparatively, they're bullish.
Who banks serve affects what they see. Bank of America supports customers.
They think consumers' future is bright. They believe this for many reasons.
The average customer has decent credit, unless the system is flawed. Bank of America's new credit card and mortgage borrowers averaged 771. New-car loan and home equity borrower averages were 791 and 797.
2008's housing crisis affected people with scores below 620.
Bank of America and the economy benefit from a robust consumer. Major problems can be avoided if individuals maintain spending.
Reasons Other Banks Are Less Confident
Spending requires income. Many companies, mostly in the computer industry, have announced they will slow or freeze hiring. Layoffs are frequently an indication of poor times ahead.
BOA is positive, but investment banks are bearish.
Jamie Dimon, CEO of JPMorgan, outlined various difficulties our economy could confront.
But geopolitical tension, high inflation, waning consumer confidence, the uncertainty about how high rates have to go and the never-before-seen quantitative tightening and their effects on global liquidity, combined with the war in Ukraine and its harmful effect on global energy and food prices are very likely to have negative consequences on the global economy sometime down the road.
That's more headwinds than tailwinds.
JPMorgan, which helps with mergers and IPOs, is less enthusiastic due to these concerns. Incoming headwinds signal drying liquidity, they say. Less business will be done.
Final Reflections
I don't think we're done. Yes, stocks are up 10% from a month ago. It's a long way from old highs.
I don't think the stock market is a strong economic indicator.
Many executives foresee a 2023 recession. According to the traditional definition, we may be in a recession when Q2 GDP statistics are released next week.
Regardless of criteria, I predict the economy will have a terrible year.
Weekly layoffs are announced. Inflation persists. Will prices return to 2020 levels if inflation cools? Perhaps. Still expensive energy. Ukraine's war has global repercussions.
I predict BOA's next quarter earnings won't be as bullish about the consumer's strength.
Sam Hickmann
3 years ago
Donor-Advised Fund Tax Benefits (DAF)
Giving through a donor-advised fund can be tax-efficient. Using a donor-advised fund can reduce your tax liability while increasing your charitable impact.
Grow Your Donations Tax-Free.
Your DAF's charitable dollars can be invested before being distributed. Your DAF balance can grow with the market. This increases grantmaking funds. The assets of the DAF belong to the charitable sponsor, so you will not be taxed on any growth.
Avoid a Windfall Tax Year.
DAFs can help reduce tax burdens after a windfall like an inheritance, business sale, or strong market returns. Contributions to your DAF are immediately tax deductible, lowering your taxable income. With DAFs, you can effectively pre-fund years of giving with assets from a single high-income event.
Make a contribution to reduce or eliminate capital gains.
One of the most common ways to fund a DAF is by gifting publicly traded securities. Securities held for more than a year can be donated at fair market value and are not subject to capital gains tax. If a donor liquidates assets and then donates the proceeds to their DAF, capital gains tax reduces the amount available for philanthropy. Gifts of appreciated securities, mutual funds, real estate, and other assets are immediately tax deductible up to 30% of Adjusted gross income (AGI), with a five-year carry-forward for gifts that exceed AGI limits.
Using Appreciated Stock as a Gift
Donating appreciated stock directly to a DAF rather than liquidating it and donating the proceeds reduces philanthropists' tax liability by eliminating capital gains tax and lowering marginal income tax.
In the example below, a donor has $100,000 in long-term appreciated stock with a cost basis of $10,000:
Using a DAF would allow this donor to give more to charity while paying less taxes. This strategy often allows donors to give more than 20% more to their favorite causes.
For illustration purposes, this hypothetical example assumes a 35% income tax rate. All realized gains are subject to the federal long-term capital gains tax of 20% and the 3.8% Medicare surtax. No other state taxes are considered.
The information provided here is general and educational in nature. It is not intended to be, nor should it be construed as, legal or tax advice. NPT does not provide legal or tax advice. Furthermore, the content provided here is related to taxation at the federal level only. NPT strongly encourages you to consult with your tax advisor or attorney before making charitable contributions.
Trevor Stark
3 years ago
Economics is complete nonsense.
Mainstream economics haven't noticed.
What come to mind when I say the word "economics"?
Probably GDP, unemployment, and inflation.
If you've ever watched the news or listened to an economist, they'll use data like these to defend a political goal.
The issue is that these statistics are total bunk.
I'm being provocative, but I mean it:
The economy is not measured by GDP.
How many people are unemployed is not counted in the unemployment rate.
Inflation is not measured by the CPI.
All orthodox economists' major economic statistics are either wrong or falsified.
Government institutions create all these stats. The administration wants to reassure citizens the economy is doing well.
GDP does not reflect economic expansion.
GDP measures a country's economic size and growth. It’s calculated by the BEA, a government agency.
The US has the world's largest (self-reported) GDP, growing 2-3% annually.
If GDP rises, the economy is healthy, say economists.
Why is the GDP flawed?
GDP measures a country's yearly spending.
The government may adjust this to make the economy look good.
GDP = C + G + I + NX
C = Consumer Spending
G = Government Spending
I = Investments (Equipment, inventories, housing, etc.)
NX = Exports minus Imports
GDP is a country's annual spending.
The government can print money to boost GDP. The government has a motive to increase and manage GDP.
Because government expenditure is part of GDP, printing money and spending it on anything will raise GDP.
They've done this. Since 1950, US government spending has grown 8% annually, faster than GDP.
In 2022, government spending accounted for 44% of GDP. It's the highest since WWII. In 1790-1910, it was 3% of GDP.
Who cares?
The economy isn't only spending. Focus on citizens' purchasing power or quality of life.
Since GDP just measures spending, the government can print money to boost GDP.
Even if Americans are poorer than last year, economists can say GDP is up and everything is fine.
How many people are unemployed is not counted in the unemployment rate.
The unemployment rate measures a country's labor market. If unemployment is high, people aren't doing well economically.
The BLS estimates the (self-reported) unemployment rate as 3-4%.
Why is the unemployment rate so high?
The US government surveys 100k persons to measure unemployment. They extrapolate this data for the country.
They come into 3 categories:
Employed
People with jobs are employed … duh.
Unemployed
People who are “jobless, looking for a job, and available for work” are unemployed
Not in the labor force
The “labor force” is the employed + the unemployed.
The unemployment rate is the percentage of unemployed workers.
Problem is unemployed definition. You must actively seek work to be considered unemployed.
You're no longer unemployed if you haven't interviewed in 4 weeks.
This shit makes no goddamn sense.
Why does this matter?
You can't interview if there are no positions available. You're no longer unemployed after 4 weeks.
In 1994, the BLS redefined "unemployed" to exclude discouraged workers.
If you haven't interviewed in 4 weeks, you're no longer counted in the unemployment rate.
If unemployment were measured by total unemployed, it would be 25%.
Because the government wants to keep the unemployment rate low, they modify the definition.
If every US resident was unemployed and had no job interviews, economists would declare 0% unemployment. Excellent!
Inflation is not measured by the CPI.
The BLS measures CPI. This month was the highest since 1981.
CPI measures the cost of a basket of products across time. Food, energy, shelter, and clothes are included.
A 9.1% CPI means the basket of items is 9.1% more expensive.
What is the CPI problem?
Here's a more detailed explanation of CPI's flaws.
In summary, CPI is manipulated to be understated.
Housing costs are understated to manipulate CPI. Housing accounts for 33% of the CPI because it's the biggest expense for most people.
This signifies it's the biggest CPI weight.
Rather than using actual house prices, the Bureau of Labor Statistics essentially makes shit up. You can read more about the process here.
Surprise! It’s bullshit
The BLS stated Shelter's price rose 5.5% this month.
House prices are up 11-21%. (Source 1, Source 2, Source 3)
Rents are up 14-26%. (Source 1, Source 2)
Why is this important?
If CPI included housing prices, it would be 12-15 percent this month, not 9.1 percent.
9% inflation is nuts. Your money's value halves every 7 years at 9% inflation.
Worse is 15% inflation. Your money halves every 4 years at 15% inflation.
If everyone realized they needed to double their wage every 4-5 years to stay wealthy, there would be riots.
Inflation drains our money's value so the government can keep printing it.
The Solution
Most individuals know the existing system doesn't work, but can't explain why.
People work hard yet lag behind. The government lies about the economy's data.
In reality:
GDP has been down since 2008
25% of Americans are unemployed
Inflation is actually 15%
People might join together to vote out kleptocratic politicians if they knew the reality.
Having reliable economic data is the first step.
People can't understand the situation without sufficient information. Instead of immigrants or billionaires, people would blame liar politicians.
Here’s the vision:
A decentralized, transparent, and global dashboard that tracks economic data like GDP, unemployment, and inflation for every country on Earth.
Government incentives influence economic statistics.
ShadowStats has already started this effort, but the calculations must be transparent, decentralized, and global to be effective.
If interested, email me at trevorstark02@gmail.com.
Here are some links to further your research:
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Sammy Abdullah
3 years ago
R&D, S&M, and G&A expense ratios for SaaS
SaaS spending is 40/40/20. 40% of operating expenses should be R&D, 40% sales and marketing, and 20% G&A. We wanted to see the statistics behind the rules of thumb. Since October 2017, 73 SaaS startups have gone public. Perhaps the rule of thumb should be 30/50/20. The data is below.
30/50/20. R&D accounts for 26% of opex, sales and marketing 48%, and G&A 22%. We think R&D/S&M/G&A should be 30/50/20.
There are outliers. There are exceptions to rules of thumb. Dropbox spent 45% on R&D whereas Zoom spent 13%. Zoom spent 73% on S&M, Dropbox 37%, and Bill.com 28%. Snowflake spent 130% of revenue on S&M, while their EBITDA margin is -192%.
G&A shouldn't stand out. Minimize G&A spending. Priorities should be product development and sales. Cloudflare, Sendgrid, Snowflake, and Palantir spend 36%, 34%, 37%, and 43% on G&A.
Another myth is that COGS is 20% of revenue. Median and averages are 29%.
Where is the profitability? Data-driven operating income calculations were simplified (Revenue COGS R&D S&M G&A). 20 of 73 IPO businesses reported operational income. Median and average operating income margins are -21% and -27%.
As long as you're growing fast, have outstanding retention, and marquee clients, you can burn cash since recurring income that doesn't churn is a valuable annuity.
The data was compelling overall. 30/50/20 is the new 40/40/20 for more established SaaS enterprises, unprofitability is alright as long as your business is expanding, and COGS can be somewhat more than 20% of revenue.
Protos
3 years ago
Plagiarism on OpenSea: humans and computers
OpenSea, a non-fungible token (NFT) marketplace, is fighting plagiarism. A new “two-pronged” approach will aim to root out and remove copies of authentic NFTs and changes to its blue tick verified badge system will seek to enhance customer confidence.
According to a blog post, the anti-plagiarism system will use algorithmic detection of “copymints” with human reviewers to keep it in check.
Last year, NFT collectors were duped into buying flipped images of the popular BAYC collection, according to The Verge. The largest NFT marketplace had to remove its delay pay minting service due to an influx of copymints.
80% of NFTs removed by the platform were minted using its lazy minting service, which kept the digital asset off-chain until the first purchase.
NFTs copied from popular collections are opportunistic money-grabs. Right-click, save, and mint the jacked JPEGs that are then flogged as an authentic NFT.
The anti-plagiarism system will scour OpenSea's collections for flipped and rotated images, as well as other undescribed permutations. The lack of detail here may be a deterrent to scammers, or it may reflect the new system's current rudimentary nature.
Thus, human detectors will be needed to verify images flagged by the detection system and help train it to work independently.
“Our long-term goal with this system is two-fold: first, to eliminate all existing copymints on OpenSea, and second, to help prevent new copymints from appearing,” it said.
“We've already started delisting identified copymint collections, and we'll continue to do so over the coming weeks.”
It works for Twitter, why not OpenSea
OpenSea is also changing account verification. Early adopters will be invited to apply for verification if their NFT stack is worth $100 or more. OpenSea plans to give the blue checkmark to people who are active on Twitter and Discord.
This is just the beginning. We are committed to a future where authentic creators can be verified, keeping scammers out.
Also, collections with a lot of hype and sales will get a blue checkmark. For example, a new NFT collection sold by the verified BAYC account will have a blue badge to verify its legitimacy.
New requests will be responded to within seven days, according to OpenSea.
These programs and products help protect creators and collectors while ensuring our community can confidently navigate the world of NFTs.
By elevating authentic content and removing plagiarism, these changes improve trust in the NFT ecosystem, according to OpenSea.
OpenSea is indeed catching up with the digital art economy. Last August, DevianArt upgraded its AI image recognition system to find stolen tokenized art on marketplaces like OpenSea.
It scans all uploaded art and compares it to “public blockchain events” like Ethereum NFTs to detect stolen art.
Dung Claire Tran
3 years ago
Is the future of brand marketing with virtual influencers?
Digital influences that mimic humans are rising.
Lil Miquela has 3M Instagram followers, 3.6M TikTok followers, and 30K Twitter followers. She's been on the covers of Prada, Dior, and Calvin Klein magazines. Miquela released Not Mine in 2017 and launched Hard Feelings at Lollapazoolas this year. This isn't surprising, given the rise of influencer marketing.
This may be unexpected. Miquela's fake. Brud, a Los Angeles startup, produced her in 2016.
Lil Miquela is one of many rising virtual influencers in the new era of social media marketing. She acts like a real person and performs the same tasks as sports stars and models.
The emergence of online influencers
Before 2018, computer-generated characters were rare. Since the virtual human industry boomed, they've appeared in marketing efforts worldwide.
In 2020, the WHO partnered up with Atlanta-based virtual influencer Knox Frost (@knoxfrost) to gather contributions for the COVID-19 Solidarity Response Fund.
Lu do Magalu (@magazineluiza) has been the virtual spokeswoman for Magalu since 2009, using social media to promote reviews, product recommendations, unboxing videos, and brand updates. Magalu's 10-year profit was $552M.
In 2020, PUMA partnered with Southeast Asia's first virtual model, Maya (@mayaaa.gram). She joined Singaporean actor Tosh Zhang in the PUMA campaign. Local virtual influencer Ava Lee-Graham (@avagram.ai) partnered with retail firm BHG to promote their in-house labels.
In Japan, Imma (@imma.gram) is the face of Nike, PUMA, Dior, Salvatore Ferragamo SpA, and Valentino. Imma's bubblegum pink bob and ultra-fine fashion landed her on the cover of Grazia magazine.
Lotte Home Shopping created Lucy (@here.me.lucy) in September 2020. She made her TV debut as a Christmas show host in 2021. Since then, she has 100K Instagram followers and 13K TikTok followers.
Liu Yiexi gained 3 million fans in five days on Douyin, China's TikTok, in 2021. Her two-minute video went viral overnight. She's posted 6 videos and has 830 million Douyin followers.
China's virtual human industry was worth $487 million in 2020, up 70% year over year, and is expected to reach $875.9 million in 2021.
Investors worldwide are interested. Immas creator Aww Inc. raised $1 million from Coral Capital in September 2020, according to Bloomberg. Superplastic Inc., the Vermont-based startup behind influencers Janky and Guggimon, raised $16 million by 2020. Craft Ventures, SV Angels, and Scooter Braun invested. Crunchbase shows the company has raised $47 million.
The industries they represent, including Augmented and Virtual reality, were worth $14.84 billion in 2020 and are projected to reach $454.73 billion by 2030, a CAGR of 40.7%, according to PR Newswire.
Advantages for brands
Forbes suggests brands embrace computer-generated influencers. Examples:
Unlimited creative opportunities: Because brands can personalize everything—from a person's look and activities to the style of their content—virtual influencers may be suited to a brand's needs and personalities.
100% brand control: Brand managers now have more influence over virtual influencers, so they no longer have to give up and rely on content creators to include brands into their storytelling and style. Virtual influencers can constantly produce social media content to promote a brand's identity and ideals because they are completely scandal-free.
Long-term cost savings: Because virtual influencers are made of pixels, they may be reused endlessly and never lose their beauty. Additionally, they can move anywhere around the world and even into space to fit a brand notion. They are also always available. Additionally, the expense of creating their content will not rise in step with their expanding fan base.
Introduction to the metaverse: Statista reports that 75% of American consumers between the ages of 18 and 25 follow at least one virtual influencer. As a result, marketers that support virtual celebrities may now interact with younger audiences that are more tech-savvy and accustomed to the digital world. Virtual influencers can be included into any digital space, including the metaverse, as they are entirely computer-generated 3D personas. Virtual influencers can provide brands with a smooth transition into this new digital universe to increase brand trust and develop emotional ties, in addition to the young generations' rapid adoption of the metaverse.
Better engagement than in-person influencers: A Hype Auditor study found that online influencers have roughly three times the engagement of their conventional counterparts. Virtual influencers should be used to boost brand engagement even though the data might not accurately reflect the entire sector.
Concerns about influencers created by computers
Virtual influencers could encourage excessive beauty standards in South Korea, which has a $10.7 billion plastic surgery industry.
A classic Korean beauty has a small face, huge eyes, and pale, immaculate skin. Virtual influencers like Lucy have these traits. According to Lee Eun-hee, a professor at Inha University's Department of Consumer Science, this could make national beauty standards more unrealistic, increasing demand for plastic surgery or cosmetic items.
Other parts of the world raise issues regarding selling items to consumers who don't recognize the models aren't human and the potential of cultural appropriation when generating influencers of other ethnicities, called digital blackface by some.
Meta, Facebook and Instagram's parent corporation, acknowledges this risk.
“Like any disruptive technology, synthetic media has the potential for both good and harm. Issues of representation, cultural appropriation and expressive liberty are already a growing concern,” the company stated in a blog post. “To help brands navigate the ethical quandaries of this emerging medium and avoid potential hazards, (Meta) is working with partners to develop an ethical framework to guide the use of (virtual influencers).”
Despite theoretical controversies, the industry will likely survive. Companies think virtual influencers are the next frontier in the digital world, which includes the metaverse, virtual reality, and digital currency.
In conclusion
Virtual influencers may garner millions of followers online and help marketers reach youthful audiences. According to a YouGov survey, the real impact of computer-generated influencers is yet unknown because people prefer genuine connections. Virtual characters can supplement brand marketing methods. When brands are metaverse-ready, the author predicts virtual influencer endorsement will continue to expand.