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
Sam Hickmann
3 years ago
What is this Fed interest rate everybody is talking about that makes or breaks the stock market?
The Federal Funds Rate (FFR) is the target interest rate set by the Federal Reserve System (Fed)'s policy-making body (FOMC). This target is the rate at which the Fed suggests commercial banks borrow and lend their excess reserves overnight to each other.
The FOMC meets 8 times a year to set the target FFR. This is supposed to promote economic growth. The overnight lending market sets the actual rate based on commercial banks' short-term reserves. If the market strays too far, the Fed intervenes.
Banks must keep a certain percentage of their deposits in a Federal Reserve account. A bank's reserve requirement is a percentage of its total deposits. End-of-day bank account balances averaged over two-week reserve maintenance periods are used to determine reserve requirements.
If a bank expects to have end-of-day balances above what's needed, it can lend the excess to another institution.
The FOMC adjusts interest rates based on economic indicators that show inflation, recession, or other issues that affect economic growth. Core inflation and durable goods orders are indicators.
In response to economic conditions, the FFR target has changed over time. In the early 1980s, inflation pushed it to 20%. During the Great Recession of 2007-2009, the rate was slashed to 0.15 percent to encourage growth.
Inflation picked up in May 2022 despite earlier rate hikes, prompting today's 0.75 percent point increase. The largest increase since 1994. It might rise to around 3.375% this year and 3.1% by the end of 2024.

Sofien Kaabar, CFA
3 years ago
How to Make a Trading Heatmap
Python Heatmap Technical Indicator
Heatmaps provide an instant overview. They can be used with correlations or to predict reactions or confirm the trend in trading. This article covers RSI heatmap creation.
The Market System
Market regime:
Bullish trend: The market tends to make higher highs, which indicates that the overall trend is upward.
Sideways: The market tends to fluctuate while staying within predetermined zones.
Bearish trend: The market has the propensity to make lower lows, indicating that the overall trend is downward.
Most tools detect the trend, but we cannot predict the next state. The best way to solve this problem is to assume the current state will continue and trade any reactions, preferably in the trend.
If the EURUSD is above its moving average and making higher highs, a trend-following strategy would be to wait for dips before buying and assuming the bullish trend will continue.
Indicator of Relative Strength
J. Welles Wilder Jr. introduced the RSI, a popular and versatile technical indicator. Used as a contrarian indicator to exploit extreme reactions. Calculating the default RSI usually involves these steps:
Determine the difference between the closing prices from the prior ones.
Distinguish between the positive and negative net changes.
Create a smoothed moving average for both the absolute values of the positive net changes and the negative net changes.
Take the difference between the smoothed positive and negative changes. The Relative Strength RS will be the name we use to describe this calculation.
To obtain the RSI, use the normalization formula shown below for each time step.
The 13-period RSI and black GBPUSD hourly values are shown above. RSI bounces near 25 and pauses around 75. Python requires a four-column OHLC array for RSI coding.
import numpy as np
def add_column(data, times):
for i in range(1, times + 1):
new = np.zeros((len(data), 1), dtype = float)
data = np.append(data, new, axis = 1)
return data
def delete_column(data, index, times):
for i in range(1, times + 1):
data = np.delete(data, index, axis = 1)
return data
def delete_row(data, number):
data = data[number:, ]
return data
def ma(data, lookback, close, position):
data = add_column(data, 1)
for i in range(len(data)):
try:
data[i, position] = (data[i - lookback + 1:i + 1, close].mean())
except IndexError:
pass
data = delete_row(data, lookback)
return data
def smoothed_ma(data, alpha, lookback, close, position):
lookback = (2 * lookback) - 1
alpha = alpha / (lookback + 1.0)
beta = 1 - alpha
data = ma(data, lookback, close, position)
data[lookback + 1, position] = (data[lookback + 1, close] * alpha) + (data[lookback, position] * beta)
for i in range(lookback + 2, len(data)):
try:
data[i, position] = (data[i, close] * alpha) + (data[i - 1, position] * beta)
except IndexError:
pass
return data
def rsi(data, lookback, close, position):
data = add_column(data, 5)
for i in range(len(data)):
data[i, position] = data[i, close] - data[i - 1, close]
for i in range(len(data)):
if data[i, position] > 0:
data[i, position + 1] = data[i, position]
elif data[i, position] < 0:
data[i, position + 2] = abs(data[i, position])
data = smoothed_ma(data, 2, lookback, position + 1, position + 3)
data = smoothed_ma(data, 2, lookback, position + 2, position + 4)
data[:, position + 5] = data[:, position + 3] / data[:, position + 4]
data[:, position + 6] = (100 - (100 / (1 + data[:, position + 5])))
data = delete_column(data, position, 6)
data = delete_row(data, lookback)
return dataMake sure to focus on the concepts and not the code. You can find the codes of most of my strategies in my books. The most important thing is to comprehend the techniques and strategies.
My weekly market sentiment report uses complex and simple models to understand the current positioning and predict the future direction of several major markets. Check out the report here:
Using the Heatmap to Find the Trend
RSI trend detection is easy but useless. Bullish and bearish regimes are in effect when the RSI is above or below 50, respectively. Tracing a vertical colored line creates the conditions below. How:
When the RSI is higher than 50, a green vertical line is drawn.
When the RSI is lower than 50, a red vertical line is drawn.
Zooming out yields a basic heatmap, as shown below.
Plot code:
def indicator_plot(data, second_panel, window = 250):
fig, ax = plt.subplots(2, figsize = (10, 5))
sample = data[-window:, ]
for i in range(len(sample)):
ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)
if sample[i, 3] > sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)
if sample[i, 3] < sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
if sample[i, 3] == sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
ax[0].grid()
for i in range(len(sample)):
if sample[i, second_panel] > 50:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)
if sample[i, second_panel] < 50:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)
ax[1].grid()
indicator_plot(my_data, 4, window = 500)Call RSI on your OHLC array's fifth column. 4. Adjusting lookback parameters reduces lag and false signals. Other indicators and conditions are possible.
Another suggestion is to develop an RSI Heatmap for Extreme Conditions.
Contrarian indicator RSI. The following rules apply:
Whenever the RSI is approaching the upper values, the color approaches red.
The color tends toward green whenever the RSI is getting close to the lower values.
Zooming out yields a basic heatmap, as shown below.
Plot code:
import matplotlib.pyplot as plt
def indicator_plot(data, second_panel, window = 250):
fig, ax = plt.subplots(2, figsize = (10, 5))
sample = data[-window:, ]
for i in range(len(sample)):
ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)
if sample[i, 3] > sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)
if sample[i, 3] < sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
if sample[i, 3] == sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
ax[0].grid()
for i in range(len(sample)):
if sample[i, second_panel] > 90:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)
if sample[i, second_panel] > 80 and sample[i, second_panel] < 90:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'darkred', linewidth = 1.5)
if sample[i, second_panel] > 70 and sample[i, second_panel] < 80:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'maroon', linewidth = 1.5)
if sample[i, second_panel] > 60 and sample[i, second_panel] < 70:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'firebrick', linewidth = 1.5)
if sample[i, second_panel] > 50 and sample[i, second_panel] < 60:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5)
if sample[i, second_panel] > 40 and sample[i, second_panel] < 50:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5)
if sample[i, second_panel] > 30 and sample[i, second_panel] < 40:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'lightgreen', linewidth = 1.5)
if sample[i, second_panel] > 20 and sample[i, second_panel] < 30:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'limegreen', linewidth = 1.5)
if sample[i, second_panel] > 10 and sample[i, second_panel] < 20:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'seagreen', linewidth = 1.5)
if sample[i, second_panel] > 0 and sample[i, second_panel] < 10:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)
ax[1].grid()
indicator_plot(my_data, 4, window = 500)Dark green and red areas indicate imminent bullish and bearish reactions, respectively. RSI around 50 is grey.
Summary
To conclude, my goal is to contribute to objective technical analysis, which promotes more transparent methods and strategies that must be back-tested before implementation.
Technical analysis will lose its reputation as subjective and unscientific.
When you find a trading strategy or technique, follow these steps:
Put emotions aside and adopt a critical mindset.
Test it in the past under conditions and simulations taken from real life.
Try optimizing it and performing a forward test if you find any potential.
Transaction costs and any slippage simulation should always be included in your tests.
Risk management and position sizing should always be considered in your tests.
After checking the above, monitor the strategy because market dynamics may change and make it unprofitable.

Sylvain Saurel
3 years ago
A student trader from the United States made $110 million in one month and rose to prominence on Wall Street.
Genius or lucky?
From the title, you might think I'm selling advertising for a financial influencer, a dubious trading site, or a training organization to attract clients. I'm suspicious. Better safe than sorry.
But not here.
Jake Freeman, 20, made $110 million in a month, according to the Financial Times. At 18, he ran for president. He made his name in markets, not politics. Two years later, he's Wall Street's prince. Interview requests flood the prodigy.
Jake Freeman bought 5 million Bed Bath & Beyond Group shares for $5.5 in July 2022 and sold them for $27 a month later. He thought the stock might double. Since speculation died down, he sold well. The stock fell 40.5% to 11 dollars on Friday, 19 August 2022. On August 22, 2022, it fell 16% to $9.
Smallholders have been buying the stock for weeks and will lose heavily if it falls further. Bed Bath & Beyond is the second most popular stock after Foot Locker, ahead of GameStop and Apple.
Jake Freeman earned $110 million thanks to a significant stock market flurry.
Online broker customers aren't the only ones with jitters. By June 2022, Ken Griffin's Citadel and Stephen Mandel's Lone Pine Capital held nearly a third of the company's capital. Did big managers sell before the stock plummeted?
Recent stock movements (derivatives) and rumors could prompt a SEC investigation.
Jake Freeman wrote to the board of directors after his investment to call for a turnaround, given the company's persistent problems and short sellers. The bathroom and kitchen products distribution group's stock soared in July 2022 due to renewed buying by private speculators, who made it one of their meme stocks with AMC and GameStop.
Second-quarter 2022 results and financial health worsened. He didn't celebrate his miraculous operation in a nightclub. He told a British newspaper, "I'm shocked." His parents dined in New York. He returned to Los Angeles to study math and economics.
Jake Freeman founded Freeman Capital Management with his savings and $25 million from family, friends, and acquaintances. They are the ones who are entitled to the $110 million he raised in one month. Will his investors pocket and withdraw all or part of their profits or will they trust the young prodigy for new stunts on Wall Street?
His operation should attract new clients. Well-known hedge funds may hire him.
Jake Freeman didn't listen to gurus or former traders. At 17, he interned at a quantitative finance and derivatives hedge fund, Volaris. At 13, he began investing with his pharmaceutical executive uncle. All countries have increased their Google searches for the young trader in the last week.
Naturally, his success has inspired resentment.
His success stirs jealousy, and he's attacked on social media. On Reddit, people who lost money on Bed Bath & Beyond, Jake Freeman's fortune, are mourning.
Several conspiracy theories circulate about him, including that he doesn't exist or is working for a Taiwanese amusement park.
If all 20 million American students had the same trading skills, they would have generated $1.46 trillion. Jake Freeman is unique. Apprentice traders' careers are often short, disillusioning, and tragic.
Two years ago, 20-year-old Robinhood client Alexander Kearns committed suicide after losing $750,000 trading options. Great traders start young. Michael Platt of BlueCrest invested in British stocks at age 12 under his grandmother's supervision and made a £30,000 fortune. Paul Tudor Jones started trading before he turned 18 with his uncle. Warren Buffett, at age 10, was discussing investments with Goldman Sachs' head. Oracle of Omaha tells all.
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Chris Newman
3 years ago
Clean Food: Get Over Yourself If You Want to Save the World.
I’m a permaculture farmer. I want to create food-producing ecosystems. My hope is a world with easy access to a cuisine that nourishes consumers, supports producers, and leaves the Earth joyously habitable.
Permaculturists, natural farmers, plantsmen, and foodies share this ambition. I believe this group of green thumbs, stock-folk, and food champions is falling to tribalism, forgetting that rescuing the globe requires saving all of its inhabitants, even those who adore cheap burgers and Coke. We're digging foxholes and turning folks who disagree with us or don't understand into monsters.
Take Dr. Daphne Miller's comments at the end of her Slow Money Journal interview:
“Americans are going to fall into two camps when all is said and done: People who buy cheap goods, regardless of quality, versus people who are willing and able to pay for things that are made with integrity. We are seeing the limits of the “buying cheap crap” approach.”
This is one of the most judgmental things I've read outside the Bible. Consequences:
People who purchase inexpensive things (food) are ignorant buffoons who prefer to choose fair trade coffee over fuel as long as the price is correct.
It all depends on your WILL to buy quality or cheaply. Both those who are WILLING and those who ARE NOT exist. And able, too.
People who are unwilling and unable are purchasing garbage. You're giving your kids bad food. Both the Earth and you are being destroyed by your actions. Your camp is the wrong one. You’re garbage! Disgrace to you.
Dr. Miller didn't say it, but words are worthless until interpreted. This interpretation depends on the interpreter's economic, racial, political, religious, family, and personal history. Complementary language insults another. Imagine how that Brown/Harvard M.D.'s comment sounds to a low-income household with no savings.
Dr. Miller's comment reflects the echo chamber into which nearly all clean food advocates speak. It asks easy questions and accepts non-solutions like raising food prices and eating less meat. People like me have cultivated an insular world unencumbered by challenges beyond the margins. We may disagree about technical details in rotationally-grazing livestock, but we short circuit when asked how our system could supply half the global beef demand. Most people have never seriously considered this question. We're so loved and affirmed that challenging ourselves doesn't seem necessary. Were generals insisting we don't need to study the terrain because God is on our side?
“Yes, the $8/lb ground beef is produced the way it should be. Yes, it’s good for my body. Yes it’s good for the Earth. But it’s eight freaking dollars, and my kid needs braces and protein. Bye Felicia, we’re going to McDonald’s.”
-Bobby Q. Homemaker
Funny clean foodies. People don't pay enough for food; they should value it more. Turn the concept of buying food with integrity into a wedge and drive it into the heart of America, dividing the willing and unwilling.
We go apeshit if you call our products high-end.
I've heard all sorts of gaslighting to defend a $10/lb pork chop as accessible (things I’ve definitely said in the past):
At Whole Foods, it costs more.
The steak at the supermarket is overly affordable.
Pay me immediately or the doctor gets paid later.
I spoke with Timbercreek Market and Local Food Hub in front of 60 people. We were asked about local food availability.
They came to me last, after my co-panelists gave the same responses I would have given two years before.
I grumbled, "Our food is inaccessible." Nope. It's beyond the wallets of nearly everyone, and it's the biggest problem with sustainable food systems. We're criminally unserious about being leaders in sustainability until we propose solutions beyond economic relativism, wishful thinking, and insisting that vulnerable, distracted people do all the heavy lifting of finding a way to afford our food. And until we talk about solutions, all this preserve the world? False.
The room fell silent as if I'd revealed a terrible secret. Long, thunderous applause followed my other remarks. But I’m probably not getting invited back to any VNRLI events.
I make pricey cuisine. It’s high-end. I have customers who really have to stretch to get it, and they let me know it. They're forgoing other creature comforts to help me make a living and keep the Earth of my grandmothers alive, and they're doing it as an act of love. They believe in us and our work.
I remember it when I'm up to my shoulders in frigid water, when my vehicle stinks of four types of shit, when I come home covered in blood and mud, when I'm hauling water in 100-degree heat, when I'm herding pigs in a rainstorm and dodging lightning bolts to close the chickens. I'm reminded I'm not alone. Their enthusiasm is worth more than money; it helps me make a life and a living. I won't label that gift less than it is to make my meal seem more accessible.
Not everyone can sacrifice.
Let's not pretend we want to go back to peasant fare, despite our nostalgia. Industrial food has leveled what rich and poor eat. How food is cooked will be the largest difference between what you and a billionaire eat. Rich and poor have access to chicken, pork, and beef. You might be shocked how recently that wasn't the case. This abundance, particularly of animal protein, has helped vulnerable individuals.
Industrial food causes environmental damage, chronic disease, and distribution inequities. Clean food promotes non-industrial, artisan farming. This creates a higher-quality, more expensive product than the competition; we respond with aggressive marketing and the "people need to value food more" shtick geared at consumers who can spend the extra money.
The guy who is NOT able is rendered invisible by clean food's elitist marketing, which is bizarre given a.) clean food insists it's trying to save the world, yet b.) MOST PEOPLE IN THE WORLD ARE THAT GUY. No one can help him except feel-good charities. That's crazy.
Also wrong: a foodie telling a kid he can't eat a 99-cent fast food hamburger because it lacks integrity. Telling him how easy it is to save his ducketts and maybe have a grass-fed house burger at the end of the month as a reward, but in the meantime get your protein from canned beans you can't bake because you don't have a stove and, even if you did, your mom works two jobs and moonlights as an Uber driver so she doesn't have time to heat that shitup anyway.
A wealthy person's attitude toward the poor is indecent. It's 18th-century Versailles.
Human rights include access to nutritious food without social or environmental costs. As a food-forest-loving permaculture farmer, I no longer balk at the concept of cultured beef and hydroponics. My food is out of reach for many people, but access to decent food shouldn't be. Cultures and hydroponics could scale to meet the clean food affordability gap without externalities. If technology can deliver great, affordable beef without environmental negative effects, I can't reject it because it's new, unusual, or might endanger my business.
Why is your farm needed if cultured beef and hydroponics can feed the world? Permaculture food forests with trees, perennial plants, and animals are crucial to economically successful environmental protection. No matter how advanced technology gets, we still need clean air, water, soil, greenspace, and food.
Clean Food cultivated in/on live soil, minimally processed, and eaten close to harvest is part of the answer, not THE solution. Clean food advocates must recognize the conflicts at the intersection of environmental, social, and economic sustainability, the disproportionate effects of those conflicts on the poor and lower-middle classes, and the immorality and impracticality of insisting vulnerable people address those conflicts on their own and judging them if they don't.
Our clients, relatives, friends, and communities need an honest assessment of our role in a sustainable future. If we're serious about preserving the world, we owe honesty to non-customers. We owe our goal and sanity to honesty. Future health and happiness of the world left to the average person's pocketbook and long-term moral considerations is a dismal proposition with few parallels.
Let's make soil and grow food. Let the lab folks do their thing. We're all interdependent.

Suzie Glassman
3 years ago
How I Stay Fit Despite Eating Fast Food and Drinking Alcohol
Here's me. Perfectionism is unnecessary.
This post isn't for people who gag at the prospect of eating french fries. I've been ridiculed for stating you can lose weight eating carbs and six-pack abs aren't good.
My family eats frozen processed meals and quick food most weeks (sometimes more). Clean eaters may think I'm unqualified to give fitness advice. I get it.
Hear me out, though. I’m a 44-year-old raising two busy kids with a weekly-traveling husband. Tutoring, dance, and guitar classes fill weeknights. I'm also juggling my job and freelancing.
I'm as worried and tired as my clients. I wish I ate only kale smoothies and salads. I can’t. Despite my mistakes, I'm fit. I won't promise you something just because it worked for me. But here’s a look at how I manage.
What I largely get right about eating
I have a flexible diet and track my daily intake. I count protein, fat, and carbs. Only on vacation or exceptional occasions do I not track.
My protein goal is 1 g per lb. I consume a lot of chicken breasts, eggs, turkey, and lean ground beef. I also occasionally drink protein shakes.
I eat 220–240 grams of carbs daily. My carb count depends on training volume and goals. I'm trying to lose weight slowly. If I want to lose weight faster, I cut carbs to 150-180.
My carbs include white rice, Daves Killer Bread, fruit, pasta, and veggies. I don't eat enough vegetables, so I take Athletic Greens. Also, V8.
Fat grams over 50 help me control my hormones. Recently, I've reached 70-80 grams. Cooking with olive oil. I eat daily dark chocolate. Eggs, butter, milk, and cheese contribute to the rest.
Those frozen meals? What can I say? Stouffer’s lasagna is sometimes needed. I order the healthiest fast food I can find (although I can never bring myself to order the salad). That's a chicken sandwich or a kid's hamburger. I rarely order fries. I eat slowly and savor each bite to feel full.
Potato chips and sugary cereals are in the pantry, but I'm not tempted. My kids eat them because I'd rather teach them moderation than total avoidance. If I eat them, I only eat one portion.
If you're not hungry and eating enough protein and fat, you won't want to eat everything in sight.
I drink once or twice a week. As a result, I rarely overdo it.
Food tracking is tedious and frustrating for many. Taking breaks and using estimates when eating out help. Not perfect, but realistic.
I practice a prolonged fast to enhance metabolic adaptability
Metabolic flexibility is the ability to switch between fuel sources (fat and carbs) based on activity intensity and time since eating. At rest or during low to moderate exertion, your body burns fat. Your body burns carbs after eating and during intense exercise.
Our metabolic flexibility can be hampered by lack of exercise, overeating, and stress. Our bodies become lousy fat burners, making weight loss difficult.
Once a week, I skip dinner (usually around 24 hours). Long-term fasting teaches my body to burn fat. It provides me one low-calorie day a week (I break the fast with a normal-sized dinner).
Fasting day helps me maintain my weight on weekends, when I typically overeat and drink.
Try an extended fast slowly. Delay breakfast by two hours. Next week, add two hours, etc. It takes practice to go that long without biting off your arm. I also suggest consulting your doctor.
I stay active.
I've always been active. As a child, I danced many nights a week, was on the high school dance team, and ran marathons in my 20s.
Often, I feel driven by an internal engine. Working from home makes it easy to exercise. If that’s not you, I get it. Everyone can benefit from raising their baseline.
After taking the kids to school, I walk two miles around the neighborhood. When I need to think, I switch off podcasts. First thing in the morning, I go for a walk.
I lift weights Monday, Wednesday, and Friday. 45 minutes is typical. I run 45-90 minutes on Tuesday and Thursday. I'm slow but reliable. On Saturdays and Sundays, I walk and add a short spin class if I'm not too tired.
I almost never forgo sleep.
I rarely stay up past 10 p.m., much to my night-owl husband's dismay. My 7-8-hour nights help me recover from workouts and handle stress. Without it, I'm grumpy.
I suppose sleep duration matters more than bedtime. Some people just can't fall asleep early. Internal clock and genetics determine sleep and wake hours.
Prioritize sleep.
Last thoughts
Fitness and diet advice is often useless. Some of the advice is inaccurate, dangerous, or difficult to follow if you have a life. I want to throw a shoe at my screen when I see headlines promising to speed up my metabolism or help me lose fat.
I studied exercise physiology for years. No shortcuts exist. No medications or cleanses reset metabolism. I play the hand I'm dealt. I realize that just because something works for me, it won't for you.
If I wanted 15% body fat and ripped abs, I'd have to be stricter. I occasionally think I’d like to get there. But then I remember I’m happy with my life. I like fast food and beer. Pizza and margaritas are favorites (not every day).
You can get it mostly right and live a healthy life.
Eric Esposito
3 years ago
$100M in NFT TV shows from Fox

Fox executives will invest $100 million in NFT-based TV shows. Fox brought in "Rick and Morty" co-creator Dan Harmon to create "Krapopolis"
Fox's Blockchain Creative Labs (BCL) will develop these NFT TV shows with Bento Box Entertainment. BCL markets Fox's WWE "Moonsault" NFT.
Fox said it would use the $100 million to build a "creative community" and "brand ecosystem." The media giant mentioned using these funds for NFT "benefits."
"Krapopolis" will be a Greek-themed animated comedy, per Rarity Sniper. Initial reports said NFT buyers could collaborate on "character development" and get exclusive perks.
Fox Entertainment may drop "Krapopolis" NFTs on Ethereum, according to new reports. Fox says it will soon release more details on its NFT plans for "Krapopolis."
Media Giants Favor "NFT Storytelling"
"Krapopolis" is one of the largest "NFT storytelling" experiments due to Dan Harmon's popularity and Fox Entertainment's reach. Many celebrities have begun exploring Web3 for TV shows.
Mila Kunis' animated sitcom "The Gimmicks" lets fans direct the show. Any "Gimmick" NFT holder could contribute to episode plots.
"The Gimmicks" lets NFT holders write fan fiction about their avatars. If show producers like what they read, their NFT may appear in an episode.
Rob McElhenney recently launched "Adimverse," a Web3 writers' community. Anyone with a "Adimverse" NFT can collaborate on creative projects and share royalties.
Many blue-chip NFTs are appearing in movies and TV shows. Coinbase will release Bored Ape Yacht Club shorts at NFT. NYC. Reese Witherspoon is working on a World of Women NFT series.
PFP NFT collections have Hollywood media partners. Guy Oseary manages Madonna's World of Women and Bored Ape Yacht Club collections. The Doodles signed with Billboard's Julian Holguin and the Cool Cats with CAA.
Web3 and NFTs are changing how many filmmakers tell stories.
