What An Inverted Yield Curve Means For Investors
The yield spread between 10-year and 2-year US Treasury bonds has fallen below 0.2 percent, its lowest level since March 2020. A flattening or negative yield curve can be a bad sign for the economy.
What Is An Inverted Yield Curve?
In the yield curve, bonds of equal credit quality but different maturities are plotted. The most commonly used yield curve for US investors is a plot of 2-year and 10-year Treasury yields, which have yet to invert.
A typical yield curve has higher interest rates for future maturities. In a flat yield curve, short-term and long-term yields are similar. Inverted yield curves occur when short-term yields exceed long-term yields. Inversions of yield curves have historically occurred during recessions.
Inverted yield curves have preceded each of the past eight US recessions. The good news is they're far leading indicators, meaning a recession is likely not imminent.
Every US recession since 1955 has occurred between six and 24 months after an inversion of the two-year and 10-year Treasury yield curves, according to the San Francisco Fed. So, six months before COVID-19, the yield curve inverted in August 2019.
Looking Ahead
The spread between two-year and 10-year Treasury yields was 0.18 percent on Tuesday, the smallest since before the last US recession. If the graph above continues, a two-year/10-year yield curve inversion could occur within the next few months.
According to Bank of America analyst Stephen Suttmeier, the S&P 500 typically peaks six to seven months after the 2s-10s yield curve inverts, and the US economy enters recession six to seven months later.
Investors appear unconcerned about the flattening yield curve. This is in contrast to the iShares 20+ Year Treasury Bond ETF TLT +2.19% which was down 1% on Tuesday.
Inversion of the yield curve and rising interest rates have historically harmed stocks. Recessions in the US have historically coincided with or followed the end of a Federal Reserve rate hike cycle, not the start.
More on Economics & Investing
Sofien Kaabar, CFA
2 years ago
Innovative Trading Methods: The Catapult Indicator
Python Volatility-Based Catapult Indicator
As a catapult, this technical indicator uses three systems: Volatility (the fulcrum), Momentum (the propeller), and a Directional Filter (Acting as the support). The goal is to get a signal that predicts volatility acceleration and direction based on historical patterns. We want to know when the market will move. and where. This indicator outperforms standard indicators.
Knowledge must be accessible to everyone. This is why my new publications Contrarian Trading Strategies in Python and Trend Following Strategies in Python now include free PDF copies of my first three books (Therefore, purchasing one of the new books gets you 4 books in total). GitHub-hosted advanced indications and techniques are in the two new books above.
The Foundation: Volatility
The Catapult predicts significant changes with the 21-period Relative Volatility Index.
The Average True Range, Mean Absolute Deviation, and Standard Deviation all assess volatility. Standard Deviation will construct the Relative Volatility Index.
Standard Deviation is the most basic volatility. It underpins descriptive statistics and technical indicators like Bollinger Bands. Before calculating Standard Deviation, let's define Variance.
Variance is the squared deviations from the mean (a dispersion measure). We take the square deviations to compel the distance from the mean to be non-negative, then we take the square root to make the measure have the same units as the mean, comparing apples to apples (mean to standard deviation standard deviation). Variance formula:
As stated, standard deviation is:
# The function to add a number of columns inside an array
def adder(Data, times):
for i in range(1, times + 1):
new_col = np.zeros((len(Data), 1), dtype = float)
Data = np.append(Data, new_col, axis = 1)
return Data
# The function to delete a number of columns starting from an index
def deleter(Data, index, times):
for i in range(1, times + 1):
Data = np.delete(Data, index, axis = 1)
return Data
# The function to delete a number of rows from the beginning
def jump(Data, jump):
Data = Data[jump:, ]
return Data
# Example of adding 3 empty columns to an array
my_ohlc_array = adder(my_ohlc_array, 3)
# Example of deleting the 2 columns after the column indexed at 3
my_ohlc_array = deleter(my_ohlc_array, 3, 2)
# Example of deleting the first 20 rows
my_ohlc_array = jump(my_ohlc_array, 20)
# Remember, OHLC is an abbreviation of Open, High, Low, and Close and it refers to the standard historical data file
def volatility(Data, lookback, what, where):
for i in range(len(Data)):
try:
Data[i, where] = (Data[i - lookback + 1:i + 1, what].std())
except IndexError:
pass
return Data
The RSI is the most popular momentum indicator, and for good reason—it excels in range markets. Its 0–100 range simplifies interpretation. Fame boosts its potential.
The more traders and portfolio managers look at the RSI, the more people will react to its signals, pushing market prices. Technical Analysis is self-fulfilling, therefore this theory is obvious yet unproven.
RSI is determined simply. Start with one-period pricing discrepancies. We must remove each closing price from the previous one. We then divide the smoothed average of positive differences by the smoothed average of negative differences. The RSI algorithm converts the Relative Strength from the last calculation into a value between 0 and 100.
def ma(Data, lookback, close, where):
Data = adder(Data, 1)
for i in range(len(Data)):
try:
Data[i, where] = (Data[i - lookback + 1:i + 1, close].mean())
except IndexError:
pass
# Cleaning
Data = jump(Data, lookback)
return Data
def ema(Data, alpha, lookback, what, where):
alpha = alpha / (lookback + 1.0)
beta = 1 - alpha
# First value is a simple SMA
Data = ma(Data, lookback, what, where)
# Calculating first EMA
Data[lookback + 1, where] = (Data[lookback + 1, what] * alpha) + (Data[lookback, where] * beta)
# Calculating the rest of EMA
for i in range(lookback + 2, len(Data)):
try:
Data[i, where] = (Data[i, what] * alpha) + (Data[i - 1, where] * beta)
except IndexError:
pass
return Datadef rsi(Data, lookback, close, where, width = 1, genre = 'Smoothed'):
# Adding a few columns
Data = adder(Data, 7)
# Calculating Differences
for i in range(len(Data)):
Data[i, where] = Data[i, close] - Data[i - width, close]
# Calculating the Up and Down absolute values
for i in range(len(Data)):
if Data[i, where] > 0:
Data[i, where + 1] = Data[i, where]
elif Data[i, where] < 0:
Data[i, where + 2] = abs(Data[i, where])
# Calculating the Smoothed Moving Average on Up and Down
absolute values
lookback = (lookback * 2) - 1 # From exponential to smoothed
Data = ema(Data, 2, lookback, where + 1, where + 3)
Data = ema(Data, 2, lookback, where + 2, where + 4)
# Calculating the Relative Strength
Data[:, where + 5] = Data[:, where + 3] / Data[:, where + 4]
# Calculate the Relative Strength Index
Data[:, where + 6] = (100 - (100 / (1 + Data[:, where + 5])))
# Cleaning
Data = deleter(Data, where, 6)
Data = jump(Data, lookback)
return Data
def relative_volatility_index(Data, lookback, close, where):
# Calculating Volatility
Data = volatility(Data, lookback, close, where)
# Calculating the RSI on Volatility
Data = rsi(Data, lookback, where, where + 1)
# Cleaning
Data = deleter(Data, where, 1)
return DataThe Arm Section: Speed
The Catapult predicts momentum direction using the 14-period Relative Strength Index.
As a reminder, the RSI ranges from 0 to 100. Two levels give contrarian signals:
A positive response is anticipated when the market is deemed to have gone too far down at the oversold level 30, which is 30.
When the market is deemed to have gone up too much, at overbought level 70, a bearish reaction is to be expected.
Comparing the RSI to 50 is another intriguing use. RSI above 50 indicates bullish momentum, while below 50 indicates negative momentum.
The direction-finding filter in the frame
The Catapult's directional filter uses the 200-period simple moving average to keep us trending. This keeps us sane and increases our odds.
Moving averages confirm and ride trends. Its simplicity and track record of delivering value to analysis make them the most popular technical indicator. They help us locate support and resistance, stops and targets, and the trend. Its versatility makes them essential trading tools.
This is the plain mean, employed in statistics and everywhere else in life. Simply divide the number of observations by their total values. Mathematically, it's:
We defined the moving average function above. Create the Catapult indication now.
Indicator of the Catapult
The indicator is a healthy mix of the three indicators:
The first trigger will be provided by the 21-period Relative Volatility Index, which indicates that there will now be above average volatility and, as a result, it is possible for a directional shift.
If the reading is above 50, the move is likely bullish, and if it is below 50, the move is likely bearish, according to the 14-period Relative Strength Index, which indicates the likelihood of the direction of the move.
The likelihood of the move's direction will be strengthened by the 200-period simple moving average. When the market is above the 200-period moving average, we can infer that bullish pressure is there and that the upward trend will likely continue. Similar to this, if the market falls below the 200-period moving average, we recognize that there is negative pressure and that the downside is quite likely to continue.
lookback_rvi = 21
lookback_rsi = 14
lookback_ma = 200
my_data = ma(my_data, lookback_ma, 3, 4)
my_data = rsi(my_data, lookback_rsi, 3, 5)
my_data = relative_volatility_index(my_data, lookback_rvi, 3, 6)Two-handled overlay indicator Catapult. The first exhibits blue and green arrows for a buy signal, and the second shows blue and red for a sell signal.
The chart below shows recent EURUSD hourly values.
def signal(Data, rvi_col, signal):
Data = adder(Data, 10)
for i in range(len(Data)):
if Data[i, rvi_col] < 30 and \
Data[i - 1, rvi_col] > 30 and \
Data[i - 2, rvi_col] > 30 and \
Data[i - 3, rvi_col] > 30 and \
Data[i - 4, rvi_col] > 30 and \
Data[i - 5, rvi_col] > 30:
Data[i, signal] = 1
return Data
Signals are straightforward. The indicator can be utilized with other methods.
my_data = signal(my_data, 6, 7)
Lumiwealth shows how to develop all kinds of algorithms. I recommend their hands-on courses in algorithmic trading, blockchain, and machine learning.
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.
After you find a trading method or approach, follow these steps:
Put emotions aside and adopt an analytical perspective.
Test it in the past in conditions and simulations taken from real life.
Try improving it and performing a forward test if you notice any possibility.
Transaction charges and any slippage simulation should always be included in your tests.
Risk management and position sizing should always be included in your tests.
After checking the aforementioned, monitor the plan because market dynamics may change and render it unprofitable.
Justin Kuepper
3 years ago
Day Trading Introduction
Historically, only large financial institutions, brokerages, and trading houses could actively trade in the stock market. With instant global news dissemination and low commissions, developments such as discount brokerages and online trading have leveled the playing—or should we say trading—field. It's never been easier for retail investors to trade like pros thanks to trading platforms like Robinhood and zero commissions.
Day trading is a lucrative career (as long as you do it properly). But it can be difficult for newbies, especially if they aren't fully prepared with a strategy. Even the most experienced day traders can lose money.
So, how does day trading work?
Day Trading Basics
Day trading is the practice of buying and selling a security on the same trading day. It occurs in all markets, but is most common in forex and stock markets. Day traders are typically well educated and well funded. For small price movements in highly liquid stocks or currencies, they use leverage and short-term trading strategies.
Day traders are tuned into short-term market events. News trading is a popular strategy. Scheduled announcements like economic data, corporate earnings, or interest rates are influenced by market psychology. Markets react when expectations are not met or exceeded, usually with large moves, which can help day traders.
Intraday trading strategies abound. Among these are:
- Scalping: This strategy seeks to profit from minor price changes throughout the day.
- Range trading: To determine buy and sell levels, range traders use support and resistance levels.
- News-based trading exploits the increased volatility around news events.
- High-frequency trading (HFT): The use of sophisticated algorithms to exploit small or short-term market inefficiencies.
A Disputed Practice
Day trading's profit potential is often debated on Wall Street. Scammers have enticed novices by promising huge returns in a short time. Sadly, the notion that trading is a get-rich-quick scheme persists. Some daytrade without knowledge. But some day traders succeed despite—or perhaps because of—the risks.
Day trading is frowned upon by many professional money managers. They claim that the reward rarely outweighs the risk. Those who day trade, however, claim there are profits to be made. Profitable day trading is possible, but it is risky and requires considerable skill. Moreover, economists and financial professionals agree that active trading strategies tend to underperform passive index strategies over time, especially when fees and taxes are factored in.
Day trading is not for everyone and is risky. It also requires a thorough understanding of how markets work and various short-term profit strategies. Though day traders' success stories often get a lot of media attention, keep in mind that most day traders are not wealthy: Many will fail, while others will barely survive. Also, while skill is important, bad luck can sink even the most experienced day trader.
Characteristics of a Day Trader
Experts in the field are typically well-established professional day traders.
They usually have extensive market knowledge. Here are some prerequisites for successful day trading.
Market knowledge and experience
Those who try to day-trade without understanding market fundamentals frequently lose. Day traders should be able to perform technical analysis and read charts. Charts can be misleading if not fully understood. Do your homework and know the ins and outs of the products you trade.
Enough capital
Day traders only use risk capital they can lose. This not only saves them money but also helps them trade without emotion. To profit from intraday price movements, a lot of capital is often required. Most day traders use high levels of leverage in margin accounts, and volatile market swings can trigger large margin calls on short notice.
Strategy
A trader needs a competitive advantage. Swing trading, arbitrage, and trading news are all common day trading strategies. They tweak these strategies until they consistently profit and limit losses.
Strategy Breakdown:
Type | Risk | Reward
Swing Trading | High | High
Arbitrage | Low | Medium
Trading News | Medium | Medium
Mergers/Acquisitions | Medium | High
Discipline
A profitable strategy is useless without discipline. Many day traders lose money because they don't meet their own criteria. “Plan the trade and trade the plan,” they say. Success requires discipline.
Day traders profit from market volatility. For a day trader, a stock's daily movement is appealing. This could be due to an earnings report, investor sentiment, or even general economic or company news.
Day traders also prefer highly liquid stocks because they can change positions without affecting the stock's price. Traders may buy a stock if the price rises. If the price falls, a trader may decide to sell short to profit.
A day trader wants to trade a stock that moves (a lot).
Day Trading for a Living
Professional day traders can be self-employed or employed by a larger institution.
Most day traders work for large firms like hedge funds and banks' proprietary trading desks. These traders benefit from direct counterparty lines, a trading desk, large capital and leverage, and expensive analytical software (among other advantages). By taking advantage of arbitrage and news events, these traders can profit from less risky day trades before individual traders react.
Individual traders often manage other people’s money or simply trade with their own. They rarely have access to a trading desk, but they frequently have strong ties to a brokerage (due to high commissions) and other resources. However, their limited scope prevents them from directly competing with institutional day traders. Not to mention more risks. Individuals typically day trade highly liquid stocks using technical analysis and swing trades, with some leverage.
Day trading necessitates access to some of the most complex financial products and services. Day traders usually need:
Access to a trading desk
Traders who work for large institutions or manage large sums of money usually use this. The trading or dealing desk provides these traders with immediate order execution, which is critical during volatile market conditions. For example, when an acquisition is announced, day traders interested in merger arbitrage can place orders before the rest of the market.
News sources
The majority of day trading opportunities come from news, so being the first to know when something significant happens is critical. It has access to multiple leading newswires, constant news coverage, and software that continuously analyzes news sources for important stories.
Analytical tools
Most day traders rely on expensive trading software. Technical traders and swing traders rely on software more than news. This software's features include:
-
Automatic pattern recognition: It can identify technical indicators like flags and channels, or more complex indicators like Elliott Wave patterns.
-
Genetic and neural applications: These programs use neural networks and genetic algorithms to improve trading systems and make more accurate price predictions.
-
Broker integration: Some of these apps even connect directly to the brokerage, allowing for instant and even automatic trade execution. This reduces trading emotion and improves execution times.
-
Backtesting: This allows traders to look at past performance of a strategy to predict future performance. Remember that past results do not always predict future results.
Together, these tools give traders a competitive advantage. It's easy to see why inexperienced traders lose money without them. A day trader's earnings potential is also affected by the market in which they trade, their capital, and their time commitment.
Day Trading Risks
Day trading can be intimidating for the average investor due to the numerous risks involved. The SEC highlights the following risks of day trading:
Because day traders typically lose money in their first months of trading and many never make profits, they should only risk money they can afford to lose.
Trading is a full-time job that is stressful and costly: Observing dozens of ticker quotes and price fluctuations to spot market trends requires intense concentration. Day traders also spend a lot on commissions, training, and computers.
Day traders heavily rely on borrowing: Day-trading strategies rely on borrowed funds to make profits, which is why many day traders lose everything and end up in debt.
Avoid easy profit promises: Avoid “hot tips” and “expert advice” from day trading newsletters and websites, and be wary of day trading educational seminars and classes.
Should You Day Trade?
As stated previously, day trading as a career can be difficult and demanding.
- First, you must be familiar with the trading world and know your risk tolerance, capital, and goals.
- Day trading also takes a lot of time. You'll need to put in a lot of time if you want to perfect your strategies and make money. Part-time or whenever isn't going to cut it. You must be fully committed.
- If you decide trading is for you, remember to start small. Concentrate on a few stocks rather than jumping into the market blindly. Enlarging your trading strategy can result in big losses.
- Finally, keep your cool and avoid trading emotionally. The more you can do that, the better. Keeping a level head allows you to stay focused and on track.
If you follow these simple rules, you may be on your way to a successful day trading career.
Is Day Trading Illegal?
Day trading is not illegal or unethical, but it is risky. Because most day-trading strategies use margin accounts, day traders risk losing more than they invest and becoming heavily in debt.
How Can Arbitrage Be Used in Day Trading?
Arbitrage is the simultaneous purchase and sale of a security in multiple markets to profit from small price differences. Because arbitrage ensures that any deviation in an asset's price from its fair value is quickly corrected, arbitrage opportunities are rare.
Why Don’t Day Traders Hold Positions Overnight?
Day traders rarely hold overnight positions for several reasons: Overnight trades require more capital because most brokers require higher margin; stocks can gap up or down on overnight news, causing big trading losses; and holding a losing position overnight in the hope of recovering some or all of the losses may be against the trader's core day-trading philosophy.
What Are Day Trader Margin Requirements?
Regulation D requires that a pattern day trader client of a broker-dealer maintain at all times $25,000 in equity in their account.
How Much Buying Power Does Day Trading Have?
Buying power is the total amount of funds an investor has available to trade securities. FINRA rules allow a pattern day trader to trade up to four times their maintenance margin excess as of the previous day's close.
The Verdict
Although controversial, day trading can be a profitable strategy. Day traders, both institutional and retail, keep the markets efficient and liquid. Though day trading is still popular among novice traders, it should be left to those with the necessary skills and resources.
Ray Dalio
3 years ago
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.
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Tim Denning
3 years ago
One of the biggest publishers in the world offered me a book deal, but I don't feel deserving of it.
My ego is so huge it won't fit through the door.
I don't know how I feel about it. I should be excited. Many of you have this exact dream to publish a book with a well-known book publisher and get a juicy advance.
Let me dissect how I'm thinking about it to help you.
How it happened
An email comes in. A generic "can we put a backlink on your website and get a freebie" email.
Almost deleted it.
Then I noticed the logo. It seemed shady. I found the URL. Check. I searched the employee's LinkedIn. Legit. I avoided middlemen. Check.
Mixed feelings. LinkedIn hasn't valued my writing for years. I'm just a guy in an unironed t-shirt whose content they sell advertising against.
They get big dollars. I get $0 and a few likes, plus some email subscribers.
Still, I felt adrenaline for hours.
I texted a few friends to see how they felt. I wrapped them.
Messages like "No shocker. You're entertaining online." I didn't like praises, so I blushed.
The thrill faded after hours. Who knows?
Most authors desire this chance.
"You entitled piece of crap, Denning!"
You may think so. Okay. My job is to stand on the internet and get bananas thrown at me.
I approached writing backwards. More important than a book deal was a social media audience converted to an email list.
Romantic authors think backward. They hope a fantastic book will land them a deal and an audience.
Rarely occurs. So I never pursued it. It's like permission-seeking or the lottery.
Not being a professional writer, I've never written a good book. I post online for fun and to express my opinions.
Writing is therapeutic. I overcome mental illness and rebuilt my life this way. Without blogging, I'd be dead.
I've always dreamed of staying alive and doing something I love, not getting a book contract. Writing is my passion. I'm a winner without a book deal.
Why I was given a book deal
You may assume I received a book contract because of my views or follows. Nope.
They gave me a deal because they like my writing style. I've heard this for eight years.
Several authors agree. One asked me to improve their writer's voice.
Takeaway: highlight your writer's voice.
What if they discover I'm writing incompetently?
An edited book is published. It's edited.
I need to master writing mechanics, thus this concerns me. I need help with commas and sentence construction.
I must learn verb, noun, and adjective. Seriously.
Writing a book may reveal my imposter status to a famous publisher. Imagine the email
"It happened again. He doesn't even know how to spell. He thinks 'less' is the correct word, not 'fewer.' Are you sure we should publish his book?"
Fears stink.
I'm capable of blogging. Even listicles. So what?
Writing for a major publisher feels advanced.
I only blog. I'm good at listicles. Digital media executives have criticized me for this.
It is allegedly clickbait.
Or it is following trends.
Alternately, growth hacking.
Never. I learned copywriting to improve my writing.
Apple, Amazon, and Tesla utilize copywriting to woo customers. Whoever thinks otherwise is the wisest person in the room.
Old-schoolers loathe copywriters.
Their novels sell nothing.
They assume their elitist version of writing is better and that the TikTok generation will invest time in random writing with no subheadings and massive walls of text they can't read on their phones.
I'm terrified of book proposals.
My friend's book proposal suggestion was contradictory and made no sense.
They told him to compose another genre. This book got three Amazon reviews. Is that a good model?
The process disappointed him. I've heard other book proposal horror stories. Tim Ferriss' book "The 4-Hour Workweek" was criticized.
Because he has thick skin, his book came out. He wouldn't be known without that.
I hate book proposals.
An ongoing commitment
Writing a book is time-consuming.
I appreciate time most. I want to focus on my daughter for the next few years. I can't recreate her childhood because of a book.
No idea how parents balance kids' goals.
My silly face in a bookstore. Really?
Genuine thought.
I don't want my face in bookstores. I fear fame. I prefer anonymity.
I want to purchase a property in a bad Australian area, then piss off and play drums. Is bookselling worth it?
Are there even bookstores anymore?
(Except for Ryan Holiday's legendary Painted Porch Bookshop in Texas.)
What's most important about books
Many were duped.
Tweets and TikTok hopscotch vids are their future. Short-form content creates devoted audiences that buy newsletter subscriptions.
Books=depth.
Depth wins (if you can get people to buy your book). Creating a book will strengthen my reader relationships.
It's cheaper than my classes, so more people can benefit from my life lessons.
A deeper justification for writing a book
Mind wandered.
If I write this book, my daughter will follow it. "Look what you can do, love, when you ignore critics."
That's my favorite.
I'll be her best leader and teacher. If her dad can accomplish this, she can too.
My kid can read my book when I'm gone to remember her loving father.
Last paragraph made me cry.
The positive
This book thing might make me sound like Karen.
The upside is... Building in public, like I have with online writing, attracts the right people.
Proof-of-work over proposals, beautiful words, or huge aspirations. If you want a book deal, try writing online instead of the old manner.
Next steps
No idea.
I'm a rural Aussie. Writing a book in the big city is intimidating. Will I do it? Lots to think about. Right now, some level of reflection and gratitude feels most appropriate.
Sometimes when you don't feel worthy, it gives you the greatest lessons. That's how I feel about getting offered this book deal.
Perhaps you can relate.
Max Chafkin
3 years ago
Elon Musk Bets $44 Billion on Free Speech's Future
Musk’s purchase of Twitter has sealed his bond with the American right—whether the platform’s left-leaning employees and users like it or not.
Elon Musk's pursuit of Twitter Inc. began earlier this month as a joke. It started slowly, then spiraled out of control, culminating on April 25 with the world's richest man agreeing to spend $44 billion on one of the most politically significant technology companies ever. There have been bigger financial acquisitions, but Twitter's significance has always outpaced its balance sheet. This is a unique Silicon Valley deal.
To recap: Musk announced in early April that he had bought a stake in Twitter, citing the company's alleged suppression of free speech. His complaints were vague, relying heavily on the dog whistles of the ultra-right. A week later, he announced he'd buy the company for $54.20 per share, four days after initially pledging to join Twitter's board. Twitter's directors noticed the 420 reference as well, and responded with a “shareholder rights” plan (i.e., a poison pill) that included a 420 joke.
Musk - Patrick Pleul/Getty Images
No one knew if the bid was genuine. Musk's Twitter plans seemed implausible or insincere. In a tweet, he referred to automated accounts that use his name to promote cryptocurrency. He enraged his prospective employees by suggesting that Twitter's San Francisco headquarters be turned into a homeless shelter, renaming the company Titter, and expressing solidarity with his growing conservative fan base. “The woke mind virus is making Netflix unwatchable,” he tweeted on April 19.
But Musk got funding, and after a frantic weekend of negotiations, Twitter said yes. Unlike most buyouts, Musk will personally fund the deal, putting up up to $21 billion in cash and borrowing another $12.5 billion against his Tesla stock.
Free Speech and Partisanship
Percentage of respondents who agree with the following
The deal is expected to replatform accounts that were banned by Twitter for harassing others, spreading misinformation, or inciting violence, such as former President Donald Trump's account. As a result, Musk is at odds with his own left-leaning employees, users, and advertisers, who would prefer more content moderation rather than less.
Dorsey - Photographer: Joe Raedle/Getty Images
Previously, the company's leadership had similar issues. Founder Jack Dorsey stepped down last year amid concerns about slowing growth and product development, as well as his dual role as CEO of payments processor Block Inc. Compared to Musk, a father of seven who already runs four companies (besides Tesla and SpaceX), Dorsey is laser-focused.
Musk's motivation to buy Twitter may be political. Affirming the American far right with $44 billion spent on “free speech” Right-wing activists have promoted a series of competing upstart Twitter competitors—Parler, Gettr, and Trump's own effort, Truth Social—since Trump was banned from major social media platforms for encouraging rioters at the US Capitol on Jan. 6, 2021. But Musk can give them a social network with lax content moderation and a real user base. Trump said he wouldn't return to Twitter after the deal was announced, but he wouldn't be the first to do so.
Trump - Eli Hiller/Bloomberg
Conservative activists and lawmakers are already ecstatic. “A great day for free speech in America,” said Missouri Republican Josh Hawley. The day the deal was announced, Tucker Carlson opened his nightly Fox show with a 10-minute laudatory monologue. “The single biggest political development since Donald Trump's election in 2016,” he gushed over Musk.
But Musk's supporters and detractors misunderstand how much his business interests influence his political ideology. He marketed Tesla's cars as carbon-saving machines that were faster and cooler than gas-powered luxury cars during George W. Bush's presidency. Musk gained a huge following among wealthy environmentalists who reserved hundreds of thousands of Tesla sedans years before they were made during Barack Obama's presidency. Musk in the Trump era advocated for a carbon tax, but he also fought local officials (and his own workers) over Covid rules that slowed the reopening of his Bay Area factory.
Teslas at the Las Vegas Convention Center Loop Central Station in April 2021. The Las Vegas Convention Center Loop was Musk's first commercial project. Ethan Miller/Getty Images
Musk's rightward shift matched the rise of the nationalist-populist right and the desire to serve a growing EV market. In 2019, he unveiled the Cybertruck, a Tesla pickup, and in 2018, he announced plans to manufacture it at a new plant outside Austin. In 2021, he decided to move Tesla's headquarters there, citing California's "land of over-regulation." After Ford and General Motors beat him to the electric truck market, Musk reframed Tesla as a company for pickup-driving dudes.
Similarly, his purchase of Twitter will be entwined with his other business interests. Tesla has a factory in China and is friendly with Beijing. This could be seen as a conflict of interest when Musk's Twitter decides how to treat Chinese-backed disinformation, as Amazon.com Inc. founder Jeff Bezos noted.
Musk has focused on Twitter's product and social impact, but the company's biggest challenges are financial: Either increase cash flow or cut costs to comfortably service his new debt. Even if Musk can't do that, he can still benefit from the deal. He has recently used the increased attention to promote other business interests: Boring has hyperloops and Neuralink brain implants on the way, Musk tweeted. Remember Tesla's long-promised robotaxis!
Musk may be comfortable saying he has no expectation of profit because it benefits his other businesses. At the TED conference on April 14, Musk insisted that his interest in Twitter was solely charitable. “I don't care about money.”
The rockets and weed jokes make it easy to see Musk as unique—and his crazy buyout will undoubtedly add to that narrative. However, he is a megabillionaire who is risking a small amount of money (approximately 13% of his net worth) to gain potentially enormous influence. Musk makes everything seem new, but this is a rehash of an old media story.
Amelia Winger-Bearskin
3 years ago
Hate NFTs? I must break some awful news to you...
If you think NFTs are awful, check out the art market.
The fervor around NFTs has subsided in recent months due to the crypto market crash and the media's short attention span. They were all anyone could talk about earlier this spring. Last semester, when passions were high and field luminaries were discussing "slurp juices," I asked my students and students from over 20 other universities what they thought of NFTs.
According to many, NFTs were either tasteless pyramid schemes or a new way for artists to make money. NFTs contributed to the climate crisis and harmed the environment, but so did air travel, fast fashion, and smartphones. Some students complained that NFTs were cheap, tasteless, algorithmically generated schlock, but others asked how this was different from other art.
I'm not sure what I expected, but the intensity of students' reactions surprised me. They had strong, emotional opinions about a technology I'd always considered administrative. NFTs address ownership and accounting, like most crypto/blockchain projects.
Art markets can be irrational, arbitrary, and subject to the same scams and schemes as any market. And maybe a few shenanigans that are unique to the art world.
The Fairness Question
Fairness, a deflating moral currency, was the general sentiment (the less of it in circulation, the more ardently we clamor for it.) These students, almost all of whom are artists, complained to the mismatch between the quality of the work in some notable NFT collections and the excessive amounts these items were fetching on the market. They can sketch a Bored Ape or Lazy Lion in their sleep. Why should they buy ramen with school loans while certain swindlers get rich?
I understand students. Art markets are unjust. They can be irrational, arbitrary, and governed by chance and circumstance, like any market. And art-world shenanigans.
Almost every mainstream critique leveled against NFTs applies just as easily to art markets
Over 50% of artworks in circulation are fake, say experts. Sincere art collectors and institutions are upset by the prevalence of fake goods on the market. Not everyone. Wealthy people and companies use art as investments. They can use cultural institutions like museums and galleries to increase the value of inherited art collections. People sometimes buy artworks and use family ties or connections to museums or other cultural taste-makers to hype the work in their collection, driving up the price and allowing them to sell for a profit. Money launderers can disguise capital flows by using market whims, hype, and fluctuating asset prices.
Almost every mainstream critique leveled against NFTs applies just as easily to art markets.
Art has always been this way. Edward Kienholz's 1989 print series satirized art markets. He stamped 395 identical pieces of paper from $1 to $395. Each piece was initially priced as indicated. Kienholz was joking about a strange feature of art markets: once the last print in a series sells for $395, all previous works are worth at least that much. The entire series is valued at its highest auction price. I don't know what a Kienholz print sells for today (inquire with the gallery), but it's more than $395.
I love Lee Lozano's 1969 "Real Money Piece." Lozano put cash in various denominations in a jar in her apartment and gave it to visitors. She wrote, "Offer guests coffee, diet pepsi, bourbon, half-and-half, ice water, grass, and money." "Offer real money as candy."
Lee Lozano kept track of who she gave money to, how much they took, if any, and how they reacted to the offer of free money without explanation. Diverse reactions. Some found it funny, others found it strange, and others didn't care. Lozano rarely says:
Apr 17 Keith Sonnier refused, later screws lid very tightly back on. Apr 27 Kaltenbach takes all the money out of the jar when I offer it, examines all the money & puts it all back in jar. Says he doesn’t need money now. Apr 28 David Parson refused, laughing. May 1 Warren C. Ingersoll refused. He got very upset about my “attitude towards money.” May 4 Keith Sonnier refused, but said he would take money if he needed it which he might in the near future. May 7 Dick Anderson barely glances at the money when I stick it under his nose and says “Oh no thanks, I intend to earn it on my own.” May 8 Billy Bryant Copley didn’t take any but then it was sort of spoiled because I had told him about this piece on the phone & he had time to think about it he said.
Smart Contracts (smart as in fair, not smart as in Blockchain)
Cornell University's Cheryl Finley has done a lot of research on secondary art markets. I first learned about her research when I met her at the University of Florida's Harn Museum, where she spoke about smart contracts (smart as in fair, not smart as in Blockchain) and new protocols that could help artists who are often left out of the economic benefits of their own work, including women and women of color.
Her talk included findings from her ArtNet op-ed with Lauren van Haaften-Schick, Christian Reeder, and Amy Whitaker.
NFTs allow us to think about and hack on formal contractual relationships outside a system of laws that is currently not set up to service our community.
The ArtNet article The Recent Sale of Amy Sherald's ‘Welfare Queen' Symbolizes the Urgent Need for Resale Royalties and Economic Equity for Artists discussed Sherald's 2012 portrait of a regal woman in a purple dress wearing a sparkling crown and elegant set of pearls against a vibrant red background.
Amy Sherald sold "Welfare Queen" to Princeton professor Imani Perry. Sherald agreed to a payment plan to accommodate Perry's budget.
Amy Sherald rose to fame for her 2016 portrait of Michelle Obama and her full-length portrait of Breonna Taylor, one of the most famous works of the past decade.
As is common, Sherald's rising star drove up the price of her earlier works. Perry's "Welfare Queen" sold for $3.9 million in 2021.
Imani Perry's early investment paid off big-time. Amy Sherald, whose work directly increased the painting's value and who was on an artist's shoestring budget when she agreed to sell "Welfare Queen" in 2012, did not see any of the 2021 auction money. Perry and the auction house got that money.
Sherald sold her Breonna Taylor portrait to the Smithsonian and Louisville's Speed Art Museum to fund a $1 million scholarship. This is a great example of what an artist can do for the community if they can amass wealth through their work.
NFTs haven't solved all of the art market's problems — fakes, money laundering, market manipulation — but they didn't create them. Blockchain and NFTs are credited with making these issues more transparent. More ideas emerge daily about what a smart contract should do for artists.
NFTs are a copyright solution. They allow us to hack formal contractual relationships outside a law system that doesn't serve our community.
Amy Sherald shows the good smart contracts can do (as in, well-considered, self-determined contracts, not necessarily blockchain contracts.) Giving back to our community, deciding where and how our work can be sold or displayed, and ensuring artists share in the equity of our work and the economy our labor creates.
