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
Thomas Huault
3 years ago
A Mean Reversion Trading Indicator Inspired by Classical Mechanics Is The Kinetic Detrender
DATA MINING WITH SUPERALGORES
Old pots produce the best soup.
Science has always inspired indicator design. From physics to signal processing, many indicators use concepts from mechanical engineering, electronics, and probability. In Superalgos' Data Mining section, we've explored using thermodynamics and information theory to construct indicators and using statistical and probabilistic techniques like reduced normal law to take advantage of low probability events.
An asset's price is like a mechanical object revolving around its moving average. Using this approach, we could design an indicator using the oscillator's Total Energy. An oscillator's energy is finite and constant. Since we don't expect the price to follow the harmonic oscillator, this energy should deviate from the perfect situation, and the maximum of divergence may provide us valuable information on the price's moving average.
Definition of the Harmonic Oscillator in Few Words
Sinusoidal function describes a harmonic oscillator. The time-constant energy equation for a harmonic oscillator is:
With
Time saves energy.
In a mechanical harmonic oscillator, total energy equals kinetic energy plus potential energy. The formula for energy is the same for every kind of harmonic oscillator; only the terms of total energy must be adapted to fit the relevant units. Each oscillator has a velocity component (kinetic energy) and a position to equilibrium component (potential energy).
The Price Oscillator and the Energy Formula
Considering the harmonic oscillator definition, we must specify kinetic and potential components for our price oscillator. We define oscillator velocity as the rate of change and equilibrium position as the price's distance from its moving average.
Price kinetic energy:
It's like:
With
and
L is the number of periods for the rate of change calculation and P for the close price EMA calculation.
Total price oscillator energy =
Given that an asset's price can theoretically vary at a limitless speed and be endlessly far from its moving average, we don't expect this formula's outcome to be constrained. We'll normalize it using Z-Score for convenience of usage and readability, which also allows probabilistic interpretation.
Over 20 periods, we'll calculate E's moving average and standard deviation.
We calculated Z on BTC/USDT with L = 10 and P = 21 using Knime Analytics.
The graph is detrended. We added two horizontal lines at +/- 1.6 to construct a 94.5% probability zone based on reduced normal law tables. Price cycles to its moving average oscillate clearly. Red and green arrows illustrate where the oscillator crosses the top and lower limits, corresponding to the maximum/minimum price oscillation. Since the results seem noisy, we may apply a non-lagging low-pass or multipole filter like Butterworth or Laguerre filters and employ dynamic bands at a multiple of Z's standard deviation instead of fixed levels.
Kinetic Detrender Implementation in Superalgos
The Superalgos Kinetic detrender features fixed upper and lower levels and dynamic volatility bands.
The code is pretty basic and does not require a huge amount of code lines.
It starts with the standard definitions of the candle pointer and the constant declaration :
let candle = record.current
let len = 10
let P = 21
let T = 20
let up = 1.6
let low = 1.6Upper and lower dynamic volatility band constants are up and low.
We proceed to the initialization of the previous value for EMA :
if (variable.prevEMA === undefined) {
variable.prevEMA = candle.close
}And the calculation of EMA with a function (it is worth noticing the function is declared at the end of the code snippet in Superalgos) :
variable.ema = calculateEMA(P, candle.close, variable.prevEMA)
//EMA calculation
function calculateEMA(periods, price, previousEMA) {
let k = 2 / (periods + 1)
return price * k + previousEMA * (1 - k)
}The rate of change is calculated by first storing the right amount of close price values and proceeding to the calculation by dividing the current close price by the first member of the close price array:
variable.allClose.push(candle.close)
if (variable.allClose.length > len) {
variable.allClose.splice(0, 1)
}
if (variable.allClose.length === len) {
variable.roc = candle.close / variable.allClose[0]
} else {
variable.roc = 1
}Finally, we get energy with a single line:
variable.E = 1 / 2 * len * variable.roc + 1 / 2 * P * candle.close / variable.emaThe Z calculation reuses code from Z-Normalization-based indicators:
variable.allE.push(variable.E)
if (variable.allE.length > T) {
variable.allE.splice(0, 1)
}
variable.sum = 0
variable.SQ = 0
if (variable.allE.length === T) {
for (var i = 0; i < T; i++) {
variable.sum += variable.allE[i]
}
variable.MA = variable.sum / T
for (var i = 0; i < T; i++) {
variable.SQ += Math.pow(variable.allE[i] - variable.MA, 2)
}
variable.sigma = Math.sqrt(variable.SQ / T)
variable.Z = (variable.E - variable.MA) / variable.sigma
} else {
variable.Z = 0
}
variable.allZ.push(variable.Z)
if (variable.allZ.length > T) {
variable.allZ.splice(0, 1)
}
variable.sum = 0
variable.SQ = 0
if (variable.allZ.length === T) {
for (var i = 0; i < T; i++) {
variable.sum += variable.allZ[i]
}
variable.MAZ = variable.sum / T
for (var i = 0; i < T; i++) {
variable.SQ += Math.pow(variable.allZ[i] - variable.MAZ, 2)
}
variable.sigZ = Math.sqrt(variable.SQ / T)
} else {
variable.MAZ = variable.Z
variable.sigZ = variable.MAZ * 0.02
}
variable.upper = variable.MAZ + up * variable.sigZ
variable.lower = variable.MAZ - low * variable.sigZWe also update the EMA value.
variable.prevEMA = variable.EMA
Conclusion
We showed how to build a detrended oscillator using simple harmonic oscillator theory. Kinetic detrender's main line oscillates between 2 fixed levels framing 95% of the values and 2 dynamic levels, leading to auto-adaptive mean reversion zones.
Superalgos' Normalized Momentum data mine has the Kinetic detrender indication.
All the material here can be reused and integrated freely by linking to this article and Superalgos.
This post is informative and not financial advice. Seek expert counsel before trading. Risk using this material.
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Adam Hayes
3 years ago
Bernard Lawrence "Bernie" Madoff, the largest Ponzi scheme in history
Madoff who?
Bernie Madoff ran the largest Ponzi scheme in history, defrauding thousands of investors over at least 17 years, and possibly longer. He pioneered electronic trading and chaired Nasdaq in the 1990s. On April 14, 2021, he died while serving a 150-year sentence for money laundering, securities fraud, and other crimes.
Understanding Madoff
Madoff claimed to generate large, steady returns through a trading strategy called split-strike conversion, but he simply deposited client funds into a single bank account and paid out existing clients. He funded redemptions by attracting new investors and their capital, but the market crashed in late 2008. He confessed to his sons, who worked at his firm, on Dec. 10, 2008. Next day, they turned him in. The fund reported $64.8 billion in client assets.
Madoff pleaded guilty to 11 federal felony counts, including securities fraud, wire fraud, mail fraud, perjury, and money laundering. Ponzi scheme became a symbol of Wall Street's greed and dishonesty before the financial crisis. Madoff was sentenced to 150 years in prison and ordered to forfeit $170 billion, but no other Wall Street figures faced legal ramifications.
Bernie Madoff's Brief Biography
Bernie Madoff was born in Queens, New York, on April 29, 1938. He began dating Ruth (née Alpern) when they were teenagers. Madoff told a journalist by phone from prison that his father's sporting goods store went bankrupt during the Korean War: "You watch your father, who you idolize, build a big business and then lose everything." Madoff was determined to achieve "lasting success" like his father "whatever it took," but his career had ups and downs.
Early Madoff investments
At 22, he started Bernard L. Madoff Investment Securities LLC. First, he traded penny stocks with $5,000 he earned installing sprinklers and as a lifeguard. Family and friends soon invested with him. Madoff's bets soured after the "Kennedy Slide" in 1962, and his father-in-law had to bail him out.
Madoff felt he wasn't part of the Wall Street in-crowd. "We weren't NYSE members," he told Fishman. "It's obvious." According to Madoff, he was a scrappy market maker. "I was happy to take the crumbs," he told Fishman, citing a client who wanted to sell eight bonds; a bigger firm would turn it down.
Recognition
Success came when he and his brother Peter built electronic trading capabilities, or "artificial intelligence," that attracted massive order flow and provided market insights. "I had all these major banks coming down, entertaining me," Madoff told Fishman. "It was mind-bending."
By the late 1980s, he and four other Wall Street mainstays processed half of the NYSE's order flow. Controversially, he paid for much of it, and by the late 1980s, Madoff was making in the vicinity of $100 million a year. He was Nasdaq chairman from 1990 to 1993.
Madoff's Ponzi scheme
It is not certain exactly when Madoff's Ponzi scheme began. He testified in court that it began in 1991, but his account manager, Frank DiPascali, had been at the firm since 1975.
Why Madoff did the scheme is unclear. "I had enough money to support my family's lifestyle. "I don't know why," he told Fishman." Madoff could have won Wall Street's respect as a market maker and electronic trading pioneer.
Madoff told Fishman he wasn't solely responsible for the fraud. "I let myself be talked into something, and that's my fault," he said, without saying who convinced him. "I thought I could escape eventually. I thought it'd be quick, but I couldn't."
Carl Shapiro, Jeffry Picower, Stanley Chais, and Norm Levy have been linked to Bernard L. Madoff Investment Securities LLC for years. Madoff's scheme made these men hundreds of millions of dollars in the 1960s and 1970s.
Madoff told Fishman, "Everyone was greedy, everyone wanted to go on." He says the Big Four and others who pumped client funds to him, outsourcing their asset management, must have suspected his returns or should have. "How can you make 15%-18% when everyone else is making less?" said Madoff.
How Madoff Got Away with It for So Long
Madoff's high returns made clients look the other way. He deposited their money in a Chase Manhattan Bank account, which merged to become JPMorgan Chase & Co. in 2000. The bank may have made $483 million from those deposits, so it didn't investigate.
When clients redeemed their investments, Madoff funded the payouts with new capital he attracted by promising unbelievable returns and earning his victims' trust. Madoff created an image of exclusivity by turning away clients. This model let half of Madoff's investors profit. These investors must pay into a victims' fund for defrauded investors.
Madoff wooed investors with his philanthropy. He defrauded nonprofits, including the Elie Wiesel Foundation for Peace and Hadassah. He approached congregants through his friendship with J. Ezra Merkin, a synagogue officer. Madoff allegedly stole $1 billion to $2 billion from his investors.
Investors believed Madoff for several reasons:
- His public portfolio seemed to be blue-chip stocks.
- His returns were high (10-20%) but consistent and not outlandish. In a 1992 interview with Madoff, the Wall Street Journal reported: "[Madoff] insists the returns were nothing special, given that the S&P 500-stock index returned 16.3% annually from 1982 to 1992. 'I'd be surprised if anyone thought matching the S&P over 10 years was remarkable,' he says.
- "He said he was using a split-strike collar strategy. A collar protects underlying shares by purchasing an out-of-the-money put option.
SEC inquiry
The Securities and Exchange Commission had been investigating Madoff and his securities firm since 1999, which frustrated many after he was prosecuted because they felt the biggest damage could have been prevented if the initial investigations had been rigorous enough.
Harry Markopolos was a whistleblower. In 1999, he figured Madoff must be lying in an afternoon. The SEC ignored his first Madoff complaint in 2000.
Markopolos wrote to the SEC in 2005: "The largest Ponzi scheme is Madoff Securities. This case has no SEC reward, so I'm turning it in because it's the right thing to do."
Many believed the SEC's initial investigations could have prevented Madoff's worst damage.
Markopolos found irregularities using a "Mosaic Method." Madoff's firm claimed to be profitable even when the S&P fell, which made no mathematical sense given what he was investing in. Markopolos said Madoff Securities' "undisclosed commissions" were the biggest red flag (1 percent of the total plus 20 percent of the profits).
Markopolos concluded that "investors don't know Bernie Madoff manages their money." Markopolos learned Madoff was applying for large loans from European banks (seemingly unnecessary if Madoff's returns were high).
The regulator asked Madoff for trading account documentation in 2005, after he nearly went bankrupt due to redemptions. The SEC drafted letters to two of the firms on his six-page list but didn't send them. Diana Henriques, author of "The Wizard of Lies: Bernie Madoff and the Death of Trust," documents the episode.
In 2008, the SEC was criticized for its slow response to Madoff's fraud.
Confession, sentencing of Bernie Madoff
Bernard L. Madoff Investment Securities LLC reported 5.6% year-to-date returns in November 2008; the S&P 500 fell 39%. As the selling continued, Madoff couldn't keep up with redemption requests, and on Dec. 10, he confessed to his sons Mark and Andy, who worked at his firm. "After I told them, they left, went to a lawyer, who told them to turn in their father, and I never saw them again. 2008-12-11: Bernie Madoff arrested.
Madoff insists he acted alone, but several of his colleagues were jailed. Mark Madoff died two years after his father's fraud was exposed. Madoff's investors committed suicide. Andy Madoff died of cancer in 2014.
2009 saw Madoff's 150-year prison sentence and $170 billion forfeiture. Marshals sold his three homes and yacht. Prisoner 61727-054 at Butner Federal Correctional Institution in North Carolina.
Madoff's lawyers requested early release on February 5, 2020, claiming he has a terminal kidney disease that may kill him in 18 months. Ten years have passed since Madoff's sentencing.
Bernie Madoff's Ponzi scheme aftermath
The paper trail of victims' claims shows Madoff's complexity and size. Documents show Madoff's scam began in the 1960s. His final account statements show $47 billion in "profit" from fake trades and shady accounting.
Thousands of investors lost their life savings, and multiple stories detail their harrowing loss.
Irving Picard, a New York lawyer overseeing Madoff's bankruptcy, has helped investors. By December 2018, Picard had recovered $13.3 billion from Ponzi scheme profiteers.
A Madoff Victim Fund (MVF) was created in 2013 to help compensate Madoff's victims, but the DOJ didn't start paying out the $4 billion until late 2017. Richard Breeden, a former SEC chair who oversees the fund, said thousands of claims were from "indirect investors"
Breeden and his team had to reject many claims because they weren't direct victims. Breeden said he based most of his decisions on one simple rule: Did the person invest more than they withdrew? Breeden estimated 11,000 "feeder" investors.
Breeden wrote in a November 2018 update for the Madoff Victim Fund, "We've paid over 27,300 victims 56.65% of their losses, with thousands more to come." In December 2018, 37,011 Madoff victims in the U.S. and around the world received over $2.7 billion. Breeden said the fund expected to make "at least one more significant distribution in 2019"
This post is a summary. Read full article here
Jan-Patrick Barnert
3 years ago
Wall Street's Bear Market May Stick Around
If history is any guide, this bear market might be long and severe.
This is the S&P 500 Index's fourth such incident in 20 years. The last bear market of 2020 was a "shock trade" caused by the Covid-19 pandemic, although earlier ones in 2000 and 2008 took longer to bottom out and recover.
Peter Garnry, head of equities strategy at Saxo Bank A/S, compares the current selloff to the dotcom bust of 2000 and the 1973-1974 bear market marked by soaring oil prices connected to an OPEC oil embargo. He blamed high tech valuations and the commodity crises.
"This drop might stretch over a year and reach 35%," Garnry wrote.
Here are six bear market charts.
Time/depth
The S&P 500 Index plummeted 51% between 2000 and 2002 and 58% during the global financial crisis; it took more than 1,000 trading days to recover. The former took 638 days to reach a bottom, while the latter took 352 days, suggesting the present selloff is young.
Valuations
Before the tech bubble burst in 2000, valuations were high. The S&P 500's forward P/E was 25 times then. Before the market fell this year, ahead values were near 24. Before the global financial crisis, stocks were relatively inexpensive, but valuations dropped more than 40%, compared to less than 30% now.
Earnings
Every stock crash, especially earlier bear markets, returned stocks to fundamentals. The S&P 500 decouples from earnings trends but eventually recouples.
Support
Central banks won't support equity investors just now. The end of massive monetary easing will terminate a two-year bull run that was among the strongest ever, and equities may struggle without cheap money. After years of "don't fight the Fed," investors must embrace a new strategy.
Bear Haunting Bear
If the past is any indication, rising government bond yields are bad news. After the financial crisis, skyrocketing rates and a falling euro pushed European stock markets back into bear territory in 2011.
Inflation/rates
The current monetary policy climate differs from past bear markets. This is the first time in a while that markets face significant inflation and rising rates.
This post is a summary. Read full article here
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Tim Soulo
3 years ago
Here is why 90.63% of Pages Get No Traffic From Google.
The web adds millions or billions of pages per day.
How much Google traffic does this content get?
In 2017, we studied 2 million randomly-published pages to answer this question. Only 5.7% of them ranked in Google's top 10 search results within a year of being published.
94.3 percent of roughly two million pages got no Google traffic.
Two million pages is a small sample compared to the entire web. We did another study.
We analyzed over a billion pages to see how many get organic search traffic and why.
How many pages get search traffic?
90% of pages in our index get no Google traffic, and 5.2% get ten visits or less.
90% of google pages get no organic traffic
How can you join the minority that gets Google organic search traffic?
There are hundreds of SEO problems that can hurt your Google rankings. If we only consider common scenarios, there are only four.
Reason #1: No backlinks
I hate to repeat what most SEO articles say, but it's true:
Backlinks boost Google rankings.
Google's "top 3 ranking factors" include them.
Why don't we divide our studied pages by the number of referring domains?
66.31 percent of pages have no backlinks, and 26.29 percent have three or fewer.
Did you notice the trend already?
Most pages lack search traffic and backlinks.
But are these the same pages?
Let's compare monthly organic search traffic to backlinks from unique websites (referring domains):
More backlinks equals more Google organic traffic.
Referring domains and keyword rankings are correlated.
It's important to note that correlation does not imply causation, and none of these graphs prove backlinks boost Google rankings. Most SEO professionals agree that it's nearly impossible to rank on the first page without backlinks.
You'll need high-quality backlinks to rank in Google and get search traffic.
Is organic traffic possible without links?
Here are the numbers:
Four million pages get organic search traffic without backlinks. Only one in 20 pages without backlinks has traffic, which is 5% of our sample.
Most get 300 or fewer organic visits per month.
What happens if we exclude high-Domain-Rating pages?
The numbers worsen. Less than 4% of our sample (1.4 million pages) receive organic traffic. Only 320,000 get over 300 monthly organic visits, or 0.1% of our sample.
This suggests high-authority pages without backlinks are more likely to get organic traffic than low-authority pages.
Internal links likely pass PageRank to new pages.
Two other reasons:
Our crawler's blocked. Most shady SEOs block backlinks from us. This prevents competitors from seeing (and reporting) PBNs.
They choose low-competition subjects. Low-volume queries are less competitive, requiring fewer backlinks to rank.
If the idea of getting search traffic without building backlinks excites you, learn about Keyword Difficulty and how to find keywords/topics with decent traffic potential and low competition.
Reason #2: The page has no long-term traffic potential.
Some pages with many backlinks get no Google traffic.
Why? I filtered Content Explorer for pages with no organic search traffic and divided them into four buckets by linking domains.
Almost 70k pages have backlinks from over 200 domains, but no search traffic.
By manually reviewing these (and other) pages, I noticed two general trends that explain why they get no traffic:
They overdid "shady link building" and got penalized by Google;
They're not targeting a Google-searched topic.
I won't elaborate on point one because I hope you don't engage in "shady link building"
#2 is self-explanatory:
If nobody searches for what you write, you won't get search traffic.
Consider one of our blog posts' metrics:
No organic traffic despite 337 backlinks from 132 sites.
The page is about "organic traffic research," which nobody searches for.
News articles often have this. They get many links from around the web but little Google traffic.
People can't search for things they don't know about, and most don't care about old events and don't search for them.
Note:
Some news articles rank in the "Top stories" block for relevant, high-volume search queries, generating short-term organic search traffic.
The Guardian's top "Donald Trump" story:
Ahrefs caught on quickly:
"Donald Trump" gets 5.6M monthly searches, so this page got a lot of "Top stories" traffic.
I bet traffic has dropped if you check now.
One of the quickest and most effective SEO wins is:
Find your website's pages with the most referring domains;
Do keyword research to re-optimize them for relevant topics with good search traffic potential.
Bryan Harris shared this "quick SEO win" during a course interview:
He suggested using Ahrefs' Site Explorer's "Best by links" report to find your site's most-linked pages and analyzing their search traffic. This finds pages with lots of links but little organic search traffic.
We see:
The guide has 67 backlinks but no organic traffic.
We could fix this by re-optimizing the page for "SERP"
A similar guide with 26 backlinks gets 3,400 monthly organic visits, so we should easily increase our traffic.
Don't do this with all low-traffic pages with backlinks. Choose your battles wisely; some pages shouldn't be ranked.
Reason #3: Search intent isn't met
Google returns the most relevant search results.
That's why blog posts with recommendations rank highest for "best yoga mat."
Google knows that most searchers aren't buying.
It's also why this yoga mats page doesn't rank, despite having seven times more backlinks than the top 10 pages:
The page ranks for thousands of other keywords and gets tens of thousands of monthly organic visits. Not being the "best yoga mat" isn't a big deal.
If you have pages with lots of backlinks but no organic traffic, re-optimizing them for search intent can be a quick SEO win.
It was originally a boring landing page describing our product's benefits and offering a 7-day trial.
We realized the problem after analyzing search intent.
People wanted a free tool, not a landing page.
In September 2018, we published a free tool at the same URL. Organic traffic and rankings skyrocketed.
Reason #4: Unindexed page
Google can’t rank pages that aren’t indexed.
If you think this is the case, search Google for site:[url]. You should see at least one result; otherwise, it’s not indexed.
A rogue noindex meta tag is usually to blame. This tells search engines not to index a URL.
Rogue canonicals, redirects, and robots.txt blocks prevent indexing.
Check the "Excluded" tab in Google Search Console's "Coverage" report to see excluded pages.
Google doesn't index broken pages, even with backlinks.
Surprisingly common.
In Ahrefs' Site Explorer, the Best by Links report for a popular content marketing blog shows many broken pages.
One dead page has 131 backlinks:
According to the URL, the page defined content marketing. —a keyword with a monthly search volume of 5,900 in the US.
Luckily, another page ranks for this keyword. Not a huge loss.
At least redirect the dead page's backlinks to a working page on the same topic. This may increase long-tail keyword traffic.
This post is a summary. See the original post here
Asher Umerie
3 years ago
What is Bionic Reading?
Senses help us navigate a complicated world. They shape our worldview - how we hear, smell, feel, and taste. People claim a sixth sense, an intuitive capacity that extends perception.
Our brain is a half-pool of grey and white matter that stores data from our senses. Brains provide us context, so zombies' obsession makes sense.
Bionic reading uses the brain's visual information and context to simplify text comprehension.
Stay with me.
What is Bionic Reading?
Bionic reading is a software application established by Swiss typographic designer Renato Casutt. The term honors the brain (bio) and technology's collaboration to better text comprehension.
The image above shows two similar paragraphs with bionic reading.
Notice anything yet?
This Twitter user did.
I did too...
Image text describes bionic reading-
New method to aid reading by using artificial fixation points. The reader focuses on the highlighted starting letters, and the brain completes the word.
How is Bionic Reading possible?
Do you remember seeing social media posts asking you to stare at a black dot for 30 seconds (or more)? You blink and see an after-image on your wall.
Our brains are skilled at identifying patterns and'seeing' familiar objects, therefore optical illusions are conceivable.
Brain and sight collaborate well. Text comprehension proves it.
Considering evolutionary patterns, humans' understanding skills may be cosmic luck.
Scientists don't know why people can read and write, but they do know what reading does to the brain.
One portion of your brain recognizes words, while another analyzes their meaning. Fixation, saccade, and linguistic transparency/opacity aid.
Let's explain some terms.
-
Fixation is how the eyes move when reading. It's where you look. If the eyes fixate less, a reader can read quicker. [Eye fixation is a physiological process](Eye fixation is a naturally occurring physiological process) impacted by the reader's vocabulary, vision span, and text familiarity.
-
Saccade - Pause and look around. That's a saccade. Rapid eye movements that alter the place of fixation, as reading text or looking around a room. They can happen willingly (when you choose) or instinctively, even when your eyes are fixed.
-
Linguistic transparency and opacity analyze how well a composite word or phrase may be deduced from its constituents.
The Bionic reading website compares these tools.
Text highlights lead the eye. Fixation, saccade, and opacity can transfer visual stimuli to text, changing typeface.
## Final Thoughts on Bionic Reading
I'm excited about how this could influence my long-term assimilation and productivity.
This technology is still in development, with prototypes working on only a few apps. Like any new tech, it will be criticized.
I'll be watching Bionic Reading closely. Comment on it!
Sanjay Priyadarshi
2 years ago
Using Ruby code, a programmer created a $48,000,000,000 product that Elon Musk admired.
Unexpected Success
Shopify CEO and co-founder Tobias Lutke. Shopify is worth $48 billion.
World-renowned entrepreneur Tobi
Tobi never expected his first online snowboard business to become a multimillion-dollar software corporation.
Tobi founded Shopify to establish a 20-person company.
The publicly traded corporation employs over 10,000 people.
Here's Tobi Lutke's incredible story.
Elon Musk tweeted his admiration for the Shopify creator.
30-October-2019.
Musk praised Shopify founder Tobi Lutke on Twitter.
Happened:
Explore this programmer's journey.
What difficulties did Tobi experience as a young child?
Germany raised Tobi.
Tobi's parents realized he was smart but had trouble learning as a toddler.
Tobi was learning disabled.
Tobi struggled with school tests.
Tobi's learning impairments were undiagnosed.
Tobi struggled to read as a dyslexic.
Tobi also found school boring.
Germany's curriculum didn't inspire Tobi's curiosity.
“The curriculum in Germany was taught like here are all the solutions you might find useful later in life, spending very little time talking about the problem…If I don’t understand the problem I’m trying to solve, it’s very hard for me to learn about a solution to a problem.”
Studying computer programming
After tenth grade, Tobi decided school wasn't for him and joined a German apprenticeship program.
This curriculum taught Tobi software engineering.
He was an apprentice in a small Siemens subsidiary team.
Tobi worked with rebellious Siemens employees.
Team members impressed Tobi.
Tobi joined the team for this reason.
Tobi was pleased to get paid to write programming all day.
His life could not have been better.
Devoted to snowboarding
Tobi loved snowboarding.
He drove 5 hours to ski at his folks' house.
His friends traveled to the US to snowboard when he was older.
However, the cheap dollar conversion rate led them to Canada.
2000.
Tobi originally decided to snowboard instead than ski.
Snowboarding captivated him in Canada.
On the trip to Canada, Tobi encounters his wife.
Tobi meets his wife Fiona McKean on his first Canadian ski trip.
They maintained in touch after the trip.
Fiona moved to Germany after graduating.
Tobi was a startup coder.
Fiona found work in Germany.
Her work included editing, writing, and academics.
“We lived together for 10 months and then she told me that she need to go back for the master's program.”
With Fiona, Tobi immigrated to Canada.
Fiona invites Tobi.
Tobi agreed to move to Canada.
Programming helped Tobi move in with his girlfriend.
Tobi was an excellent programmer, therefore what he did in Germany could be done anywhere.
He worked remotely for his German employer in Canada.
Tobi struggled with remote work.
Due to poor communication.
No slack, so he used email.
Programmers had trouble emailing.
Tobi's startup was developing a browser.
After the dot-com crash, individuals left that startup.
It ended.
Tobi didn't intend to work for any major corporations.
Tobi left his startup.
He believed he had important skills for any huge corporation.
He refused to join a huge corporation.
Because of Siemens.
Tobi learned to write professional code and about himself while working at Siemens in Germany.
Siemens culture was odd.
Employees were distrustful.
Siemens' rigorous dress code implies that the corporation doesn't trust employees' attire.
It wasn't Tobi's place.
“There was so much bad with it that it just felt wrong…20-year-old Tobi would not have a career there.”
Focused only on snowboarding
Tobi lived in Ottawa with his girlfriend.
Canada is frigid in winter.
Ottawa's winters last.
Almost half a year.
Tobi wanted to do something worthwhile now.
So he snowboarded.
Tobi began snowboarding seriously.
He sought every snowboarding knowledge.
He researched the greatest snowboarding gear first.
He created big spreadsheets for snowboard-making technologies.
Tobi grew interested in selling snowboards while researching.
He intended to sell snowboards online.
He had no choice but to start his own company.
A small local company offered Tobi a job.
Interested.
He must sign papers to join the local company.
He needed a work permit when he signed the documents.
Tobi had no work permit.
He was allowed to stay in Canada while applying for permanent residency.
“I wasn’t illegal in the country, but my state didn’t give me a work permit. I talked to a lawyer and he told me it’s going to take a while until I get a permanent residency.”
Tobi's lawyer told him he cannot get a work visa without permanent residence.
His lawyer said something else intriguing.
Tobis lawyer advised him to start a business.
Tobi declined this local company's job offer because of this.
Tobi considered opening an internet store with his technical skills.
He sold snowboards online.
“I was thinking of setting up an online store software because I figured that would exist and use it as a way to sell snowboards…make money while snowboarding and hopefully have a good life.”
What brought Tobi and his co-founder together, and how did he support Tobi?
Tobi lived with his girlfriend's parents.
In Ottawa, Tobi encounters Scott Lake.
Scott was Tobis girlfriend's family friend and worked for Tobi's future employer.
Scott and Tobi snowboarded.
Tobi pitched Scott his snowboard sales software idea.
Scott liked the idea.
They planned a business together.
“I was looking after the technology and Scott was dealing with the business side…It was Scott who ended up developing relationships with vendors and doing all the business set-up.”
Issues they ran into when attempting to launch their business online
Neither could afford a long-term lease.
That prompted their online business idea.
They would open a store.
Tobi anticipated opening an internet store in a week.
Tobi seeks open-source software.
Most existing software was pricey.
Tobi and Scott couldn't afford pricey software.
“In 2004, I was sitting in front of my computer absolutely stunned realising that we hadn’t figured out how to create software for online stores.”
They required software to:
to upload snowboard images to the website.
people to look up the types of snowboards that were offered on the website. There must be a search feature in the software.
Online users transmit payments, and the merchant must receive them.
notifying vendors of the recently received order.
No online selling software existed at the time.
Online credit card payments were difficult.
How did they advance the software while keeping expenses down?
Tobi and Scott needed money to start selling snowboards.
Tobi and Scott funded their firm with savings.
“We both put money into the company…I think the capital we had was around CAD 20,000(Canadian Dollars).”
Despite investing their savings.
They minimized costs.
They tried to conserve.
No office rental.
They worked in several coffee shops.
Tobi lived rent-free at his girlfriend's parents.
He installed software in coffee cafes.
How were the software issues handled?
Tobi found no online snowboard sales software.
Two choices remained:
Change your mind and try something else.
Use his programming expertise to produce something that will aid in the expansion of this company.
Tobi knew he was the sole programmer working on such a project from the start.
“I had this realisation that I’m going to be the only programmer who has ever worked on this, so I don’t have to choose something that lots of people know. I can choose just the best tool for the job…There is been this programming language called Ruby which I just absolutely loved ”
Ruby was open-source and only had Japanese documentation.
Latin is the source code.
Tobi used Ruby twice.
He assumed he could pick the tool this time.
Why not build with Ruby?
How did they find their first time operating a business?
Tobi writes applications in Ruby.
He wrote the initial software version in 2.5 months.
Tobi and Scott founded Snowdevil to sell snowboards.
Tobi coded for 16 hours a day.
His lifestyle was unhealthy.
He enjoyed pizza and coke.
“I would never recommend this to anyone, but at the time there was nothing more interesting to me in the world.”
Their initial purchase and encounter with it
Tobi worked in cafes then.
“I was working in a coffee shop at this time and I remember everything about that day…At some time, while I was writing the software, I had to type the email that the software would send to tell me about the order.”
Tobi recalls everything.
He checked the order on his laptop at the coffee shop.
Pennsylvanian ordered snowboard.
Tobi walked home and called Scott. Tobi told Scott their first order.
They loved the order.
How were people made aware about Snowdevil?
2004 was very different.
Tobi and Scott attempted simple website advertising.
Google AdWords was new.
Ad clicks cost 20 cents.
Online snowboard stores were scarce at the time.
Google ads propelled the snowdevil brand.
Snowdevil prospered.
They swiftly recouped their original investment in the snowboard business because to its high profit margin.
Tobi and Scott struggled with inventories.
“Snowboards had really good profit margins…Our biggest problem was keeping inventory and getting it back…We were out of stock all the time.”
Selling snowboards returned their investment and saved them money.
They did not appoint a business manager.
They accomplished everything alone.
Sales dipped in the spring, but something magical happened.
Spring sales plummeted.
They considered stocking different boards.
They naturally wanted to add boards and grow the business.
However, magic occurred.
Tobi coded and improved software while running Snowdevil.
He modified software constantly. He wanted speedier software.
He experimented to make the software more resilient.
Tobi received emails requesting the Snowdevil license.
They intended to create something similar.
“I didn’t stop programming, I was just like Ok now let me try things, let me make it faster and try different approaches…Increasingly I got people sending me emails and asking me If I would like to licence snowdevil to them. People wanted to start something similar.”
Software or skateboards, your choice
Scott and Tobi had to choose a hobby in 2005.
They might sell alternative boards or use software.
The software was a no-brainer from demand.
Daniel Weinand is invited to join Tobi's business.
Tobis German best friend is Daniel.
Tobi and Scott chose to use the software.
Tobi and Scott kept the software service.
Tobi called Daniel to invite him to Canada to collaborate.
Scott and Tobi had quit snowboarding until then.
How was Shopify launched, and whence did the name come from?
The three chose Shopify.
Named from two words.
First:
Shop
Final part:
Simplify
Shopify
Shopify's crew has always had one goal:
creating software that would make it simple and easy for people to launch online storefronts.
Launched Shopify after raising money for the first time.
Shopify began fundraising in 2005.
First, they borrowed from family and friends.
They needed roughly $200k to run the company efficiently.
$200k was a lot then.
When questioned why they require so much money. Tobi told them to trust him with their goals. The team raised seed money from family and friends.
Shopify.com has a landing page. A demo of their goal was on the landing page.
In 2006, Shopify had about 4,000 emails.
Shopify rented an Ottawa office.
“We sent a blast of emails…Some people signed up just to try it out, which was exciting.”
How things developed after Scott left the company
Shopify co-founder Scott Lake left in 2008.
Scott was CEO.
“He(Scott) realized at some point that where the software industry was going, most of the people who were the CEOs were actually the highly technical person on the founding team.”
Scott leaving the company worried Tobi.
Tobis worried about finding a new CEO.
To Tobi:
A great VC will have the network to identify the perfect CEO for your firm.
Tobi started visiting Silicon Valley to meet with venture capitalists to recruit a CEO.
Initially visiting Silicon Valley
Tobi came to Silicon Valley to start a 20-person company.
This company creates eCommerce store software.
Tobi never wanted a big corporation. He desired a fulfilling existence.
“I stayed in a hostel in the Bay Area. I had one roommate who was also a computer programmer. I bought a bicycle on Craiglist. I was there for a week, but ended up staying two and a half weeks.”
Tobi arrived unprepared.
When venture capitalists asked him business questions.
He answered few queries.
Tobi didn't comprehend VC meetings' terminology.
He wrote the terms down and looked them up.
Some were fascinated after he couldn't answer all these queries.
“I ended up getting the kind of term sheets people dream about…All the offers were conditional on moving our company to Silicon Valley.”
Canada received Tobi.
He wanted to consult his team before deciding. Shopify had five employees at the time.
2008.
A global recession greeted Tobi in Canada. The recession hurt the market.
His term sheets were useless.
The economic downturn in the world provided Shopify with a fantastic opportunity.
The global recession caused significant job losses.
Fired employees had several ideas.
They wanted online stores.
Entrepreneurship was desired. They wanted to quit work.
People took risks and tried new things during the global slump.
Shopify subscribers skyrocketed during the recession.
“In 2009, the company reached neutral cash flow for the first time…We were in a position to think about long-term investments, such as infrastructure projects.”
Then, Tobi Lutke became CEO.
How did Tobi perform as the company's CEO?
“I wasn’t good. My team was very patient with me, but I had a lot to learn…It’s a very subtle job.”
2009–2010.
Tobi limited the company's potential.
He deliberately restrained company growth.
Tobi had one costly problem:
Whether Shopify is a venture or a lifestyle business.
The company's annual revenue approached $1 million.
Tobi battled with the firm and himself despite good revenue.
His wife was supportive, but the responsibility was crushing him.
“It’s a crushing responsibility…People had families and kids…I just couldn’t believe what was going on…My father-in-law gave me money to cover the payroll and it was his life-saving.”
Throughout this trip, everyone supported Tobi.
They believed it.
$7 million in donations received
Tobi couldn't decide if this was a lifestyle or a business.
Shopify struggled with marketing then.
Later, Tobi tried 5 marketing methods.
He told himself that if any marketing method greatly increased their growth, he would call it a venture, otherwise a lifestyle.
The Shopify crew brainstormed and voted on marketing concepts.
Tested.
“Every single idea worked…We did Adwords, published a book on the concept, sponsored a podcast and all the ones we tracked worked.”
To Silicon Valley once more
Shopify marketing concepts worked once.
Tobi returned to Silicon Valley to pitch investors.
He raised $7 million, valuing Shopify at $25 million.
All investors had board seats.
“I find it very helpful…I always had a fantastic relationship with everyone who’s invested in my company…I told them straight that I am not going to pretend I know things, I want you to help me.”
Tobi developed skills via running Shopify.
Shopify had 20 employees.
Leaving his wife's parents' home
Tobi left his wife's parents in 2014.
Tobi had a child.
Shopify has 80,000 customers and 300 staff in 2013.
Public offering in 2015
Shopify investors went public in 2015.
Shopify powers 4.1 million e-Commerce sites.
Shopify stores are 65% US-based.
It is currently valued at $48 billion.