Jack Dorsey and Jay-Z Launch 'Bitcoin Academy' in Brooklyn rapper's home
The new Bitcoin Academy will teach Jay-Marcy Z's Houses neighbors "What is Cryptocurrency."
Jay-Z grew up in Brooklyn's Marcy Houses. The rapper and Block CEO Jack Dorsey are giving back to his hometown by creating the Bitcoin Academy.
The Bitcoin Academy will offer online and in-person classes, including "What is Money?" and "What is Blockchain?"
The program will provide participants with a mobile hotspot and a small amount of Bitcoin for hands-on learning.
Students will receive dinner and two evenings of instruction until early September. The Shawn Carter Foundation will help with on-the-ground instruction.
Jay-Z and Dorsey announced the program Thursday morning. It will begin at Marcy Houses but may be expanded.
Crypto Blockchain Plug and Black Bitcoin Billionaire, which has received a grant from Block, will teach the classes.
Jay-Z, Dorsey reunite
Jay-Z and Dorsey have previously worked together to promote a Bitcoin and crypto-based future.
In 2021, Dorsey's Block (then Square) acquired the rapper's streaming music service Tidal, which they propose using for NFT distribution.
Dorsey and Jay-Z launched an endowment in 2021 to fund Bitcoin development in Africa and India.
Dorsey is funding the new Bitcoin Academy out of his own pocket (as is Jay-Z), but he's also pushed crypto-related charitable endeavors at Block, including a $5 million fund backed by corporate Bitcoin interest.
This post is a summary. Read full article here
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CyberPunkMetalHead
3 years ago
It's all about the ego with Terra 2.0.
UST depegs and LUNA crashes 99.999% in a fraction of the time it takes the Moon to orbit the Earth.
Fat Man, a Terra whistle-blower, promises to expose Do Kwon's dirty secrets and shady deals.
The Terra community has voted to relaunch Terra LUNA on a new blockchain. The Terra 2.0 Pheonix-1 blockchain went live on May 28, 2022, and people were airdropped the new LUNA, now called LUNA, while the old LUNA became LUNA Classic.
Does LUNA deserve another chance? To answer this, or at least start a conversation about the Terra 2.0 chain's advantages and limitations, we must assess its fundamentals, ideology, and long-term vision.
Whatever the result, our analysis must be thorough and ruthless. A failure of this magnitude cannot happen again, so we must magnify every potential breaking point by 10.
Will UST and LUNA holders be compensated in full?
The obvious. First, and arguably most important, is to restore previous UST and LUNA holders' bags.
Terra 2.0 has 1,000,000,000,000 tokens to distribute.
25% of a community pool
Holders of pre-attack LUNA: 35%
10% of aUST holders prior to attack
Holders of LUNA after an attack: 10%
UST holders as of the attack: 20%
Every LUNA and UST holder has been compensated according to the above proposal.
According to self-reported data, the new chain has 210.000.000 tokens and a $1.3bn marketcap. LUNC and UST alone lost $40bn. The new token must fill this gap. Since launch:
LUNA holders collectively own $1b worth of LUNA if we subtract the 25% community pool airdrop from the current market cap and assume airdropped LUNA was never sold.
At the current supply, the chain must grow 40 times to compensate holders. At the current supply, LUNA must reach $240.
LUNA needs a full-on Bull Market to make LUNC and UST holders whole.
Who knows if you'll be whole? From the time you bought to the amount and price, there are too many variables to determine if Terra can cover individual losses.
The above distribution doesn't consider individual cases. Terra didn't solve individual cases. It would have been huge.
What does LUNA offer in terms of value?
UST's marketcap peaked at $18bn, while LUNC's was $41bn. LUNC and UST drove the Terra chain's value.
After it was confirmed (again) that algorithmic stablecoins are bad, Terra 2.0 will no longer support them.
Algorithmic stablecoins contributed greatly to Terra's growth and value proposition. Terra 2.0 has no product without algorithmic stablecoins.
Terra 2.0 has an identity crisis because it has no actual product. It's like Volkswagen faking carbon emission results and then stopping car production.
A project that has already lost the trust of its users and nearly all of its value cannot survive without a clear and in-demand use case.
Do Kwon, how about him?
Oh, the Twitter-caller-poor? Who challenges crypto billionaires to break his LUNA chain? Who dissolved Terra Labs South Korea before depeg? Arrogant guy?
That's not a good image for LUNA, especially when making amends. I think he should step down and let a nicer person be Terra 2.0's frontman.
The verdict
Terra has a terrific community with an arrogant, unlikeable leader. The new LUNA chain must grow 40 times before it can start making up its losses, and even then, not everyone's losses will be covered.
I won't invest in Terra 2.0 or other algorithmic stablecoins in the near future. I won't be near any Do Kwon-related project within 100 miles. My opinion.
Can Terra 2.0 be saved? Comment below.

CoinTelegraph
4 years ago
2 NFT-based blockchain games that could soar in 2022
NFTs look ready to rule 2022, and the recent pivot toward NFT utility in P2E gaming could make blockchain gaming this year’s sector darling.
After the popularity of decentralized finance (DeFi) came the rise of nonfungible tokens (NFTs), and to the surprise of many, NFTs took the spotlight and now remain front and center with the highest volume in sales occurring at the start of January 2022.
While 2021 became the year of NFTs, GameFi applications did surpass DeFi in terms of user popularity. According to data from DappRadar, Bloomberg gathered:
Nearly 50% of active cryptocurrency wallets connected to decentralized applications in November were for playing games. The percentage of wallets linked to decentralized finance, or DeFi, dapps fell to 45% during the same period, after months of being the leading dapp use case.
Blockchain play-to-earn (P2E) game Axie infinity skyrocketed and kicked off a gaming craze that is expected to continue all throughout 2022. Crypto pundits and gaming advocates have high expectations for P2E blockchain-based games and there’s bound to be a few sleeping giants that will dominate the sector.
Let’s take a look at five blockchain games that could make waves in 2022.
DeFi Kingdoms
The inspiration for DeFi Kingdoms came from simple beginnings — a passion for investing that lured the developers to blockchain technology. DeFi Kingdoms was born as a visualization of liquidity pool investing where in-game ‘gardens’ represent literal and figurative token pairings and liquidity pool mining.
As shown in the game, investors have a portion of their LP share within a plot filled with blooming plants. By attaching the concept of growth to DeFi protocols within a play-and-earn model, DeFi Kingdoms puts a twist on “playing” a game.
Built on the Harmony Network, DeFi Kingdoms became the first project on the network to ever top the DappRadar charts. This could be attributed to an influx of individuals interested in both DeFi and blockchain games or it could be attributed to its recent in-game utility token JEWEL surging.
JEWEL is a utility token that allows users to purchase NFTs in-game buffs to increase a base-level stat. It is also used for liquidity mining to grant users the opportunity to make more JEWEL through staking.
JEWEL is also a governance token that gives holders a vote in the growth and evolution of the project. In the past four months, the token price surged from $1.23 to an all-time high of $22.52. At the time of writing, JEWEL is down by nearly 16%, trading at $19.51.
Surging approximately 1,487% from its humble start of $1.23 four months ago in September, JEWEL token price has increased roughly 165% this last month alone, according to data from CoinGecko.
Guild of Guardians
Guild of Guardians is one of the more anticipated blockchain games in 2022 and it is built on ImmutableX, the first layer-two solution built on Ethereum that focuses on NFTs. Aiming to provide more access, it will operate as a free-to-play mobile role-playing game, modeling the P2E mechanics.
Similar to blockchain games like Axie Infinity, Guild of Guardians in-game assets can be exchanged. The project seems to be of interest to many gamers and investors with its NFT founder sale and token launch generating nearly $10 million in volume.
Launching its in-game token in October of 2021, the Guild of Guardians (GOG) tokens are ERC-20 tokens known as ‘gems’ inside the game. Gems are what power key features in the game such as minting in-game NFTs and interacting with the marketplace, and are available to earn while playing.
For the last month, the Guild of Guardians token has performed rather steadily after spiking to its all-time high of $2.81 after its launch. Despite the token being down over 50% from its all-time high, at the time of writing, some members of the community are looking forward to the possibility of staking and liquidity pools, which are features that tend to help stabilize token prices.

Dylan Smyth
4 years ago
10 Ways to Make Money Online in 2022
As a tech-savvy person (and software engineer) or just a casual technology user, I'm sure you've had this same question countless times: How do I make money online? and how do I make money with my PC/Mac?
You're in luck! Today, I will list the top 5 easiest ways to make money online. Maybe a top ten in the future? Top 5 tips for 2022.
1. Using the gig economy
There are many websites on the internet that allow you to earn extra money using skills and equipment that you already own.
I'm referring to the gig economy. It's a great way to earn a steady passive income from the comfort of your own home. For some sites, premium subscriptions are available to increase sales and access features like bidding on more proposals.
Some of these are:
- Freelancer
- Upwork
- Fiverr (⭐ my personal favorite)
- TaskRabbit
2. Mineprize
MINEPRIZE is a great way to make money online. What's more, You need not do anything! You earn money by lending your idle CPU power to MINEPRIZE.
To register with MINEPRIZE, all you need is an email address and a password. Let MINEPRIZE use your resources, and watch the money roll in! You can earn up to $100 per month by letting your computer calculate. That's insane.
3. Writing
“O Romeo, Romeo, why art thou Romeo?” Okay, I admit that not all writing is Shakespearean. To be a copywriter, you'll need to be fluent in English. Thankfully, we don't have to use typewriters anymore.
Writing is a skill that can earn you a lot of money (claps for the rhyme).
Here are a few ways you can make money typing on your fancy keyboard:
Self-publish a book
Write scripts for video creators
Write for social media
Book-checking
Content marketing help
What a list within a list!
4. Coding
Yes, kids. You've probably coded before if you understand
You've probably coded before if you understand
print("hello world");
Computational thinking (or coding) is one of the most lucrative ways to earn extra money, or even as a main source of income.
Of course, there are hardcode coders (like me) who write everything line by line, binary di — okay, that last part is a bit exaggerated.
But you can also make money by writing websites or apps or creating low code or no code platforms.
But you can also make money by writing websites or apps or creating low code or no code platforms.
Some low-code platforms
Sheet : spreadsheets to apps :
Loading... We'll install your new app... No-Code Your team can create apps and automate tasks. Agile…
www.appsheet.com
Low-code platform | Business app creator - Zoho Creator
Work is going digital, and businesses of all sizes must adapt quickly. Zoho Creator is a...
www.zoho.com
Sell your data with TrueSource. NO CODE NEEDED
Upload data, configure your product, and earn in minutes.
www.truesource.io
Cool, huh?
5. Created Content
If we use the internet correctly, we can gain unfathomable wealth and extra money. But this one is a bit more difficult. Unlike some of the other items on this list, it takes a lot of time up front.
I'm referring to sites like YouTube and Medium. It's a great way to earn money both passively and actively. With the likes of Jake- and Logan Paul, PewDiePie (a.k.a. Felix Kjellberg) and others, it's never too late to become a millionaire on YouTube. YouTubers are always rising to the top with great content.
6. NFTs and Cryptocurrency
It is now possible to amass large sums of money by buying and selling digital assets on NFTs and cryptocurrency exchanges. Binance's Initial Game Offer rewards early investors who produce the best results.
One awesome game sold a piece of its plot for US$7.2 million! It's Axie Infinity. It's free and available on Google Play and Apple Store.
7. Affiliate Marketing
Affiliate marketing is a form of advertising where businesses pay others (like bloggers) to promote their goods and services. Here's an example. I write a blog (like this one) and post an affiliate link to an item I recommend buying — say, a camera — and if you buy the camera, I get a commission!
These programs pay well:
- Elementor
- AWeber
- Sendinblue
- ConvertKit\sLeadpages
- GetResponse
- SEMRush\sFiverr
- Pabbly
8. Start a blog
Now, if you're a writer or just really passionate about something or a niche, blogging could potentially monetize that passion!
Create a blog about anything you can think of. It's okay to start right here on Medium, as I did.
9. Dropshipping
And I mean that in the best possible way — drop shopping is ridiculously easy to set up, but difficult to maintain for some.
Luckily, Shopify has made setting up an online store a breeze. Drop-shipping from Alibaba and DHGate is quite common. You've got a winner if you can find a local distributor willing to let you drop ship their product!
10. Set up an Online Course
If you have a skill and can articulate it, online education is for you.
Skillshare, Pluralsight, and Coursera have all made inroads in recent years, upskilling people with courses that YOU can create and earn from.
That's it for today! Please share if you liked this post. If not, well —
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Victoria Kurichenko
3 years ago
My Blog Is in Google's Top 10—Here's How to Compete
"Competition" is beautiful and hateful.
Some people bury their dreams because they are afraid of competition. Others challenge themselves, shaping our world.
Competition is normal.
It spurs innovation and progress.
I wish more people agreed.
As a marketer, content writer, and solopreneur, my readers often ask:
"I want to create a niche website, but I have no ideas. Everything's done"
"Is a website worthwhile?"
I can't count how many times I said, "Yes, it makes sense, and you can succeed in a competitive market."
I encourage and share examples, but it's not enough to overcome competition anxiety.
I launched an SEO writing website for content creators a year ago, knowing it wouldn't beat Ahrefs, Semrush, Backlinko, etc.
Not needed.
Many of my website's pages rank highly on Google.
Everyone can eat the pie.
In a competitive niche, I took a different approach.
Look farther
When chatting with bloggers that want a website, I discovered something fascinating.
They want to launch a website but have no ideas. As a next step, they start listing the interests they believe they should work on, like wellness, lifestyle, investments, etc. I could keep going.
Too many generalists who claim to know everything confuse many.
Generalists aren't trusted.
We want someone to fix our problems immediately.
I don't think broad-spectrum experts are undervalued. People have many demands that go beyond generalists' work. Narrow-niche experts can help.
I've done SEO for three years. I learned from experts and courses. I couldn't find a comprehensive SEO writing resource.
I read tons of articles before realizing that wasn't it. I took courses that covered SEO basics eventually.
I had a demand for learning SEO writing, but there was no solution on the market. My website fills this micro-niche.
Have you ever had trouble online?
Professional courses too general, boring, etc.?
You've bought off-topic books, right?
You're not alone.
Niche ideas!
Big players often disregard new opportunities. Too small. Individual content creators can succeed here.
In a competitive market:
Never choose wide subjects
Think about issues you can relate to and have direct experience with.
Be a consumer to discover both the positive and negative aspects of a good or service.
Merchandise your annoyances.
Consider ways to transform your frustrations into opportunities.
The right niche is half-success. Here is what else I did to hit the Google front page with my website.
An innovative method for choosing subjects
Why publish on social media and websites?
Want likes, shares, followers, or fame?
Some people do it for fun. No judgment.
I bet you want more.
You want to make decent money from blogging.
Writing about random topics, even if they are related to your niche, won’t help you attract an audience from organic search. I'm a marketer and writer.
I worked at companies with dead blogs because they posted for themselves, not readers. They did not follow SEO writing rules; that’s why most of their content flopped.
I learned these hard lessons and grew my website from 0 to 3,000+ visitors per month while working on it a few hours a week only. Evidence:
I choose website topics using these criteria:
- Business potential. The information should benefit my audience and generate revenue. There would be no use in having it otherwise.
My topics should help me:
Attract organic search traffic with my "fluff-free" content -> Subscribers > SEO ebook sales.
Simple and effective.
- traffic on search engines. The number of monthly searches reveals how popular my topic is all across the world. If I find that no one is interested in my suggested topic, I don't write a blog article.
- Competition. Every search term is up against rivals. Some are more popular (thus competitive) since more websites target them in organic search. A new website won't score highly for keywords that are too competitive. On the other side, keywords with moderate to light competition can help you rank higher on Google more quickly.
- Search purpose. The "why" underlying users' search requests is revealed. I analyze search intent to understand what users need when they plug various queries in the search bar and what content can perfectly meet their needs.
My specialty website produces money, ranks well, and attracts the target audience because I handpick high-traffic themes.
Following these guidelines, even a new website can stand out.
I wrote a 50-page SEO writing guide where I detailed topic selection and share my front-page Google strategy.
My guide can help you run a successful niche website.
In summary
You're not late to the niche-website party.
The Internet offers many untapped opportunities.
We need new solutions and are willing to listen.
There are unexplored niches in any topic.
Don't fight giants. They have their piece of the pie. They might overlook new opportunities while trying to keep that piece of the pie. You should act now.

Liam Vaughan
3 years ago
Investors can bet big on almost anything on a new prediction market.
Kalshi allows five-figure bets on the Grammys, the next Covid wave, and future SEC commissioners. Worst-case scenario
On Election Day 2020, two young entrepreneurs received a call from the CFTC chairman. Luana Lopes Lara and Tarek Mansour spent 18 months trying to start a new type of financial exchange. Instead of betting on stock prices or commodity futures, people could trade instruments tied to real-world events, such as legislation, the weather, or the Oscar winner.
Heath Tarbert, a Trump appointee, shouted "Congratulations." "You're competing with 1840s-era markets. I'm sure you'll become a powerhouse too."
Companies had tried to introduce similar event markets in the US for years, but Tarbert's agency, the CFTC, said no, arguing they were gambling and prone to cheating. Now the agency has reversed course, approving two 24-year-olds who will have first-mover advantage in what could become a huge new asset class. Kalshi Inc. raised $30 million from venture capitalists within weeks of Tarbert's call, his representative says. Mansour, 26, believes this will be bigger than crypto.
Anyone who's read The Wisdom of Crowds knows prediction markets' potential. Well-designed markets can help draw out knowledge from disparate groups, and research shows that when money is at stake, people make better predictions. Lopes Lara calls it a "bullshit tax." That's why Google, Microsoft, and even the US Department of Defense use prediction markets internally to guide decisions, and why university-linked political betting sites like PredictIt sometimes outperform polls.
Regulators feared Wall Street-scale trading would encourage investors to manipulate reality. If the stakes are high enough, traders could pressure congressional staffers to stall a bill or bet on whether Kanye West's new album will drop this week. When Lopes Lara and Mansour pitched the CFTC, senior regulators raised these issues. Politically appointed commissioners overruled their concerns, and one later joined Kalshi's board.
Will Kanye’s new album come out next week? Yes or no?
Kalshi's victory was due more to lobbying and legal wrangling than to Silicon Valley-style innovation. Lopes Lara and Mansour didn't invent anything; they changed a well-established concept's governance. The result could usher in a new era of market-based enlightenment or push Wall Street's destructive tendencies into the real world.
If Kalshi's founders lacked experience to bolster their CFTC application, they had comical youth success. Lopes Lara studied ballet at the Brazilian Bolshoi before coming to the US. Mansour won France's math Olympiad. They bonded over their work ethic in an MIT computer science class.
Lopes Lara had the idea for Kalshi while interning at a New York hedge fund. When the traders around her weren't working, she noticed they were betting on the news: Would Apple hit a trillion dollars? Kylie Jenner? "It was anything," she says.
Are mortgage rates going up? Yes or no?
Mansour saw the business potential when Lopes Lara suggested it. He interned at Goldman Sachs Group Inc., helping investors prepare for the UK leaving the EU. Goldman sold clients complex stock-and-derivative combinations. As he discussed it with Lopes Lara, they agreed that investors should hedge their risk by betting on Brexit itself rather than an imperfect proxy.
Lopes Lara and Mansour hypothesized how a marketplace might work. They settled on a "event contract," a binary-outcome instrument like "Will inflation hit 5% by the end of the month?" The contract would settle at $1 (if the event happened) or zero (if it didn't), but its price would fluctuate based on market sentiment. After a good debate, a politician's election odds may rise from 50 to 55. Kalshi would charge a commission on every trade and sell data to traders, political campaigns, businesses, and others.
In October 2018, five months after graduation, the pair flew to California to compete in a hackathon for wannabe tech founders organized by the Silicon Valley incubator Y Combinator. They built a website in a day and a night and presented it to entrepreneurs the next day. Their prototype barely worked, but they won a three-month mentorship program and $150,000. Michael Seibel, managing director of Y Combinator, said of their idea, "I had to take a chance!"
Will there be another moon landing by 2025?
Seibel's skepticism was rooted in America's historical wariness of gambling. Roulette, poker, and other online casino games are largely illegal, and sports betting was only legal in a few states until May 2018. Kalshi as a risk-hedging platform rather than a bookmaker seemed like a good idea, but convincing the CFTC wouldn't be easy. In 2012, the CFTC said trading on politics had no "economic purpose" and was "contrary to the public interest."
Lopes Lara and Mansour cold-called 60 Googled lawyers during their time at Y Combinator. Everyone advised quitting. Mansour recalls the pain. Jeff Bandman, a former CFTC official, helped them navigate the agency and its characters.
When they weren’t busy trying to recruit lawyers, Lopes Lara and Mansour were meeting early-stage investors. Alfred Lin of Sequoia Capital Operations LLC backed Airbnb, DoorDash, and Uber Technologies. Lin told the founders their idea could capitalize on retail trading and challenge how the financial world manages risk. "Come back with regulatory approval," he said.
In the US, even small bets on most events were once illegal. Under the Commodity Exchange Act, the CFTC can stop exchanges from listing contracts relating to "terrorism, assassination, war" and "gaming" if they are "contrary to the public interest," which was often the case.
Will subway ridership return to normal? Yes or no?
In 1988, as academic interest in the field grew, the agency allowed the University of Iowa to set up a prediction market for research purposes, as long as it didn't make a profit or advertise and limited bets to $500. PredictIt, the biggest and best-known political betting platform in the US, also got an exemption thanks to an association with Victoria University of Wellington in New Zealand. Today, it's a sprawling marketplace with its own subculture and lingo. PredictIt users call it "Rules Cuck Panther" when they lose on a technicality. Major news outlets cite PredictIt's odds on Discord and the Star Spangled Gamblers podcast.
CFTC limits PredictIt bets to $850. To keep traders happy, PredictIt will often run multiple variations of the same question, listing separate contracts for two dozen Democratic primary candidates, for example. A trader could have more than $10,000 riding on a single outcome. Some of the site's traders are current or former campaign staffers who can answer questions like "How many tweets will Donald Trump post from Nov. 20 to 27?" and "When will Anthony Scaramucci's role as White House communications director end?"
According to PredictIt co-founder John Phillips, politicians help explain the site's accuracy. "Prediction markets work well and are accurate because they attract people with superior information," he said in a 2016 podcast. “In the financial stock market, it’s called inside information.”
Will Build Back Better pass? Yes or no?
Trading on nonpublic information is illegal outside of academia, which presented a dilemma for Lopes Lara and Mansour. Kalshi's forecasts needed to be accurate. Kalshi must eliminate insider trading as a regulated entity. Lopes Lara and Mansour wanted to build a high-stakes PredictIt without the anarchy or blurred legal lines—a "New York Stock Exchange for Events." First, they had to convince regulators event trading was safe.
When Lopes Lara and Mansour approached the CFTC in the spring of 2019, some officials in the Division of Market Oversight were skeptical, according to interviews with people involved in the process. For all Kalshi's talk of revolutionizing finance, this was just a turbocharged version of something that had been rejected before.
The DMO couldn't see the big picture. The staff review was supposed to ensure Kalshi could complete a checklist, "23 Core Principles of a Designated Contract Market," which included keeping good records and having enough money. The five commissioners decide. With Trump as president, three of them were ideologically pro-market.
Lopes Lara, Mansour, and their lawyer Bandman, an ex-CFTC official, answered the DMO's questions while lobbying the commissioners on Zoom about the potential of event markets to mitigate risks and make better decisions. Before each meeting, they would write a script and memorize it word for word.
Will student debt be forgiven? Yes or no?
Several prediction markets that hadn't sought regulatory approval bolstered Kalshi's case. Polymarket let customers bet hundreds of thousands of dollars anonymously using cryptocurrencies, making it hard to track. Augur, which facilitates private wagers between parties using blockchain, couldn't regulate bets and hadn't stopped users from betting on assassinations. Kalshi, by comparison, argued it was doing everything right. (The CFTC fined Polymarket $1.4 million for operating an unlicensed exchange in January 2022. Polymarket says it's now compliant and excited to pioneer smart contract-based financial solutions with regulators.
Kalshi was approved unanimously despite some DMO members' concerns about event contracts' riskiness. "Once they check all the boxes, they're in," says a CFTC insider.
Three months after CFTC approval, Kalshi announced funding from Sequoia, Charles Schwab, and Henry Kravis. Sequoia's Lin, who joined the board, said Tarek, Luana, and team created a new way to invest and engage with the world.
The CFTC hadn't asked what markets the exchange planned to run since. After approval, Lopes Lara and Mansour had the momentum. Kalshi's March list of 30 proposed contracts caused chaos at the DMO. The division handles exchanges that create two or three new markets a year. Kalshi’s business model called for new ones practically every day.
Uncontroversial proposals included weather and GDP questions. Others, on the initial list and later, were concerning. DMO officials feared Covid-19 contracts amounted to gambling on human suffering, which is why war and terrorism markets are banned. (Similar logic doomed ex-admiral John Poindexter's Policy Analysis Market, a Bush-era plan to uncover intelligence by having security analysts bet on Middle East events.) Regulators didn't see how predicting the Grammy winners was different from betting on the Patriots to win the Super Bowl. Who, other than John Legend, would need to hedge the best R&B album winner?
Event contracts raised new questions for the DMO's product review team. Regulators could block gaming contracts that weren't in the public interest under the Commodity Exchange Act, but no one had defined gaming. It was unclear whether the CFTC had a right or an obligation to consider whether a contract was in the public interest. How was it to determine public interest? Another person familiar with the CFTC review says, "It was a mess." The agency didn't comment.
CFTC staff feared some event contracts could be cheated. Kalshi wanted to run a bee-endangerment market. The DMO pushed back, saying it saw two problems symptomatic of the asset class: traders could press government officials for information, and officials could delay adding the insects to the list to cash in.
The idea that traders might manipulate prediction markets wasn't paranoid. In 2013, academics David Rothschild and Rajiv Sethi found that an unidentified party lost $7 million buying Mitt Romney contracts on Intrade, a now-defunct, unlicensed Irish platform, in the runup to the 2012 election. The authors speculated that the trader, whom they dubbed the “Romney Whale,” may have been looking to boost morale and keep donations coming in.
Kalshi said manipulation and insider trading are risks for any market. It built a surveillance system and said it would hire a team to monitor it. "People trade on events all the time—they just use options and other instruments. This brings everything into the open, Mansour says. Kalshi didn't include election contracts, a red line for CFTC Democrats.
Lopes Lara and Mansour were ready to launch kalshi.com that summer, but the DMO blocked them. Product reviewers were frustrated by spending half their time on an exchange that represented a tiny portion of the derivatives market. Lopes Lara and Mansour pressed politically appointed commissioners during the impasse.
Tarbert, the chairman, had moved on, but Kalshi found a new supporter in Republican Brian Quintenz, a crypto-loving former hedge fund manager. He was unmoved by the DMO's concerns, arguing that speculation on Kalshi's proposed events was desirable and the agency had no legal standing to prevent it. He supported a failed bid to allow NFL futures earlier this year. Others on the commission were cautious but supportive. Given the law's ambiguity, they worried they'd be on shaky ground if Kalshi sued if they blocked a contract. Without a permanent chairman, the agency lacked leadership.
To block a contract, DMO staff needed a majority of commissioners' support, which they didn't have in all but a few cases. "We didn't have the votes," a reviewer says, paraphrasing Hamilton. By the second half of 2021, new contract requests were arriving almost daily at the DMO, and the demoralized and overrun division eventually accepted defeat and stopped fighting back. By the end of the year, three senior DMO officials had left the agency, making it easier for Kalshi to list its contracts unimpeded.
Today, Kalshi is growing. 32 employees work in a SoHo office with big windows and exposed brick. Quintenz, who left the CFTC 10 months after Kalshi was approved, is on its board. He joined because he was interested in the market's hedging and risk management opportunities.
Mid-May, the company's website had 75 markets, such as "Will Q4 GDP be negative?" Will NASA land on the moon by 2025? The exchange recently reached 2 million weekly contracts, a jump from where it started but still a small number compared to other futures exchanges. Early adopters are PredictIt and Polymarket fans. Bets on the site are currently capped at $25,000, but Kalshi hopes to increase that to $100,000 and beyond.
With the regulatory drawbridge down, Lopes Lara and Mansour must move quickly. Chicago's CME Group Inc. plans to offer index-linked event contracts. Kalshi will release a smartphone app to attract customers. After that, it hopes to partner with a big brokerage. Sequoia is a major investor in Robinhood Markets Inc. Robinhood users could have access to Kalshi so that after buying GameStop Corp. shares, they'd be prompted to bet on the Oscars or the next Fed commissioner.
Some, like Illinois Democrat Sean Casten, accuse Robinhood and its competitors of gamifying trading to encourage addiction, but Kalshi doesn't seem worried. Mansour says Kalshi's customers can't bet more than they've deposited, making debt difficult. Eventually, he may introduce leveraged bets.
Tension over event contracts recalls another CFTC episode. Brooksley Born proposed regulating the financial derivatives market in 1994. Alan Greenspan and others in the government opposed her, saying it would stifle innovation and push capital overseas. Unrestrained, derivatives grew into a trillion-dollar industry until 2008, when they sparked the financial crisis.
Today, with a midterm election looming, it seems reasonable to ask whether Kalshi plans to get involved. Elections have historically been the biggest draw in prediction markets, with 125 million shares traded on PredictIt for 2020. “We can’t discuss specifics,” Mansour says. “All I can say is, you know, we’re always working on expanding the universe of things that people can trade on.”
Any election contracts would need CFTC approval, which may be difficult with three Democratic commissioners. A Republican president would change the equation.

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