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Howey Test and Cryptocurrencies: 'Every ICO Is a Security'
What Is the Howey Test?
To determine whether a transaction qualifies as a "investment contract" and thus qualifies as a security, the Howey Test refers to the U.S. Supreme Court cass: the Securities Act of 1933 and the Securities Exchange Act of 1934. According to the Howey Test, an investment contract exists when "money is invested in a common enterprise with a reasonable expectation of profits from others' efforts."
The test applies to any contract, scheme, or transaction. The Howey Test helps investors and project backers understand blockchain and digital currency projects. ICOs and certain cryptocurrencies may be found to be "investment contracts" under the test.
Understanding the Howey Test
The Howey Test comes from the 1946 Supreme Court case SEC v. W.J. Howey Co. The Howey Company sold citrus groves to Florida buyers who leased them back to Howey. The company would maintain the groves and sell the fruit for the owners. Both parties benefited. Most buyers had no farming experience and were not required to farm the land.
The SEC intervened because Howey failed to register the transactions. The court ruled that the leaseback agreements were investment contracts.
This established four criteria for determining an investment contract. Investing contract:
- An investment of money
- n a common enterprise
- With the expectation of profit
- To be derived from the efforts of others
In the case of Howey, the buyers saw the transactions as valuable because others provided the labor and expertise. An income stream was obtained by only investing capital. As a result of the Howey Test, the transaction had to be registered with the SEC.
Howey Test and Cryptocurrencies
Bitcoin is notoriously difficult to categorize. Decentralized, they evade regulation in many ways. Regardless, the SEC is looking into digital assets and determining when their sale qualifies as an investment contract.
The SEC claims that selling digital assets meets the "investment of money" test because fiat money or other digital assets are being exchanged. Like the "common enterprise" test.
Whether a digital asset qualifies as an investment contract depends on whether there is a "expectation of profit from others' efforts."
For example, buyers of digital assets may be relying on others' efforts if they expect the project's backers to build and maintain the digital network, rather than a dispersed community of unaffiliated users. Also, if the project's backers create scarcity by burning tokens, the test is met. Another way the "efforts of others" test is met is if the project's backers continue to act in a managerial role.
These are just a few examples given by the SEC. If a project's success is dependent on ongoing support from backers, the buyer of the digital asset is likely relying on "others' efforts."
Special Considerations
If the SEC determines a cryptocurrency token is a security, many issues arise. It means the SEC can decide whether a token can be sold to US investors and forces the project to register.
In 2017, the SEC ruled that selling DAO tokens for Ether violated federal securities laws. Instead of enforcing securities laws, the SEC issued a warning to the cryptocurrency industry.
Due to the Howey Test, most ICOs today are likely inaccessible to US investors. After a year of ICOs, then-SEC Chair Jay Clayton declared them all securities.
SEC Chairman Gensler Agrees With Predecessor: 'Every ICO Is a Security'
Howey Test FAQs
How Do You Determine If Something Is a Security?
The Howey Test determines whether certain transactions are "investment contracts." Securities are transactions that qualify as "investment contracts" under the Securities Act of 1933 and the Securities Exchange Act of 1934.
The Howey Test looks for a "investment of money in a common enterprise with a reasonable expectation of profits from others' efforts." If so, the Securities Act of 1933 and the Securities Exchange Act of 1934 require disclosure and registration.
Why Is Bitcoin Not a Security?
Former SEC Chair Jay Clayton clarified in June 2018 that bitcoin is not a security: "Cryptocurrencies: Replace the dollar, euro, and yen with bitcoin. That type of currency is not a security," said Clayton.
Bitcoin, which has never sought public funding to develop its technology, fails the SEC's Howey Test. However, according to Clayton, ICO tokens are securities.
A Security Defined by the SEC
In the public and private markets, securities are fungible and tradeable financial instruments. The SEC regulates public securities sales.
The Supreme Court defined a security offering in SEC v. W.J. Howey Co. In its judgment, the court defines a security using four criteria:
- An investment contract's existence
- The formation of a common enterprise
- The issuer's profit promise
- Third-party promotion of the offering
Read original post.
More on Web3 & Crypto
Ajay Shrestha
2 years ago
Bitcoin's technical innovation: addressing the issue of the Byzantine generals
The 2008 Bitcoin white paper solves the classic computer science consensus problem.
Issue Statement
The Byzantine Generals Problem (BGP) is called after an allegory in which several generals must collaborate and attack a city at the same time to win (figure 1-left). Any general who retreats at the last minute loses the fight (figure 1-right). Thus, precise messengers and no rogue generals are essential. This is difficult without a trusted central authority.
In their 1982 publication, Leslie Lamport, Robert Shostak, and Marshall Please termed this topic the Byzantine Generals Problem to simplify distributed computer systems.
Consensus in a distributed computer network is the issue. Reaching a consensus on which systems work (and stay in the network) and which don't makes maintaining a network tough (i.e., needs to be removed from network). Challenges include unreliable communication routes between systems and mis-reporting systems.
Solving BGP can let us construct machine learning solutions without single points of failure or trusted central entities. One server hosts model parameters while numerous workers train the model. This study describes fault-tolerant Distributed Byzantine Machine Learning.
Bitcoin invented a mechanism for a distributed network of nodes to agree on which transactions should go into the distributed ledger (blockchain) without a trusted central body. It solved BGP implementation. Satoshi Nakamoto, the pseudonymous bitcoin creator, solved the challenge by cleverly combining cryptography and consensus mechanisms.
Disclaimer
This is not financial advice. It discusses a unique computer science solution.
Bitcoin
Bitcoin's white paper begins:
“A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution.” Source: https://www.ussc.gov/sites/default/files/pdf/training/annual-national-training-seminar/2018/Emerging_Tech_Bitcoin_Crypto.pdf
Bitcoin's main parts:
The open-source and versioned bitcoin software that governs how nodes, miners, and the bitcoin token operate.
The native kind of token, known as a bitcoin token, may be created by mining (up to 21 million can be created), and it can be transferred between wallet addresses in the bitcoin network.
Distributed Ledger, which contains exact copies of the database (or "blockchain") containing each transaction since the first one in January 2009.
distributed network of nodes (computers) running the distributed ledger replica together with the bitcoin software. They broadcast the transactions to other peer nodes after validating and accepting them.
Proof of work (PoW) is a cryptographic requirement that must be met in order for a miner to be granted permission to add a new block of transactions to the blockchain of the cryptocurrency bitcoin. It takes the form of a valid hash digest. In order to produce new blocks on average every 10 minutes, Bitcoin features a built-in difficulty adjustment function that modifies the valid hash requirement (length of nonce). PoW requires a lot of energy since it must continually generate new hashes at random until it satisfies the criteria.
The competing parties known as miners carry out continuous computing processing to address recurrent cryptography issues. Transaction fees and some freshly minted (mined) bitcoin are the rewards they receive. The amount of hashes produced each second—or hash rate—is a measure of mining capacity.
Cryptography, decentralization, and the proof-of-work consensus method are Bitcoin's most unique features.
Bitcoin uses encryption
Bitcoin employs this established cryptography.
Hashing
digital signatures based on asymmetric encryption
Hashing (SHA-256) (SHA-256)
Hashing converts unique plaintext data into a digest. Creating the plaintext from the digest is impossible. Bitcoin miners generate new hashes using SHA-256 to win block rewards.
A new hash is created from the current block header and a variable value called nonce. To achieve the required hash, mining involves altering the nonce and re-hashing.
The block header contains the previous block hash and a Merkle root, which contains hashes of all transactions in the block. Thus, a chain of blocks with increasing hashes links back to the first block. Hashing protects new transactions and makes the bitcoin blockchain immutable. After a transaction block is mined, it becomes hard to fabricate even a little entry.
Asymmetric Cryptography Digital Signatures
Asymmetric cryptography (public-key encryption) requires each side to have a secret and public key. Public keys (wallet addresses) can be shared with the transaction party, but private keys should not. A message (e.g., bitcoin payment record) can only be signed by the owner (sender) with the private key, but any node or anybody with access to the public key (visible in the blockchain) can verify it. Alex will submit a digitally signed transaction with a desired amount of bitcoin addressed to Bob's wallet to a node to send bitcoin to Bob. Alex alone has the secret keys to authorize that amount. Alex's blockchain public key allows anyone to verify the transaction.
Solution
Now, apply bitcoin to BGP. BGP generals resemble bitcoin nodes. The generals' consensus is like bitcoin nodes' blockchain block selection. Bitcoin software on all nodes can:
Check transactions (i.e., validate digital signatures)
2. Accept and propagate just the first miner to receive the valid hash and verify it accomplished the task. The only way to guess the proper hash is to brute force it by repeatedly producing one with the fixed/current block header and a fresh nonce value.
Thus, PoW and a dispersed network of nodes that accept blocks from miners that solve the unfalsifiable cryptographic challenge solve consensus.
Suppose:
Unreliable nodes
Unreliable miners
Bitcoin accepts the longest chain if rogue nodes cause divergence in accepted blocks. Thus, rogue nodes must outnumber honest nodes in accepting/forming the longer chain for invalid transactions to reach the blockchain. As of November 2022, 7000 coordinated rogue nodes are needed to takeover the bitcoin network.
Dishonest miners could also try to insert blocks with falsified transactions (double spend, reverse, censor, etc.) into the chain. This requires over 50% (51% attack) of miners (total computational power) to outguess the hash and attack the network. Mining hash rate exceeds 200 million (source). Rewards and transaction fees encourage miners to cooperate rather than attack. Quantum computers may become a threat.
Visit my Quantum Computing post.
Quantum computers—what are they? Quantum computers will have a big influence. towardsdatascience.com
Nodes have more power than miners since they can validate transactions and reject fake blocks. Thus, the network is secure if honest nodes are the majority.
Summary
Table 1 compares three Byzantine Generals Problem implementations.
Bitcoin white paper and implementation solved the consensus challenge of distributed systems without central governance. It solved the illusive Byzantine Generals Problem.
Resources
Resources
Source-code for Bitcoin Core Software — https://github.com/bitcoin/bitcoin
Bitcoin white paper — https://bitcoin.org/bitcoin.pdf
https://www.microsoft.com/en-us/research/publication/byzantine-generals-problem/
https://www.microsoft.com/en-us/research/uploads/prod/2016/12/The-Byzantine-Generals-Problem.pdf
Genuinely Distributed Byzantine Machine Learning, El-Mahdi El-Mhamdi et al., 2020. ACM, New York, NY, https://doi.org/10.1145/3382734.3405695
Franz Schrepf
3 years ago
What I Wish I'd Known About Web3 Before Building
Cryptoland rollercoaster
I've lost money in crypto.
Unimportant.
The real issue: I didn’t understand how.
I'm surrounded with winners. To learn more, I created my own NFTs, currency, and DAO.
Web3 is a hilltop castle. Everything is valuable, decentralized, and on-chain.
The castle is Disneyland: beautiful in images, but chaotic with lengthy lines and kids spending too much money on dressed-up animals.
When the throng and businesses are gone, Disneyland still has enchantment.
The Real Story of Web3
NFTs
Scarcity. Scarce NFTs. That's their worth.
Skull. Rare-looking!
Nonsense.
Bored Ape Yacht Club vs. my NFTs?
Marketing.
BAYC is amazing, but not for the reasons people believe. Apecoin and Otherside's art, celebrity following, and innovation? Stunning.
No other endeavor captured the zeitgeist better. Yet how long did you think it took to actually mint the NFTs?
1 hour? Maybe a week for the website?
Minting NFTs is incredibly easy. Kid-friendly. Developers are rare. Think about that next time somebody posts “DevS dO SMt!?”
NFTs will remain popular. These projects are like our Van Goghs and Monets. Still, be wary. It still uses exclusivity and wash selling like the OG art market.
Not all NFTs are art-related.
Soulbound and anonymous NFTs could offer up new use cases. Property rights, privacy-focused ID, open-source project verification. Everything.
NFTs build online trust through ownership.
We just need to evolve from the apes first.
NFTs' superpower is marketing until then.
Crypto currency
What the hell is a token?
99% of people are clueless.
So I invested in both coins and tokens. Same same. Only that they are not.
Coins have their own blockchain and developer/validator community. It's hard.
Creating a token on top of a blockchain? Five minutes.
Most consumers don’t understand the difference, creating an arbitrage opportunity: pretend you’re a serious project without having developers on your payroll.
Few market sites help. Take a look. See any tokens?
There's a hint one click deeper.
Some tokens are legitimate. Some coins are bad investments.
Tokens are utilized for DAO governance and DApp payments. Still, know who's behind a token. They might be 12 years old.
Coins take time and money. The recent LUNA meltdown indicates that currency investing requires research.
DAOs
Decentralized Autonomous Organizations (DAOs) don't work as you assume.
Yes, members can vote.
A productive organization requires more.
I've observed two types of DAOs.
Total decentralization total dysfunction
Centralized just partially. Community-driven.
A core team executes the DAO's strategy and roadmap in successful DAOs. The community owns part of the organization, votes on decisions, and holds the team accountable.
DAOs are public companies.
Amazing.
A shareholder meeting's logistics are staggering. DAOs may hold anonymous, secure voting quickly. No need for intermediaries like banks to chase up every shareholder.
Successful DAOs aren't totally decentralized. Large-scale voting and collaboration have never been easier.
And that’s all that matters.
Scale, speed.
My Web3 learnings
Disneyland is enchanting. Web3 too.
In a few cycles, NFTs may be used to build trust, not clout. Not speculating with coins. DAOs run organizations, not themselves.
Finally, some final thoughts:
NFTs will be a very helpful tool for building trust online. NFTs are successful now because of excellent marketing.
Tokens are not the same as coins. Look into any project before making a purchase. Make sure it isn't run by three 9-year-olds piled on top of one another in a trench coat, at the very least.
Not entirely decentralized, DAOs. We shall see a future where community ownership becomes the rule rather than the exception once we acknowledge this fact.
Crypto Disneyland is a rollercoaster with loops that make you sick.
Always buckle up.
Have fun!
Sam Hickmann
4 years ago
A quick guide to formatting your text on INTΞGRITY
[06/20/2022 update] We have now implemented a powerful text editor, but you can still use markdown.
Markdown:
Headers
SYNTAX:
# This is a heading 1
## This is a heading 2
### This is a heading 3
#### This is a heading 4
RESULT:
This is a heading 1
This is a heading 2
This is a heading 3
This is a heading 4
Emphasis
SYNTAX:
**This text will be bold**
~~Strikethrough~~
*You **can** combine them*
RESULT:
This text will be italic
This text will be bold
You can combine them
Images
SYNTAX:
RESULT:
Videos
SYNTAX:
https://www.youtube.com/watch?v=7KXGZAEWzn0
RESULT:
Links
SYNTAX:
[Int3grity website](https://www.int3grity.com)
RESULT:
Tweets
SYNTAX:
https://twitter.com/samhickmann/status/1503800505864130561
RESULT:
Blockquotes
SYNTAX:
> Human beings face ever more complex and urgent problems, and their effectiveness in dealing with these problems is a matter that is critical to the stability and continued progress of society. \- Doug Engelbart, 1961
RESULT:
Human beings face ever more complex and urgent problems, and their effectiveness in dealing with these problems is a matter that is critical to the stability and continued progress of society. - Doug Engelbart, 1961
Inline code
SYNTAX:
Text inside `backticks` on a line will be formatted like code.
RESULT:
Text inside backticks on a line will be formatted like code.
Code blocks
SYNTAX:
'''js
function fancyAlert(arg) {
if(arg) {
$.facebox({div:'#foo'})
}
}
'''
RESULT:
function fancyAlert(arg) {
if(arg) {
$.facebox({div:'#foo'})
}
}
Maths
We support LaTex to typeset math. We recommend reading the full documentation on the official website
SYNTAX:
$$[x^n+y^n=z^n]$$
RESULT:
[x^n+y^n=z^n]
Tables
SYNTAX:
| header a | header b |
| ---- | ---- |
| row 1 col 1 | row 1 col 2 |
RESULT:
| header a | header b | header c |
|---|---|---|
| row 1 col 1 | row 1 col 2 | row 1 col 3 |
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Architectural Digest
3 years ago
Take a look at The One, a Los Angeles estate with a whopping 105,000 square feet of living area.
The interiors of the 105,000-square-foot property, which sits on a five-acre parcel in the wealthy Los Angeles suburb of Bel Air and is suitably titled The One, have been a well guarded secret. We got an intimate look inside this world-record-breaking property, as well as the creative and aesthetic geniuses behind it.
The estate appears to float above the city, surrounded on three sides by a moat and a 400-foot-long running track. Completed over eight years—and requiring 600 workers to build—the home was designed by architect Paul McClean and interior designer Kathryn Rotondi, who were enlisted by owner and developer Nile Niami to help it live up to its standard.
"This endeavor seemed both exhilarating and daunting," McClean says. However, the home's remarkable location and McClean's long-standing relationship with Niami persuaded him to "build something unique and extraordinary" rather than just take on the job.
And McClean has more than delivered.
The home's main entrance leads to a variety of meeting places with magnificent 360-degree views of the Pacific Ocean, downtown Los Angeles, and the San Gabriel Mountains, thanks to its 26-foot-high ceilings. There is water at the entrance area, as well as a sculpture and a bridge. "We often employ water in our design approach because it provides a sensory change that helps you acclimatize to your environment," McClean explains.
Niami wanted a neutral palette that would enable the environment and vistas to shine, so she used black, white, and gray throughout the house.
McClean has combined the home's inside with outside "to create that quintessential L.A. lifestyle but on a larger scale," he says, drawing influence from the local environment and history of Los Angeles modernism. "We separated the entertaining spaces from the living portions to make the house feel more livable. The former are on the lowest level, which serves as a plinth for the rest of the house and minimizes its apparent mass."
The home's statistics, in addition to its eye-catching style, are equally impressive. There are 42 bathrooms, 21 bedrooms, a 5,500-square-foot master suite, a 30-car garage gallery with two car-display turntables, a four-lane bowling alley, a spa level, a 30-seat movie theater, a "philanthropy wing (with a capacity of 200) for charity galas, a 10,000-square-foot sky deck, and five swimming pools.
Rotondi, the creator of KFR Design, collaborated with Niami on the interior design to create different spaces that flow into one another despite the house's grandeur. "I was especially driven to 'wow factor' components in the hospitality business," Rotondi says, citing top luxury hotel brands such as Aman, Bulgari, and Baccarat as sources of inspiration. Meanwhile, the home's color scheme, soft textures, and lighting are a nod to Niami and McClean's favorite Tom Ford boutique on Rodeo Drive.
The house boasts an extraordinary collection of art, including a butterfly work by Stephen Wilson on the lower level and a Niclas Castello bespoke panel in black and silver in the office, thanks to a cooperation between Creative Art Partners and Art Angels. There is also a sizable collection of bespoke furniture pieces from byShowroom.
A house of this size will never be erected again in Los Angeles, thanks to recently enacted city rules, so The One will truly be one of a kind. "For all of us, this project has been such a long and instructive trip," McClean says. "It was exciting to develop and approached with excitement, but I don't think any of us knew how much effort and time it would take to finish the project."
Pen Magnet
3 years ago
Why Google Staff Doesn't Work
Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.
To boost employee efficiency.
Not surprising. Few envisioned Google declaring a productivity drive.
Sunder Pichai's speech:
“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”
The primary driver driving Google's efficiency push is:
Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.
Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.
Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.
Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.
In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.
FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.
Google has hardly ever discussed effectiveness:
Apparently openly.
Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.
Amazon trumps Google. In reality, it treats its employees poorly.
Google was the founding father of the modern-day open culture.
Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.
20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.
After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.
Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?
If so, would Google follow suit?
If so, how does Google go about doing it?
Before discussing Google's likely plan, let's examine programming productivity.
What determines a programmer's productivity is simple:
How would we answer Google's questions?
As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.
Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.
Deconstruct our main question.
How exactly do you change the culture of the firm so that productivity increases?
How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.
How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)
How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?
When implementing a large-scale organizational change, success must be carefully measured.
The fastest way to do something is to do it right, no matter how long it takes.
You require clearly-defined group/team/role segregation and solid pass/fail matrices to:
You can give performers rewards.
Ones that are average can be inspired to improve
Underachievers may receive assistance or, in the worst-case scenario, rehabilitation
As a 20-year programmer, I associate productivity with greatness.
Doing something well, no matter how long it takes, is the fastest way to do it.
Let's discuss a programmer's productivity.
Why productivity is a strange term in programming:
Productivity is work per unit of time.
Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.
As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.
All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.
Time is money — is not just a proverb, but an economical fact.
Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.
Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.
Programming productivity isn't linear, unlike manufacturing and maintenance.
Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.
Reversing the programming duties has no effect. Experts aren't needed for productivity.
These patterns remind me of an XKCD comic.
Programming productivity depends on two factors:
The capacity of the programmer and his or her command of the principles of computer science
His or her productive bursts, how often they occur, and how long they last as they engineer the answer
At some point, productivity measurement becomes Schrödinger’s cat.
Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.
Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.
Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.
Google can pull it off if it wants to.
What Google meant in reality when it said that employee productivity has decreased:
When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.
They can't multiply their work's influence over time.
Programmers who produce excellent modules or products are unsure on how to use them.
The best data scientists are unable to add the proper parameters in their models.
Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.
Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.
Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.
So, Google employees aren't productive.
How to fix it?
Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.
SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.
Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.
Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.
Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).
In conclusion:
Software development isn't linear. Why should the makers be measured?
Notation for The Big O
I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)
The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)
Google (or any large corporation) can do this.
Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.
Plot the influence of each employee over time using the X and Y axes, respectively.
Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).
Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.
After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.
Example of a Big(O) Category:
If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.
The Google interview truth:
O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.
O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.
CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.
Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.
UX/UI Designers must still prototype UI elements despite improved design tools.
All test cases are proportional to use cases/functional units, hence testers' work is O(N).
Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.
Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.
Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.
The fastest way to do something is to do it right, no matter how long it takes.
Conclusion:
Google is at the liberal extreme of the employee-handling spectrum
Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.
Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.
Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.
Any attempt to redefine people's measurements will affect the organization emotionally.
The more Google compares apples to apples, the higher its chances for future rebirth.
Quant Galore
3 years ago
I created BAW-IV Trading because I was short on money.
More retail traders means faster, more sophisticated, and more successful methods.
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Only requires a laptop and an internet connection.
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Background
You don't need to know the arithmetic details to use this method.
Black-Scholes is a popular option pricing model. It's best for pricing European options. European options are only exercisable at expiration, unlike American options. American options are always exercisable.
American options carry a premium to cover for the risk of early exercise. The Black-Scholes model doesn't account for this premium, hence it can't price genuine, traded American options.
Barone-Adesi-Whaley (BAW) model. BAW modifies Black-Scholes. It accounts for exercise risk premium and stock dividends. It adds the option's early exercise value to the Black-Scholes value.
The trader need not know the formulaic derivations of this model.
https://ir.nctu.edu.tw/bitstream/11536/14182/1/000264318900005.pdf
Strategy
This strategy targets implied volatility. First, we'll locate liquid options that expire within 30 days and have minimal implied volatility.
After selecting the option that meets the requirements, we price it to get the BAW implied volatility (we choose BAW because it's a more accurate Black-Scholes model). If estimated implied volatility is larger than market volatility, we'll capture the spread.
(Calculated IV — Market IV) = (Profit)
Some approaches to target implied volatility are pricey and inaccessible to individual investors. The best and most cost-effective alternative is to acquire a straddle and delta hedge. This may sound terrifying and pricey, but as shown below, it's much less so.
The Trade
First, we want to find our ideal option, so we use OpenBB terminal to screen for options that:
Have an IV at least 5% lower than the 20-day historical IV
Are no more than 5% out-of-the-money
Expire in less than 30 days
We query:
stocks/options/screen/set low_IV/scr --export Output.csv
This uses the screener function to screen for options that satisfy the above criteria, which we specify in the low IV preset (more on custom presets here). It then saves the matching results to a csv(Excel) file for viewing and analysis.
Stick to liquid names like SPY, AAPL, and QQQ since getting out of a position is just as crucial as getting in. Smaller, illiquid names have higher inefficiencies, which could restrict total profits.
We calculate IV using the BAWbisection model (the bisection is a method of calculating IV, more can be found here.) We price the IV first.
According to the BAW model, implied volatility at this level should be priced at 26.90%. When re-pricing the put, IV is 24.34%, up 3%.
Now it's evident. We must purchase the straddle (long the call and long the put) assuming the computed implied volatility is more appropriate and efficient than the market's. We just want to speculate on volatility, not price fluctuations, thus we delta hedge.
The Fun Starts
We buy both options for $7.65. (x100 multiplier). Initial delta is 2. For every dollar the stock price swings up or down, our position value moves $2.
We want delta to be 0 to avoid price vulnerability. A delta of 0 suggests our position's value won't change from underlying price changes. Being delta-hedged allows us to profit/lose from implied volatility. Shorting 2 shares makes us delta-neutral.
That's delta hedging. (Share price * shares traded) = $330.7 to become delta-neutral. You may have noted that delta is not truly 0.00. This is common since delta-hedging means getting as near to 0 as feasible, since it is rare for deltas to align at 0.00.
Now we're vulnerable to changes in Vega (and Gamma, but given we're dynamically hedging, it's not a big risk), or implied volatility. We wanted to gamble that the position's IV would climb by at least 2%, so we'll maintain it delta-hedged and watch IV.
Because the underlying moves continually, the option's delta moves continuously. A trader can short/long 5 AAPL shares at most. Paper trading lets you practice delta-hedging. Being quick-footed will help with this tactic.
Profit-Closing
As expected, implied volatility rose. By 10 minutes before market closure, the call's implied vol rose to 27% and the put's to 24%. This allowed us to sell the call for $4.95 and the put for $4.35, creating a profit of $165.
You may pull historical data to see how this trade performed. Note the implied volatility and pricing in the final options chain for August 5, 2022 (the position date).
Final Thoughts
Congratulations, that was a doozy. To reiterate, we identified tickers prone to increased implied volatility by screening OpenBB's low IV setting. We double-checked the IV by plugging the price into Options-BAW Quant's model. When volatility was off, we bought a straddle and delta-hedged it. Finally, implied volatility returned to a normal level, and we profited on the spread.
The retail trading space is very quickly catching up to that of institutions. Commissions and fees used to kill this method, but now they cost less than $5. Watching momentum, technical analysis, and now quantitative strategies evolve is intriguing.
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