More on Web3 & Crypto

Jeff John Roberts
3 years ago
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

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.

Isaac Benson
3 years ago
What's the difference between Proof-of-Time and Proof-of-History?

Blockchain validates transactions with consensus algorithms. Bitcoin and Ethereum use Proof-of-Work, while Polkadot and Cardano use Proof-of-Stake.
Other consensus protocols are used to verify transactions besides these two. This post focuses on Proof-of-Time (PoT), used by Analog, and Proof-of-History (PoH), used by Solana as a hybrid consensus protocol.
PoT and PoH may seem similar to users, but they are actually very different protocols.
Proof-of-Time (PoT)
Analog developed Proof-of-Time (PoT) based on Delegated Proof-of-Stake (DPoS). Users select "delegates" to validate the next block in DPoS. PoT uses a ranking system, and validators stake an equal amount of tokens. Validators also "self-select" themselves via a verifiable random function."
The ranking system gives network validators a performance score, with trustworthy validators with a long history getting higher scores. System also considers validator's fixed stake. PoT's ledger is called "Timechain."
Voting on delegates borrows from DPoS, but there are changes. PoT's first voting stage has validators (or "time electors" putting forward a block to be included in the ledger).
Validators are chosen randomly based on their ranking score and fixed stake. One validator is chosen at a time using a Verifiable Delay Function (VDF).
Validators use a verifiable delay function to determine if they'll propose a Timechain block. If chosen, they validate the transaction and generate a VDF proof before submitting both to other Timechain nodes.
This leads to the second process, where the transaction is passed through 1,000 validators selected using the same method. Each validator checks the transaction to ensure it's valid.
If the transaction passes, validators accept the block, and if over 2/3 accept it, it's added to the Timechain.
Proof-of-History (PoH)
Proof-of-History is a consensus algorithm that proves when a transaction occurred. PoH uses a VDF to verify transactions, like Proof-of-Time. Similar to Proof-of-Work, VDFs use a lot of computing power to calculate but little to verify transactions, similar to (PoW).
This shows users and validators how long a transaction took to verify.
PoH uses VDFs to verify event intervals. This process uses cryptography to prevent determining output from input.
The outputs of one transaction are used as inputs for the next. Timestamps record the inputs' order. This checks if data was created before an event.
PoT vs. PoH
PoT and PoH differ in that:
PoT uses VDFs to select validators (or time electors), while PoH measures time between events.
PoH uses a VDF to validate transactions, while PoT uses a ranking system.
PoT's VDF-elected validators verify transactions proposed by a previous validator. PoH uses a VDF to validate transactions and data.
Conclusion
Both Proof-of-Time (PoT) and Proof-of-History (PoH) validate blockchain transactions differently. PoT uses a ranking system to randomly select validators to verify transactions.
PoH uses a Verifiable Delay Function to validate transactions, verify how much time has passed between two events, and allow validators to quickly verify a transaction without malicious actors knowing the input.
You might also like

Tim Denning
3 years ago
I Posted Six Times a Day for 210 Days on Twitter. Here's What Happened.
I'd spend hours composing articles only to find out they were useless. Twitter solved the problem.
Twitter is wrinkled, say critics.
Nope. Writing is different. It won't make sense until you write there.
Twitter is resurgent. People are reading again. 15-second TikToks overloaded our senses.
After nuking my 20,000-follower Twitter account and starting again, I wrote every day for 210 days.
I'll explain.
I came across the strange world of microblogging.
Traditional web writing is filler-heavy.
On Twitter, you must be brief. I played Wordle.
Twitter Threads are the most popular writing format. Like a blog post. It reminds me of the famous broetry posts on LinkedIn a few years ago.
Threads combine tweets into an article.
Sharp, concise sentences
No regard for grammar
As important as the information is how the text looks.
Twitter Threads are like Michael Angelo's David monument. He chipped away at an enormous piece of marble until a man with a big willy appeared.
That's Twitter Threads.
I tried to remove unnecessary layers from several of my Wordpress blog posts. Then I realized something.
Tweeting from scratch is easier and more entertaining. It's quicker and makes you think more concisely.
Superpower: saying much with little words. My long-form writing has improved. My article sentences resemble tweets.
You never know what will happen.
Twitter's subcultures are odd. Best-performing tweets are strange.
Unusual trend: working alone and without telling anyone. It's a rebellion against Instagram influencers who share their every moment.
Early on, random thoughts worked:
My friend’s wife is Ukrainian. Her family are trapped in the warzone. He is devastated. And here I was complaining about my broken garage door. War puts everything in perspective. Today is a day to be grateful for peace.
Documenting what's happening triggers writing. It's not about viral tweets. Helping others matters.
There are numerous anonymous users.
Twitter uses pseudonyms.
You don't matter. On sites like LinkedIn, you must use your real name. Welcome to the Cyberpunk metaverse of Twitter :)
One daily piece of writing is a powerful habit.
Habits build creator careers. Read that again.
Twitter is an easy habit to pick up. If you can't tweet in one sentence, something's wrong. Easy-peasy-japanese.
Not what I tweeted, but my constancy, made the difference.
Daily writing is challenging, especially if your supervisor is on your back. Twitter encourages writing.
Tweets evolved as the foundation of all other material.
During my experiment, I enjoyed Twitter's speed.
Tweets get immediate responses, comments, and feedback. My popular tweets become newspaper headlines. I've also written essays from tweet discussions.
Sometimes the tweet and article were clear. Twitter sometimes helped me overcome writer's block.
I used to spend hours composing big things that had little real-world use.
Twitter helped me. No guessing. Data guides my coverage and validates concepts.
Test ideas on Twitter.
It took some time for my email list to grow.
Subscribers are a writer's lifeblood.
Without them, you're broke and homeless when Mark Zuckerberg tweaks the algorithms for ad dollars. Twitter has three ways to obtain email subscribers:
1. Add a link to your bio.
Twitter allows bio links (LinkedIn now does too). My eBook's landing page is linked. I collect emails there.
2. Start an online newsletter.
Twitter bought newsletter app Revue. They promote what they own.
I just established up a Revue email newsletter. I imported them weekly into my ConvertKit email list.
3. Create Twitter threads and include a link to your email list in the final tweet.
Write Twitter Threads and link the last tweet to your email list (example below).
Initial email subscribers were modest.
Numbers are growing. Twitter provides 25% of my new email subscribers. Some days, 50 people join.
Without them, my writing career is over. I'd be back at a 9-5 job begging for time off to spend with my newborn daughter. Nope.
Collect email addresses or die trying.
As insurance against unsubscribes and Zucks, use a second email list or Discord community.
What I still need to do
Twitter's fun. I'm wiser. I need to enable auto-replies and auto-DMs (direct messages).
This adds another way to attract subscribers. I schedule tweets with Tweet Hunter.
It’s best to go slow. People assume you're an internet marketer if you spam them with click requests.
A human internet marketer is preferable to a robot. My opinion.
210 days on Twitter taught me that. I plan to use the platform until I'm a grandfather unless Elon ruins it.

Leonardo Castorina
3 years ago
How to Use Obsidian to Boost Research Productivity
Tools for managing your PhD projects, reading lists, notes, and inspiration.
As a researcher, you have to know everything. But knowledge is useless if it cannot be accessed quickly. An easy-to-use method of archiving information makes taking notes effortless and enjoyable.
As a PhD student in Artificial Intelligence, I use Obsidian (https://obsidian.md) to manage my knowledge.
The article has three parts:
- What is a note, how to organize notes, tags, folders, and links? This section is tool-agnostic, so you can use most of these ideas with any note-taking app.
- Instructions for using Obsidian, managing notes, reading lists, and useful plugins. This section demonstrates how I use Obsidian, my preferred knowledge management tool.
- Workflows: How to use Zotero to take notes from papers, manage multiple projects' notes, create MOCs with Dataview, and more. This section explains how to use Obsidian to solve common scientific problems and manage/maintain your knowledge effectively.
This list is not perfect or complete, but it is my current solution to problems I've encountered during my PhD. Please leave additional comments or contact me if you have any feedback. I'll try to update this article.
Throughout the article, I'll refer to your digital library as your "Obsidian Vault" or "Zettelkasten".
Other useful resources are listed at the end of the article.
1. Philosophy: Taking and organizing notes
Carl Sagan: “To make an apple pie from scratch, you must first create the universe.”
Before diving into Obsidian, let's establish a Personal Knowledge Management System and a Zettelkasten. You can skip to Section 2 if you already know these terms.
Niklas Luhmann, a prolific sociologist who wrote 400 papers and 70 books, inspired this section and much of Zettelkasten. Zettelkasten means “slip box” (or library in this article). His Zettlekasten had around 90000 physical notes, which can be found here.
There are now many tools available to help with this process. Obsidian's website has a good introduction section: https://publish.obsidian.md/hub/
Notes
We'll start with "What is a note?" Although it may seem trivial, the answer depends on the topic or your note-taking style. The idea is that a note is as “atomic” (i.e. You should read the note and get the idea right away.
The resolution of your notes depends on their detail. Deep Learning, for example, could be a general description of Neural Networks, with a few notes on the various architectures (eg. Recurrent Neural Networks, Convolutional Neural Networks etc..).
Limiting length and detail is a good rule of thumb. If you need more detail in a specific section of this note, break it up into smaller notes. Deep Learning now has three notes:
- Deep Learning
- Recurrent Neural Networks
- Convolutional Neural Networks
Repeat this step as needed until you achieve the desired granularity. You might want to put these notes in a “Neural Networks” folder because they are all about the same thing. But there's a better way:
#Tags and [[Links]] over /Folders/
The main issue with folders is that they are not flexible and assume that all notes in the folder belong to a single category. This makes it difficult to make connections between topics.
Deep Learning has been used to predict protein structure (AlphaFold) and classify images (ImageNet). Imagine a folder structure like this:
- /Proteins/
- Protein Folding
- /Deep Learning/
- /Proteins/
Your notes about Protein Folding and Convolutional Neural Networks will be separate, and you won't be able to find them in the same folder.
This can be solved in several ways. The most common one is to use tags rather than folders. A note can be grouped with multiple topics this way. Obsidian tags can also be nested (have subtags).
You can also link two notes together. You can build your “Knowledge Graph” in Obsidian and other note-taking apps like Obsidian.
My Knowledge Graph. Green: Biology, Red: Machine Learning, Yellow: Autoencoders, Blue: Graphs, Brown: Tags.
My Knowledge Graph and the note “Backrpropagation” and its links.
Backpropagation note and all its links
Why use Folders?
Folders help organize your vault as it grows. The main suggestion is to have few folders that "weakly" collect groups of notes or better yet, notes from different sources.
Among my Zettelkasten folders are:
My Zettelkasten's 5 folders
They usually gather data from various sources:
MOC: Map of Contents for the Zettelkasten.
Projects: Contains one note for each side-project of my PhD where I log my progress and ideas. Notes are linked to these.
Bio and ML: These two are the main content of my Zettelkasten and could theoretically be combined.
Papers: All my scientific paper notes go here. A bibliography links the notes. Zotero .bib file
Books: I make a note for each book I read, which I then split into multiple notes.
Keeping images separate from other files can help keep your main folders clean.
I will elaborate on these in the Workflow Section.
My general recommendation is to use tags and links instead of folders.
Maps of Content (MOC)
Making Tables of Contents is a good solution (MOCs).
These are notes that "signposts" your Zettelkasten library, directing you to the right type of notes. It can link to other notes based on common tags. This is usually done with a title, then your notes related to that title. As an example:
An example of a Machine Learning MOC generated with Dataview.
As shown above, my Machine Learning MOC begins with the basics. Then it's on to Variational Auto-Encoders. Not only does this save time, but it also saves scrolling through the tag search section.
So I keep MOCs at the top of my library so I can quickly find information and see my library. These MOCs are generated automatically using an Obsidian Plugin called Dataview (https://github.com/blacksmithgu/obsidian-dataview).
Ideally, MOCs could be expanded to include more information about the notes, their status, and what's left to do. In the absence of this, Dataview does a fantastic job at creating a good structure for your notes.
In the absence of this, Dataview does a fantastic job at creating a good structure for your notes.
2. Tools: Knowing Obsidian
Obsidian is my preferred tool because it is free, all notes are stored in Markdown format, and each panel can be dragged and dropped. You can get it here: https://obsidian.md/
Obsidian interface.
Obsidian is highly customizable, so here is my preferred interface:
The theme is customized from https://github.com/colineckert/obsidian-things
Alternatively, each panel can be collapsed, moved, or removed as desired. To open a panel later, click on the vertical "..." (bottom left of the note panel).
My interface is organized as follows:
How my Obsidian Interface is organized.
Folders/Search:
This is where I keep all relevant folders. I usually use the MOC note to navigate, but sometimes I use the search button to find a note.
Tags:
I use nested tags and look into each one to find specific notes to link.
cMenu:
Easy-to-use menu plugin cMenu (https://github.com/chetachiezikeuzor/cMenu-Plugin)
Global Graph:
The global graph shows all your notes (linked and unlinked). Linked notes will appear closer together. Zoom in to read each note's title. It's a bit overwhelming at first, but as your library grows, you get used to the positions and start thinking of new connections between notes.
Local Graph:
Your current note will be shown in relation to other linked notes in your library. When needed, you can quickly jump to another link and back to the current note.
Links:
Finally, an outline panel and the plugin Obsidian Power Search (https://github.com/aviral-batra/obsidian-power-search) allow me to search my vault by highlighting text.
Start using the tool and worry about panel positioning later. I encourage you to find the best use-case for your library.
Plugins
An additional benefit of using Obsidian is the large plugin library. I use several (Calendar, Citations, Dataview, Templater, Admonition):
Obsidian Calendar Plugin: https://github.com/liamcain
It organizes your notes on a calendar. This is ideal for meeting notes or keeping a journal.
Calendar addon from hans/obsidian-citation-plugin
Obsidian Citation Plugin: https://github.com/hans/
Allows you to cite papers from a.bib file. You can also customize your notes (eg. Title, Authors, Abstract etc..)
Plugin citation from hans/obsidian-citation-plugin
Obsidian Dataview: https://github.com/blacksmithgu/
A powerful plugin that allows you to query your library as a database and generate content automatically. See the MOC section for an example.
Allows you to create notes with specific templates like dates, tags, and headings.
Templater. Obsidian Admonition: https://github.com/valentine195/obsidian-admonition
Blocks allow you to organize your notes.
Plugin warning. Obsidian Admonition (valentine195)
There are many more, but this list should get you started.
3. Workflows: Cool stuff
Here are a few of my workflows for using obsidian for scientific research. This is a list of resources I've found useful for my use-cases. I'll outline and describe them briefly so you can skim them quickly.
3.1 Using Templates to Structure Notes
3.2 Free Note Syncing (Laptop, Phone, Tablet)
3.3 Zotero/Mendeley/JabRef -> Obsidian — Managing Reading Lists
3.4 Projects and Lab Books
3.5 Private Encrypted Diary
3.1 Using Templates to Structure Notes
Plugins: Templater and Dataview (optional).
To take effective notes, you must first make adding new notes as easy as possible. Templates can save you time and give your notes a consistent structure. As an example:
An example of a note using a template.
### [[YOUR MOC]]
# Note Title of your note
**Tags**::
**Links**::
The top line links to your knowledge base's Map of Content (MOC) (see previous sections). After the title, I add tags (and a link between the note and the tag) and links to related notes.
To quickly identify all notes that need to be expanded, I add the tag “#todo”. In the “TODO:” section, I list the tasks within the note.
The rest are notes on the topic.
Templater can help you create these templates. For new books, I use the following template:
### [[Books MOC]]
# Title
**Author**::
**Date::
**Tags::
**Links::
A book template example.
Using a simple query, I can hook Dataview to it.
dataview
table author as Author, date as “Date Finished”, tags as “Tags”, grade as “Grade”
from “4. Books”
SORT grade DESCENDING
using Dataview to query templates.
3.2 Free Note Syncing (Laptop, Phone, Tablet)
No plugins used.
One of my favorite features of Obsidian is the library's self-contained and portable format. Your folder contains everything (plugins included).
Ordinary folders and documents are available as well. There is also a “.obsidian” folder. This contains all your plugins and settings, so you can use it on other devices.
So you can use Google Drive, iCloud, or Dropbox for free as long as you sync your folder (note: your folder should be in your Cloud Folder).
For my iOS and macOS work, I prefer iCloud. You can also use the paid service Obsidian Sync.
3.3 Obsidian — Managing Reading Lists and Notes in Zotero/Mendeley/JabRef
Plugins: Quotes (required).
3.3 Zotero/Mendeley/JabRef -> Obsidian — Taking Notes and Managing Reading Lists of Scientific Papers
My preferred reference manager is Zotero, but this workflow should work with any reference manager that produces a .bib file. This file is exported to my cloud folder so I can access it from any platform.
My Zotero library is tagged as follows:
My reference manager's tags
For readings, I usually search for the tags “!!!” and “To-Read” and select a paper. Annotate the paper next (either on PDF using GoodNotes or on physical paper).
Then I make a paper page using a template in the Citations plugin settings:
An example of my citations template.
Create a new note, open the command list with CMD/CTRL + P, and find the Citations “Insert literature note content in the current pane” to see this lovely view.
Citation generated by the article https://doi.org/10.1101/2022.01.24.22269144
You can then convert your notes to digital. I found that transcribing helped me retain information better.
3.4 Projects and Lab Books
Plugins: Tweaker (required).
PhD students offering advice on thesis writing are common (read as regret). I started asking them what they would have done differently or earlier.
“Deep stuff Leo,” one person said. So my main issue is basic organization, losing track of my tasks and the reasons for them.
As a result, I'd go on other experiments that didn't make sense, and have to reverse engineer my logic for thesis writing. - PhD student now wise Postdoc
Time management requires planning. Keeping track of multiple projects and lab books is difficult during a PhD. How I deal with it:
- One folder for all my projects
- One file for each project
I use a template to create each project
### [[Projects MOC]]
# <% tp.file.title %>
**Tags**::
**Links**::
**URL**::
**Project Description**::## Notes:
### <% tp.file.last_modified_date(“dddd Do MMMM YYYY”) %>
#### Done:
#### TODO:
#### Notes
You can insert a template into a new note with CMD + P and looking for the Templater option.
I then keep adding new days with another template:
### <% tp.file.last_modified_date("dddd Do MMMM YYYY") %>
#### Done:
#### TODO:
#### Notes:
This way you can keep adding days to your project and update with reasonings and things you still have to do and have done. An example below:
Example of project note with timestamped notes.
3.5 Private Encrypted Diary
This is one of my favorite Obsidian uses.
Mini Diary's interface has long frustrated me. After the author archived the project, I looked for a replacement. I had two demands:
- It had to be private, and nobody had to be able to read the entries.
- Cloud syncing was required for editing on multiple devices.
Then I learned about encrypting the Obsidian folder. Then decrypt and open the folder with Obsidian. Sync the folder as usual.
Use CryptoMator (https://cryptomator.org/). Create an encrypted folder in Cryptomator for your Obsidian vault, set a password, and let it do the rest.
If you need a step-by-step video guide, here it is:
Conclusion
So, I hope this was helpful!
In the first section of the article, we discussed notes and note-taking techniques. We discussed when to use tags and links over folders and when to break up larger notes.
Then we learned about Obsidian, its interface, and some useful plugins like Citations for citing papers and Templater for creating note templates.
Finally, we discussed workflows and how to use Zotero to take notes from scientific papers, as well as managing Lab Books and Private Encrypted Diaries.
Thanks for reading and commenting :)
Read original post here

Cody Collins
2 years ago
The direction of the economy is as follows.
What quarterly bank earnings reveal
Big banks know the economy best. Unless we’re talking about a housing crisis in 2007…
Banks are crucial to the U.S. economy. The Fed, communities, and investments exchange money.
An economy depends on money flow. Banks' views on the economy can affect their decision-making.
Most large banks released quarterly earnings and forward guidance last week. Others were pessimistic about the future.
What Makes Banks Confident
Bank of America's profit decreased 30% year-over-year, but they're optimistic about the economy. Comparatively, they're bullish.
Who banks serve affects what they see. Bank of America supports customers.
They think consumers' future is bright. They believe this for many reasons.
The average customer has decent credit, unless the system is flawed. Bank of America's new credit card and mortgage borrowers averaged 771. New-car loan and home equity borrower averages were 791 and 797.
2008's housing crisis affected people with scores below 620.
Bank of America and the economy benefit from a robust consumer. Major problems can be avoided if individuals maintain spending.
Reasons Other Banks Are Less Confident
Spending requires income. Many companies, mostly in the computer industry, have announced they will slow or freeze hiring. Layoffs are frequently an indication of poor times ahead.
BOA is positive, but investment banks are bearish.
Jamie Dimon, CEO of JPMorgan, outlined various difficulties our economy could confront.
But geopolitical tension, high inflation, waning consumer confidence, the uncertainty about how high rates have to go and the never-before-seen quantitative tightening and their effects on global liquidity, combined with the war in Ukraine and its harmful effect on global energy and food prices are very likely to have negative consequences on the global economy sometime down the road.
That's more headwinds than tailwinds.
JPMorgan, which helps with mergers and IPOs, is less enthusiastic due to these concerns. Incoming headwinds signal drying liquidity, they say. Less business will be done.
Final Reflections
I don't think we're done. Yes, stocks are up 10% from a month ago. It's a long way from old highs.
I don't think the stock market is a strong economic indicator.
Many executives foresee a 2023 recession. According to the traditional definition, we may be in a recession when Q2 GDP statistics are released next week.
Regardless of criteria, I predict the economy will have a terrible year.
Weekly layoffs are announced. Inflation persists. Will prices return to 2020 levels if inflation cools? Perhaps. Still expensive energy. Ukraine's war has global repercussions.
I predict BOA's next quarter earnings won't be as bullish about the consumer's strength.
