💲 Ethereum, The Amazon of Crypto

Happy Monday dear subscribers! In today’s Newsletter, Ethereum growth is not over!!

In today’s bulletin, we are covering:

• Surfing the Market, with analysis about Mid Caps and AI Index
• Don’t miss the News about Ethereuim’s potential and Crypto in politics
• Predicate is under the spotlight.
• A short article about Long-Term Management Capital Collapse

Morning ladies and gentlemen! Really ugly weekend for the Crypto market. Taking a look into the Mid Caps Index we can see a breakdown on the key support to levels not seen since 2 months. Let’s see the response over the main range at $3, which will be critical:

The AI Index is back to the main horizontal support breaching below the $5 range. Also at a very critical stage, needs a strong bounce to jump back the momentum:

Ethereum’s Untapped Potential: The Amazon of the Crypto World?

According to 21Shares analyst Leena ElDeeb, Wall Street investors remain cautious about Ethereum’s potential, drawing a parallel to Amazon’s early days when its long-term potential was still uncertain. Ethereum has evolved significantly, now powering over $140 billion in decentralized finance.

• Comparison with Amazon: Ethereum’s complex use cases resemble Amazon’s early potential, suggesting long-term growth.
• Low ETF Inflows: Spot Ether ETFs have seen 9% of Bitcoin ETF inflows, as investors remain cautious.
• Institutional Hesitation: Short-term investors await clarity on Ethereum’s potential and staking approvals from U.S. regulators.
• Growing Ecosystem: Ethereum boasts 200,000+ developers and support from firms like BlackRock, PayPal, and Visa.
• Layer-2 Revenue Impact: Layer-2 adoption reduces Ethereum mainnet fees short-term but could contribute to growth long-term.

As spot Ether ETFs have seen modest inflows compared to Bitcoin ETFs, experts believe greater understanding and market maturity are necessary for more institutional interest.

Crypto in Politics: Key Legislation Shaping the Future of Digital Assets in the 2024 U.S. Election

As the 2024 U.S. elections approach, digital assets have emerged as a significant political issue, with industry advocates pushing for pro-crypto policies.

Despite this, the U.S. still lacks a comprehensive regulatory framework, leaving legislation fragmented.

• Growing Political Focus: Digital assets have become a central topic in the 2024 U.S. election, spotlighting regulatory uncertainty.
• FIT21 Act: Proposes regulatory clarity, with assets regulated by the CFTC if sufficiently decentralized.
• CBDC Anti-Surveillance State Act: Opposes a consumer-facing CBDC, favoring privacy.
• Clarity for Payment Stablecoins Act: Proposes state-level regulation for smaller stablecoin issuers.
• Digital Asset Anti-Money Laundering Act: Requires crypto providers to follow traditional financial reporting standards.
• Keep Your Coins Act: Protects consumers’ rights to use self-custodial wallets.
• Other Important Bills: Include acts on investor accessibility, anti-illicit finance, and blockchain regulatory clarity.

Key bills include acts addressing decentralization, stablecoins, CBDCs, and anti-money laundering. Understanding these bills is critical for crypto-focused voters as they evaluate candidates’ positions.

Predicate

The Origins:

Predicate is a network for simplifying transaction prerequisites that uses a generalizable policy engine built for smart contracts.

Users of Predicate define rules for on-chain interactions that end up building a pre-transaction logic into decentralized applications. The combination of those rules are used to make policies, which are stored on Ethereum and can be updated at any time by the policy owner.

The Operative:

Once Predicate has been integrated into an application the order flow would look like this:

1. Client sends a request to validate a transaction that’s sent to the Operators.
2. Operators verify if the transaction can be approved or denied according to the rules of the corresponding policy.
3. Middleware sends the response (approved/denied) to the client’s interface.
4. If favorable, the Client can now sign and submit the transaction on-chain, including Predicate Signatures in the data field.
5. Before on-chain execution the Client contract verifies signature validity.

Summary:

The project managed to raise $7 Million in funding recently with backers like 1k(x), Tribe Capital or Frigment Capital among multiple others. The launching date is still to be announced.

In blockchain technology, a comprehensive framework to implement rules and policies at the smart contract level is something that will be more necessary as network activity and applications become more complex.

Long-Term Management Capital Collapse

If I told you to invest your money in a fund managed by Nobel laureates in economics, you’d probably think it’s a safe bet and nothing could go wrong, right? Well, you might think differently after reading this story.

What was LTMC?

Long-Term Capital Management (LTCM) was founded in 1994 by John Meriwether (former head of bond trading at Salomon Brothers) as a hedge fund that used mathematical models for arbitrage in the markets. The team included academics Myron Scholes and Robert C. Merton, who would go on to win the Nobel Prize in Economics in 1997 for developing the Black & Scholes option pricing model 🏅

The capital for the hedge fund came from companies and individuals with strong connections in the financial system, but millionaires and celebrities also jumped on board. By its first day of operations in 1994, LTCM had $1.01 billion in capital 💰

The fund was a success in its early years, generating 40% annual returns. Everything was going well until 1998, when they lost $4.6 billion in less than four months. The fund had to be bailed out by a group of 14 banks under the supervision of the FED to prevent a larger market collapse 🚨

What Happened?

The main strategy was bond arbitrage (analyzing pairs of bonds with a certain spread, and when that spread widened, shorting one bond and buying the other, expecting the spread to return to normal). This is also known as convergence trading.

At that time, LTCM was the brightest star on Wall Street 🌟

Since the margins in this type of operation are usually low, to achieve significant results, LTCM used highly leveraged positions, risking more than was prudent 💸

By 1998, the firm had equity of $4.7 billion and had borrowed over $124.5 billion, with assets of around $129 billion, resulting in a debt-to-equity ratio of over 25 to 1. It also held off-balance sheet derivative positions with a notional value of approximately $1.25 trillion, most of which were in interest rate derivatives like interest rate swaps. These swaps, originally intended to manage risk, ended up becoming a powerful tool for speculation.

The Downfall

In 1996, the fund posted a gain of 40%, but by 1997, it dropped to just 17%, which was in line with other hedge funds. This decrease occurred because other firms began copying LTCM’s strategies, leaving fewer arbitrage opportunities. In response, LTCM began investing in emerging market debt and foreign currencies 👀

> The 1997 Asian crisis and the 1998 Russian crisis severely impacted the firm. By 1998, a bailout was necessary to prevent LTCM’s collapse from dragging down the rest of the market. Too big to fail, right? 😒

They failed to raise more capital, and it became evident they were facing an unsolvable problem. Goldman Sachs and Warren Buffett offered $250 million, but this was significantly lower than its market value at the beginning of the year: $4.7 billion!

With no way out,** the Fed organized a $3.625 billion bailout from various financial institutions**. Something very similar happened during the 2008 subprime crisis following the fall of Lehman Brothers.

The Aftermath

After the rescue, LTCM continued operating and even made a 10% gain the following year, but by 2000, it was liquidated, and the banks that participated in the bailout were repaid 🤝

In 1999, Meriwether created another fund, which collapsed during the 2008 crisis, and then opened a third fund in 2010. The strategies he used were the same as those during LTCM’s time… 🤡

In its annual reports, Merrill Lynch noted that mathematical risk models “may provide a greater sense of security than warranted; therefore, reliance on these models should be limited.”

PD: A good reading about this story is the book: When genius failed 📚

⚠️ Are you looking for the Best Trading Courses?

• Professional lessons
• From Basic to Advanced
• Technical Analysis Guides

✅ Join here: https://tradingdoji.com/