finds – Earlybirds Invest https://earlybirdsinvest.com Latest Crypto News Sat, 06 Sep 2025 21:43:44 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.7 https://i0.wp.com/earlybirdsinvest.com/wp-content/uploads/2024/12/cropped-New-Project-2024-12-17T235703.455.png?fit=32%2C32&ssl=1 finds – Earlybirds Invest https://earlybirdsinvest.com 32 32 240146708 VirusTotal finds hidden malware phishing campaign in SVG files https://earlybirdsinvest.com/virustotal-finds-hidden-malware-phishing-campaign-in-svg-files/ https://earlybirdsinvest.com/virustotal-finds-hidden-malware-phishing-campaign-in-svg-files/#respond Sat, 06 Sep 2025 21:43:44 +0000 https://earlybirdsinvest.com/virustotal-finds-hidden-malware-phishing-campaign-in-svg-files/

Malware phishing

VirusTotal has discovered a phishing campaign hidden in SVG files that create convincing portals impersonating Colombia’s judicial system that deliver malware.

VirusTotal detected this campaign after it added support for SVGs to its AI Code Insight platform.

VirusTotal’s AI Code Insight feature analyzes uploaded file samples using machine learning to generate summaries of suspicious or malicious behavior found in the files.

After adding support for SVGs, VirusTotal found an SVG file that had zero detections by antivirus scans, but whose AI-powered Code Insight feature detected using JavaScript to display HTML, impersonating a portal for Colombia’s government judiciary system.

VirusTotal Code insights detecting a malicious SVG file
VirusTotal Code insights detecting a malicious SVG file
Source: VirusTotal

SVG, or Scalable Vector Graphics, is used to generate images of lines, shapes, and text through textual mathematical formulas in the file.

However, threat actors have begun increasingly using SVG files in attacks, as they can also be used to display HTML using the element and execute JavaScript when the graphic is loaded.

In the campaign discovered by Virustotal, SVG image files are used to render fake portals that display a phony download progress bar, ultimately prompting the user to download a password-protected zip archive [VirusTotal]. The password for this file is displayed in the fake portal page.

“As shown in the screenshots below, the fake portal is rendered exactly as described, simulating an official government document download process,” explains VirusTotal.

“The phishing site includes case numbers, security tokens, and visual cues to build trust, all of it crafted within an SVG file.”

Fake portal for Colombia’s judicial system​​​​​​​
Fake portal for Colombia’s judicial system
Source: VirusTotal

BleepingComputer found that the extracted file contains four files: a legitimate executable from the Comodo Dragon web browser, renamed to be an official judicial document, a malicious DLL [VirusTotal], and what appears to be two encrypted files.

Extracted password-protected archive
Extracted password-protected archive
Source: BleepingComputer

If the user opens the executable, the malicious DLL will be sideloaded to install further malware on the system.

After detecting this initial SVG, VirusTotal identified 523 previously uploaded SVG files that were part of the same campaign but had evaded detection by security software.

The addition of SVG support to AI Code Insights was crucial in exposing this particular campaign, as VirusTotal noted that the use of AI makes it easier to identify new malicious campaigns.

“This is where Code Insight helps most: giving context, saving time, and helping focus on what really matters. It’s not magic, and it won’t replace expert analysis, but it’s one more tool to cut through the noise and get to the point faster,” concludes VirusTotal.

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46% of environments had passwords cracked, nearly doubling from 25% last year.

Get the Picus Blue Report 2025 now for a comprehensive look at more findings on prevention, detection, and data exfiltration trends.

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Bitcoin finds support on a short-term holder cost basis, how long does it last? https://earlybirdsinvest.com/bitcoin-finds-support-on-a-short-term-holder-cost-basis-how-long-does-it-last/ https://earlybirdsinvest.com/bitcoin-finds-support-on-a-short-term-holder-cost-basis-how-long-does-it-last/#respond Tue, 02 Sep 2025 03:10:26 +0000 https://earlybirdsinvest.com/bitcoin-finds-support-on-a-short-term-holder-cost-basis-how-long-does-it-last/ Bitcoin has seen rebounds since retesting the realized prices of short-term holders.

Bitcoin short-term holders have made it possible for prices to act as support

As Cryptoquant author IT Tech explained in X Post, Bitcoin found support by achieving short-term holder prices during the latest DIP. The “realized price” here refers to an on-chain indicator that measures the cost base of the average investor on the BTC network.

If the cryptocurrency price exceeds this metric, it means that the entire holder is in a state of net unrealized profit. On the other hand, being under the indicator means that the entire market is red.

In the context of the current topic, realised prices for only certain segments of investors are interesting. Short term holder (STH). This cohort includes holders who have purchased coins within the last 155 days.

STHS supplements one of the two main sectors of the Bitcoin market, which was made based on holding time, with the other side known as the Long Term Holder (LTHS).

What makes these groups different is that investors in the former tend to be weaker hands who move in panic every time volatility appears in the sector, while members of the latter exhibit high conviction behavior.

For any investor, their cost base is at a critical level and STH is particularly whimsical, so when realised prices are retested, they usually have some kind of response. This has led to the price of assets that have observed various interactions with this metric in the past.

As the chart below shared by analysts suggests, one such interaction may have occurred in the past day.

Bitcoin Sth has made the price come true

As shown in the graph above, Bitcoin Sth now achieves around $107,500. In BTC’s latest DIP, its price went slightly under this mark, but it turns out to be a high rebound.

Generally, STH buys to adhere to their cost standards if the emotions between them are bullish. At such times, they believe that the price of their damaged mark will be an opportunity to “buy dip”

Given the fact that the assets could find support at the realised price of STH, it appears that STH still thinks the bullish regime is on. That said, Bitcoin has only seen a small rebound so far, so it remains to be seen whether its assets are above the level or if there will be another retest.

In a scenario where metric breakdowns occur, cryptocurrencies could face a shift towards a short-term bearish trend that took place in February this year.

BTC price

At the time of writing, Bitcoin has dropped by 2% to around $109,200 over the past seven days.

Bitcoin Price Chart

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AI Is Squeezing Out Entry-Level Jobs, New Stanford Study Finds https://earlybirdsinvest.com/ai-is-squeezing-out-entry-level-jobs-new-stanford-study-finds/ https://earlybirdsinvest.com/ai-is-squeezing-out-entry-level-jobs-new-stanford-study-finds/#respond Thu, 28 Aug 2025 20:42:27 +0000 https://earlybirdsinvest.com/ai-is-squeezing-out-entry-level-jobs-new-stanford-study-finds/

A recent study from Stanford University offers new insight into how artificial intelligence (AI) is affecting the job market.

The research, based on employment data from payroll company ADP, examined how jobs in fields more likely to be influenced by AI have changed.

The study found that people just starting their careers are being impacted the most. Since 2022, job opportunities for young workers in AI-sensitive roles have decreased by 13%. In comparison, older workers in the same fields have not seen the same kind of decline.

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For those just starting out in fields like customer support and software development, job numbers fell by about 20% between late 2022 and mid-2025. However, for more experienced workers doing similar jobs, employment actually increased.

Other areas affected similarly include accounting, administrative support, programming, and sales. Across these types of jobs, people aged 22 to 25 saw a 6% drop in employment. In contrast, older employees in the same industries experienced growth between 6% and 9%.

One reason for this trend may be that newer workers tend to rely more on the type of information that AI systems are also trained on.

On the other hand, more experienced employees often have practical knowledge gained over time. These skills, such as effective communication, decision-making, or work-specific insights, are more difficult for AI to copy.

On August 19, Microsoft’s head of artificial intelligence (AI), Mustafa Suleyman, raised concerns about the rapid progress of AI. What did he say? Read the full story.


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Study Finds Doctors Lose Skill After Relying on AI in Colonoscopies https://earlybirdsinvest.com/study-finds-doctors-lose-skill-after-relying-on-ai-in-colonoscopies/ https://earlybirdsinvest.com/study-finds-doctors-lose-skill-after-relying-on-ai-in-colonoscopies/#respond Wed, 20 Aug 2025 03:14:43 +0000 https://earlybirdsinvest.com/study-finds-doctors-lose-skill-after-relying-on-ai-in-colonoscopies/

A study in Poland has shown that gastroenterologists became less effective at spotting abnormalities after they grew used to working with artificial intelligence (AI) during colonoscopies.

According to an August 19 report by National Public Radio (NPR), the research was carried out at four clinics where doctors tested a system that reviewed live video and marked suspicious areas in real time.

When the software highlighted a region, doctors could check it immediately. The system was successful while in use, but the study also revealed an unintended effect.

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After relying on the tool, doctors’ ability to detect possible polyps fell from 28.4% before the trial to 22.4% once the AI was switched off. This means that detection rates dropped by about one-fifth when the automated help was removed.

The findings were published in The Lancet Gastroenterology and Hepatology.

Lead researcher Marcin Romańczyk, a gastroenterologist at H-T Medical Center in Tychy, said the results came as a surprise. He noted that many specialists were trained through textbooks and mentorship, but not in using advanced technology like AI, which is spreading through healthcare.

Romańczyk suggested that one possible reason for the drop is that clinicians may unconsciously wait for the system to mark a suspicious area, instead of carefully scanning the footage themselves.

Anthropic recently added a new option to certain Claude models that lets them close a chat in very limited cases. What does the feature include? Read the full story.


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MEXC finds that 67% of Gen Z crypto traders use AI tools, resulting in fewer panic sells https://earlybirdsinvest.com/mexc-finds-that-67-of-gen-z-crypto-traders-use-ai-tools-resulting-in-fewer-panic-sells/ https://earlybirdsinvest.com/mexc-finds-that-67-of-gen-z-crypto-traders-use-ai-tools-resulting-in-fewer-panic-sells/#respond Fri, 25 Jul 2025 07:39:25 +0000 https://earlybirdsinvest.com/mexc-finds-that-67-of-gen-z-crypto-traders-use-ai-tools-resulting-in-fewer-panic-sells/

A growing majority of Gen Z crypto traders are turning to artificial intelligence (AI) to guide their strategies and it’s making them less prone to panic selling.

According to a July 24 report from MEXC Research, which analyzed over 780,000 Gen Z trading accounts in the second quarter, found that 67% of users aged 18 to 27 had deployed at least one AI-powered bot or strategy in the past 90 days.

Traders using AI-driven tools recorded 47% fewer panic-sell incidents during periods of market stress compared to those trading manually.

A tactical ‘on–off’ relationship

Gen Z’s engagement with AI isn’t passive. The cohort averaged 11.4 days per month using AI tools, which is more than double users over 30. Furthermore, they accounted for 60% of all AI bot activations on the exchange. 

Yet, they don’t leave bots running indefinitely, as 73% switched them on during volatility or news spikes and turned them off during low-volume, sideways markets. Overall, 58% of Gen Z AI interactions occurred during periods of elevated readings on MEXC’s internal volatility index.

This behavior points to fluid control rather than full delegation. Gen Z configures conditions and lets automation execute when emotions are most likely to interfere. They also check AI-generated signals 2.4 times more often than traditional indicators, suggesting they view machine output as the primary decision feed in fast markets.=

Generational differences

MEXC’s data indicates that AI is serving as both a risk-management layer and a convenience feature. Gen Z traders using bots were 1.9x less likely to trade reactively in the first three minutes of major events, a window that MEXC flags as prone to costly errors.

They were also 2.4x more likely to employ structured stop-loss and take-profit rules, reinforcing that automation is being used to maintain absolute boundaries, not just identify entries.

Cross-generational comparisons reveal that millennials continue to lean toward thesis-driven, chart- and report-heavy workflows, treating AI as a supplement to pre-set strategies. 

Only 22% of millennials and 7% of Gen X reported turning to AI during high-volatility windows, versus Gen Z’s 73%.

Psychologically, millennials seek a sense of persistent manual control. Gen Z toggles autonomy based on stress, noise, and attention bandwidth, a pattern mirroring those seen in gaming and social platforms.

MEXC projects that by 2028, more than 80% of Gen Z traders will rely on AI for full-cycle portfolio management, from dynamic rebalancing to tax automation. 

That demand aligns with broader forecasts, putting the AI trading platform market at nearly $70 billion by 2034, growing over 20% CAGR from 2025 to 2034.

Mentioned in this article
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Survey finds gaps in mainstream Bitcoin coverage, leaving institutional investors exposed https://earlybirdsinvest.com/survey-finds-gaps-in-mainstream-bitcoin-coverage-leaving-institutional-investors-exposed/ https://earlybirdsinvest.com/survey-finds-gaps-in-mainstream-bitcoin-coverage-leaving-institutional-investors-exposed/#respond Tue, 08 Jul 2025 23:31:51 +0000 https://earlybirdsinvest.com/survey-finds-gaps-in-mainstream-bitcoin-coverage-leaving-institutional-investors-exposed/

A second-quarter survey of 18 mainstream news outlets logged 1,116 Bitcoin (BTC) stories and measured sentiment at 31% positive, 41% neutral, and 28% negative, according to Bitcoin analysis firm Perception.

The data reveal a significant gap between finance-focused media that cover the market extensively and legacy publications that rarely address it.

Sparse coverage

Perception counted two Bitcoin articles in The Wall Street Journal, 11 in the Financial Times, and 11 in The New York Times. These totals trailed every finance-oriented title in the sample and even lagged mid-tier general outlets. 

Audiences that rely on these newspapers for market intelligence received almost no information on an asset that outperformed broad indexes again in the quarter. The report referred to this mismatch as an “editorial blind-spot risk” because institutional investors may base their portfolio decisions on incomplete information.

High-volume business channels drove the most constructive coverage. Forbes produced 194 Bitcoin stories with a positive-to-negative ratio of roughly 1.8:1. At the same time, CNBC published 141 items at 2.5:1; and Fortune filed 117 pieces that leaned modestly positive.

These outlets focused on adoption metrics, exchange-traded funds (ETFs), treasury allocations, and mining economics, presenting Bitcoin as a viable macro asset rather than a novelty.

Negative framing clustered elsewhere. The Independent ran 45 stories with a 2.3:1 negative tilt, while Fox News and Barron’s delivered smaller volumes but similar skepticism, focusing on crime, cybersecurity breaches, and price volatility. 

Perception grouped coverage into three narrative blocs: enthusiastic adoption (Forbes, CNBC), willful minimalism (WSJ, FT, NYT), and persistent skepticism led by traditional general interest outlets.

Information asymmetry

According to the report, the divergence matters because large-cap digital assets now trade with liquidity comparable to some G-10 currencies, and exchange-listed spot ETFs cleared record volumes during the quarter. 

Asset managers that monitor only the low-volume publications may miss regulatory developments, fund flow data, and corporate treasury moves that the high-volume cohort documents in near real-time.

The report concluded that the coverage split creates both risk and opportunity: risk for institutions that depend on undersupplied channels and opportunity for readers who follow the outlets that closely track market mechanics. 

With sentiment and story counts quantifiable every quarter, portfolio teams can benchmark media exposure against price action and adjust their information sources accordingly.

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Cardano's ADA Finds 'Strong Support' After Dramatic Price Swings Amid Heightened Volatility https://earlybirdsinvest.com/cardanos-ada-finds-strong-support-after-dramatic-price-swings-amid-heightened-volatility/ https://earlybirdsinvest.com/cardanos-ada-finds-strong-support-after-dramatic-price-swings-amid-heightened-volatility/#respond Fri, 06 Jun 2025 14:56:46 +0000 https://earlybirdsinvest.com/cardanos-ada-finds-strong-support-after-dramatic-price-swings-amid-heightened-volatility/

The cryptocurrency market is experiencing heightened volatility amid an escalating feud between President Donald Trump and his former head of the Department of Government Efficiency, Elon Musk, over the state of the U.S. economy.

Cardano’s ADA

has also seen extreme price swings amid market uncertainties.

After dropping from $0.688 to $0.621, ADA found strong support and rebounded, forming an ascending channel with resistance at $0.644, according to CoinDesk Research’s technical analysis model. The technical indicators suggest a potential renewed bullish momentum as the cryptocurrency reclaims the $0.640 level with decreasing volatility.

At press time, ADA is trading at $0.66, down about 1.8% over the past 24 hours, while the broader market gauge CoinDesk 20 Index fell 1%.

Some recent news within the ADA ecosystem has provided the market with potential catalysts for the token.

Institutional interest in the Cardano blockchain continues to grow, with Franklin Templeton, a $1.6 trillion asset manager, now running Cardano nodes. Additionally, Norway’s NBX has recently partnered with Cardano to build Bitcoin-based DeFi, highlighting the blockchain’s secure design for institutional adoption.

The successful execution of the first Bitcoin-to-Cardano transaction involving Ordinals marks a significant milestone that could potentially unlock $1.5 trillion in cross-chain trading opportunities.

Technical Analysis Highlights

  • Sharp decline from $0.688 to $0.621 (10.29% drop) occurred on exceptionally high volume.
  • Strong support zone established at $0.620-$0.623 where buyers aggressively stepped in.
  • Recovery formed an ascending channel with resistance at $0.644.
  • Overall range of $0.070 (10.29%) highlights the extreme market conditions.
  • Potential renewed bullish momentum as ADA reclaimed the $0.640 level with decreasing volatility.
  • Hourly price action showed a possible recovery pattern from $0.641 to $0.643.
  • Short-term resistance level established at $0.643-$0.644.

Disclaimer: Parts of this article were generated with the assistance from AI tools and reviewed by our editorial team to ensure accuracy and adherence to our standards. For more information, see CoinDesk’s full AI Policy.

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Ethereum Price Finds Its Footing: Bulls Prepare for Another Push https://earlybirdsinvest.com/ethereum-price-finds-its-footing-bulls-prepare-for-another-push/ https://earlybirdsinvest.com/ethereum-price-finds-its-footing-bulls-prepare-for-another-push/#respond Mon, 26 May 2025 04:04:01 +0000 https://earlybirdsinvest.com/ethereum-price-finds-its-footing-bulls-prepare-for-another-push/

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Ethereum price found support at $2,460 and started a fresh increase. ETH is now rising and might aim for a move above the $2,600 resistance zone.

  • Ethereum started a decent increase above the $2,500 and $2,520 levels.
  • The price is trading above $2,520 and the 100-hourly Simple Moving Average.
  • There was a break above a connecting bearish trend line with resistance at $2,540 on the hourly chart of ETH/USD (data feed via Kraken).
  • The pair could gain strength if it clears the $2,600 resistance in the near term.

Ethereum Price Finds Support

Ethereum price started a decent increase after Bitcoin traded to a new all-time high. ETH tested the $2,720 zone before there was a downside correction. The price dipped below $2,500 and tested $2,450.

A low was formed at $2,463 and the price is again rising. There was a move above the $2,500 resistance. The price surpassed the 23.6% Fib retracement level of the downward move from the $2,729 swing high to the $2,463 low. There was also a break above a connecting bearish trend line with resistance at $2,540 on the hourly chart of ETH/USD.

Ethereum price is now trading above $2,520 and the 100-hourly Simple Moving Average. On the upside, the price could face resistance near the $2,600 level. It is near the 50% Fib retracement level of the downward move from the $2,729 swing high to the $2,463 low.

The next key resistance is near the $2,630 level. The first major resistance is near the $2,650 level. A clear move above the $2,650 resistance might send the price toward the $2,720 resistance.

Ethereum Price
Source: ETHUSD on TradingView.com

An upside break above the $2,720 resistance might call for more gains in the coming sessions. In the stated case, Ether could rise toward the $2,800 resistance zone or even $2,850 in the near term.

Are Dips Supported In ETH?

If Ethereum fails to clear the $2,600 resistance, it could start a fresh decline. Initial support on the downside is near the $2,520 level. The first major support sits near the $2,500 zone.

A clear move below the $2,500 support might push the price toward the $2,460 support. Any more losses might send the price toward the $2,420 support level in the near term. The next key support sits at $2,350.

Technical Indicators

Hourly MACDThe MACD for ETH/USD is gaining momentum in the bullish zone.

Hourly RSIThe RSI for ETH/USD is now above the 50 zone.

Major Support Level – $2,500

Major Resistance Level – $2,600

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New study finds self-driving cars safer than human drivers https://earlybirdsinvest.com/new-study-finds-self-driving-cars-safer-than-human-drivers/ https://earlybirdsinvest.com/new-study-finds-self-driving-cars-safer-than-human-drivers/#respond Sun, 04 May 2025 23:58:23 +0000 https://earlybirdsinvest.com/new-study-finds-self-driving-cars-safer-than-human-drivers/

I have some bad news: You are almost certainly a worse driver than you think you are.

Humans drive distracted. They drive drowsy. They drive angry. And, worst of all, they drive impaired far more often than they should. Even when we’re firing on all cylinders, our Stone Age-adapted brains are often no match for the speed and complexity of high-speed driving. There’s as much as a 2.5-second lag between what we perceive and how fast we can react in a vehicle traveling 60 mph, which means a car will travel the equivalent of two basketball court lengths before its driver can even hit the brake.

The result of this very human fallibility is blood on the streets. Nearly 1.2 million people die in road crashes globally each year, enough to fill nine jumbo jets each day. Here in the US, the government estimates there were 39,345 traffic fatalities in 2024, which adds up to a bus’s worth of people perishing every 12 hours.

The good news is there are much, much better drivers coming online, and they have everything human drivers don’t: They don’t need sleep. They don’t get angry. They don’t get drunk. And their brains can handle high-speed decision-making with ease.

The average American adult will spend around three years of their life driving. If robots could take the wheel instead, well, think of all the Netflix shows we could stream instead.

But the true benefit of a self-driving revolution will be in lives saved. And new data from the autonomous vehicle company Waymo suggests that those savings could be very great indeed.

In a peer-reviewed study that is set to be published in the journal Traffic Injury Prevention, Waymo analyzed the safety performance of its autonomous vehicles over the course of 56.7 million miles driven in Austin, Los Angeles, Phoenix, and San Francisco — all without a human safety driver present to take the wheel in an emergency. They then compared that data to human driving safety over the same number of miles driven on the same kind of roads.

The results of the study, almost certainly the biggest and most comprehensive research on self-driving car safety yet released, are striking.

A master class in driving safety

Compared to human drivers, the Waymo self-driving cars had:

  • 81 percent fewer airbag-deploying crashes
  • 85 percent fewer crashes with suspected serious or worse injuries
  • 96 percent fewer injury crashes at intersections (primarily because Waymo detects red lights faster than humans)
  • 92 percent fewer crashes that involve injuries to pedestrians.

Had the typical human-driven fleet of cars covered those same 56.7 million miles, the Waymo researchers project it would have resulted in an estimated 181 additional injury crashes, 78 additional air-bag crashes, and 11 extra serious-injury crashes.

But the numbers really get eye-popping when you extend this data across all 3.3 trillion vehicle miles driven by humans in the US in a typical year. Back-of-the-envelope calculations suggest that if the same 85 percent reduction seen in serious crashes held true for fatal ones — a big if, to be clear, since the study had too few fatal events to measure — we’d save approximately 34,000 lives a year. That’s five times the number of Americans who died in the Iraq and Afghanistan wars combined.

Don’t get in the way of progress

Of course, there are plenty of caveats to the Waymo study and even more obstacles before we could ever achieve anything like what’s outlined above.

In part because serious injury crashes are (thankfully) very rare, even 56.7 million miles isn’t long enough for researchers to be really sure that such crashes would occur significantly less often with robot drivers, so more data will be needed there. Waymo’s cars were also being driven largely in warm, sunny locations, operating in geofenced areas that had been heavily mapped by the company. It’s far less certain how they might do in, let’s say, the snowy streets of Boston in the winter.

This is also a company-run study, though it has been peer-reviewed by outside experts. And even if we decided to go all in on AI drivers, actually producing enough autonomous vehicles to begin to replace human-driven cars and trucks would be an enormous undertaking, to say the least.

Still, the data looks so good, and the death toll on our roads is so high that I’d argue slowing down autonomous vehicles is actually costing lives. And there’s a risk that’s precisely what will happen.

Too often the public focuses on unusual, outlier events with self-driving cars, while the carnage that occurs thanks to human drivers on a daily basis is simply treated as background noise. (That’s an example of two common psychological biases: availability bias, which causes us to judge risk by outlier events that jump easily to mind, and base-rate neglect, where we ignore the underlying frequency of events.) This misapprehension is something I often see in news coverage and consumption, and it’s one of the reasons I started Good News.

The result is that public opinion has been turning against self-driving cars in recent years, to the point where vandals have attacked autonomous vehicles on the street. And of course, given that nearly 5 million Americans make their living primarily through driving, any wide-scale movement to self-driving vehicles would bring significant economic disruption.

But still, 34,000 lives saved on an annual basis would represent tremendous progress. Maybe, after about 100 years of trying, it’s time to give something else a chance behind the wheel.

A version of this story originally appeared in the Good News newsletter. Sign up here!

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Stablecoin loan repayments flag early signs of Ethereum volatility, report finds https://earlybirdsinvest.com/stablecoin-loan-repayments-flag-early-signs-of-ethereum-volatility-report-finds/ https://earlybirdsinvest.com/stablecoin-loan-repayments-flag-early-signs-of-ethereum-volatility-report-finds/#respond Tue, 08 Apr 2025 02:19:47 +0000 https://earlybirdsinvest.com/stablecoin-loan-repayments-flag-early-signs-of-ethereum-volatility-report-finds/

Repayments of on-chain loans using stablecoins can often serve as an early warning indicator of liquidity shifts and volatility spikes in Ethereum’s (ETH) price, according to a recent Amberdata report. 

The report highlighted how lending behaviors within DeFi ecosystems, particularly repayment frequency, can serve as early indicators of emerging market stress.

The study examined the connection between Ethereum price movements and stablecoin-based lending activity involving USDC, USDT, and DAI. The analysis revealed a consistent relationship between heightened repayment activity and increased ETH price fluctuations.

Volatility framework

The report used the Garman-Klass (GK) estimator. This statistical model accounts for the full intraday price range, including open, high, low, and close prices, rather than relying solely on closing prices. 

According to the report, this method enables more accurate measurement of price swings, particularly during high-activity periods in the market.

Amberdata applied the GK estimator to ETH price data across trading pairs with USDC, USDT, and DAI. The resulting volatility values were then correlated with DeFi lending metrics to assess how transactional behaviors influence market trends. 

Across all three stablecoin ecosystems, the number of loan repayments showed the strongest and most consistent positive correlation with Ethereum volatility. For USDC, the correlation was 0.437; for USDT, 0.491; and DAI, 0.492. 

These results suggest that frequent repayment activity tends to coincide with market uncertainty or stress, during which traders and institutions adjust their positions to manage risk.

A rising number of repayments may reflect de-risking behaviors, such as closing leveraged positions or reallocating capital in response to price movements. Amberdata views this as evidence that repayment activity may be an early indicator of changes in liquidity conditions and upcoming Ethereum market volatility spikes.

In addition to repayment frequency, withdrawal-related metrics displayed moderate correlations with ETH volatility. For instance, the withdrawal amounts and frequency ratio in the USDC ecosystem exhibited correlations of 0.361 and 0.357, respectively.

These numbers suggest that fund outflows from lending platforms, regardless of size, may signal defensive positioning by market participants, reducing liquidity and amplifying price sensitivity.

Borrowing behavior and transaction volume effects

The report also examined other lending metrics, including borrowed amounts and repayment volumes. In the USDT ecosystem, the dollar-denominated amounts for repayments and borrows correlate with ETH volatility at 0.344 and 0.262, respectively. 

While less pronounced than the count-based repayment signals, these metrics still contribute to the broader picture of how transactional intensity can reflect market sentiment.

DAI displayed a similar pattern on a smaller scale. The frequency of loan settlements remained a strong signal, while the ecosystem’s smaller average transaction sizes muted the correlation strength of volume-based metrics. 

Notably, metrics such as dollar-denominated withdrawals in DAI showed a very low correlation (0.047), reinforcing the importance of transaction frequency over transaction size in identifying volatility signals in this context.

Multicollinearity in lending metrics

The report also highlighted the issue of multicollinearity, which is high intercorrelation between independent variables within each stablecoin lending dataset. 

For example, in the USDC ecosystem, the number of repays and withdrawals showed a pairwise correlation of 0.837, indicating that these metrics may capture similar user behavior and could introduce redundancy in predictive models.

Nevertheless, the analysis concludes that repayment activity is a robust indicator of market stress, offering a data-driven lens through which DeFi metrics can interpret and anticipate price conditions in Ethereum markets.

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