BTC $80,066.30 -1.03%
ETH $2,322.33 -0.99%
BNB $739.23 -2.30%
XRP $1.29 -2.10%
SOL $100.20 -1.72%
TRX $0.3311 -0.10%
DOGE $0.0786 -1.22%
ADA $0.2001 -2.19%
BCH $278.58 -5.90%
LINK $11.59 -0.48%
HYPE $88.45 +9.44%
AAVE $132.86 -0.29%
SUI $0.9175 -1.18%
XLM $0.1697 -0.35%
ZEC $1,270.39 -1.95%
AAPL $348.50 +0.56%
AMZN $250.29 -1.30%
GOOGL $288.27 -11.29%
MSFT $537.50 +1.16%
META $619.07 -0.55%
NVDA $214.47 -2.53%
TSLA $403.28 -1.78%
SNDK $1,365.55 +0.30%
INTC $92.53 -2.99%
SPCX $143.26 -4.04%
MU $955.70 -0.73%
AMD $565.79 -0.54%
BTC $80,066.30 -1.03%
ETH $2,322.33 -0.99%
BNB $739.23 -2.30%
XRP $1.29 -2.10%
SOL $100.20 -1.72%
TRX $0.3311 -0.10%
DOGE $0.0786 -1.22%
ADA $0.2001 -2.19%
BCH $278.58 -5.90%
LINK $11.59 -0.48%
HYPE $88.45 +9.44%
AAVE $132.86 -0.29%
SUI $0.9175 -1.18%
XLM $0.1697 -0.35%
ZEC $1,270.39 -1.95%
AAPL $348.50 +0.56%
AMZN $250.29 -1.30%
GOOGL $288.27 -11.29%
MSFT $537.50 +1.16%
META $619.07 -0.55%
NVDA $214.47 -2.53%
TSLA $403.28 -1.78%
SNDK $1,365.55 +0.30%
INTC $92.53 -2.99%
SPCX $143.26 -4.04%
MU $955.70 -0.73%
AMD $565.79 -0.54%

cycle

All
Article
Flash

Analyst: In each U.S. midterm election cycle, Bitcoin has shown a significant pullback, and attention should be paid to the key support level of $73,000

Cryptocurrency analyst Ali Charts stated that as the U.S. midterm elections on November 3 approach, investors may overlook the recurring phenomenon of Bitcoin pullbacks observed in previous election cycles. He believes that this election may once again be accompanied by significant volatility, and the downside risk is worth noting, with a key focus on the lower price level of $73,000. According to his statistics, during the U.S. midterm election cycles in 2010, 2014, 2018, and 2022, Bitcoin experienced pullbacks of 72%, 65%, 52%, and 27%, respectively.However, he emphasized that correlation does not imply causation; the election itself may not necessarily be the reason for the decline, as these pullbacks are also influenced by the overall market cycle of Bitcoin, liquidity conditions, and investor sentiment. Fourth-quarter returns also exhibit similar characteristics: in 2014, 2018, and 2022, Bitcoin fell by 16.7%, 42.16%, and 14.75% in the fourth quarter, respectively. The only exception was in 2010, when it rose by 391%, but Bitcoin was still in its early development stage at that time. Therefore, in the past four midterm election years, three of those years recorded negative returns in the fourth quarter.Regarding the subsequent trend, Ali Charts indicated that the area around $73,000 is close to the average purchase cost of current short-term Bitcoin holders, which can be used to observe the positions of recent investors entering the market. He pointed out that in an established bull market, Bitcoin often finds support near the cost of short-term holders after experiencing a significant pullback. He believes that if selling pressure accelerates after the election on November 3, pushing Bitcoin back down to around $73,000, that area will become an important position to test whether buyers are still willing to maintain the overall bullish trend. If the price continues to rebound from that area, it will strengthen the bullish judgment; in terms of operations, he will wait for signs of selling pressure exhaustion and renewed demand before considering establishing long positions.

first_img a16z General Partner David Haber: Long-cycle intelligent agents can charge based on results

David Haber, a general partner at a16z, stated that long-cycle intelligent agents can now progress towards goals across dozens of steps and various interaction methods over weeks to months. He noted that AI previously handled short tasks with clear boundaries, where customer service was implemented earlier due to verifiable results and edge cases manageable by humans; now, intelligent agents can guide insurance clients from the initial call to payout, mortgage clients from pre-approval to closing, and business leads from demonstration to signing, gaining returns based on revenue growth rather than just cost savings.He used the example of plaintiff lawyers preparing cases, stating that the process resembles a relay race, where value can easily be lost at handoff points. Potential clients often contact multiple law firms simultaneously, and slow responses or evaluations can lead to loss; after signing, evidence collection is limited by manpower, and firms may not follow up with witnesses who did not answer the fifth call, making it difficult to review low-value cases item by item. Missing bills or unexplained treatment gaps can also lower settlement amounts. Long-cycle intelligent agents can assess in real-time around the clock, utilizing sub-agents to advance evidence collection and client updates via phone, email, or text, while maintaining complete records from call logs to medical records.Haber proposed three commercialization paths: selling platforms to existing teams, taking over outsourced services, or vertically integrating as a full-stack service provider, such as purchasing debt portfolios and completing collections. He mentioned that most states in the U.S. prohibit non-lawyers from sharing attorney fees, so the plaintiff legal scenario needs to align pricing with settlement amounts but cannot directly share profits.
app_icon
ChainCatcher Building the Web3 world with innovations.