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Justcryptopays

Crypto enthusiast | Exploring blockchain | insightful and Trader | CMC KOL
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Crypto Volatility: How Traders Can Profit From Market SwingsCryptocurrency markets are famous for one defining characteristic volatility. Unlike traditional equities or bonds, major digital assets like $BTC and Litecoin (LTC) can swing 10–30% or more in a single day sometimes much more. While volatility scares conservative investors, it creates opportunities for knowledgeable traders to profit from price movements in both directions. What Is Crypto Volatility? Volatility measures how dramatically prices move over time. In crypto: Bitcoin : historically has seen annualized volatility far above most stocks Litecoin : correlated with BTC but often more erratic has experienced huge range-bound swings from its lows to all-time highs This volatility is driven by factors like 24/7 trading, sentiment-driven news cycles, shifting liquidity, and macroeconomic events that affect risk assets. Historical BTC & LTC Spikes Bitcoin 2020–2021 Rally + Crash: Bitcoin surged from roughly $10,000 to over $64,000 in less than a year, before crashing back toward $30,000 within months a move of nearly ±50%+ peak-to-trough 2011–2013 Experiences: Early in its life, BTC bounced from $31 to nearly $300, then collapsed again COVID Crash (March 2020): BTC’s largest one-day drop was about 50%, followed by an aggressive rebound the kind of volatility that infuses opportunity and risk. Litecoin (LTC) $LTC , one of the oldest Bitcoin forks, has shown even larger historical percentage moves: In the 2013–2015 era, LTC fell 97% from its peak to valley, then rallied to a new high in 2017 a 27,600% gain from earlier lows. Its all-time high of over $400 remains a landmark of crypto volatility. These dramatic movements underline why volatility isn’t just noise it fuels tradable price swings. How Traders Make Money From Volatility Swing Trading Swing traders hold positions for days to weeks to capture significant price swings as markets trend up or down. They use tools like RSI, MACD, and Fibonacci retracements to time entries and exits This strategy works in BTC and LTC alike watch for sharp pullbacks followed by momentum continuation to enter positions. Scalping Scalpers make many small trades within short timeframes aiming to profit from frequent mini-swings. Volatility creates constant opportunities for quick entry/exit patterns. It requires discipline, fast reactions, and platforms with low fees. Arbitrage During volatile periods, price spreads between exchanges often widen. Traders buy on a cheaper exchange and sell on a more expensive one. Crypto arbitrage is especially relevant across global exchanges where liquidity imbalances arise.This strategy works well in highly volatile regimes where prices momentarily dislocate across platforms. Derivatives Advanced traders use futures, options, and other derivatives to tailor risk and amplify profits: Futures allow directional bets on price movement with leverage. Options strategies (like straddles or strangles) profit when price swings either way, even if direction is uncertain. Why Volatility Is the Trader’s Friend Traditional investors often interpret volatility as instability and heightened risk. Traders, on the other hand, see it as opportunity in motion. Rapid price swings create clear entry and exit points. Temporary imbalances in price open the door for strategic positioning. Different market conditions allow traders to apply multiple approaches, from short-term scalping to longer-term swing setups. Most importantly, volatility rewards those who stay disciplined, manage risk carefully, and stick to a well-defined plan. In conclusion BTC and LTC volatility isn’t randomly chaotic it’s systematic and repeatable. Historical spikes give traders a roadmap for patterns, reactions, and range boundaries. With a solid strategy, good risk controls, and technical discipline, crypto market swings are not just fluctuations they’re opportunities. #CZAMAonBinanceSquare

Crypto Volatility: How Traders Can Profit From Market Swings

Cryptocurrency markets are famous for one defining characteristic volatility. Unlike traditional equities or bonds, major digital assets like $BTC and Litecoin (LTC) can swing 10–30% or more in a single day sometimes much more.
While volatility scares conservative investors, it creates opportunities for knowledgeable traders to profit from price movements in both directions.
What Is Crypto Volatility?
Volatility measures how dramatically prices move over time. In crypto:
Bitcoin : historically has seen annualized volatility far above most stocks
Litecoin : correlated with BTC but often more erratic has experienced huge range-bound swings from its lows to all-time highs
This volatility is driven by factors like 24/7 trading, sentiment-driven news cycles, shifting liquidity, and macroeconomic events that affect risk assets.
Historical BTC & LTC Spikes
Bitcoin
2020–2021 Rally + Crash:
Bitcoin surged from roughly $10,000 to over $64,000 in less than a year, before crashing back toward $30,000 within months a move of nearly ±50%+ peak-to-trough
2011–2013 Experiences:
Early in its life, BTC bounced from $31 to nearly $300, then collapsed again
COVID Crash (March 2020):
BTC’s largest one-day drop was about 50%, followed by an aggressive rebound the kind of volatility that infuses opportunity and risk.
Litecoin (LTC)
$LTC , one of the oldest Bitcoin forks, has shown even larger historical percentage moves:
In the 2013–2015 era, LTC fell 97% from its peak to valley, then rallied to a new high in 2017 a 27,600% gain from earlier lows.
Its all-time high of over $400 remains a landmark of crypto volatility.
These dramatic movements underline why volatility isn’t just noise it fuels tradable price swings.
How Traders Make Money From Volatility
Swing Trading
Swing traders hold positions for days to weeks to capture significant price swings as markets trend up or down. They use tools like RSI, MACD, and Fibonacci retracements to time entries and exits
This strategy works in BTC and LTC alike watch for sharp pullbacks followed by momentum continuation to enter positions.
Scalping
Scalpers make many small trades within short timeframes aiming to profit from frequent mini-swings. Volatility creates constant opportunities for quick entry/exit patterns. It requires discipline, fast reactions, and platforms with low fees.
Arbitrage
During volatile periods, price spreads between exchanges often widen.
Traders buy on a cheaper exchange and sell on a more expensive one. Crypto arbitrage is especially relevant across global exchanges where liquidity imbalances arise.This strategy works well in highly volatile regimes where prices momentarily dislocate across platforms.
Derivatives
Advanced traders use futures, options, and other derivatives to tailor risk and amplify profits:
Futures allow directional bets on price movement with leverage. Options strategies (like straddles or strangles) profit when price swings either way, even if direction is uncertain.
Why Volatility Is the Trader’s Friend
Traditional investors often interpret volatility as instability and heightened risk. Traders, on the other hand, see it as opportunity in motion. Rapid price swings create clear entry and exit points. Temporary imbalances in price open the door for strategic positioning.
Different market conditions allow traders to apply multiple approaches, from short-term scalping to longer-term swing setups. Most importantly, volatility rewards those who stay disciplined, manage risk carefully, and stick to a well-defined plan.
In conclusion BTC and LTC volatility isn’t randomly chaotic it’s systematic and repeatable. Historical spikes give traders a roadmap for patterns, reactions, and range boundaries. With a solid strategy, good risk controls, and technical discipline, crypto market swings are not just fluctuations they’re opportunities.
#CZAMAonBinanceSquare
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AI-Driven Trading Bots vs Manual Trading: Who Wins in Volatile Markets?Volatility is the lifeblood of financial markets and nowhere is this more evident than in crypto. When $BTC spikes 8% in an hour or altcoins swing double digits overnight, traders face a defining question: Do algorithms outperform human intuition when markets turn chaotic? Let's break it down What Are AI-Driven Trading Bots AI-driven trading bots are automated software programs that use artificial intelligence and machine learning to analyze market data and execute trades without human intervention. Instead of a trader manually watching charts, these bots: Scan large amounts of real-time data Identify patterns and probabilities Generate buy/sell signals Execute trades automatically Manage risk based on preset rules Why Bots Thrive in Volatile Markets 1. Speed & Execution Markets can move in milliseconds. Bots execute instantly no hesitation, no emotional delay. 2. 24/7 Operation Crypto never sleeps. Bots monitor markets around the clock without fatigue. 3. Data Processing Power AI models analyze order books, funding rates, volatility clusters, and on-chain metrics simultaneously. 4. Emotionless Decisions Fear and greed destroy human traders during flash crashes. Bots follow predefined rules. Where Bots Struggle Overfitting to past data Poor performance during black swan events Strategy breakdown in regime shifts Dependence on clean liquidity and stable infrastructure When volatility becomes irrational rather than statistical, bots can malfunction or amplify losses. What Is Manual Trading? Manual trading is when a human trader personally analyzes the market and executes buy or sell orders without automated systems making decisions for them. Every step from chart analysis to clicking buy or sell is controlled by the trader. The Case for Manual Trading Manual trading relies on discretion, macro interpretation, market psychology, and experience. Why Humans Still Matter 1. Context Awareness Humans understand narratives ETF approvals, regulatory shocks, geopolitical risk. For example, during major news tied to Bitcoin or Ethereum, discretionary traders can react to tone and sentiment before models adjust. 2. Adaptive Thinking Markets change regimes trending, ranging, panic-driven. Experienced traders can shift strategies faster than rigid algorithms. 3. Creative Risk Management Humans can reduce exposure, hedge creatively, or step aside entirely during extreme uncertainty. Where Humans Fail Emotional bias (revenge trading, FOMO, panic selling) Inconsistent discipline Slower execution Fatigue in 24/7 markets In highly volatile environments, emotions become the biggest liability. Performance in Volatile Markets: Who Has the Edge? 1. Structured Volatility (Trending + Liquidity Present) Bots often outperform. Momentum models and breakout algorithms thrive. 2. News-Driven Spikes Manual traders may win. Context and interpretation beat pure pattern recognition. 3. Flash Crashes / Liquidity Gaps Mixed results. Bots can either capture arbitrage instantly or get liquidated rapidly. 4. Extended Sideways Chop Both struggle but disciplined humans may preserve capital better. What Is the Hybrid Model in Trading? The hybrid model in trading is a combination of AI-driven automation and human decision making. Instead of choosing between bots or manual trading, traders use both allowing technology to handle speed and data, while humans manage strategy and risk. How the Hybrid Model Works 1. AI Handles the Heavy Lifting Scans markets 24/7 Detects patterns and volatility shifts Generates trade signals Executes trades instantly 2. Humans Provide Oversight Adjust strategy during regime changes Interpret macro events and narratives Manage portfolio-level risk Override or pause systems during extreme conditions The Hybrid Model: The Real Winner Increasingly, professional traders combine both approaches: AI for signal generation Automation for execution Human oversight for risk control Institutional desks use algorithms to exploit micro-inefficiencies while portfolio managers oversee macro exposure. The edge is no longer bot vs human. It’s bot plus human. Key comparison between AI trading and Manual trading 1.Speed AI Bots: Instant Manual Trading: Slower 2. Emotional Control AI Bots: Perfect Manual Trading: Vulnerable 3. Adaptability AI Bots: Depends on model Manual Trading: High (if experienced) 4. 24/7 Capability AI Bots: Yes Manual Trading: Limited 5. Narrative Awareness AI Bots: Weak Manual Trading: Strong In conclusion, In highly volatile crypto markets, the winner often depends on the type of movement unfolding. During short-term, high-frequency chaos, AI-driven bots typically have the advantage thanks to their speed and precision. But when markets shift due to powerful narratives or macro regime changes, experienced human traders tend to perform better because they can interpret context and adapt quickly. Over the long run, however, neither speed nor intuition guarantees success disciplined risk management does. The real edge isn’t about ego or raw intelligence; it’s about structure and consistency. Markets don’t consistently reward who is smartest they reward who manages risk best. And in volatile conditions, the trader who controls downside exposure whether human or algorithm is the one who ultimately survives and wins. #CPIWatch

AI-Driven Trading Bots vs Manual Trading: Who Wins in Volatile Markets?

Volatility is the lifeblood of financial markets and nowhere is this more evident than in crypto. When $BTC spikes 8% in an hour or altcoins swing double digits overnight, traders face a defining question:
Do algorithms outperform human intuition when markets turn chaotic?
Let's break it down
What Are AI-Driven Trading Bots
AI-driven trading bots are automated software programs that use artificial intelligence and machine learning to analyze market data and execute trades without human intervention.
Instead of a trader manually watching charts, these bots:
Scan large amounts of real-time data
Identify patterns and probabilities
Generate buy/sell signals
Execute trades automatically
Manage risk based on preset rules
Why Bots Thrive in Volatile Markets
1. Speed & Execution Markets can move in milliseconds. Bots execute instantly no hesitation, no emotional delay.
2. 24/7 Operation Crypto never sleeps. Bots monitor markets around the clock without fatigue.
3. Data Processing Power AI models analyze order books, funding rates, volatility clusters, and on-chain metrics simultaneously.
4. Emotionless Decisions Fear and greed destroy human traders during flash crashes. Bots follow predefined rules.
Where Bots Struggle
Overfitting to past data
Poor performance during black swan events
Strategy breakdown in regime shifts
Dependence on clean liquidity and stable infrastructure
When volatility becomes irrational rather than statistical, bots can malfunction or amplify losses.
What Is Manual Trading?
Manual trading is when a human trader personally analyzes the market and executes buy or sell orders without automated systems making decisions for them.
Every step from chart analysis to clicking buy or sell is controlled by the trader.
The Case for Manual Trading
Manual trading relies on discretion, macro interpretation, market psychology, and experience.
Why Humans Still Matter
1. Context Awareness Humans understand narratives ETF approvals, regulatory shocks, geopolitical risk.
For example, during major news tied to Bitcoin or Ethereum, discretionary traders can react to tone and sentiment before models adjust.
2. Adaptive Thinking Markets change regimes trending, ranging, panic-driven. Experienced traders can shift strategies faster than rigid algorithms.
3. Creative Risk Management Humans can reduce exposure, hedge creatively, or step aside entirely during extreme uncertainty.
Where Humans Fail
Emotional bias (revenge trading, FOMO, panic selling)
Inconsistent discipline
Slower execution
Fatigue in 24/7 markets
In highly volatile environments, emotions become the biggest liability.
Performance in Volatile Markets: Who Has the Edge?
1. Structured Volatility (Trending + Liquidity Present)
Bots often outperform.
Momentum models and breakout algorithms thrive.
2. News-Driven Spikes
Manual traders may win.
Context and interpretation beat pure pattern recognition.
3. Flash Crashes / Liquidity Gaps
Mixed results.
Bots can either capture arbitrage instantly or get liquidated rapidly.
4. Extended Sideways Chop
Both struggle but disciplined humans may preserve capital better.
What Is the Hybrid Model in Trading?
The hybrid model in trading is a combination of AI-driven automation and human decision making.
Instead of choosing between bots or manual trading, traders use both allowing technology to handle speed and data, while humans manage strategy and risk.
How the Hybrid Model Works
1. AI Handles the Heavy Lifting
Scans markets 24/7
Detects patterns and volatility shifts
Generates trade signals
Executes trades instantly
2. Humans Provide Oversight
Adjust strategy during regime changes
Interpret macro events and narratives
Manage portfolio-level risk
Override or pause systems during extreme conditions
The Hybrid Model: The Real Winner
Increasingly, professional traders combine both approaches:
AI for signal generation
Automation for execution
Human oversight for risk control
Institutional desks use algorithms to exploit micro-inefficiencies while portfolio managers oversee macro exposure.
The edge is no longer bot vs human.
It’s bot plus human.
Key comparison between AI trading and Manual trading
1.Speed
AI Bots: Instant
Manual Trading: Slower
2. Emotional Control
AI Bots: Perfect
Manual Trading: Vulnerable
3. Adaptability
AI Bots: Depends on model
Manual Trading: High (if experienced)
4. 24/7 Capability
AI Bots: Yes
Manual Trading: Limited
5. Narrative Awareness
AI Bots: Weak
Manual Trading: Strong
In conclusion, In highly volatile crypto markets, the winner often depends on the type of movement unfolding. During short-term, high-frequency chaos, AI-driven bots typically have the advantage thanks to their speed and precision. But when markets shift due to powerful narratives or macro regime changes, experienced human traders tend to perform better because they can interpret context and adapt quickly.
Over the long run, however, neither speed nor intuition guarantees success disciplined risk management does. The real edge isn’t about ego or raw intelligence; it’s about structure and consistency. Markets don’t consistently reward who is smartest they reward who manages risk best. And in volatile conditions, the trader who controls downside exposure whether human or algorithm is the one who ultimately survives and wins.
#CPIWatch
$BTC Bitcoin bounced cleanly from our micro support and is now pushing through the 5th wave of wave (5). For now, the move still has room to extend higher. A break below the intraday low would be the first real signal that a local top is in. Until that happens, bears remain under pressure. #USJoblessClaimsFallTo206000
$BTC

Bitcoin bounced cleanly from our micro support and is now pushing through the 5th wave of wave (5).

For now, the move still has room to extend higher. A break below the intraday low would be the first real signal that a local top is in.

Until that happens, bears remain under pressure.
#USJoblessClaimsFallTo206000
$BTC has broken above the descending trendline, signaling a strong shift in momentum. This move looks increasingly like the start of wave-(3) to the upside. If a wave-(4) pullback follows, the key support zone sits between $69,720 and $67,750. #CryptoRally
$BTC has broken above the descending trendline, signaling a strong shift in momentum. This move looks increasingly like the start of wave-(3) to the upside.

If a wave-(4) pullback follows, the key support zone sits between $69,720 and $67,750.
#CryptoRally
🩸 Crypto bears just took a historic hit. Around $2.74B in short positions were wiped out within 24 hours, accounting for 92% of nearly $3B in total liquidations. $BTC shorts alone made up $1.37B, while $ETH shorts added another $1.01B both setting record levels. The only larger liquidation event came during the October 10 crash, but that time, it was longs getting crushed as the market dropped. This time, the leverage was stacked on the bearish side. A brutal reminder of what happens when the market moves against an overcrowded trade. #CryptoRally
🩸 Crypto bears just took a historic hit.

Around $2.74B in short positions were wiped out within 24 hours, accounting for 92% of nearly $3B in total liquidations.

$BTC shorts alone made up $1.37B, while $ETH shorts added another $1.01B both setting record levels.

The only larger liquidation event came during the October 10 crash, but that time, it was longs getting crushed as the market dropped.

This time, the leverage was stacked on the bearish side.

A brutal reminder of what happens when the market moves against an overcrowded trade.
#CryptoRally
Bitcoin is showing an unusual divergence from global M2. Historically, $BTC and global M2 moved together in roughly 83% of 12-month periods. Now, global M2 is at record highs, up 7.2% YoY, while BTC is down nearly 45%. That’s a massive disconnect. A similar divergence in 2021 preceded a 55% BTC crash, followed by a strong recovery. This time, the divergence has lasted much longer. The big question is whether Bitcoin eventually catches up with liquidity or whether this signals a deeper shift in the market. #FOMCWatch
Bitcoin is showing an unusual divergence from global M2.

Historically, $BTC and global M2 moved together in roughly 83% of 12-month periods.

Now, global M2 is at record highs, up 7.2% YoY, while BTC is down nearly 45%.

That’s a massive disconnect.

A similar divergence in 2021 preceded a 55% BTC crash, followed by a strong recovery.

This time, the divergence has lasted much longer.

The big question is whether Bitcoin eventually catches up with liquidity or whether this signals a deeper shift in the market.
#FOMCWatch
As with BTC and the broader crypto market, $LTC may be approaching a phase where its corrective rally starts gaining momentum. The preferred scenario remains a B-wave recovery, with price potentially moving toward the $52–$58 resistance zone before another C-wave decline develops. The key distinction is that near-term strength does not necessarily signal the end of the broader correction. A rally into resistance could simply be another corrective leg before the larger downside move resumes. What matters most is how the wave structure develops and whether price action confirms the expected sequence. The $52–$58 region is a potential resistance area, not a guaranteed target. The structure should determine the probabilities not the target. #MetaplanetToInvest2100BTCInSuperLeague
As with BTC and the broader crypto market, $LTC may be approaching a phase where its corrective rally starts gaining momentum.

The preferred scenario remains a B-wave recovery, with price potentially moving toward the $52–$58 resistance zone before another C-wave decline develops.

The key distinction is that near-term strength does not necessarily signal the end of the broader correction. A rally into resistance could simply be another corrective leg before the larger downside move resumes.

What matters most is how the wave structure develops and whether price action confirms the expected sequence. The $52–$58 region is a potential resistance area, not a guaranteed target.

The structure should determine the probabilities not the target.
#MetaplanetToInvest2100BTCInSuperLeague
🚨 UPDATE: Bitcoin’s spot demand is on the verge of turning positive for the first time since February. Historically, similar shifts have been bullish, with an 18.1% median gain over the following 60 days and a 78% win rate, according to CryptoQuant. It’s not a guarantee that $BTC will rally, but it does suggest the underlying demand is improving and that could matter more than the day-to-day market noise. #EthereumOpensGlamsterdamEarlyTestnet
🚨 UPDATE: Bitcoin’s spot demand is on the verge of turning positive for the first time since February.

Historically, similar shifts have been bullish, with an 18.1% median gain over the following 60 days and a 78% win rate, according to CryptoQuant.

It’s not a guarantee that $BTC will rally, but it does suggest the underlying demand is improving and that could matter more than the day-to-day market noise.
#EthereumOpensGlamsterdamEarlyTestnet
$BTC Bitcoin may have put in a local top for wave 3, with the next key area to watch being the $64,119–$63,616 support zone for a potential wave-4 pullback. As long as BTC holds this range, the broader wave structure remains constructive and another move higher is still possible. However, a decisive breakdown below $63,616 would weaken that count significantly and suggest the pattern is turning bearish. For now, the reaction around this support zone is more important than the pullback itself. A strong defense keeps the bullish structure alive; losing it would shift the risk toward a deeper correction. #VIXFallsTo2026Low
$BTC

Bitcoin may have put in a local top for wave 3, with the next key area to watch being the $64,119–$63,616 support zone for a potential wave-4 pullback.

As long as BTC holds this range, the broader wave structure remains constructive and another move higher is still possible. However, a decisive breakdown below $63,616 would weaken that count significantly and suggest the pattern is turning bearish.

For now, the reaction around this support zone is more important than the pullback itself. A strong defense keeps the bullish structure alive; losing it would shift the risk toward a deeper correction.
#VIXFallsTo2026Low
$SOL Solana’s downside structure is still intact, even with selling pressure starting to ease. Holding above $70.50 would keep the door open for a recovery toward the $89–94 resistance zone, but that move alone wouldn’t confirm a trend reversal. The bigger level to watch is $62. A decisive break below it would weaken the current setup and expose $49 first, followed by $43 and potentially $32 if the broader correction accelerates. Until SOL develops a clear 5-wave impulsive structure, the recovery should be treated as corrective rather than the start of a new uptrend. There’s room for a bounce, but not enough confirmation yet to call the bottom. #DollarHits3MonthLow
$SOL

Solana’s downside structure is still intact, even with selling pressure starting to ease. Holding above $70.50 would keep the door open for a recovery toward the $89–94 resistance zone, but that move alone wouldn’t confirm a trend reversal.

The bigger level to watch is $62. A decisive break below it would weaken the current setup and expose $49 first, followed by $43 and potentially $32 if the broader correction accelerates.

Until SOL develops a clear 5-wave impulsive structure, the recovery should be treated as corrective rather than the start of a new uptrend. There’s room for a bounce, but not enough confirmation yet to call the bottom.
#DollarHits3MonthLow
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🚨 UPDATE: $ETH Foundation has launched the Platåberget testnet, giving developers an early chance to test the upcoming Glamsterdam upgrade ahead of the Aug. 20 fork. This is more than just another testnet launch. It gives developers a chance to catch bugs, test how the upgrade performs under real conditions, and make adjustments before anything reaches mainnet. With Glamsterdam being a major step in Ethereum’s roadmap, getting this testing phase right will be important for a smooth rollout. #EthereumFoundationLaunchesGlamsterdamTestnet
🚨 UPDATE: $ETH Foundation has launched the Platåberget testnet, giving developers an early chance to test the upcoming Glamsterdam upgrade ahead of the Aug. 20 fork.

This is more than just another testnet launch. It gives developers a chance to catch bugs, test how the upgrade performs under real conditions, and make adjustments before anything reaches mainnet.

With Glamsterdam being a major step in Ethereum’s roadmap, getting this testing phase right will be important for a smooth rollout.
#EthereumFoundationLaunchesGlamsterdamTestnet
$XLM remains stuck in a broad sideways range, while the recovery from the January/February low is still only a 3-wave move. So far, there’s no clear confirmation that a lasting bottom is in. Another low remains the preferred scenario, with $0.138–$0.14 acting as the next key support zone. If that fails, the rising trendline around $0.125–$0.13 could provide the next level of support. #ChinaJulyOutputRetailInvestmentAllMiss
$XLM remains stuck in a broad sideways range, while the recovery from the January/February low is still only a 3-wave move. So far, there’s no clear confirmation that a lasting bottom is in.

Another low remains the preferred scenario, with $0.138–$0.14 acting as the next key support zone. If that fails, the rising trendline around $0.125–$0.13 could provide the next level of support.
#ChinaJulyOutputRetailInvestmentAllMiss
$BTC has broken above the descending trendline and successfully retested it as support. For now, the move still looks like a 3-wave structure. We need to see waves 4 and 5 develop before we can have stronger confirmation that wave-(2) has bottomed. #IsraelStrikesLebanonKillsHezbollahCommander
$BTC has broken above the descending trendline and successfully retested it as support. For now, the move still looks like a 3-wave structure. We need to see waves 4 and 5 develop before we can have stronger confirmation that wave-(2) has bottomed.
#IsraelStrikesLebanonKillsHezbollahCommander
$BTC : This is the first warning sign for me. Price has broken below the 78.6% Fib retracement, while the reaction from the 88.7% Fib level has been pretty weak. That’s a reason to stay cautious for now. However, if BTC manages to break above the descending trendline, it could signal that the bulls are starting to regain control. #USJulyRetailSalesFall0.6%
$BTC : This is the first warning sign for me. Price has broken below the 78.6% Fib retracement, while the reaction from the 88.7% Fib level has been pretty weak.

That’s a reason to stay cautious for now.

However, if BTC manages to break above the descending trendline, it could signal that the bulls are starting to regain control.
#USJulyRetailSalesFall0.6%
අර්ධ වශයෙන් සත්යයි
🇺🇸 ETF FLOWS: Spot $ETH and XRP ETFs recorded net inflows on Aug. 13, while $BTC spot ETFs saw another day of outflows. BTC: -$131.13M ETH: +$6.72M XRP: +$2.25M #RedditToJoinSP500
🇺🇸 ETF FLOWS: Spot $ETH and XRP ETFs recorded net inflows on Aug. 13, while $BTC spot ETFs saw another day of outflows.

BTC: -$131.13M
ETH: +$6.72M
XRP: +$2.25M
#RedditToJoinSP500
📊 INSIGHT: $BTC short-term holder supply continues to decline. According to CryptoQuant analyst Darkfost, this pattern has historically shown up around the later stages of bear markets. #USJulyCPI&PPIDueThisWeek
📊 INSIGHT: $BTC short-term holder supply continues to decline.

According to CryptoQuant analyst Darkfost, this pattern has historically shown up around the later stages of bear markets.
#USJulyCPI&PPIDueThisWeek
තවත් අන්තර්ගතයන් ගවේෂණය කිරීමට ඇතුල් වන්න
Binance චතුරශ්‍රය හි ගෝලීය ක්‍රිප්ටෝ පරිශීලකයින් හා එක්වන්න
⚡️ ක්‍රිප්ටෝ පිළිබඳ නවතම සහ ප්‍රයෝජනවත් තොරතුරු ලබා ගන්න.
💬 ලොව විශාලතම ක්‍රිප්ටෝ හුවමාරුව මගින් විශ්වාස කෙරේ.
👍 සත්‍යායනය කරන ලද නිර්මාණකරුවන්ගෙන් සැබෑ විදසුන් සොයා ගන්න.
විද්‍යුත් තැපෑල / දුරකථන අංකය
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වේදිකා කොන්දේසි සහ නියමයන්