KINZA_SAIM
10.6k Публикации
KINZA_SAIM
“Crypto Enthusiast | Binance Trader | BTC • ETH • Altcoins • DeFi • NFTs | Technical & Fundamental Analyst | Scalper • Swing Trader • Long-Term Investor | Web3
Отваряне на търговията
Чест трейдър
1.5 години
124 Следвани
19.0K+ Последователи
8.9K+ Харесано
Публикации
Портфолио
Всички
Оферти
На живо
#BitcoinNetworkActivityNearAllTimeHigh
$HYPE is showing early stabilization after a downside liquidity sweep, followed by a recovery attempt from the demand zone. Price action suggests buyers are stepping in to absorb selling pressure and defend short-term structure.
EP
70.2 - 71.0
TP
TP1 72.0
TP2 73.8
TP3 75.5
SL
69.0
Liquidity was taken below recent lows before price entered a consolidation phase. Structure remains fragile, but early absorption indicates potential for a relief move if buyers continue defending the demand area.
A clean reclaim of local resistance would be needed to confirm continuation strength.
$HYPE is showing early stabilization after a downside liquidity sweep, followed by a recovery attempt from the demand zone. Price action suggests buyers are stepping in to absorb selling pressure and defend short-term structure.
EP
70.2 - 71.0
TP
TP1 72.0
TP2 73.8
TP3 75.5
SL
69.0
Liquidity was taken below recent lows before price entered a consolidation phase. Structure remains fragile, but early absorption indicates potential for a relief move if buyers continue defending the demand area.
A clean reclaim of local resistance would be needed to confirm continuation strength.
🟢🟢
73%
🔴🔴
27%
11 Гласа • Гласуването приключи
#IranAnnouncesStraitOfHormuzClosure
$RE is showing early stabilization after a downside liquidity sweep, followed by a recovery attempt from the demand zone. Price action suggests buyers are stepping in to absorb selling pressure and defend short-term structure.
EP
0.972 - 0.982
TP
TP1 0.960
TP2 0.940
TP3 0.915
SL
0.995
Liquidity was taken below recent lows before price entered a consolidation phase. Structure remains fragile, but early absorption indicates potential for a relief move if buyers continue defending the demand area.
A clean reclaim of local resistance would be needed to confirm continuation strength.
$RE is showing early stabilization after a downside liquidity sweep, followed by a recovery attempt from the demand zone. Price action suggests buyers are stepping in to absorb selling pressure and defend short-term structure.
EP
0.972 - 0.982
TP
TP1 0.960
TP2 0.940
TP3 0.915
SL
0.995
Liquidity was taken below recent lows before price entered a consolidation phase. Structure remains fragile, but early absorption indicates potential for a relief move if buyers continue defending the demand area.
A clean reclaim of local resistance would be needed to confirm continuation strength.
Bullish 🟢
65%
Bearish 🔴
35%
34 Гласа • Гласуването приключи
#DigitalCreditMarketsWorstDayDrop
$BICO is showing early stabilization after a downside liquidity sweep, followed by a recovery attempt from the demand zone. Price action suggests buyers are stepping in to absorb selling pressure and defend short-term structure.
EP
0.0410 - 0.0420
TP
TP1 0.0430
TP2 0.0448
TP3 0.0465
SL
0.0398
Liquidity was taken below recent lows before price entered a consolidation phase. Structure remains fragile, but early absorption indicates potential for a relief move if buyers continue defending the demand area.
A clean reclaim of local resistance would be needed to confirm continuation strength.
$BICO is showing early stabilization after a downside liquidity sweep, followed by a recovery attempt from the demand zone. Price action suggests buyers are stepping in to absorb selling pressure and defend short-term structure.
EP
0.0410 - 0.0420
TP
TP1 0.0430
TP2 0.0448
TP3 0.0465
SL
0.0398
Liquidity was taken below recent lows before price entered a consolidation phase. Structure remains fragile, but early absorption indicates potential for a relief move if buyers continue defending the demand area.
A clean reclaim of local resistance would be needed to confirm continuation strength.
UP 🟢
67%
DWON🔴
33%
6 Гласа • Гласуването приключи
Open AI tools are getting better every month, but the real gap I keep noticing isn’t capability — it’s trust and usability.
Most people are now surrounded by AI apps: chat models for writing, separate tools for reasoning, different platforms for images, and another layer for automation. On paper it looks powerful, but in practice it often turns into constant context switching and fragmented workflows. You’re not really “using AI” anymore — you’re managing tools.
That’s why OpenGradient caught my attention.
Instead of treating AI as isolated apps, it pushes a different direction: a decentralized environment where models can run, interact, and be verified. The interesting shift here isn’t just about performance — it’s about removing blind trust from the equation. If AI starts influencing finance, DeFi, and on-chain systems, then “it works” is no longer enough. We start needing proof of what happened and why.
At the same time, the real user pain is becoming clearer: not choosing the “best” model, but managing multiple models smoothly. Different tasks need different strengths — writing, reasoning, visual generation — but jumping between tabs breaks the flow.
A unified, multi-model workspace changes the question from “which AI is best?” to “which path should this task take?”
Long term, the winners may not just be the smartest models, but the systems that make AI feel connected, verifiable, and actually usable in one place.
#opg $OPG @OpenGradient
Most people are now surrounded by AI apps: chat models for writing, separate tools for reasoning, different platforms for images, and another layer for automation. On paper it looks powerful, but in practice it often turns into constant context switching and fragmented workflows. You’re not really “using AI” anymore — you’re managing tools.
That’s why OpenGradient caught my attention.
Instead of treating AI as isolated apps, it pushes a different direction: a decentralized environment where models can run, interact, and be verified. The interesting shift here isn’t just about performance — it’s about removing blind trust from the equation. If AI starts influencing finance, DeFi, and on-chain systems, then “it works” is no longer enough. We start needing proof of what happened and why.
At the same time, the real user pain is becoming clearer: not choosing the “best” model, but managing multiple models smoothly. Different tasks need different strengths — writing, reasoning, visual generation — but jumping between tabs breaks the flow.
A unified, multi-model workspace changes the question from “which AI is best?” to “which path should this task take?”
Long term, the winners may not just be the smartest models, but the systems that make AI feel connected, verifiable, and actually usable in one place.
#opg $OPG @OpenGradient
I keep coming back to @OpenGradient because it feels like one of the few projects trying to solve something real instead of just spinning another token story. The part that stands out to me is the bridge between developers and actual demand. A lot of chains and AI-linked projects get stuck on the supply side, meaning there are builders, but no clear reason for users to show up. Here, the incentive loop looks more practical: developers want a place where they can ship useful models, while users want results they can trust without having to believe every claim blindly.
That matters a lot. In crypto, “activity” can be fake fast. Real demand is slower. It shows up in repeat usage, not just one-time hype. What I watch here is whether the ecosystem keeps creating reasons for people to return, and whether liquidity stays healthy enough for the market to price that in properly.
The main risk, in my view, is still execution. A good idea can still struggle if onboarding is clunky or if trust assumptions are too heavy for normal users. But the structure makes sense to me so far. The question is whether OpenGradient can turn technical usefulness into sticky behavior before the market moves on.
#opg $OPG @OpenGradient
That matters a lot. In crypto, “activity” can be fake fast. Real demand is slower. It shows up in repeat usage, not just one-time hype. What I watch here is whether the ecosystem keeps creating reasons for people to return, and whether liquidity stays healthy enough for the market to price that in properly.
The main risk, in my view, is still execution. A good idea can still struggle if onboarding is clunky or if trust assumptions are too heavy for normal users. But the structure makes sense to me so far. The question is whether OpenGradient can turn technical usefulness into sticky behavior before the market moves on.
#opg $OPG @OpenGradient
Most AI platforms still work the same way.
You ask a question, get an answer, and then trust that everything happened exactly as claimed behind the scenes.
The problem is that users usually have no way to verify it.
OpenGradient is built around a different idea.
Instead of relying on trust in a company or platform, it provides a decentralized network where AI models can be hosted, used for inference, and verified through the network itself.
What stands out is the focus on making AI activity more transparent.
Rather than treating model execution as something hidden from users, the goal is to make important parts of the process observable and verifiable.
As AI becomes more involved in research, business, and everyday decisions, knowing how results are produced may become just as important as the results themselves.
That is the gap OpenGradient is trying to address.
The idea is simple: confidence in AI should come from the ability to verify what happened, not from having to trust whoever controls the system.
#opg $OPG @OpenGradient
You ask a question, get an answer, and then trust that everything happened exactly as claimed behind the scenes.
The problem is that users usually have no way to verify it.
OpenGradient is built around a different idea.
Instead of relying on trust in a company or platform, it provides a decentralized network where AI models can be hosted, used for inference, and verified through the network itself.
What stands out is the focus on making AI activity more transparent.
Rather than treating model execution as something hidden from users, the goal is to make important parts of the process observable and verifiable.
As AI becomes more involved in research, business, and everyday decisions, knowing how results are produced may become just as important as the results themselves.
That is the gap OpenGradient is trying to address.
The idea is simple: confidence in AI should come from the ability to verify what happened, not from having to trust whoever controls the system.
#opg $OPG @OpenGradient
I’ve been thinking a lot about how most AI systems today still feel locked behind closed doors. You use them, but you never really know how they’re running, who controls them, or what happens behind the scenes. It’s fast, sure… but it doesn’t feel open.
That’s why @OpenGradient caught my attention.
It’s building something called Open Intelligence basically a decentralized setup where AI models aren’t just hosted in one place. They can be run, verified, and scaled across a network instead of sitting inside a single company’s infrastructure. That shift sounds small at first, but it actually changes a lot about trust and transparency.
What stood out to me is the idea that inference itself becomes a shared layer. So instead of relying on one provider to process everything, the workload is distributed, and the results can be verified. That opens doors for more open participation, especially for developers who want access without being boxed in by traditional platforms.
It also feels like a step toward making AI less of a “black box” and more of a public utility something that anyone can plug into, build on, or audit if needed.
Still early days, but the direction makes sense. If AI is going to keep scaling the way it is, centralized control starts to look like a bottleneck rather than an advantage.
OpenGradient is basically pushing that conversation forward.
@OpenGradient #OPG $OPG
That’s why @OpenGradient caught my attention.
It’s building something called Open Intelligence basically a decentralized setup where AI models aren’t just hosted in one place. They can be run, verified, and scaled across a network instead of sitting inside a single company’s infrastructure. That shift sounds small at first, but it actually changes a lot about trust and transparency.
What stood out to me is the idea that inference itself becomes a shared layer. So instead of relying on one provider to process everything, the workload is distributed, and the results can be verified. That opens doors for more open participation, especially for developers who want access without being boxed in by traditional platforms.
It also feels like a step toward making AI less of a “black box” and more of a public utility something that anyone can plug into, build on, or audit if needed.
Still early days, but the direction makes sense. If AI is going to keep scaling the way it is, centralized control starts to look like a bottleneck rather than an advantage.
OpenGradient is basically pushing that conversation forward.
@OpenGradient #OPG $OPG
Проверени
I’ve spent the last few weeks watching how @OpenGradient approaches governance, and what stands out is that it feels less like a voting experiment and more like actual network ownership.
A lot of projects give communities control over surface-level decisions. Logo updates, campaigns, or minor proposals. But OPG governance focuses on the parts that truly define the protocol: TEE hardware support, gas economics, treasury direction, and core upgrades.
The TEE hardware discussion is especially interesting because it is not just a technical choice. It is a decision about trust. The hardware layer becomes part of the security model, and choosing the wrong path could create long-term dependency on a single ecosystem or vendor.
What caught my attention is that governance participation appears more active than what we usually see in early-stage networks. Real involvement matters because infrastructure decisions should not be shaped by a small group of passive holders.
That said, decentralization still has challenges. Voting power concentration remains something to watch. When a limited number of wallets control a large portion of influence, the quality of governance depends on whether those holders act in the network’s long-term interest.
Beyond governance, the bigger idea behind OpenGradient is verification.
AI today is often judged by the quality of answers, but the next phase may require proving how those answers were created. The model, the execution environment, the data flow, and the final output all become part of the trust equation.
Maybe the future of AI is not only about smarter models.
Maybe it is about creating systems where we can verify what happened before we trust the result.
#opg $OPG @OpenGradient
$EVAA $BSB
A lot of projects give communities control over surface-level decisions. Logo updates, campaigns, or minor proposals. But OPG governance focuses on the parts that truly define the protocol: TEE hardware support, gas economics, treasury direction, and core upgrades.
The TEE hardware discussion is especially interesting because it is not just a technical choice. It is a decision about trust. The hardware layer becomes part of the security model, and choosing the wrong path could create long-term dependency on a single ecosystem or vendor.
What caught my attention is that governance participation appears more active than what we usually see in early-stage networks. Real involvement matters because infrastructure decisions should not be shaped by a small group of passive holders.
That said, decentralization still has challenges. Voting power concentration remains something to watch. When a limited number of wallets control a large portion of influence, the quality of governance depends on whether those holders act in the network’s long-term interest.
Beyond governance, the bigger idea behind OpenGradient is verification.
AI today is often judged by the quality of answers, but the next phase may require proving how those answers were created. The model, the execution environment, the data flow, and the final output all become part of the trust equation.
Maybe the future of AI is not only about smarter models.
Maybe it is about creating systems where we can verify what happened before we trust the result.
#opg $OPG @OpenGradient
$EVAA $BSB
I remember thinking that liquid staking had already solved most of the “yield versus liquidity” trade-off in crypto. The idea seemed clean: stake assets, keep a liquid receipt token, earn base yield. At first, I assumed that would be enough for most capital in proof-of-stake systems.
What changed my view was watching how quickly yield compression and incentive layering returned. Once base staking yields became predictable, capital started chasing stacked yield opportunities, often by reusing the same underlying collateral across multiple protocols. That’s where restaking models began to make more sense structurally.
Bedrock (BR) fits into this evolution as a multi-asset liquid restaking layer, extending beyond Ethereum into Bitcoin and DePIN-linked rewards. What caught my attention is not the yield itself, but the way it attempts to aggregate fragmented incentive markets into a single liquidity wrapper. In theory, this improves capital efficiency by allowing the same asset to participate in multiple security and reward regimes without forcing full withdrawal cycles.
The interesting part is how this changes operator behavior. If rewards depend on shared security assumptions across heterogeneous networks, then slashing risk, correlation risk, and reward volatility become deeply intertwined. This is where I think the market misses something: higher yield is often just compensation for hidden dependency risk across systems that were never designed to be composable.
As a trader, I’d spend more time watching net TVL stability, reward sustainability without emissions, and whether inflows persist after incentive adjustments. If liquidity is sticky only during incentive periods, the model may be more reflexive than durable.
#bedrock $BR @Bedrock
What changed my view was watching how quickly yield compression and incentive layering returned. Once base staking yields became predictable, capital started chasing stacked yield opportunities, often by reusing the same underlying collateral across multiple protocols. That’s where restaking models began to make more sense structurally.
Bedrock (BR) fits into this evolution as a multi-asset liquid restaking layer, extending beyond Ethereum into Bitcoin and DePIN-linked rewards. What caught my attention is not the yield itself, but the way it attempts to aggregate fragmented incentive markets into a single liquidity wrapper. In theory, this improves capital efficiency by allowing the same asset to participate in multiple security and reward regimes without forcing full withdrawal cycles.
The interesting part is how this changes operator behavior. If rewards depend on shared security assumptions across heterogeneous networks, then slashing risk, correlation risk, and reward volatility become deeply intertwined. This is where I think the market misses something: higher yield is often just compensation for hidden dependency risk across systems that were never designed to be composable.
As a trader, I’d spend more time watching net TVL stability, reward sustainability without emissions, and whether inflows persist after incentive adjustments. If liquidity is sticky only during incentive periods, the model may be more reflexive than durable.
#bedrock $BR @Bedrock
$AIN USDT is showing powerful bullish momentum with price up 4.9%, supported by a solid volume increase of 474.6%, indicating strong market participation and continued buyer interest. The asset is currently trading around 0.10448, with an impressive 41.6% gain in 24h, showing a strong upside trend but also increased volatility risk.
📍 Entry Zone: 0.10000 – 0.10500
🎯 TP1: 0.11200
🎯 TP2: 0.12000
🎯 TP3: 0.13500
🛡 SL: 0.09500
Support: 0.10000 / 0.09500
Resistance: 0.11200 – 0.12000
Momentum remains bullish, but after a strong 24h move, watch for pullbacks. A breakout above resistance with volume confirmation can fuel the next leg higher. 🔥📈
📍 Entry Zone: 0.10000 – 0.10500
🎯 TP1: 0.11200
🎯 TP2: 0.12000
🎯 TP3: 0.13500
🛡 SL: 0.09500
Support: 0.10000 / 0.09500
Resistance: 0.11200 – 0.12000
Momentum remains bullish, but after a strong 24h move, watch for pullbacks. A breakout above resistance with volume confirmation can fuel the next leg higher. 🔥📈
$PIEVERSE USDT is showing strong bullish momentum with price up 3.0%, supported by a major volume increase of 1276.3%, indicating rising market participation and strong buyer activity. The asset is currently trading around 0.6357, with a 6.6% gain in 24h, suggesting positive short-term structure and continuation potential.
📍 Entry Zone: 0.6200 – 0.6380
🎯 TP1: 0.6600
🎯 TP2: 0.7000
🎯 TP3: 0.7600
🛡 SL: 0.5950
Support: 0.6200 / 0.5950
Resistance: 0.6600 – 0.7000
Strong volume confirms momentum, but watch resistance carefully. A clean breakout with sustained buying pressure can push price toward higher targets. 🔥📈
📍 Entry Zone: 0.6200 – 0.6380
🎯 TP1: 0.6600
🎯 TP2: 0.7000
🎯 TP3: 0.7600
🛡 SL: 0.5950
Support: 0.6200 / 0.5950
Resistance: 0.6600 – 0.7000
Strong volume confirms momentum, but watch resistance carefully. A clean breakout with sustained buying pressure can push price toward higher targets. 🔥📈
$FIGHT USDT is showing a strong short-term recovery move with price up 5.1%, backed by a major volume surge of 1480.2%, indicating heavy market activity and increased trader interest. However, the asset is still down 13.9% in 24h, trading around 0.003821, showing that buyers are attempting a rebound after recent weakness.
📍 Entry Zone: 0.003700 – 0.003850
🎯 TP1: 0.004100
🎯 TP2: 0.004500
🎯 TP3: 0.005000
🛡 SL: 0.003450
Support: 0.003700 / 0.003450
Resistance: 0.004100 – 0.004500
High volume suggests a possible momentum shift. If buyers break resistance and maintain volume, recovery can extend further. Risk remains elevated due to the recent downside trend. 🔥📈
📍 Entry Zone: 0.003700 – 0.003850
🎯 TP1: 0.004100
🎯 TP2: 0.004500
🎯 TP3: 0.005000
🛡 SL: 0.003450
Support: 0.003700 / 0.003450
Resistance: 0.004100 – 0.004500
High volume suggests a possible momentum shift. If buyers break resistance and maintain volume, recovery can extend further. Risk remains elevated due to the recent downside trend. 🔥📈
$GENIUS USDT is showing a steady bullish attempt with price up 2.0%, supported by a strong volume increase of 671.6%, indicating rising market participation and potential momentum buildup. The asset is currently trading around 0.4695, with a 1.1% gain in 24h, suggesting buyers are gradually stepping in near current levels.
📍 Entry Zone: 0.4600 – 0.4720
🎯 TP1: 0.4850
🎯 TP2: 0.5100
🎯 TP3: 0.5500
🛡 SL: 0.4400
Support: 0.4600 / 0.4400
Resistance: 0.4850 – 0.5100
A breakout above resistance with continued volume strength can trigger the next bullish move. Momentum favors buyers while price stays above key support.
📍 Entry Zone: 0.4600 – 0.4720
🎯 TP1: 0.4850
🎯 TP2: 0.5100
🎯 TP3: 0.5500
🛡 SL: 0.4400
Support: 0.4600 / 0.4400
Resistance: 0.4850 – 0.5100
A breakout above resistance with continued volume strength can trigger the next bullish move. Momentum favors buyers while price stays above key support.
$PLAY USDT is facing heavy selling pressure with price down 6.22%, while volume has surged 1568.6%, showing intense market activity and strong volatility. The asset is currently trading around 0.0364, with a major 27.4% decline in 24h, indicating a bearish short-term structure but also possible oversold bounce opportunities.
📍 Entry Zone: 0.03500 – 0.03700
🎯 TP1: 0.03950
🎯 TP2: 0.04300
🎯 TP3: 0.04800
🛡 SL: 0.03300
Support: 0.03500 / 0.03300
Resistance: 0.03950 – 0.04300
Massive volume suggests a major battle between buyers and sellers. If support holds and buyers regain control, a recovery move can develop; otherwise, downside risk remains active.
📍 Entry Zone: 0.03500 – 0.03700
🎯 TP1: 0.03950
🎯 TP2: 0.04300
🎯 TP3: 0.04800
🛡 SL: 0.03300
Support: 0.03500 / 0.03300
Resistance: 0.03950 – 0.04300
Massive volume suggests a major battle between buyers and sellers. If support holds and buyers regain control, a recovery move can develop; otherwise, downside risk remains active.
$SPORTFUN USDT is showing strong bullish momentum with price up 3.9%, backed by an explosive volume increase of 4567.5%, indicating heavy market participation and rising trader interest. The asset is currently trading around 0.04997, with a solid 10.8% gain in 24h, suggesting buyers are pushing for further upside continuation.
📍 Entry Zone: 0.04800 – 0.05050
🎯 TP1: 0.05300
🎯 TP2: 0.05700
🎯 TP3: 0.06200
🛡 SL: 0.04550
Support: 0.04800 / 0.04550
Resistance: 0.05300 – 0.05700
Strong volume confirms momentum, but watch key resistance levels carefully. A breakout with continued buying pressure can open the path toward higher targets.
📍 Entry Zone: 0.04800 – 0.05050
🎯 TP1: 0.05300
🎯 TP2: 0.05700
🎯 TP3: 0.06200
🛡 SL: 0.04550
Support: 0.04800 / 0.04550
Resistance: 0.05300 – 0.05700
Strong volume confirms momentum, but watch key resistance levels carefully. A breakout with continued buying pressure can open the path toward higher targets.
$HEMI USDT is showing strong volatility with price down 4.42%, while volume has surged 1618.1%, indicating heavy market activity and aggressive buying/selling pressure. The asset is currently trading around 0.005686, down 7.4% in 24h, showing short-term weakness but with increased attention from traders.
📍 Entry Zone: 0.005500 – 0.005750
🎯 TP1: 0.006000
🎯 TP2: 0.006400
🎯 TP3: 0.007000
🛡 SL: 0.005200
Support: 0.005500 / 0.005200
Resistance: 0.006000 – 0.006400
High volume suggests a potential volatility move ahead. If buyers defend support and reclaim resistance, a recovery bounce can develop. Until then, caution remains as sellers hold short-term control.
📍 Entry Zone: 0.005500 – 0.005750
🎯 TP1: 0.006000
🎯 TP2: 0.006400
🎯 TP3: 0.007000
🛡 SL: 0.005200
Support: 0.005500 / 0.005200
Resistance: 0.006000 – 0.006400
High volume suggests a potential volatility move ahead. If buyers defend support and reclaim resistance, a recovery bounce can develop. Until then, caution remains as sellers hold short-term control.
$VELVET USDT is showing extremely strong bullish momentum with price up 6.0% intraday, supported by a notable volume increase of 488.5%, indicating aggressive market participation. The asset is currently trading around 0.86463, with a massive +132.8% gain in 24h, suggesting a powerful breakout and trend continuation phase.
📍 Entry Zone: 0.820 – 0.880
🎯 TP1: 0.950
🎯 TP2: 1.100
🎯 TP3: 1.350
🛡 SL: 0.760
Support: 0.820 / 0.760
Resistance: 0.950 – 1.100
Momentum is extremely strong but extended—watch for volatility and potential sharp pullbacks. As long as price holds above support, bullish continuation remains in play. 🔥📈
📍 Entry Zone: 0.820 – 0.880
🎯 TP1: 0.950
🎯 TP2: 1.100
🎯 TP3: 1.350
🛡 SL: 0.760
Support: 0.820 / 0.760
Resistance: 0.950 – 1.100
Momentum is extremely strong but extended—watch for volatility and potential sharp pullbacks. As long as price holds above support, bullish continuation remains in play. 🔥📈
$SKHYNIX USDT is showing steady bullish momentum with price rising 2.8%, supported by a strong volume increase of 851.1%, indicating active institutional-style participation and sustained buying interest. The asset is currently trading around 1428.68, with a 2.9% gain in 24h, suggesting a stable uptrend with controlled continuation.
📍 Entry Zone: 1385 – 1435
🎯 TP1: 1465
🎯 TP2: 1510
🎯 TP3: 1580
🛡 SL: 1350
Support: 1385 / 1350
Resistance: 1465 – 1510
If momentum continues with volume confirmation, price may extend toward higher resistance zones. Trend remains positive as long as structure holds above support. 🔥📈
📍 Entry Zone: 1385 – 1435
🎯 TP1: 1465
🎯 TP2: 1510
🎯 TP3: 1580
🛡 SL: 1350
Support: 1385 / 1350
Resistance: 1465 – 1510
If momentum continues with volume confirmation, price may extend toward higher resistance zones. Trend remains positive as long as structure holds above support. 🔥📈
$EDGE USDT is showing short-term bullish recovery within a broader weak structure. The price is up 2.8% intraday, supported by a strong volume surge of 1557.8%, indicating active market participation and possible reversal attempts. However, the asset is still down 3.2% in 24h, trading around 0.399, suggesting it is not fully out of corrective pressure yet.
📍 Entry Zone: 0.385 – 0.405
🎯 TP1: 0.420
🎯 TP2: 0.445
🎯 TP3: 0.480
🛡 SL: 0.372
Support: 0.385 / 0.372
Resistance: 0.420 – 0.445
If buyers maintain volume and reclaim resistance, a stronger reversal could develop. Otherwise, expect consolidation with volatility around key support. 🔥📊
📍 Entry Zone: 0.385 – 0.405
🎯 TP1: 0.420
🎯 TP2: 0.445
🎯 TP3: 0.480
🛡 SL: 0.372
Support: 0.385 / 0.372
Resistance: 0.420 – 0.445
If buyers maintain volume and reclaim resistance, a stronger reversal could develop. Otherwise, expect consolidation with volatility around key support. 🔥📊
Влезте, за да разгледате още съдържание