After peaking at a parabolic price of 300, ZECASH has been on a weighty downtrend for eons -- trimming down it's valuation every single month and coming back to ground to almost 10x from its peak.
Now, based on recent long term data metrics, ZEC is finally shifting massively after 2.5 years! That's a long wait! This shift is massive -- it's happening for a good reason.
As seen on diagram, we are seeing a bear clearance based on long term metrics. Bear dissolvement has been spotted this month, August -- for the first time in ages.
Net buying activity has surge exponentially from the current range signifying renewed interest, and buyers positioning on the enormous growth prospect of the coin.
The RR ratio of ZEC is too attractive to be missed at 8-10x.
The current bargain range is an ideal seeding area.
One of the few coins which boast a juicy RR from this corrective season.

Spotted at 40.0
Interim target at 120.0
Long term at 300.
TAYOR.

Trade active
Moving based on expectation.
Expect more weighty rise from here on.
Trade active
ZEC is looking solid based on recent movements -- and it's looking to make another upside ''checkmark'' soon as seen on this diagram
Trade active
Daily data update:

ZEC has retraced to a higher base after that overheated rise from a few weeks ago.
Not based on daily metrics, accumulated has re-started and a new round of ascend is in order now.
Spotted at 28.0

THIS IS RIPE.

to experience unreal returns
we plant a year ahead of the crowd
where the initial listing on CEX is simply a SHOW of SKILLS
and the Artificial Depression is a GiFT or simply
accommodation to friends and previous MOONBOYS

size you entries
and good luck
there are no bad coins
only bad entries

Here on $BTC btcusd price has form head and shoulder pattern and now try to go down so there is a chance of moving down if the line 59290 break and a trader should go for SHORT with profit target of 57520, 55539 and 53095 . Use money management
$BTC

Hi guys, this is my overview for BTCSDUT, feel free to check it and write your feedback in comments👊
Some time ago price entered to falling channel, where it declined to support line, breaking $63900 level.
BTC rose to resistance line and bounced down, breaking $57200 level, but then price started to grow in another channel.
In rising channel, BTC broke $57200 level and later rose to resistance line, which coincided with $63900 level.
Price made a little gap, and even later rose higher than $63900 level, but soon turned around and started to decline.
In a short time, BTC exited from rising channel, broke $63900 level, and continued to move down close resistance line.
I think that price can make small movement up and then continue to decline, between resistance line, to $57200 level.
If this post is useful to you, you can support me with like/boost and advice in comments❤️

Bitcoin is currently moving near the Resistance zone($62,860-$62,110) and 21_SMA(Weekly) and 200_SMA(Daily).
According to the Elliott wave theory, Bitcoin seems to be completing main wave 4. The structure of the main wave 4 appears to be an Expanding Flat Correction(ABC/3-3-5).
I expect Bitcoin to break down to the Support zone($60,000-$59,100) once again.
⚠️Note: Considering that the Trading Volume is usually low on Saturday and Sunday, it is more reasonable to expect the Support zone($60,000-$59,100) to break at the beginning of next week. Of course, the tension between Iran and Israel can change the scenario at any moment, and the support zone will be broken.⚠️
⚠️Note: If Bitcoin breaks the Resistance zone($62,860-$62,110) and 21_SMA(Weekly), we can expect the BTC pump to near $65,000.⚠️

Bitcoin Analyze (BTCUSDT), 4-hour time frame⏰.
Do not forget to put Stop loss for your positions (For every position you want to open).
Please follow your strategy and updates; this is just my Idea, and I will gladly see your ideas in this post.
Please do not forget the ✅' like'✅ button 🙏😊 & Share it with your friends; thanks, and Trade safe.

Good night my dear reader, I have an important analysis for you today. This is likely the final warning before a major crash, a long-term bearish continuation move.
Bitcoin produced a failed signal when it failed to stay above MA200 recently in late September. This major resistance level is confirmed by the fact that Bitcoin closed five sessions/candles below it.
If you are having doubt about Bitcoin's next move, let it go, you do not need it; it is going down.
If you are having hope about Bitcoin moving up before moving down, let it go, it is a waste of time and energy and it soon can turn out into a waste of money if you are positioned in any way that isn't bearish.
The market is going down, Bitcoin is going down and I am here to warn before the event happens. I am here as a beacon of light to guide your soul in a very important moment. I hope to be able to be of service to you.
The chart is bearish in so many ways. The bearish bias shown on this chart is confirmed in so many ways, where to start?
The DXY is bullish and this has an inverse relation with Bitcoin. Tether Dominance (USDT.D) is also bullish and this too moves contrary to Bitcoin.
The geopolitical situation is quite messed up right now and this puts bearish pressure on the market.
The FED is cutting interest rates after years of rising interest rates. When this happens, the market tends to crash.
There is a presidential election in the USA. The market tends to be 100% bullish after the election. Before the elections it can be quite shaky.
All the major stocks, the world giants, peaked recently and some even in July and have already confirmed lower highs, which means that they have been dropping for more than two months.
Bitcoin has been going down for almost 7 months and is about to reach the climax of the corrective phase, a.k.a., a massive crash.
Bitcoin's last bullish wave, from November 2022 through March 2024, lasted a total of 16 months. While the entire growth phase was super long, most of the growth happened in just a few months. In the last three. It took almost seven months of consolidation to produce these three months of growth.
The bearish consolidation has been going for 6.5 months. The meat of the bearish move can happen fast and strong just as it happened with the meat of the bullish move. Long consolidation before bullish breakout, long consolidation before bearish breakdown.
If you are spot, simply a holder, this might not be a big deal because it will all be over in a matter of months. But if you are doing leverage, just keep in mind that recently more than 600M worth of LONG positions were liquidated and the whales are getting ready to liquidate twice as much. Are you going to be in that pack? I don't know.
The chart is bearish and Bitcoin is going down.
I am telling you so.
You don't have to belief me of course, just look at the chart.
You can corroborate all the data points that I just shared.
This is all unbiased technical analysis, with a high level of success.

Thank you for reading.
You are appreciated.
Your comments are welcomed.
Post anything that comes to your mind... We want to read what you have to say.

I love you.
Namaste.

There Is a Bull Flag By The Clear ABC Structure Formed At The Chart And The Price Breakout From The Trend Line By The Strong Valid Candle, Expect a Impulsive Move To The 0.5440$ As a Next Scalp Target

Bitcoin is ready to go higher! I expect Bitcoin to hit 64,000 - 63,500 USDT in the immediate short-term for the following reasons:

The falling wedge is breaking out, the price is now above the main trendline, and the downtrend is exhausted. My Elliott Wave count suggests that we have completed the corrective pattern WXYXZ (triple three). Bitcoin created 2 major FVG (fair value gaps) above the current price. Usually these gaps tend to be filled pretty quickly, so be ready for the bull price action!The 200 1H MA (simple moving average) needs to be tested as well. We saw a breakout of this MA, but never seen a retest of it.October is statistically an extremely profitable month for Bitcoin, so this gives us a statistical advantage.
Bitcoin is currently the most bullish coin from the high-cap category. Altcoins are not performing well, why? For this, we need to look at the BTC.D (Bitcoin Dominance) chart. I expect BTC.D to go up to 60%. After that, we should see an alt season!
Write a comment, and please hit boost and follow for more ideas. Trading is not hard if you have a good coach! This is not a trade setup, as there is no stop-loss or profit target. I share my trades privately. Thank you, and I wish you successful trades!

Bitcoin holders have faced a tough market in recent months, but the longer-term outlook offers hope. The price appears to be forming bullish patterns like a cup and handle or an inverse head and shoulders. A break of the trend line at $74,000 could trigger a surge toward $127,000.

In the short term, Bitcoin is stuck in a bull flag. To push higher, the price needs to break above $66,670 or $69,293. These levels are crucial, as breaking them may ignite the larger cup and handle breakout, signaling a strong upward move.

What is your take on BTC?
This content is not directed to residents of the EU or UK. Any opinions, news, research, analyses, prices or other information contained on this website is provided as general market commentary and does not constitute investment advice. ThinkMarkets will not accept liability for any loss or damage including, without limitation, to any loss of profit which may arise directly or indirectly from use of or reliance on such information.

🚀 DOT/USDT is rebounding, and a clear long opportunity is presenting itself! 🔥 I won’t go into too much detail—just check the chart and let me know what you think.
$DOT #DOTUSD

Here we have a classic reversal sequence. Notice the consolidation pattern (black) that leads to a breakdown (blue), this is normally followed by a trend reversal.

Filecoin (FILBTC) hit bottom and is very likely to turn soon, really soon.

We are seeing all the signals that support this conclusion. A very strong bullish divergence with the RSI, since April 2024. The exact same with the MACD.

We can also see the strong rise in trading volume before the breakdown phase. This also indicates that buyers were anxious to enter the game since early 2024. The breakdown is the market owners taking up liquidity but after this breakdown the potential for a bullish wave strengthens.

We are likely to see FILBTC grow next.

Thank you for reading.

Namaste.
$FIL #Filecoin/USDT

On the above weekly chart price has enjoyed a massive 3000% rally. A number of reasons now exist to be bearish. They include:

1) Broken market structure, failed support.
2) Trend reversal.
3) High negative divergence. Almost as strong as the positive divergence the rally began with.
4) The target areas for support include 60% and 80% correction to $8 and $5, respectively.
5) This should take about 1 year to play out.

Is it possible price action continues printing higher lows? Sure.
Is it probable? No.
Ww
Trade active
Nothing has changed that would void this idea. A few message asking.

We are easily hooked on the dopamine rush of seeing profitable equity curves during backtesting. The allure of parabolic returns is often so strong it is blinding to the inherent flaws that exist, to varying degrees, in every backtest.
Backtesting, while often seen as an essential step in designing and verifying trading strategies - is far from a foolproof method. Many traders place too much confidence in their backtested results, only to see their strategies fail when used in the live markets. The reality is that backtesting is riddled with limitations and biases that lead to a false sense of security in a strategy’s effectiveness. Let’s take a comprehensive look into the many flaws of backtesting, and explore the common pitfalls of using a simple back test as your only method of verifying a strategy's efficacy.
1. Choosing the Winning Team After the Game is Already Over
(Selection Bias)
When selecting which instruments for backtesting, it is common to choose assets you are already interested in or those that performed well in the past. This introduces selection bias, as the strategy is tested on assets that may have been outliers. While this may produce impressive backtest results, it creates an illusion of reliability that may not hold up when applied to other assets or future market conditions - a theme that will be common for most of the explored backtesting drawbacks.
Example:
Imagine backtesting a Long only strategy using only tech stocks that surged during a market boom. The strategy might look incredibly successful in the backtest, but when applied to other sectors or different market phases it will most likely fail to perform - because the selection was based on past winners rather than a broader, more balanced approach.

2. You Only See the Ships that Make it to Shore
(Survivorship Bias)
Similar to the above, survivorship bias occurs when backtests only include assets that have survived of the test period - excluding those that were delisted, went bankrupt, or failed entirely. This creates a skewed dataset, inflating performance metrics beyond reasonable levels once again. By only focusing on assets that are still around, you overlook the fact that many others didn’t make it - and these failures could have significantly impacted the strategy’s results. By ignoring delisted companies, or rug-pulled crypto projects, you inherently induce a selection bias - as purely because your chosen instruments didn’t go to zero they must have performed better.
Example:
Suppose you backtest a low-cap cryptocurrency strategy. If your backtest spans for, say, five years the test can give the illusion of success - but what’s missing is the hundreds of tokens that were launched and failed during the same period. How can we possibly assume that we will be lucky enough to only pick tokens that survive the next five years?
3. Reading Tomorrow’s News Today
(Look-Ahead Bias)
Look ahead bias occurs when future information is unintentionally used in past decision making during a backtest. This can often occur due to coding errors in an automated system which leads to unreasonable and unrepeatable results. Look-ahead bias isn’t limited to algorithmic backtesting - it can also affect manual backtests. Traders will often miss false signals because they can already see the outcome of the trade. This knowledge of the future can affect the accuracy of a manual backtest - both as a conscious decision by the trader but also subconsciously.

if Current_Price < Tomorrows_Close
strategy.entry("Enter a Long Position", strategy.long)

4. Perfecting the Final Chord, but Forgetting the Song
(Recency Bias)
Recency bias occurs when traders place too much emphasis on the most recent data or market conditions in a backtest. This usually occurs when a trader feels they missed an opportunity in the past few months - and tries to develop a strategy that would have captured that specific move. By focusing too heavily on recent history, it is easy to neglect the fact that markets usually move in long cyclical phases. This over optimisation for recent conditions will, at best, result in a strategy that performs well in the short term but fails as soon as market dynamics shift.
Example
Frustrated by missing the most recent leg of the bull market, a trader develops a strategy that would have perfectly performed during this period. However, when the trader begins live trading at the top of the market, the strategy quickly fails. It was only optimized for that short and specific market phase and was unable to adapt to the changing market conditions.
5. Forcing the Square into the Round Hole
(Overfitting)
Overfitting occurs when a strategy is excessively optimized for historical data, capturing noise and random fluctuations rather than meaningful patterns. Overfitting is common when traders test too many parameter combinations, tweaking their strategy until it fits the past data perfectly. In contrast to the previous point, this over optimisation can occur on data of any length, whether years or even longer periods.
Example
Adjusting a large range of parameters in a high frequency strategy by incredibly small increments and deciding to use the calibrations that yield the highest performance.

6. Mixing Oil and Water
(Conflating Trend and Mean Reversion Systems)
Traders often attempt to design strategies that perform well in both trending and mean reverting environments, which leads to muddled logic and poor performance in ALL environments. A trend following strategy is meant to capitalize on sustained price movements, and should naturally underperform during mean-reverting or ‘ranging’ periods. In a range-bound market, a trend-following strategy will often buy near the top of the range after detecting strength, only for the price to reverse. Conversely, a mean reversion strategy is built to profit from oscillations around a stable point and forcing both approaches into a single system results in unrealistic backtest performance and poor real-world results.
One of the common mistakes is when a trend following strategy ‘accidently’ performs well during mean-reverting periods. This skews the backtest metrics because any gains during non-trending markets are multiplied significantly during actual trends. As a result, the backtest shows artificially positive performance - but the strategy quickly falls apart in live trading. Normally, a trend following strategy would incur losses during a range-bound market and only begin to recover once a new trend emerges. However, if a strategy is overfit to handle both the trend and mean reversion periods of the past, it doesn’t need to recover losses and instead compounds gains during the entire trend. This creates inflated backtest results that won’t hold up in real trading.
Example:
A trader develops a trend following system that, through over-optimization, performs surprisingly well during mean-reversion phases. In the backtest, the strategy shows strong returns, even in ranging markets. However, in live trading, the system fails, leaving the trader with poor performance. Instead, the trader should have accepted ‘lower’ returns from a strategy that wasn’t overfit - because in live markets robust strategies with mediocre backtests perform better than overfit strategies that only excel in backtesting.
7. Seeing the World Through a Keyhole
(Limited Data Skewed by Outliers)
Strategies built on assets with limited data are highly susceptible to skew results, especially when outliers dominate the dataset. Without sufficient data, it becomes nearly impossible to assess whether a strategy can consistently perform into the future. Some strategies, like trend following, are designed to capture outliers, that is, the periods of performance above the norm. The issue arises when testing on a small sample as it’s difficult to determine if the strategy can consistently capture trends or just got lucky.
Example:
A trader develops a trend following strategy for a cryptocurrency that has recently launched. The backtest shows massive gains, as it is common for projects to make large returns as soon as they are listed. However without enough data history, it is impossible to assess the actual effectiveness of this strategy, as its performance metrics are positively skewed by the ‘listing pump.’

The image shows a cryptocurrency project launched in October 2020. At first glance, the EMA Crossover strategy appears profitable, but a closer look reveals that most of the profit comes from the first trade, which is considered an outlier. If that trade was removed, the strategy as a whole would become unprofitable. Following this strategy is essentially betting on the project to experience another sharp rise similar to what occurred in 2020. While technically this isn’t impossible, it is much riskier - a more proven and verified strategy would increase your probability of success.
8. Designing a Car that Doesn’t Fit on the Road
(Execution Constraints and Positions Sizing)
In backtesting, real world constraints such as minimum or maximum order sizes are often ignored, leading to unrealistic trade execution. Traders may find that they either don’t have enough capital to satisfy the minimum order size - either immediately or after a small drawdown. Additionally, compounded returns on a backtest can lead to absurd positions sizes that could never be bought or sold in the real market. This particularly is more problematic for deep backtestests.
Example:
A backtest shows spectacular growth, with the account size ballooning overtime and resulting in an extremely high profit percentage. However, in real-word conditions, the required position size to continue executing the strategy becomes so large that it exceeds the liquidity of the market - making it impossible to receive comparable profit percentages on real world trading.

9. Death by a Thousand Paper Cuts
(Not Accounting for Fees, Commissions and Slippage)
When performing a backtest, traders often overlook critical transaction costs such as fees, slippages and spreads. These seemingly small costs can accumulate and significantly erode profits, especially strategies that rely on frequent trades with a low average return per trade. Slippage also should include execution slippage - the time delay between receiving a signal from a system, placing an order and its execution. This is particularly problematic for lower timeframe trading where even minor delays can drastically swing a strategy from profitable to unprofitable
Example:
A day trader runs a backtest on a scalping strategy and sees parabolic returns. However in live trading, the small profits from each trade are wiped out by broker commissions, spreads and the slippage that occurs from both position sizing, and when trades are executed slightly later than expected. This strategy, while successful in the backtest, failed to account for the ‘death by a thousand paper cuts.’

10. Filling Half of the Grocery Cart
(Partial Order Fills)
In low liquidity environments, or when trading large position sizes, partial order fills are common - meaning traders only get a portion of their order executed at their desired price. This can significantly impact returns. Backtests will usually assume complete fills at the exact target price. However, in reality a trader experiencing a partial order fill must decide whether to complete the position at a worse price or leave a portion of the target position size out of the market. Both choices will lead to results that are not comparable to the backtested results.
Example:
A trader places a limit order to buy 100 shares of a low-liquidity stock at a price of $10. The order is only partially filled, with 60 shares bought at $10, while the remaining 40 shares require the new, higher price. The trader now faces the choice of paying more, or leaving part of the trade out. This is a major deviation from the backtest, which assumed the complete position was bought at $10.
11. Betting on Lightning Striking Twice
(Black Swan Events)
Black swan events are rare, inherently unpredictable, and have a significant impact on financial markets. Strategies designed to avoid drawdowns during these events are at risk of being overfit. Traders often fall into the trap of building systems that avoid drawdowns during past black swan events - overfitting their strategies to these rare occurrences. These strategies are unlikely to succeed in regular market conditions and contain no extra edge in protecting a trader from future black swans events.Example:
After the FTX collapse caused a sharp drop in crypto prices, a trader chooses to develop a swing trading strategy designed to avoid all losses during this event. However, by optimizing the strategy to exit positions before the collapse, the trader unintentionally overfits it. As a result, the strategy begins to sell off positions too early in other situations, cutting profits short. Prior to the FTX collapse, the market was still in an uptrend, and there were no clear signs of an impending downturn - so attempting to optimize for such a rare event ends up compromising the strategy’s performance in more typical market conditions.

12. Expecting a Weeks Pay After Only Working One Shift
(Time of Day and Day of Week Restrictions)
Many traders are only able to trade during specific hours or days of the week, yet their backtests often include data from periods where they are unavailable - such as overnight sessions. This creates an unrealistic expectation of returns. For example, in markets like crypto that trade 24/7, backtesting a day trading strategy on the full market period gives a false impression of potential profits if you can only trade during certain hours. Additionally, market participants also differ depending on the time of day, as entire countries wake up and go to sleep at different times of day. One could make the assumption that human behavior as a whole might be the same, but the number of participants and liquidity will definitely change.
Example:
A day trader backtests a strategy using 24/7 crypto market data - but is only able to trade on weekday afternoons due to other commitments.
13. Siphoning Gas from a Moving Car
(Capital Drain and Addition)
Backtests frequently assume infinite compounding, where no capital is ever added or withdrawn from the trading account. In practice, however, traders will regularly add or remove funds - which significantly impacts the performance of a strategy. For instance, withdrawing money during a drawdown forces the strategy to work harder to recover losses, as it now requires higher returns to break even. Similarly, adding capital can skew results by altering position sizing. While it is necessary to manage capital in this way, backtests usually don’t account for these changes and once again, leads to results that are not repeated in practice.
Example:
A trader consistently pulls a portion of profits from their account each month. In the backtest, no withdrawals are considered, and the strategy appears highly profitable. However, in live trading these regular withdrawals put pressure on the account, and especially over longer periods of time, this reduced level of compound will lead to significant underperformance relative to the backtest due to the reduced compounding effect on returns.
14. Your Subscription Service Increase Price Without You Realizing
(Interest Rates and Funding Costs)
The ‘cost of capital’ - such as leverage costs, interest rate and funding fees - can fluctuate over time, but backtests often overlook these dynamic costs or even fail to account for them altogether. In live markets, these changes can significantly erode profit margins. Not considering these costs, especially the factors affecting their variability, can easily turn a profitable backtest into an unprofitable strategy in live trading.Example:
A trader backtests a strategy for use in cryptocurrency perpetual futures. The strategy is designed for bull markets but fails to account for the rising funding rates frequently seen during periods of high demand. As the cost to maintain an open position skyrockets, the trader’s profit margins quickly shrink, making the strategy far less viable than the backtest indicated. This is particularly dangerous because as the funding fees erode the position’s margin, the liquidation price rises faster than expected, potentially resulting in the entire position being liquidated - even though the trade appeared profitable on paper.
15. You Can’t Ride the Wave Past the Shore
(Alpha Decay)
In highly competitive markets, especially in high-frequency trading, the edge of a strategy (alpha) can erode over time as more participants exploit similar inefficiencies. This gradual loss of profitability - known as alpha decay - often isn’t captured in backtesting, which assumes static market conditions. Alpha decay is particularly relevant in high-frequency trading, where competition and frontrunning are more intense, while it tends to be less of an issue in higher time-frame swing trading.

16. Playing Chess Against Yourself and Expecting to Win Every Time
(Psychological Factors)
Psychological biases still affect fully systematic traders. The assumption that traders will follow their strategy without hesitation or emotional interference rarely holds true in live trading, especially during periods of drawdown or high volatility. Manual and automated traders alike feel the same compulsion after experiencing drawdown. The temptation to tweak or abandon a strategy during this period is strong and often leads to the worst decision. It is well documented anecdotally that many traders find that after modifying a ‘losing’ strategy, the new version performs worse than the original, as it has been adjusted to avoid the losses of the past and misses future gains by virtue of overfitting.Example:
An algorithmic trader watches as their automated strategy experiences a significant drawdown. Panicking, the trader tweaks the parameters in order to avoid further losses. Shortly after, the original strategy would have recovered, but the modified version continues to struggle as the adjustments were made in reaction to short term losses instead of accounting for long term performance.
Final Note:
Congratulations if you made it this far! This might not be the most exciting topic, but it’s essential knowledge for every trader and investor. This article was written to warn you of the dangers of relying on backtests - and provides a checklist of common pitfalls to watch out for. Whether you’re running your own backtest or reviewing someone else’s, it’s critical to look beyond the shiny numbers and assess the real-world viability. What looks great on paper may not hold up in the real world.

Best of luck in the markets - but remember: stay prudent, and you’ll make your own luck!

Sorry, I'm going to start shorting

Sell now:
TP59800
TP55710
TP52800
TP50678
SL64000

Bitcoin recently completed a harmonic pattern near the 66,500 level.
The initial price reaction was positive, increasing the likelihood of the beginning of a bearish movement. This harmonic pattern adds more weight to the bearish scenario we are considering.

However, from a different perspective, BTC has been making significant upward and downward moves. When we refer to past movements, BTC is currently in a similar area.

I am looking for profit-taking opportunities near strong zones where the price has previously reacted, specifically around 59,800; 55700; and 52,800. And 50600

Good luck to you

Forecasting a pullback to 50k, as i expect the out of the ordinary volume on 08/05/24- 15min, hourly, 4hr, & daily, to gravitate price back towards it; high volume candles are very likely to get backfilled due to orderbook instability- see yellow fib lines for source and measurement. This is not bearish. This is important for bitcoin to conquer this level as she gears to move higher. There are many things i cant fully articulate in my charts so if you have any questions let me know.

Yello Paradisers! 🚨 If #TONUSDT corrects lower, we could see a potential bounce from the identified demand zones. But for this to happen, we need confirmation.

💎TONUSDT needs to display a Change of Character (I-CHoCH) on the lower time frames, which would shift the structure to a bullish outlook and strengthen the likelihood of a bounce from this zone.

💎If the price falls below the initial zone, it could drop to our stronger demand area below. Don’t forget that there’s a supportive trendline in this region, which could act as an inducement for price. To validate this setup, look out for bullish patterns like a W pattern, Inverse Head and Shoulders, or signs of bullish divergence—these will make it a higher probability move to the upside.

💎However, if we see a strong candle close below these levels, it would invalidate this setup, and we would need to reassess the scenario. Remember, TON is fundamentally solid, so the focus should be on high-probability long setups. Patience and precision are key here, Paradisers!

Stay strategic and wait for the best opportunities—consistency is what sets the pros apart from the rest.

MyCryptoParadise
iFeel the success🌴
#ton

The price perfectly fulfilled my previous idea. It hit the target level. On the daily timeframe,
has been in a consolidation phase between support and resistance since August. Recently, a triangle pattern formed at the top of the range zone before the price dropped, likely influenced by the downturn in
Currently, the price is approaching the psychological level of 2300, which has historically been respected multiple times. Additionally, the market is making lower highs and higher lows, indicating a narrowing price action. If the price approaches the 2300 level and shows signs of rejection, such as increased buying pressure, I expect a bounce off this support level. My target is resistance zone around 2525

Traders, if you liked this idea or if you have your own opinion about it, write in the comments. I will be glad 👩‍💻

JASMY is forming a falling wedge on Daily timeframe , Up we go if we do breakout. the price can be bullish and I expect the price to go up to the Fibonacci line of 0.618 = 0.027 Stay tuned for more updates, thanks.

✨We spend hours finding potential opportunities and writing useful ideas, we would be happy if you support us.
Best regards CobraVanguard.💚
_ _ _ _ __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
✅Thank you, and for more ideas, hit ❤️Like❤️ and 🌟Follow🌟!
⚠️Things can change...
The markets are always changing and even with all these signals, the market changes tend to be strong and fast!!

we are in a strong resistance for #BTC_DOMINANCE so we have to expect reversal from here
& If this happened means.......

1. we are in #altcoins bottoms
2. #altcoins season is coming so soon
3.it is the right time to invest in #altcoins not #BTC

*********** This is my expectation for next weeks **********
******( MAY BE I AM COMLETELY WRONG, PLEASE DO YOUR OWN PLANS ) *******
#BTCUSDT

#bitcoin #BTC
#Investingcoins #Crypto_investing

hello guys.

I see a double hunt!

you can get a long position as a scalp one!

___________________________

✓✓✓ Always do your research.
❒❒❒ If you have any questions, you can write them in the comments below, and I will answer them.
❤︎ ❤︎ ❤︎And please don't forget to support this idea with your likes and comment