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EUR/USD - High Probability Trade SetupLooking at this chart price is appearing Bearish but I have other beliefs. As you can see on a Monthly TF you can notice a clear Elliots Wave 1-5 Pattern Followed by this current breakout. Typically Liquidity will sit higher and will remain untouched after breakout as shows in this graph, I believe we have seen a large swing point being at a Phycological Level and now on smaller time frames we are seeing Bullish movements. To confirm this Theory on the Daily we have noticed the previous Bullish movment took out Swing High Liquidity and is extremely Oversold. Price will be falling but to where..? We have creating a Change Of Character and unless this changes im now looking for Buy positions. We are creating Higher Highs in the 4H and breaking previous structure points. On the Chart I have market out key levels being OTE zones, Discount areas and Liquidity all being lower than the current price suggesting this pullback period will inverse this imbalance before pushing us into Higher Highs once again Will be adjusting our Entry Models as price action moves Good Luck to all Traders who follow along
Long
by jamesibartram
1
Gold Breaks $2725 Resistance, Eyes Record HighGold is peeking above resistance at $2725, extending the bullish trend in place since late December. If it can push above this level and preferably close there, it creates a decent bullish setup, allowing for longs to be established above with a tight stop beneath for protection. The obvious target would be the record high of $2790 set in late October. Momentum indicators such as RSI (14) and MACD are trending higher, providing bullish signals that improve the probability of the break sticking. With price signals from US Treasury futures pointing to the possibility of lower yields near-term, a scenario that could also keep dollar gains capped, the macro environment looks more conducive for upside than periods in the recent past. Good luck! DS
FOREXCOM:XAUUSDLong
by FOREXcom
1
#ZECUSDT #1h (ByBit) Falling broadening wedge breakoutZcash regained 50MA support and broke out bullish on hourly, looks good for short-term recovery towards 200MA resistance and more. ⚡️⚡️ #ZEC/USDT ⚡️⚡️ Exchanges: ByBit USDT Signal Type: Regular (Long) Leverage: Isolated (10.0X) Amount: 4.8% Current Price: 49.41 Entry Targets: 1) 48.62 Take-Profit Targets: 1) 52.63 Stop Targets: 1) 46.61 Published By: @Zblaba $CRYPTO:ZEC BYBIT:ZECUSDT.P #Zcash #Privacy z.cash Risk/Reward= 1:2.0 Expected Profit= +82.5% Possible Loss= -41.3% Estimated Gaintime= 2-3 days
Long
by TradingOn
1
I need objective information to help me interpret the chart Hello, traders. If you "Follow", you can always get new information quickly. Please click "Boost" as well. Have a nice day today. ------------------------------------- With this decline, the BW(100) indicator was created at 104556.23. Accordingly, the high boundary section is the 101947.24-104556.23 section. Unfortunately, since it fell below 101947.24, the key is whether it can receive support near the MS-Signal (M-Signal on the 1D chart) indicator, i.e., around 98892.0, and rise. If it falls below the MS-Signal (M-Signal on the 1D chart) indicator and shows resistance, it is highly likely to turn into a short-term downtrend. - The settings for the StochRSI indicator I use are 14, 7, 3, 3 (RSI, Stoch, K, D). The source value is ohlc4. If you set it as above, it will show a movement similar to the StochRSI indicator on my chart. When the StochRSI indicator - falls in the overbought zone, - is located near the 50 point, - rises in the oversold zone, volatility is likely to occur. However, you should check whether there is support near the support and resistance points drawn on the 1M, 1W, and 1D charts and think of a corresponding response plan. Therefore, by checking the relationship between the movement of the StochRSI indicator and the support and resistance points drawn on the 1M, 1W, and 1D charts, you can choose the point where you can make a trade. If you can calculate these selection points, I think it is highly likely that you will be able to create a trading strategy that suits your investment style. It is good to predict future movements with trends or waves, but if you can calculate the point where you can actually make a trade, I think you can create a better trading strategy. - I wrote a long article, but 1. Will the StochRSI indicator fall in the overbought zone? 2. Will it receive support near the MS-Signal (M-Signal on the 1D chart) indicator? 3. Will it rise to the high boundary section? You should focus on the three things above. --------------------------------- The method of drawing support and resistance points is drawn according to the arrangement of candles. This method can actually include subjective thoughts, so it requires skill. Therefore, if possible, I recommend that you sign up as a paid member of TradingView and share my charts with me, and use the HA-High, HA-Low, BW(100), BW(0), OBV, +100, -100 indicators that appear on 1M, 1W, and 1D charts by the HA-MS_BW+v2 indicator as horizontal lines and use them as support and resistance points. Then, even if others look at the charts, they will be easier to understand, and it will be easier to share opinions on trading strategies according to each other's investment styles. By utilizing indicators that anyone can use in this way, you will be able to view the charts objectively. If you trade based on what others tell you, you will likely not be able to respond quickly when sudden volatility occurs. Therefore, when creating a trading strategy, you should roughly think about how to respond to all cases, both when it goes up and when it goes down. That's why it's best to draw support and resistance points or other reference materials on your chart if possible and prepare countermeasures accordingly. - Thank you for reading to the end. I hope you have a successful trade. --------------------------------------------------
Education
by readCrypto
RUS 2000 | Market Crash AheadDetailed analysis in regards to my latest video. Comparing RUS to the general markets we can see that SPX is overperforming which can be used as a leading indicator to prepare for a possible crash to come most likely mid year Q2 - Q4 and bleeding into 2026. I also added DJT to the mix and it also is underperforming to what the SPX is doing now days. What does this mean for crypto? We can see BTC attempt to make one more leg to the upside, no more than $300k and at least a 100% runup from current levels ~($108k). Altcoins will most likely look to rip Q2 - Q3 as BTC.D struggles to run any higher. DXY is also at a structural low ~(100) and will look to finish its goal to hit ~120. My original call since 2021 was to see BTC hit $300k by 2025 - 2026. We'll see if price action surprises me! My SPX call in 2023 also gladly hit $6,000..we'll see whats next to come👀
FX:US2000
by Nathanl19
Will Solana (SOL) Reach $1000? Positive Momentum Beyonds Memes Solana (SOL), known for its high transaction speeds and low fees, has experienced periods of significant growth and equally dramatic pullbacks. The question on many investors' minds is whether SOL can reach the ambitious target of $1000. While key technical indicators point to positive momentum, the network faces challenges that extend beyond the fleeting influence of meme hype. This article examines the factors influencing Solana's price trajectory, weighing its potential for significant growth against the hurdles it must overcome. Technical Indicators Paint a Bullish Picture (For Now) Currently, several technical indicators suggest positive momentum for SOL. The price consistently holding above both the 50 and 200-day moving averages is a bullish sign. These moving averages are widely used by traders to identify trends, with the 50-day MA representing short-term momentum and the 200-day MA indicating the long-term trend. When the price is above both, it suggests a healthy uptrend. Other technical indicators, such as Relative Strength Index (RSI) and Moving Average Convergence Divergence (MACD), can provide further insights. If the RSI is trending upwards without reaching overbought levels (typically above 70), it suggests growing buying pressure. A bullish crossover on the MACD (where the MACD line crosses above the signal line) can also signal a potential price increase. However, relying solely on technical analysis can be misleading. While these indicators can identify trends, they don't account for fundamental factors like network performance, adoption, and competition. Beyond Meme Hype: Fundamental Strength and Adoption Solana's initial surge in popularity was partly fueled by meme coins and NFT projects built on its blockchain. While this generated significant interest and trading volume, it also created a perception of Solana being driven by hype rather than fundamental value. For SOL to reach $1000, it needs to demonstrate sustainable growth based on real-world adoption and utility. Several factors contribute to Solana's fundamental strength: • High Transaction Speed and Low Fees: Solana's architecture allows for significantly faster transaction processing and lower fees compared to networks like Ethereum. This makes it attractive for decentralized applications (dApps) requiring high throughput, such as decentralized finance (DeFi) platforms and NFT marketplaces. • Growing Ecosystem: Despite facing challenges, Solana's ecosystem continues to grow, with new projects and developers building on the network. This expansion is crucial for attracting users and driving demand for SOL. • Technological Advancements: Ongoing development and upgrades to the Solana network aim to improve its stability, scalability, and security. These advancements are essential for addressing past network outages and building trust among users. Challenges and Roadblocks Despite the positive momentum and fundamental strengths, Solana faces significant challenges: • Network Stability: Solana has experienced several network outages in the past, raising concerns about its reliability. Addressing these issues and ensuring network stability is crucial for attracting institutional investors and mainstream adoption. • Competition: Solana faces intense competition from other layer-1 blockchains like Ethereum, Cardano, and Avalanche. These networks are also developing and improving their technology, making it challenging for Solana to maintain its competitive edge. • Negative Perception: The past network outages and association with meme coin hype have created a negative perception of Solana in some parts of the crypto community. Overcoming this perception and building trust will be a key challenge. • Coinbase Withdrawal Delays: The recent criticism of Coinbase for delays in processing Solana withdrawals is a concerning development. Such issues can erode user confidence and negatively impact the network's reputation. While Coinbase has its own operational issues and this may not be solely a Solana problem, it still reflects poorly on the overall user experience. The $1000 Target: A Realistic or Distant Dream? Reaching $1000 would require a significant increase in Solana's market capitalization. This would necessitate widespread adoption of the network, sustained growth in its ecosystem, and overcoming the existing challenges. While the current technical indicators are positive, they are not a guarantee of future price appreciation. The success of Solana depends on its ability to: • Maintain Network Stability: Addressing network outages and ensuring consistent uptime is paramount. • Attract Developers and Users: Growing the ecosystem with innovative dApps and attracting a larger user base is crucial. • Overcome Negative Perception: Building trust and addressing concerns about network reliability is essential for mainstream adoption. • Compete Effectively: Staying ahead of the competition in the rapidly evolving blockchain landscape is vital. Conclusion Solana has the potential for significant growth, driven by its technological advantages and growing ecosystem. However, reaching the ambitious target of $1000 is a challenging task. While positive momentum is evident in current technical indicators, the network faces significant hurdles, including network stability issues, competition, and negative perception. Overcoming these challenges and demonstrating sustainable growth based on real-world utility will be crucial for Solana to achieve its full potential. The recent Coinbase withdrawal delays highlight the importance of smooth user experience and operational efficiency for any blockchain network aiming for mass adoption. Investors should carefully weigh these factors before making investment decisions.
COINBASE:SOLUSDLong
by bryandowningqln
combined guide for both the **Regime Classifier** and **kNN Here’s the combined guide for both the **Regime Classifier** and **kNN (k-Nearest Neighbors)** indicators with emojis, tailored for your TradingView chart description: --- ### **🔑 Individual Lesson Steps** #### **Lesson 1: What is a Regime Classifier?** 👽 **Defining Market Regimes** - A **market regime** refers to distinct market conditions based on price behavior and volatility. - **Types of Market Regimes:** - 🚀 **Advance** (Uptrend) - 📉 **Decline** (Downtrend) - 🔄 **Accumulation** (Consolidation) - ⬆️⬇️ **Distribution** (Topping/Bottoming Patterns) 👾 **Why it Matters:** - Identifying market regimes helps traders tailor their strategies, manage risk, and make more accurate decisions. --- #### **Lesson 2: Anatomy of the Regime Classifier Indicator** 👽 **Core Components** - **Median Filtering:** Smooths out price data to capture significant trends. - **Clustering Model:** Classifies price trends and volatility into distinct regimes. - **Volatility Analysis:** Analyzes price volatility with rolling windows to detect high and low volatility phases. 👾 **Advanced Features:** - **Dynamic Cycle Oscillator (DCO):** Tracks price momentum and cyclic behavior. - **Regime Visualization:** Color-coded display of market conditions to make trends and patterns clearer. --- #### **Lesson 3: Configuring the Regime Classifier Indicator** 👽 **Customization Settings** - **Filter Window Size:** Adjusts sensitivity for detecting trends. - **ATR Lookback Period:** Determines how far back the volatility is calculated. - **Clustering Window & Refit Interval:** Fine-tunes how the indicator adapts to new market conditions. - **Dynamic Cycle Oscillator Settings:** Tailors lookback periods and smoothing factors. 👾 **Why It’s Useful:** - Customizing these settings helps traders optimize the indicator for different trading styles (e.g., scalping, swing trading, long-term investing). --- #### **Lesson 4: Using the Indicator for Regime-Based Trading Strategies** 👽 **Adapt Strategies Based on Regimes** - **Advance Regime:** Focus on long positions and trend-following strategies. - **Decline Regime:** Prioritize short positions or hedging strategies. - **Accumulation Regime:** Watch for breakout opportunities. - **Distribution Regime:** Look for trend reversals or fading trends. 👾 **Using the Dynamic Cycle Oscillator for Confirmation:** - 🌡️ **Overbought/Oversold Conditions:** Identify potential reversals. - 🔄 **Trend Momentum:** Confirm if the trend is gaining or losing strength. --- #### **Lesson 5: Combining Volatility and Price Trends for High-Confidence Trades** 👽 **Interpreting Volatility Clusters** - 🔥 **High Volatility:** Indicates caution, risk management, or hedging opportunities. - 🌿 **Low Volatility:** Suggests consolidation or trend continuation. 👾 **How Volatility Clusters Interact with Price Trends:** - Combine trend direction with volatility analysis to refine trade entries and exits for more precise decisions. --- #### **Lesson 6: Backtesting and Live Application** 👽 **Validate Using Historical Data** - Guide traders on **backtesting** strategies using historical data to see how the indicator would have performed. 👾 **Real-Time Application:** - Implement the Regime Classifier in **live markets** to monitor ongoing price conditions and gain actionable insights. --- ### **🔑 kNN (k-Nearest Neighbors) Indicator Lesson Steps** #### **Lesson 1: What is kNN?** 👽 **Defining kNN** - **k-Nearest Neighbors** is a machine learning algorithm that makes predictions based on the proximity of data points. - It identifies the nearest neighbors of a data point and classifies it according to the majority class of those neighbors. 👾 **Why it Matters:** - **kNN** helps traders forecast price movement, trends, and potential reversals by analyzing historical data. --- #### **Lesson 2: Anatomy of the kNN Indicator** 👽 **Core Components** - **Training Data:** Historical price data used to identify the neighbors of a point. - **Distance Metric:** Determines the closeness of data points (e.g., Euclidean distance). - **k Parameter:** The number of nearest neighbors to consider for predictions. 👾 **Advanced Features:** - **Distance Calculation:** Helps assess how similar current price movement is to historical patterns. - **Prediction:** The majority of the nearest neighbors determines the expected price movement (up or down). --- #### **Lesson 3: Configuring the kNN Indicator** 👽 **Customization Settings** - **k (Number of Neighbors):** Adjust to control how many historical data points influence predictions. - **Distance Metric:** Choose from Euclidean, Manhattan, or other metrics based on data characteristics. - **Window Size:** Defines how many data points (e.g., time periods) are used for analysis. 👾 **Why It’s Useful:** - Tuning these settings allows traders to adjust the sensitivity and precision of predictions, optimizing for various trading styles. --- #### **Lesson 4: Using the kNN Indicator for Predictive Trading Strategies** 👽 **Predicting Price Movements** - Use **kNN** to identify trend directions and price reversals based on historical proximity. - **Uptrend Prediction:** Identify moments where the nearest neighbors suggest a continuation of the trend. - **Downtrend Prediction:** Signal when the majority of neighbors point toward price decline. 👾 **Using Predictions to Enhance Trade Entries:** - Use **kNN** signals in conjunction with **Regime Classifier** regimes to validate and enhance entry and exit points. --- #### **Lesson 5: Combining kNN Predictions with Regime Classifier for Precision** 👽 **Refining Trade Confidence** - Cross-reference **kNN predictions** (uptrend/downtrend) with **Regime Classifier’s** regime identification for higher precision trades. - **Example:** If **kNN** predicts an uptrend and the **Regime Classifier** signals an **Advance** regime, you can confidently go long. --- #### **Lesson 6: Backtesting and Live Application** 👽 **Validate Predictions with Historical Data** - Backtest using **kNN** on past price data to measure accuracy in predicting trends and reversals. - **Real-Time Application:** Implement **kNN** in live markets alongside **Regime Classifier** for comprehensive decision-making. --- ### **🔄 Combined Lessons for Advanced Mastery** #### **Combo 1: Regime Identification and kNN Predictions for Strategy Optimization** 💡 **Objective:** Combine market regime identification with kNN predictions to refine trading strategies. - Merge **Lesson 1 (Understanding Regimes)** and **Lesson 1 (What is kNN?)**. - **Practical Exercise:** Use both indicators to identify regimes and predict price trends in live charts. --- #### **Combo 2: Customization, Practical Usage, and Enhanced Predictions** 💡 **Objective:** Equip traders to fine-tune both indicators for their unique strategies. - Merge **Lesson 3 (Settings Configuration for Regime Classifier)** and **Lesson 3 (kNN Indicator Configuration)**. - Walkthrough: Customize settings and combine both indicators to predict price trends and adjust strategies accordingly. --- #### **Combo 3: Comprehensive Trading Strategy with Regime Classifier and kNN** 💡 **Objective:** Build a full-fledged trading system using both indicators for market regime analysis and predictive signals. - Combine **all lessons** for a complete, systematic trading approach: - 🔍 **Identify market regimes** - 🔄 **Use kNN predictions** to assess potential price movements - 📈 **Combine with Dynamic Cycle Oscillator** for entry/exit timing - 💥 **Execute trades** with a comprehensive strategy --- These lessons and combos provide traders with the essential tools to master both the **Regime Classifier** and **k-Nearest Neighbors** indicators, from understanding the fundamentals to implementing advanced strategies and refining predictions for more accurate market analysis.
Education
by bencryptoknight
Trend Identifier Indicator This is my Trend Identifier Indicator, the most affordable among all my paid indicators. Take a look at its performance on BTC—it’s simple yet highly effective. It’s designed to be user-friendly, making it ideal for beginners as well as experienced traders. Here’s how it works: • Green indicates a Buy Signal. • Red indicates a Sell Signal. • Gray represents a Sideways Market. For added clarity: • An “S” with a black dot in the gray zone indicates a sideways market. • An “S” in red with a red background clearly indicates a sell signal. • Buy signals are straightforward and highlighted in green. As you can see, the indicator beautifully captures the market trends. It removes confusion by visually separating buy, sell, and sideways signals, ensuring you know exactly what action to take. Its performance speaks for itself—it’s doing its job exceptionally well! If you’re interested in subscribing to this indicator, message me for more details. Thank you!
by TradeTechanalysis
MARKET ANOMALY DETECTOR (MAD) - PAID INDICATORThe Market Anomaly Detector (MAD) indicator displayed in the chart appears to effectively capture potential tops and bottoms based on price and momentum conditions. Here’s a detailed textual summary of its performance: Key Observations from the Chart: 1. Capturing Bottoms: • The green zones and buy signals (marked with green labels) align closely with areas where the price reverses from downward trends, indicating that the MAD indicator successfully detects oversold conditions or areas of bullish divergence. • The confluence of the green shaded areas with the lower bounds of the volatility bands further supports the accuracy of the buy signals in identifying trend reversals. 2. Identifying Tops: • The red zones and sell signals (marked with red labels) correspond to local peaks where the price reverses from upward trends. This suggests that the MAD indicator effectively detects overbought conditions or bearish divergence. • The sell signals also tend to align with price closing above the upper volatility band, highlighting the MAD’s ability to identify overextensions in price. 3. Z-Score and RSI Filters: • The Z-Score values and RSI thresholds displayed in the chart (e.g., Z-Score: 0.77, RSI: 52.77) appear to act as reliable filters to validate signal accuracy. • These additional parameters help the indicator avoid false signals in sideways markets by ensuring that trends are well-defined before signals are generated. 4. Trend Detection and Cooldown: • The indicator employs background shading (green for bullish trends, red for bearish trends, and grey for sideways markets) to provide a clear visual representation of the overall market structure. • A cooldown mechanism appears to prevent excessive signals in choppy or low-volatility conditions, making the signals more actionable and reducing noise. 5. Support for Reversal Strategies: • The MAD indicator excels in detecting early signs of trend reversals. By combining divergence-based logic with volatility and momentum filters, it helps traders identify actionable entries and exits. Effectiveness in Capturing Tops and Bottoms: • The MAD indicator demonstrates high precision in aligning buy signals with significant lows and sell signals with notable highs. • The visual clarity of the shaded regions and the confluence of signals with volatility bands make it particularly useful for trend-following or counter-trend strategies. • While the indicator is highly effective, minor lag in signal generation might occur due to the reliance on confirmations from momentum and volatility parameters. This trade-off enhances reliability but may slightly delay entries in fast-moving markets. Improvements for Enhanced Accuracy: • Fine-tuning Z-Score and RSI thresholds could improve responsiveness to extreme conditions. • Adding additional filters, such as volume or time-of-day considerations, may help reduce false signals further in low-volume conditions. Conclusion: The MAD indicator performs exceptionally well in detecting tops and bottoms, leveraging a combination of momentum, volatility, and trend analysis. It is highly suited for traders looking for actionable buy/sell signals while maintaining a balance between accuracy and noise reduction. Message me to know more about getting this indicator.
Short
by TradeTechanalysis
ADA/USDT Long Trade Plan: Leveraging Dow Theory and Fibonacci ReThe trade plan for ADA/USDT leverages Dow Theory and Fibonacci retracement principles, aiming to enter at the 0.382 retracement level (1.0593) within a confirmed uptrend. The stop loss is placed below the last lower low at 0.8783 to minimize risk in case of a trend reversal. The take profit target is calculated at 1.2403, offering a 1:1 reward-to-risk ratio. This setup aligns with the market's higher highs and higher lows structure, ensuring an entry at a key support level while maintaining strict risk management and a favorable trade outlook.
Long
by Naqash16046
ETHENA - Identifying a trend shift using RSI, MACD, EMA and DivFirst post of 2025 to start the new year Journaling and using Basic tools Offered by Tradingview. The most Common Used by traders are RSI MACD and EMA's. I am going use these indicators with descriptors of what I came to understand after reading the "About script" and applying them to my trade Ideas to see If I can correctly Identify Strength and Weakness in markets. I have plotted out on the charts what the use cases are for these tools. RSI, MACD and EMA's are momentum Indicators, They are not used to identify where a reversal will happen but over a period of time where you can see trend start to shift or continue trending based on the Information they provide.
CRYPTO:ENAUSDLong
by Iamthebomb
3
Trade Idea Week 20 Jan 2025: EURUSDBullish Thesis Key Drivers: The EUR/USD remains in a long-term bearish trend in the 4-hour timeframe, characterised by lower highs and lower lows. However, recent price action shows signs of consolidation around a critical support zone near 1.0250–1.0280, presenting opportunities for both upward retracements and continued downward moves. Indicators like the MACD suggest weakening bearish momentum, while the ADX shows a weak trend environment, implying traders would focus on key levels for directional triggers. Eurozone Economic Data: Improved PMI readings (forecasted above 50 for services) may signal resilience in the Eurozone economy, potentially boosting EUR sentiment. ECB President Lagarde's Speech: Any hints of future hawkish monetary policy could support the EUR. Entry: 1.0280 Target TP1: 1.0320 Extended Target: 1.0340 (Weak High from 4-hour chart) Stop Loss: Below 1.0250 to protect against a breakdown of support. Risk/Reward: 1:2 Bearish Thesis Key Drivers: The long-term bearish trend remains dominant, making the 1.0340–1.0380 resistance zone a strong candidate for selling opportunities. Price action in this area aligns with the broader trend, and bearish rejections are likely to signal further downside. Entry: Between 1.0320–1.0340 Target TP1: 1.0280 (short-term support) Extended Target: 1.0250 (next demand zone on higher timeframe) Stop Loss: Below Above 1.0360 to guard against a breakout above the strong resistance. Risk/Reward: 1:2 Key Events: Tuesday (Jan 21): German ZEW Sentiment Data: Monitor the release for unexpected positive or negative surprises. UK Employment Data: Indirect EUR movements may occur due to the EUR/GBP pair correlation. Wednesday (Jan 22): ECB President Lagarde's speech. Hawkish tones could favor the bull thesis, while dovish comments could strengthen the bear thesis. Trade Ideas are for informational purposes only.
Long
by Shiven_80eight
Iron Ore: Momentum Builds, 200DMA in SightIron ore futures have seen a decent rally over the past fortnight, rebounding from below $100 a tonne on strong volumes to take out downtrend resistance dating back to early December before going on with the move. The price is now testing a zone that includes minor horizontal resistance at $102.25 and downtrend established in October when Chinese markets were rollicking along in peak stimulus mode. With momentum indicators firmly with the bulls, traders should be alert for a potential extension of the rally. If we see the price push above this zone, longs could be established with a stop beneath for protection. The 200-day moving average looms as a potential target with $107.30 the next after that. Take note of how poorly the price has traded above the 200-day moving average over recent months. As such, if the price action falters around this level again, those seeking the higher target may want to reconsider the merits of the trade. Good luck! DS
SGX:FEF2!Long
by FOREXcom