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EURUSD trade ideas

EUR/USD 21.07.25EUR/USD: Uptrend Continues — Targeting 1.1859** Market Overview: EUR/USD has bounced off the 1.1570–1.1540 support zone, confirming the integrity of the uptrend. The pair remains inside a rising channel and is approaching key resistance on the D1 level. Technical Signals & Formations: — EMA(144) on 8H acts as dynamic support — Key support at 1.1570–1.1540 held strong — Bullish momentum targets the 1.1859 resistance (D1) — Bullish candlestick pattern formed on rebound Key Levels: Support: 1.1570, 1.1540 Resistance: 1.1859 (D1) Scenario: Primary: continuation toward 1.1859 Alternative: if 1.1540 breaks, possible retracement to 1.1450
Long
by DENOLLAFINANCERU
EURUSD - M15 Supply Zone RetestThe current price action shows that the market is expected to first fill the Fair Value Gap (FVG) area, which acts as a price inefficiency zone demanding liquidity clearance. After the FVG is filled, the price is anticipated to retest the Higher Time Frame (HTF) Supply Zone, which serves as a strong resistance area. Following the retest of the supply zone, the prevailing downtrend is likely to resume, pushing the price downwards towards the HTF Demand Zone. This demand zone is identified as a key support level where buying interest is expected to emerge, potentially halting the decline temporarily or initiating a reversal. This trading plan emphasizes waiting patiently for the FVG fill as a prerequisite step before looking for a supply zone retest confirmation to enter short positions targeting the demand zone below, aligning with the overall bearish trend continuation.
Short
by famousone_chn
EURUSD - Bullish Bias with Tactical Short Setup• Pair: EURUSD • Bias: Bullish overall | Tactical short into demand • HTF Overview (4H): • Bullish structure confirmed. • Price took out SSL liquidity — likely draw is internal structure OB below. • Expecting deeper pullback before continuation. • MTF Refinement (30M): • Looking for price to sell off into 4H OB. • Price already mitigated 30M OB and rejected — watching for follow-through. • LTF Confirmation (5M): • Still in analysis mode — waiting on a CHoCH from 5M OB. • Green lines on chart reflect 5M internal structure. • Entry Zone: • Enter short only after 5M shift confirms. • Ride short into 4H OB demand zone. • Targets: • Short-term: 30M lows. • Major: 4H OB for bullish reaction. • Mindset Note: • No rush to enter — analysis leads, execution follows. • Let price deliver confirmation before switching to trader mode. Bless Trading!
Short
by Juicemannn
DXY was looking for More Liquidity to sweepIt appears that the DXY was searching for more liquidity before continuing its decline. There are good buying areas for the EURUSD, as the liquidity swept to the bottom, and the immediate rebound indicates the strength of this area and can be considered a buying zone. This area coincides with the 61 Fibonacci support line, confirming the possibility of an upside move. The GBPUSD was targeting the bottom to trigger a liquidity sweep on the weekly timeframe. This is also an SMT signal, but it is somewhat weak, but it confirms the complete vision of the analysis.
Long
by Mr_Liquidity1
The Ineffectiveness of Day Trading: A Critical Review of EmpiricThe Allure of Quick Profits Day trading has gained considerable popularity as an investment strategy among retail investors, particularly following technological advances in electronic trading platforms and commission-free brokerage services. This analysis examines the available empirical evidence from various markets and time periods to evaluate the economic viability of day trading as an investment strategy. The most comprehensive study on the subject comes from Barber et al. (2011), who analyzed the behavior of over 360,000 day traders in Taiwan. Their results show that over 80 percent of day traders lose money, and less than 1 percent can achieve consistently profitable results. These findings align with similar studies from other markets and confirm the systematic unprofitability of day trading for the vast majority of participants. Day trading represents a systematically unprofitable investment strategy for retail investors, rooted in cognitive biases (Kahneman & Tversky, 1979), excessive transaction costs, and market microstructure inefficiencies (O'Hara, 1995). Long-term passive investment strategies demonstrate superior risk-adjusted returns with significantly lower resource requirements. What the Research Shows The research landscape on day trading is clear and consistent across various markets. A systematic review of the most important studies follows established standards of financial market research. The inclusion criteria for relevant studies encompass empirical investigations with substantial sample sizes (more than 1,000 traders), minimum observation periods of 12 months, and quantitative performance measures. The available literature is based on millions of trading accounts from various developed markets. The historical development of day trading shows clear parallels to technological developments in the financial sector. Before deregulation through Electronic Communication Networks by the SEC in 1997, it was impossible for retail investors to trade directly in the market. With the rise of online brokers like E*TRADE and Ameritrade, day trading became accessible to the mass public for the first time. This technical opening coincided with aggressive marketing that promoted free trades, low fees, and success stories of individual traders. Empirical Findings Evidence from various markets shows consistent patterns. Barber et al. (2011) document that 84.3 percent of 360,000 analyzed day traders in Taiwan suffered losses, with a median return of minus 8.7 percent. Similar studies from the United States confirm loss rates exceeding 90 percent of participants. Jordan and Diltz (2003) conclude that even experienced day traders are hardly able to beat the market after costs in the long term. The long-term results are even more sobering: only a fraction of all day traders remain profitable over extended periods, while a significant portion abandons the activity within two years. The transaction cost analysis is based on realistic market conditions. A calculation example illustrates the structural challenges: with an assumed daily trading volume of $50,000 and eight round trips per day, substantial costs arise from commissions (approximately 0.1% per trade), bid-ask spreads (averaging 0.02-0.05%), and market impact (about 0.01% for smaller volumes). Annual Cost Calculation Example: - 252 trading days × 8 trades = 2,016 trades/year - Commission costs: 2,016 × $2.50 = $5,040 - Spread costs: $50,000 × 0.03% × 2,016 = $30,240 - Total costs: approximately $35,000 or 70% of daily trading volume This cost structure means that day traders must achieve gross returns of well over 70 percent annually just to break even, while passive investors bear annual costs of only 0.1 to 0.3 percent (Bogle, 2007). Behavioral Analysis and Cognitive Biases Behavioral research explains why day trading remains attractive despite poor success prospects. Odean (1999) shows that overconfident investors trade excessively and thereby reduce their expected returns. The disposition effect documented by Shefrin and Statman (1985) leads traders to realize gains too early and hold losses too long. Kahneman and Tversky's (1979) Prospect Theory explains systematic biases in decision-making under uncertainty. Loss aversion leads to losses weighing psychologically heavier than equivalent gains, resulting in irrational holding of losing positions. The gambler's fallacy manifests in the erroneous assumption of many day traders that past losses make future gains more likely. Recency bias leads to overweighting recent events. These psychological factors reinforce each other and create a vicious cycle of irrational decisions. Comparative Analysis: Day Trading versus Passive Strategies A comparison with established investment strategies illustrates the systematic disadvantages of day trading. Malkiel (2011) documents long-term returns of diversified portfolios at 6-8 percent real, while Barber and Odean (2000) show that frequent trading systematically reduces returns. Historical data shows that the S&P 500 Index achieved an average annual return of 10.2 percent with 15.8 percent volatility over 30 years (Sharpe ratio: 0.65). Day traders, in contrast, typically exhibit negative Sharpe ratios as losses dominate amid high volatility. The time investment differs dramatically: day trading requires 40-50 hours of weekly attention, while passive investing demands less than one hour per week. Studies also show health burdens from the constant stress of active trading. Market Microstructure and Professional Trading Market structure systematically favors institutional players. High-frequency trading firms possess latency advantages in the microsecond range, while retail traders operate with delays exceeding 100 milliseconds. They utilize co-location services and process data volumes inaccessible to private investors. Market-making operations profit from bid-ask spreads and exchange rebate programs. They operate under different regulatory frameworks and have access to dark pools and proprietary technology. Day trading mathematically represents a zero-sum game that becomes negative after costs. Since the sum of all trading gains and losses equals zero, but transaction costs are positive, the expected return for all participants collectively is necessarily negative. Alternative Investment Strategies Academic literature comprehensively documents the superiority of passive strategies. Bogle (2007) demonstrates through long-term data that low-cost index funds consistently achieve better net returns than active strategies. Passive Strategy Calculation Example: An investment of €10,000 in a low-cost ETF (0.15% TER) with 7% annual returns yields approximately €37,000 after 20 years. To achieve this result, day traders would need to consistently earn over 15% gross returns after costs—a scenario that is empirically nearly impossible. Factor-based investing offers additional improvements: Fama and French (1992) documented excess returns for value and size factors that are systematically and cost-effectively accessible. Limitations of the Evidence The research landscape has certain constraints. Survivorship bias in datasets may underestimate actual losses, as unsuccessful traders disappear from samples more quickly. Additionally, definitions of day trading vary between studies. External validity is influenced by changing market structures. Algorithmic trading and new financial instruments may alter established patterns. Nevertheless, the fundamental problems of high costs and systematic behavioral biases persist. Conclusion The empirical evidence is clear: day trading represents a loss-making activity for the vast majority of participants. The combination of high transaction costs, systematic behavioral biases, and structural market disparities makes consistent profitability nearly impossible. While isolated success stories exist, they represent statistical outliers rather than replicable strategies. The scientific evidence speaks unequivocally in favor of long-term, low-cost, and diversified investment strategies as superior alternatives to day trading. Those who nonetheless engage in day trading should be aware that they are not only competing against the market, but against mathematical and psychological realities that practically preclude a high probability of success. References Barber, Brad M., Yi-Tsung Lee, Yu-Jane Liu, and Terrance Odean. "Do Individual Day Traders Make Money? Evidence from Taiwan." *Review of Financial Studies* 24, no. 8 (2011): 2892-2922. Barber, Brad M., and Terrance Odean. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors." *Journal of Finance* 55, no. 2 (2000): 773-806. Bogle, John C. *The Little Book of Common Sense Investing*. Hoboken: Wiley, 2007. Fama, Eugene F., and Kenneth R. French. "The Cross-Section of Expected Stock Returns." *Journal of Finance* 47, no. 2 (1992): 427-465. Jordan, Douglas J., and J. David Diltz. "The Profitability of Day Traders." *Financial Analysts Journal* 59, no. 6 (2003): 85-94. Kahneman, Daniel, and Amos Tversky. "Prospect Theory: An Analysis of Decision under Risk." *Econometrica* 47, no. 2 (1979): 263-291. Malkiel, Burton G. *A Random Walk Down Wall Street*. 10th ed. New York: Norton, 2011. Odean, Terrance. "Do Investors Trade Too Much?" *American Economic Review* 89, no. 5 (1999): 1279-1298. O'Hara, Maureen. *Market Microstructure Theory*. Oxford: Blackwell Publishers, 1995. Shefrin, Hersh, and Meir Statman. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence." *Journal of Finance* 40, no. 3 (1985): 777-790.
Education
by EdgeTools
EUR/USD Daily Chart Analysis For Week of July 18, 2025Technical Analysis and Outlook: In the current trading session, the Euro has continued its decline, completing our Mean Support level of 1.160. Recent analyses indicate that the Euro is likely to experience a sustained downward trend, with an anticipated retest at the Mean Support level of 1.159 and a possible further decline to reach a Currency Dip of 1.152. Nevertheless, it is crucial to consider the potential for a dead-cat bounce toward the Mean Resistance level of 1.167, which could trigger a significant reversal of the downtrend and target a Currency Dip of 1.152.
by TradeSelecter
EURUSD: Bears Are Winning! Short! My dear friends, Today we will analyse EURUSD together☺️ The market is at an inflection zone and price has now reached an area around 1.16557 where previous reversals or breakouts have occurred.And a price reaction that we are seeing on multiple timeframes here could signal the next move down so we can enter on confirmation, and target the next key level of 1.16419..Stop-loss is recommended beyond the inflection zone. ❤️Sending you lots of Love and Hugs❤️
Short
by FreeXauusdSignals
EURUSD / Euro – U.S. Dollar (4H) – ABC Bullish Structure EURUSD / Euro – U.S. Dollar (4H) – ABC Bullish Structure with Double Bottom Base Pattern Overview: Pattern Type: ABC Bullish + Corrective Double Bottom Asset: EURUSD Timeframe: 4H Trade Type: Bullish Bias – Monitoring for continuation after rejection from cluster support 🔎 Key Levels XA: 1.14663 → 1.18299 AB: 1.18299 → 1.16292 BC: 1.16292 → 1.17216 CD: Completion just under 1.15621 cluster Major Fib Cluster: 0.707% XA, 0.886 AB, 50% CD, Prior Horizontal Support Zone 📐 Fibonacci Extensions & Key Ratios 38.2% retracement: 1.16180 50.0% retracement: 1.15750 161.8% extension: 1.18150 💡 Price Action & Setup Price has completed an ABC corrective leg, forming a clean double bottom at the D point, hovering over the fib-rich support cluster. The rejection candle shows buyer interest, and the recent higher low structure implies potential for continuation, especially if price reclaims and holds above 1.1650 short-term structure. 🧠 Market Sentiment DXY easing slightly after strong dollar dominance EUR macro calendar quiet – technicals may dominate next moves Strong base = smart money accumulation likely underway 📊 Next Potential Movement Break above 1.1675 opens path toward 1.1720, then possibly 1.1815 If 1.1575 cluster fails → risk of full XA retracement 🛡 Risk Management Aggressive long entries already in play Conservative entries should wait for higher low confirmation above 1.1650 Protective stop: under 1.1550 zone 📌 Conclusion This is a bullish structure with a corrective double bottom base sitting right inside a dense confluence zone. Price is compressing between key fibs – expect a directional move next week. Keep your eye on the 1.1675 breakout or 1.1570 loss for next major decision. “In the densest zones of indecision, patterns and confluence provide the clearest map.”
Long
by TradeChartPatternsLikeThePros