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Introduction: Technological advancements continue to reshape markets, with artificial intelligence (AI) dominating headlines in recent years. However, the next major frontier appears to be quantum computing. The ratio between the quantum computing sector NASDAQ:QTUM and technology AMEX:XLK provides a unique perspective on this emerging trend. Analysis: Key Breakout: The QTUM-to-XLK ratio has recently broken out of a rounding bottom formation, a classic bullish reversal pattern. This breakout signals growing investor enthusiasm and capital flow into quantum computing, suggesting it may be the next major growth story in tech. Higher Highs and Higher Lows: The ratio is printing a series of higher-highs and higher-lows, confirming a bullish trend. As long as this structure remains intact, quantum computing warrants serious attention. Healthy Consolidation: After the recent surge, a pause or slight pullback would be a healthy consolidation within the broader uptrend. Such moves often precede the next leg higher. Implications for Investors: The breakout highlights quantum computing's increasing importance and potential. This sector could mirror the early stages of AI adoption, suggesting substantial long-term growth opportunities for QTUM-related investments. Trade Setup: Bullish Scenario: Entry: Look for pullbacks to support levels or a continuation of higher-highs for confirmation of trend strength. Target: Watch for the ratio to continue trending upward, signaling outperformance of QTUM over XLK. Stop Loss: Place stops below recent lows to manage risk in case of a deeper correction. Bearish Scenario: A breakdown below the trendline or failure to print higher-highs would signal potential weakness, warranting caution. Conclusion: Quantum computing is emerging as the market’s next big focus, with the QTUM-to-XLK ratio breakout suggesting robust momentum in the sector. While a pullback could offer better entry opportunities, the long-term growth story for quantum computing remains compelling. Are you ready for the quantum revolution? Let’s discuss in the comments below! Charts: (Include charts showing the QTUM-to-XLK ratio breakout, the rounding bottom formation, and key levels of support and resistance. Highlight the trendline and any recent consolidation zones.) Tags: #QuantumComputing #Technology #QTUM #XLK #EmergingTrends #TechnicalAnalysis #GrowthInvesting
The price perfectly fulfilled my last idea. It hit the target. OKX:TONUSDT is currently showing a pattern of lower highs and higher lows, indicating that price action is narrowing down, which often suggests a potential breakout. As observed, the market is oscillating between the 5.00 and 6.00 levels, having taken liquidity below the psychological level of 5.00 twice. This may imply that the market is building a range below the 6.00 mark before making a move higher. Given that the price has respected the support level multiple times, I expect it to bounce off this level. If this support holds above it, we could see a gradual move higher, possibly starting in the beginning of next year. My goal is resistance zoen around 6.40 https://www.tradingview.com/chart/TONUSDT/Sx73afUX-Lingrid-TONUSDT-in-DEEP-Correction-Phase/ Traders, if you liked this idea or if you have your own opinion about it, write in the comments. I will be glad ??
https://www.tradingview.com/x/HAO7EmYI/ Take a look at our analysis for SILVER. Time Frame: 12h Current Trend: Bearish Sentiment: Overbought (based on 7-period RSI) Forecast: Bearish The market is approaching a significant resistance area 29.812. Due to the fact that we see a positive bearish reaction from the underlined area, I strongly believe that sellers will manage to push the price all the way down to 28.778 level. P.S The term oversold refers to a condition where an asset has traded lower in price and has the potential for a price bounce. Overbought refers to market scenarios where the instrument is traded considerably higher than its fair value. Overvaluation is caused by market sentiments when there is positive news. Like and subscribe and comment my ideas if you enjoy them!
//@version=4 study("Channel, Triangle, and Flag Patterns with MTF Channel", shorttitle="CTF Patterns MTF", overlay=true) // Multi-Timeframe Channel Parameters higher_timeframe = input("60", title="Higher Timeframe") len = input(20, title="Channel Length") src = close // Higher Timeframe Channel Calculation high_channel_htf = security(syminfo.tickerid, higher_timeframe, highest(src, len)) low_channel_htf = security(syminfo.tickerid, higher_timeframe, lowest(src, len)) plot(high_channel_htf, color=color.red, linewidth=2, title="Upper Channel Line (HTF)") plot(low_channel_htf, color=color.green, linewidth=2, title="Lower Channel Line (HTF)") // Current Timeframe Channel Calculation high_channel = highest(src, len) low_channel = lowest(src, len) plot(high_channel, color=color.red, linewidth=1, title="Upper Channel Line") plot(low_channel, color=color.green, linewidth=1, title="Lower Channel Line") // Triangle and Flag Patterns pivot_high = pivothigh(src, 5, 5) pivot_low = pivotlow(src, 5, 5) triangle_pattern = (pivot_high and pivot_low and high < high and low > low ) flag_pattern = (pivot_high and pivot_low and high > high and low < low ) // Plot Patterns plotshape(series=triangle_pattern, location=location.belowbar, color=color.blue, style=shape.labelup, text="Triangle") plotshape(series=flag_pattern, location=location.abovebar, color=color.orange, style=shape.labeldown, text="Flag") // Alerts for Patterns alertcondition(triangle_pattern, title="Triangle Pattern", message="Triangle pattern detected") alertcondition(flag_pattern, title="Flag Pattern", message="Flag pattern detected")
https://www.tradingview.com/x/rQedSgP1/ Please, check our technical outlook for EURUSD. Time Frame: 12h Current Trend: Bearish Sentiment: Overbought (based on 7-period RSI) Forecast: Bearish The market is on a crucial zone of supply 1.040. The above-mentioned technicals clearly indicate the dominance of sellers on the market. I recommend shorting the instrument, aiming at 1.025 level. P.S We determine oversold/overbought condition with RSI indicator. When it drops below 30 - the market is considered to be oversold. When it bounces above 70 - the market is considered to be overbought. Like and subscribe and comment my ideas if you enjoy them!
MFFL on daily TF, price has started to move downwards. It is following Cypher pattern and 93% chances are that it will follow it till price drops to 193~195. Additionally, RSI has also dipped close to 60 level and still going downwards. KVO also is dipping downwards but still above zero line; as soon as Blue line downwards crosses Green line price will start to drop sharply. If KVO dips below zero then selling pressure will be enormous. Therefore, a cautious approach should be followed while getting in to it. My recommendations would be to buy at dip of 193 and that too after analyzing it again as it may even slip to 120~130. Alternatively, buying after it crosses 290 will be better approach as then it will be in the next bull run leg. TPs are calculated on Fib based Ext tool. Trade Values have been marked on the chart.
The issue arises when you rely solely on a webhook as your exit strategy, especially in scenarios like today's with NMDC. TradingView’s webhook mechanism, while efficient for many tasks, can create havoc if used indiscriminately for entries, exits, or modifications without human oversight. Today, NMDC is generating a cascade of signals—short, long, SL hit, TGT hit, and more—because the platform hasn’t yet adjusted for the stock split properly. Algorithms dependent on such incomplete or inaccurate data can spiral into a disaster, executing trades based on flawed inputs. This is a clear reminder to always validate your data sources and integrate fallback mechanisms to avoid such pitfalls. Moreover, this kind of situation can lead to reverse signals that algorithms tuned for mean reversion might latch onto, seeing the seemingly favorable risk-reward (Rr) ratio. However, because the source data lacks significant market influence, the resulting trades could prove inconsequential or even misleading. The broader market may ignore such anomalies, leaving your algorithm chasing shadows. This highlights the importance of understanding market psychology and herd behavior. Traders often move in predictable patterns, and seemingly unrelated factors can trigger unexpected market reactions. For example, Berkshire Hathaway’s stock once saw price spikes correlating with the release of Anne Hathaway’s movies—not because of any fundamental connection, but due to name-based algorithmic trading. Such quirks underscore the need to approach automated trading with caution, ensuring a robust system that accounts for anomalies and prevents over-reliance on any single data source or strategy.