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SYMBOL
LAST
BID
ASK
HIGH
LOW
NET CHG.
%CHG.
SPREAD
SOURCE
SPX
S&P 500 Index
7500.57
7500.57
7500.57
7511.07
7468.32
+80.46
+ 1.08%
--
--
DJI
Dow Jones Industrial Average
51564.69
51564.69
51564.69
51949.26
51554.53
+72.15
+ 0.14%
--
--
IXIC
NASDAQ Composite Index
26517.94
26517.94
26517.94
26559.74
26188.69
+496.30
+ 1.91%
--
--
USDX
US Dollar Index
100.480
100.480
100.560
100.870
100.450
-0.110
-0.11%
--
--
EURUSD
Euro / US Dollar
1.14646
1.14646
1.14725
1.14803
1.14176
+0.00079
+ 0.07%
--
--
GBPUSD
Pound Sterling / US Dollar
1.32275
1.32275
1.32387
1.32404
1.31628
+0.00233
+ 0.18%
--
--
XAUUSD
Gold / US Dollar
4151.42
4151.42
4151.83
4212.98
4121.53
-57.74
-1.37%
--
--
WTI
Light Sweet Crude Oil
76.502
76.502
76.532
76.663
74.888
+1.104
+ 1.46%
--
--

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The U.S. Dollar Index Fell On The 19th

TIME
ACT
FCST
PREV
IMPACT
U.S. Philadelphia Fed Business Activity Index (SA) (Jun)

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U.S. Philadelphia Fed Manufacturing Employment Index (Jun)

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Canada Industrial Product Price Index YoY (May)

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U.S. Weekly Continued Jobless Claims (SA)

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U.S. Conference Board Leading Economic Index MoM (May)

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U.S. Conference Board Coincident Economic Index MoM (May)

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U.S. Conference Board Lagging Economic Index MoM (May)

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U.S. Conference Board Leading Economic Index (May)

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U.S. EIA Weekly Natural Gas Stocks Change

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  • WTI
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U.S. Weekly Total Oil Rig Count

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U.S. Weekly Total Rig Count

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Argentina Trade Balance (May)

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U.S. Weekly Treasuries Held by Foreign Central Banks

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South Korea PPI MoM (May)

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U.K. GfK Consumer Confidence Index (Jun)

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  • GBPUSD
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Japan National Core CPI YoY (May)

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USDJPY
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Japan National CPI MoM (Not SA) (May)

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USDJPY
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Japan National CPI YoY (May)

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Japan National CPI MoM (May)

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Japan CPI MoM (May)

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U.K. Retail Sales YoY (SA) (May)

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Germany PPI MoM (May)

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Germany PPI YoY (May)

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U.K. Core Retail Sales YoY (SA) (May)

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U.K. Retail Sales MoM (SA) (May)

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Turkey Capacity Utilization (Jun)

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Russia Key Rate

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Canada Core Retail Sales MoM (SA) (Apr)

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Canada Retail Sales MoM (SA) (Apr)

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  • USDCAD
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ECB Chief Economist Lane Speaks
Argentina Retail Sales YoY (Apr)

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China, Mainland 1-Year Loan Prime Rate (LPR)

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Turkey Consumer Confidence Index (Jun)

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Canada Trimmed CPI YoY (SA) (May)

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Argentina Unemployment Rate (Q1)

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Germany 2-Year Schatz Auction Avg. Yield

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U.K. CBI Industrial Prices Expectations (Jun)

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U.K. CBI Industrial Trends - Orders (Jun)

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Mexico Retail Sales MoM (Apr)

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U.S. Weekly Redbook Index YoY

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U.S. Richmond Fed Manufacturing Composite Index (Jun)

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U.S. 2-Year Note Auction Avg. Yield

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Argentina GDP YoY (Constant Prices) (Q1)

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U.S. API Weekly Cushing Crude Oil Stocks

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U.S. API Weekly Gasoline Stocks

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Australia RBA Trimmed Mean CPI YoY

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Germany Ifo Current Business Situation Index (SA) (Jun)

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Germany IFO Business Climate Index (SA) (Jun)

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Germany Ifo Business Expectations Index (SA) (Jun)

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Q&A with Experts
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    RPGFX flag
    Durrani
    hi
    @Durrani Hello my friend, how did your trading week go today?
    BNCB flag
    EuroTrader
    @BNCBso how do you track your daily bias. you know using these tools you really need to understand the concept of getting your bias right
    @EuroTrader I look at H1 Timeframe and determine structure and use 200 EMA.
    RPGFX flag
    BNCB
    @EuroTrader I use Liquidity sweep during London session.
    @BNCB And so far what can you say about that? What are your observations? How much has it been working and what peculiarities have you noticed?
    RPGFX flag
    BNCB
    @EuroTrader I look at H1 Timeframe and determine structure and use 200 EMA.
    @BNCB How do you combine the 200 length EMA with the London session liquidity sweep
    BNCB flag
    RPGFX
    @BNCB How do you combine the 200 length EMA with the London session liquidity sweep
    @RPGFX I determine bias by it.
    EuroTrader flag
    BNCB
    @EuroTrader I look at H1 Timeframe and determine structure and use 200 EMA.
    @BNCBOhh. I'll advice that you also learn about market structure and learn what market regimes are
    BNCB flag
    EuroTrader
    @BNCBOhh. I'll advice that you also learn about market structure and learn what market regimes are
    @EuroTrader I struggle in determining bias on H1 timeframe.
    EuroTrader flag
    BNCB
    @EuroTrader I struggle in determining bias on H1 timeframe.
    @BNCBokay yu should learn how to identify a trending and ranging markets first of all
    EuroTrader flag
    BNCB
    @EuroTrader I struggle in determining bias on H1 timeframe.
    @BNCBIf you understand orderflow i would have thought you how to use orderflow to identify it
    BNCB flag
    Is it just higher highs/lows and lower highs/lows to determine market structure?
    EuroTrader flag
    BNCB
    Is it just higher highs/lows and lower highs/lows to determine market structure?
    @BNCByes you can use that also and you can also use volume profile to determine it
    EuroTrader flag
    BNCB
    Is it just higher highs/lows and lower highs/lows to determine market structure?
    @BNCBAnother way i do it is this is looking at options marksts to determine which side of the marksts are more aggressive
    BNCB flag
    @EuroTrader I will be looking at your suggestions. Thanks---
    EuroTrader flag
    BNCB
    @EuroTrader I will be looking at your suggestions. Thanks---
    @BNCBokay . maybe we would talk better tomorrow during the day. it's weekend
    Mankind flag
    00:10
    john flag
    bears remain to have an upper hand in this market
    john flag
    Nawhdir Øt94 flag
    EuroTrader
    @BNCBokay . maybe we would talk better tomorrow during the day. it's weekend
    @EuroTraderya, sekarang sudah siang,
    Nawhdir Øt94 flag
    john
    @johnpenasaran akan dimana dibuka hari senin
    Kung Fu flag
    Nawhdir Øt94
    @johnpenasaran akan dimana dibuka hari senin
    @Nawhdir Øt94How reliable is this data, this fundamental piece of information that's been shared here? I don't trust such fundamentals though. I believe more in the reality of technicals when the market opens.
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          How Can FUD in Cryptocurrencies and Stocks Affect Your Trading?

          FXOpen

          Forex

          Cryptocurrency

          Summary:

          FUD—fear, uncertainty, and doubt—shapes market sentiment, often leading to panic-driven sell-offs and volatility. Whether in stocks or crypto, FUD spreads through media, social platforms, and influential figures, sometimes distorting prices beyond fundamental value. This article explores “What does FUD mean in crypto and stocks?”, how it spreads, its psychological impact, and how traders assess whether fear is justified.

          What Is FUD?

          What does FUD mean in stocks and crypto? FUD stands for fear, uncertainty, and doubt and plays a significant role in financial markets. It refers to the spread of negative sentiment—whether intentional or not—that causes traders to hesitate, panic, or make decisions based on emotions rather than analysis. FUD can be natural and artificial and can come from a variety of sources, including media reports, social media discussions, regulatory updates, and influential investors voicing concerns.
          In markets, FUD often leads to sell-offs, heightened volatility, and price fluctuations that don’t always reflect an asset’s true value. For example, if a major financial news outlet publishes a report suggesting a company is struggling, investors may rush to offload shares, pushing the price down. The same happens with digital assets when rumours of regulation, security flaws, or industry-wide collapses circulate.

          Not all FUD is unfounded, but it thrives on uncertainty, making it difficult for traders to separate real risks from exaggerated fears. This distinction matters because reacting impulsively to FUD can mean exiting positions prematurely or missing potential opportunities when the market recovers.

          How FUD Spreads in Financial Markets

          FUD spreads quickly in financial markets because traders react to uncertainty, often before verifying the facts. Misinformation, speculation, or even vague concerns can lead to panic selling and price swings. While some FUD emerges from legitimate risks, much of it is fuelled by media, social platforms, and influential figures.

          Media and Social Platforms

          News outlets and financial media amplify uncertainty, sometimes unintentionally. A negative headline—even if the actual report is more balanced—can trigger a wave of selling. Social media accelerates this effect, as platforms like X (Twitter), Reddit, and Telegram allow rumours to spread within minutes. In some cases, misleading posts gain traction before facts emerge, shaping sentiment before traders have a chance to analyse the situation.

          Regulatory Concerns

          Markets react strongly to regulatory uncertainty. If a government proposes restrictions or new taxes, traders often assume the worst, even if details are unclear. This can lead to sharp downturns in affected sectors, with price movements driven by speculation rather than policy changes that have actually been implemented.

          Influential Figures and Institutions

          When well-known investors, CEOs, or policymakers express concerns, markets take notice. A single statement from a central bank official about inflation or interest rates can cause massive swings as traders scramble to reposition based on perceived risks.

          Corporate and Economic Events

          Earnings reports, executive resignations, or supply chain disruptions fuel uncertainty. Even misinterpreted data—like a temporary dip in revenue—can cause exaggerated market reactions. Likewise, broader economic concerns, such as rising inflation or geopolitical instability, create waves of uncertainty that affect multiple asset classes.

          The Psychological Impact of FUD on Traders

          FUD doesn’t just affect prices but influences how traders think and react. Markets are driven by psychology as much as by fundamentals, and uncertainty can lead to irrational decision-making. When fear takes over, traders often move away from analysis and start making emotional choices, which can create unnecessary losses or missed opportunities.

          Fear-Driven Decision-Making

          FUD triggers the fear of losing money, leading traders to close positions prematurely. Instead of assessing the actual risk, they react to the worst-case scenario, assuming a downturn will continue indefinitely. This often happens when negative news spreads rapidly, creating panic even when there’s no solid evidence that an asset is in trouble.

          Herd Mentality and Overreaction

          Markets are deeply influenced by herd behaviour. When enough traders sell due to FUD, others follow, fearing they’ll be left holding a declining asset. This amplifies volatility and can cause price drops that are far larger than justified by fundamentals. It also works in reverse—when FUD fades, prices often recover just as quickly.

          Confirmation Bias and Selective Thinking

          Once traders expect negative outcomes, they start looking for information that confirms their fears. This reinforces FUD, making it harder to take an objective view. Even if new data contradicts the negative sentiment, traders influenced by FUD may cling to the bearish narrative, staying on the sidelines while prices recover.

          Notable Examples of FUD in Stocks and Digital Assets

          Severe market swings are often triggered by FUD, meaning in crypto and stock markets, billions in market value can be quickly wiped out before sentiment stabilises. While some concerns turn out to be valid, many price drops triggered by FUD prove temporary once the fear fades.

          Tesla’s Stock Volatility

          Tesla has been a prime example of FUD in stocks, meaning speculative concerns causing sharp price swings despite strong fundamentals. Over the years, concerns about battery supply shortages, regulatory scrutiny, and Elon Musk’s public statements have triggered sell-offs. In 2022, news that Musk was selling Tesla shares to finance his Twitter acquisition led to a steep decline despite no fundamental issues with the company itself. The stock later rebounded when investor confidence returned.

          2023 Banking Sector Panic

          In March 2023, Silicon Valley Bank collapsed after concerns about liquidity and capital reserves caused depositors to pull funds en masse. Fear spread quickly, hitting other bank stocks—even those with strong balance sheets. Traders acted before understanding the full picture, leading to unnecessary declines in financial sector stocks.

          Regulatory Crackdowns and Digital Asset Sell-Offs

          The digital asset market has repeatedly been hit by crypto FUD surrounding government regulation. In 2021, China’s crackdown triggered FUD in crypto, meaning widespread fear of stricter regulations, leading to a market downturn. Similarly, in 2023, the SEC’s legal actions against major exchanges caused panic selling, even though long-term adoption trends remained positive.

          Change in Market Sentiment

          On 22 December 2017, Bitcoin dropped below $11,000, losing nearly a third of its value in just five days. This decline marked its worst week since 2013, following a rapid surge that brought it close to $20,000 on Sunday.
          While no single factor fully explained the dramatic fall, growing warnings about the risks of investing in the volatile and unregulated market—Denmark’s central bank governor even labelled it a “deadly” gamble—contributed to the decline.
          How Can FUD in Cryptocurrencies and Stocks Affect Your Trading?_1

          How Traders Analyse and React to FUD

          FUD creates uncertainty, but traders who analyse market reactions critically can spot potential opportunities and avoid impulsive decisions. Instead of reacting emotionally, they assess whether the fear is justified by real data or if it's just market noise.

          Fundamental Analysis vs. Speculation

          Traders first determine whether FUD is backed by actual risks. If a company's financials remain strong despite negative news or a regulatory development lacks concrete action, the sell-off may be driven more by sentiment than reality. This applies to both stocks and digital assets, where FUD often causes overreactions that later correct.

          Sentiment and News Monitoring

          Some traders track social media sentiment, news headlines, and analyst opinions to gauge how widespread FUD has become. When negative sentiment peaks but no new damaging information emerges, the market may be nearing a reversal. Tools like Google Trends and market sentiment indices help traders understand whether fear is fading or intensifying.

          Volume and Volatility Indicators

          FUD-driven moves often come with spikes in trading volume and volatility as traders panic-sell into uncertainty. A surge in volume without a fundamental reason can signal a short-term emotional reaction rather than a lasting market shift.

          Contrarian Strategies

          Some traders take advantage of oversold conditions caused by FUD, buying when prices drop irrationally. While risky, historical patterns show that FUD-driven dips often reverse once fear subsides. Analysing past market reactions helps traders identify whether fear has gone too far.

          The Difference Between FUD and Genuine Market Concerns

          FUD in crypto and stocks thrives on uncertainty, but not all negative news is exaggerated or baseless. The key difference between FUD and genuine market concerns is whether the fear is driven by facts and data or speculation and emotion.
          Real market risks are backed by tangible developments—declining earnings, rising debt, regulatory enforcement, or economic downturns. When a company consistently misses revenue targets or central banks tighten monetary policy, the impact is measurable. Traders can assess financial reports, macroeconomic indicators, or industry trends to gauge the scale of the problem.
          FUD, on the other hand, often stems from rumours, misleading headlines, or misinterpretations of events. For example, a vague statement about a possible regulatory crackdown can trigger panic, even if no concrete action follows. Similarly, a company’s stock might fall sharply on news of an executive resignation despite no change to its core business. These reactions are driven by perception rather than financial reality.

          Traders separate the two by looking at historical market behaviour, financial fundamentals, and whether fear aligns with actual data. While both FUD and real risks can cause volatility, genuine concerns tend to have longer-term consequences, whereas FUD-driven sell-offs often reverse once sentiment stabilises.

          Source:FXOpen

          Risk Warnings and Disclaimers
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          The risk of loss in trading financial instruments such as stocks, FX, commodities, futures, bonds, ETFs and crypto can be substantial. You may sustain a total loss of the funds that you deposit with your broker. Therefore, you should carefully consider whether such trading is suitable for you in light of your circumstances and financial resources.

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