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TRUMP Quant Signals TRUTH 2025-11-06════════════════════════════════════════════════════════════════════════════════ 💰 TRUMP TRUTH SOCIAL SIGNALS Generated: November 06, 2025 at 11:39 PM ════════════════════════════════════════════════════════════════════════════════ 📊 5 Total Opportunities • ✅ 5 Ready to Trade • ⏸️ 0 Monitor ──────────────────────────────────────────────────────────────────────────────── ┌─ #1 ✅ NYSE:WMT • Score: 90/100 • ENTER NOW │ │ 📅 DTE: 3-7 days │ 🟢 Risk Level: Low Risk (1/10) │ │ 📰 Catalyst: Explicit mention of Thanksgiving price drop as Republican achievement │ 📊 Setup: Bullish momentum from Trump posts │ 🎯 Target: Monitor political developments │ 📈 Options: CALL options for upside exposure │ │ 💡 Trade - High conviction political catalyst │ ⚠️ Risk: Political news can reverse quickly └─────────────────────────────────────────────────────────────────────────────── ┌─ #2 ✅ NYSE:XOM • Score: 85/100 • ENTER NOW │ │ 📅 DTE: 3-7 days │ 🟢 Risk Level: Low Risk (2/10) │ │ 📰 Catalyst: Energy dominance theme and lower oil/gas prices │ 📊 Setup: Bullish momentum from Trump posts │ 🎯 Target: Monitor political developments │ 📈 Options: CALL options for upside exposure │ │ 💡 Trade - High conviction political catalyst │ ⚠️ Risk: Political news can reverse quickly └─────────────────────────────────────────────────────────────────────────────── ┌─ #3 ✅ NYSE:LMT • Score: 80/100 • ENTER NOW │ │ 📅 DTE: 3-7 days │ 🟢 Risk Level: Low Risk (2/10) │ │ 📰 Catalyst: Military and border security emphasis │ 📊 Setup: Bullish momentum from Trump posts │ 🎯 Target: Monitor political developments │ 📈 Options: CALL options for upside exposure │ │ 💡 Trade - High conviction political catalyst │ ⚠️ Risk: Political news can reverse quickly └─────────────────────────────────────────────────────────────────────────────── ┌─ #4 ✅ NYSE:CAT • Score: 75/100 • ENTER NOW │ │ Image 📅 DTE: 3-7 days │ 🟢 Risk Level: Low Risk (3/10) │ │ 📰 Catalyst: Infrastructure and manufacturing focus in trade deals │ 📊 Setup: Bullish momentum from Trump posts │ 🎯 Target: Monitor political developments │ 📈 Options: CALL options for upside exposure │ │ 💡 Trade - High conviction political catalyst │ ⚠️ Risk: Political news can reverse quickly └─────────────────────────────────────────────────────────────────────────────── ┌─ #5 ✅ NYSE:JPM • Score: 70/100 • ENTER NOW │ │ 📅 DTE: 3-7 days │ 🟢 Risk Level: Low Risk (3/10) │ │ 📰 Catalyst: Economic growth and deregulation narrative │ 📊 Setup: Bullish momentum from Trump posts │ 🎯 Target: Monitor political developments │ 📈 Options: CALL options for upside exposure │ │ 💡 Trade - High conviction political catalyst │ ⚠️ Risk: Political news can reverse quickly └─────────────────────────────────────────────────────────────────────────────── ──────────────────────────────────────────────────────────────────────────────── 📖 QUICK GUIDE: ✅ ENTER NOW → High probability setup, optimal timing, low-medium risk ⏸️ WAIT → Monitor for better entry or catalyst resolution 🟢 Low Risk → Heat 1-3 (stable, far from catalysts) 🟡 Med Risk → Heat 4-6 (moderate volatility) 🔴 High Risk → Heat 7-10 (near catalysts, high volatility) 💎 Position Sizing: 2-5% per trade • Max 2-3 concurrent positions 🎯 Exit Strategy: Take profit at 50% max gain or stop at 2x loss ════════════════════════════════════════════════════════════════════════════════
NASDAQ:DJTLong
by quantsignals
Digital Dominates the Market and Old Methods Fall Behind1. The Rise of the Digital Era The digital era began with the advent of computers and the internet but truly accelerated with smartphones, artificial intelligence (AI), big data, and automation. These technologies didn’t just improve existing systems; they created entirely new ways of doing business. Digitalization allowed information to flow faster, decisions to be data-driven, and processes to be more efficient. For instance, e-commerce giants like Amazon, Alibaba, and Flipkart have replaced traditional brick-and-mortar stores as dominant retail forces. Customers now shop online, compare prices instantly, and get deliveries at their doorsteps — conveniences that were unimaginable two decades ago. Similarly, in finance, digital payment systems like UPI, PayPal, and cryptocurrency have made cash transactions almost obsolete in many regions. 2. Speed and Efficiency: The Core of Digital Dominance One of the most significant advantages of digital systems is speed. Digital tools can process massive amounts of data in seconds, something manual systems could never achieve. Businesses can now analyze trends, predict demand, and make instant adjustments in pricing or supply chains. For example, algorithms in stock markets execute millions of trades per second, optimizing profits based on market data — a task that human traders simply cannot match. In logistics, GPS tracking and automated warehouses ensure timely deliveries and reduced operational costs. Efficiency is also enhanced through automation. Robots, AI chatbots, and machine learning systems perform repetitive tasks, allowing human workers to focus on creativity and strategy. This blend of automation and intelligence has become the new norm in production, healthcare, and customer service. 3. Data: The New Currency In the digital world, data is power. Every click, purchase, and search generates valuable data that companies use to understand consumer behavior. This information helps businesses personalize products, target advertisements, and improve customer satisfaction. Old methods relied on surveys or assumptions to gauge customer preferences, which were often inaccurate or outdated. Today, real-time analytics tools like Google Analytics, Meta Ads Manager, and CRM platforms provide detailed insights within minutes. As a result, companies can make evidence-based decisions instead of relying on guesswork. For instance, Netflix uses viewer data to recommend shows, while Spotify curates music playlists using AI algorithms. These personalized experiences are key to retaining customers in the digital marketplace. 4. The Fall of Traditional Business Models Traditional business methods, which depended heavily on manual labor, paperwork, and face-to-face interactions, are struggling to compete in a digital-first environment. The COVID-19 pandemic accelerated this shift — businesses without a digital presence suffered major losses or closures, while those that embraced technology thrived. Brick-and-mortar retail stores have been replaced by online platforms. Newspapers are losing readers to digital media outlets and social networks. Even traditional banking, once reliant on in-person visits, has moved online through mobile banking and fintech apps. Moreover, digital marketing has replaced conventional advertising. Television and print ads are losing relevance as companies turn to social media, influencer collaborations, and targeted online campaigns to reach audiences more effectively. 5. Global Connectivity and Market Expansion Digital technology has eliminated geographical barriers. A small business in India can sell products to customers in Europe or the U.S. through online platforms. Social media allows brands to build global reputations, while digital payment systems and logistics networks simplify international trade. Old methods, which relied on local marketing and limited reach, could never achieve this level of global exposure. Today’s startups can scale faster than ever before because the digital world provides instant access to millions of potential customers. 6. Innovation and Adaptation: The Key to Survival In this digital-dominated market, innovation is the ultimate survival strategy. Companies that fail to adapt risk becoming irrelevant. Kodak is a classic example — once a photography giant, it fell behind because it ignored the rise of digital cameras. Similarly, Nokia, a leading mobile manufacturer, lost market share after failing to adapt to smartphone technology. In contrast, businesses that embrace digital transformation, like Apple, Tesla, and Google, continue to lead their industries. They innovate continuously, leveraging AI, machine learning, and automation to stay ahead of competitors. The lesson is clear: technology evolves rapidly, and only those willing to evolve with it can sustain success. 7. Digital Transformation in Key Sectors a) Finance: Fintech innovations have revolutionized banking. Digital wallets, online trading platforms, and blockchain technology have reduced dependency on traditional banking. b) Education: E-learning platforms like Coursera and Byju’s have replaced conventional classrooms for millions, offering flexibility and accessibility. c) Healthcare: Telemedicine, AI diagnostics, and wearable devices now monitor patient health remotely, reducing hospital visits. d) Manufacturing: Smart factories use IoT (Internet of Things) and robotics to enhance production efficiency. e) Media and Entertainment: Streaming services have replaced cable television, and social media has become a primary source of news and engagement. Each of these sectors illustrates how old systems fade as digital tools redefine efficiency and user experience. 8. The Challenges of Digital Dominance While digital transformation brings numerous benefits, it also presents challenges. Cybersecurity threats, data privacy concerns, and the risk of automation-driven unemployment are major issues. Small businesses often struggle to afford the technology required to stay competitive. Furthermore, digital dependence can lead to inequality — regions with poor internet connectivity or digital literacy may fall behind economically. Hence, governments and organizations must focus on digital inclusion and cybersecurity to ensure a balanced digital future. 9. The Future: A Fully Digital Ecosystem Looking ahead, the world is moving toward complete digital integration. Artificial intelligence, quantum computing, and blockchain will dominate future innovations. Physical money may vanish, replaced entirely by digital currencies. Autonomous vehicles, smart cities, and virtual reality workplaces are becoming realities. The Internet of Everything — where every object is connected — will redefine how people live and work. Old methods will not disappear entirely, but they will become niche or nostalgic alternatives rather than mainstream options. 10. Conclusion The dominance of digital technology marks one of the most profound shifts in human history. It has redefined efficiency, speed, and accessibility while transforming every aspect of business and daily life. Traditional methods, though valuable in their time, can no longer meet the demands of an interconnected, data-driven economy. In the digital age, adaptation is not optional — it is essential. Those who embrace change, invest in innovation, and harness the power of data will lead the future. The world has entered an era where the digital dominates the market, and the old methods, while respected, inevitably fall behind.
NASDAQ:NFLXEducation
by GlobalWolfStreet
ESPR 1W: cholesterol therapy for patients and investors alikeEsperion Therapeutics (ESPR) has broken its long descending trendline and retested the $2.4–$2.6 support area, forming a solid triple bottom with rising volume. The stock is now holding above key moving averages, signaling accumulation. While above $2.5, the technical setup points to a move toward $6.4, aligning with major resistance and the 200-week MA. Fundamentally, the company enters one of its strongest phases in years. Following earlier liquidity struggles, Esperion has stabilized its operations and regained investor confidence. The core growth driver is Nexletol (bempedoic acid), a non-statin cholesterol-lowering therapy for patients intolerant to statins. In 2025, combined Nexletol and Nexlizet sales jumped over 45% year-on-year, surpassing $170 million for the first nine months. Recent safety data were positive, leading to new approvals across Europe and Japan - expanding partnerships and licensing revenues. Cash position strengthened via milestone payments from Daiichi Sankyo and Viatris, reducing debt and supporting R&D without new dilution. Challenges remain: profitability is still out of reach, as marketing and development expenses stay high, though liquidity provides breathing room. The broader biotech sector’s rebound amid rate-cut expectations adds tailwind to revenue-backed small caps like Esperion. Tactically, holding above $2.5 keeps the bullish trajectory intact toward $6.4. A weekly close below $2.3 would negate the setup and re-test lower support, though current accumulation favors the upside. Esperion helps reduce cholesterol - ironic that its chart still raises investors’ heart rate.
NASDAQ:ESPRLong
by TotoshkaTrades
MSTR: The Software Company That Gave Up on SoftwareMSTR The Next Barings Bank - Short to Zero MicroStrategy (MSTR) stopped being a software company years ago. They couldn't grow revenue, so Michael Saylor found a new pitch: leverage the entire company to buy Bitcoin and sell the "vision" to retail investors. The Revenue Reality: 2015: $529.87M revenue 2021: $510.76M revenue (DOWN after 6 years) 2023: $496.26M revenue 2024: $463.46M revenue TTM: $474.94M revenue Ten years. NEGATIVE revenue growth. When you can't grow your actual business, you pivot to selling a pipe dream. That's exactly what Saylor did. The Ponzi Structure Here's the model: Borrow billions to buy Bitcoin Bitcoin goes up (hopefully) Stock goes up because you "own Bitcoin" Issue more stock at inflated prices Buy more Bitcoin with diluted shares Repeat until it breaks The problem: They have no control over Bitcoin long-term. They can move it short-term with their buying, but in reality? They're passengers on a volatile asset with $7.26B in debt. The Numbers Don't Lie Balance Sheet Explosion: Total debt 2019: $0 Total debt 2024: $7.26B Total assets jumped from $4.76B (2023) to $25.84B (2024) - all Bitcoin Revenue declining while taking on billions in debt Operating Performance: Net income 2024: -$1.17B (loss) Net margin: -3,797% (you read that right) Operating income: -$63.12M (negative) Free cash flow 2024: -$66.51M (-780% change) EBITDA 2024: -$24.53M The actual software business is dying while Saylor pumps Bitcoin on Twitter. Barings Bank 2.0: The Nick Leeson Parallel In 1995, Nick Leeson was a derivatives trader at Barings Bank. He bought Nikkei futures at the 40-year top, kept doubling down to cover losses, and hid everything in error account 88888. Result: 233-year-old bank collapsed in weeks. Michael Saylor is doing the exact same thing: Leveraged to the tits buying Bitcoin near tops $7.26B in debt on a declining software business No way out if Bitcoin crashes The interest payments alone will kill him The market already knows: While Nasdaq hits all-time highs, MSTR is 50% off its highs. That's not a dip. That's the market pricing in the collapse before it happens. The Technical Setup Current price: ~$269 Key breakdown level: $230 If $230 breaks: Next stop: $180 (support from previous consolidation) Then: $114 area (major support zone) Ultimate target: $0 Why these areas matter: $230 = Last line of defense before panic selling $180 = Where late buyers give up hope $114 = Pre-Bitcoin-mania valuation (actual software business worth) $0 = When the debt spiral becomes unsustainable Chart pattern: Classic distribution. Lower highs, weakening momentum, while indices rip higher. The Catalyst: Bitcoin Goes Into Crypto Winter When Bitcoin cracks (see my other post on October 10th liquidation): The death spiral: Bitcoin drops 50%+ MSTR's "asset base" collapses Debt-to-equity ratio explodes Credit downgrades trigger margin calls Forced liquidation of Bitcoin holdings More Bitcoin selling accelerates crypto winter MSTR goes to zero Saylor's only escape: Bitcoin stays elevated forever AND he can keep issuing diluted shares to cover debt payments. Reality: Neither of those things will likely to happen. The Pipe Dream They're Selling "We're a Bitcoin treasury company!" No. You're a failing software company with declining revenue that gambled the entire operation on a volatile asset you can't control. You can't control Bitcoin's price long-term You can't control regulatory changes You can't control macro conditions You can't control when crypto winter comes You're just holding bags with $7.26B in debt. The Short Thesis Entry: Current levels ($269) or breakdown below $230 Targets: First target: $180 Second target: $114 Ultimate target: $0 Stop loss: Above $320 (invalidation if Bitcoin makes new highs and MSTR participates) Timeframe: 6-18 months for full thesis to play out Catalysts: Bitcoin entering crypto winter (foundation cracked October 10th) Credit downgrades Forced Bitcoin liquidation Revenue continues declining Debt payments become unsustainable Risk Factors What could go wrong with this short: Bitcoin has a blow-off top before winter Saylor successfully issues more diluted shares at elevated prices Retail continues buying the "Bitcoin exposure" narrative Some institution bails him out (unlikely) Why I'm short: The math doesn't work. You can't have: Negative revenue growth for a decade $7.26B in debt No control over your primary asset Negative operating cash flow ...and survive when that asset drops 70-80% (which it will). The Comparison 1995: Nick Leeson buys Nikkei futures at 40-year top Doubles down with borrowed money Hides losses in account 88888 Collapses 233-year-old Barings Bank 2025: Michael Saylor buys Bitcoin near all-time highs Leverages entire company with $7.26B debt Pumps Bitcoin on Twitter while software business dies About to collapse MSTR History doesn't repeat, but it rhymes. Final Word The market is telling you everything you need to know: Nasdaq: All-time highs Bitcoin: Near all-time highs MSTR: Down 50% from highs When the asset you're leveraged on is strong, and the indices are strong, but YOUR STOCK is down 50%... The market is pricing in collapse. MSTR → Zero #MSTR #Bitcoin #BTC #CryptoWinter #ShortSetup #TechnicalAnalysis #Leverage #DebtCrisis
PYTH:MSTRShort
by onlytrade2win
1
ICPUSDT - many positive indicators!The coin ICP has pumped nearly 160% in just one week, and believe it or not — all that move happened without even breaking out of the accumulation range it’s been forming for over 275 days. So imagine what will happen once it finally breaks out! The high volume and bullish indicators on the chart suggest that this coin’s minimum target is around $30, meaning roughly a 5x potential from the current level. It has already broken above the 0.618 Fibonacci resistance, broken the main trendline (marked in blue), and even formed a Golden Cross pattern. It’s still inside the accumulation zone for now, so this is your early entry opportunity — because once it breaks out, you won’t catch it again. Mark my words. Best Regards: Ceciliones🎯
Long
by ceciliones
10
XAU/USD – Holds Its Range, Preparing for a Year-End Expansion🔍 Market Context Friday’s New York session closed with a two-sided liquidity sweep, yet gold managed to hold its structural balance, maintaining the same rhythm seen over the past two weeks — sideways to mildly bearish, but firmly supported. This behavior shows that buyers are still defending key zones, especially around 3,940$ – 3,980$, which MMFLOW highlighted multiple times last week as the decisive liquidity floor. From a macro lens, the Fed’s cautious tone has slowed expectations for aggressive rate cuts — but the probability of another reduction before Q1 2026 remains alive. As we move toward the final stretch of the year, thinner liquidity and seasonal safe-haven flows could help gold establish a mid-term bottom, setting the stage for the next impulsive leg. 📊 Technical Structure (H4) The current chart presents a clear 5-wave recovery structure within a tightening range — a classic setup before expansion. Key Technical Zones: • 💎 Support Zone: 3,942$ – 3,982$ (liquidity base + strong absorption area) • 🎯 Wave 3 Target: 4,072$ – 4,133$ (first reaction zone) • ⚙️ Extended Target / Wave 5: 4,189$ – 4,201$ (Fibo 1.618 projection) • ⚠️ Invalidation: Below 3,940$ → loss of short-term structure, possible re-accumulation lower. The structure remains sideways but constructive, and a confirmed breakout of the descending trendline could act as the catalyst for a year-end bullish continuation. 🎯 MMFLOW TRADING View Smart money continues to accumulate within equilibrium zones, with every liquidity sweep appearing more like preparation than rejection. As long as gold stays above 3,970$, the bullish bias remains valid — with a 60%+ probability of a move toward 4,130$+ in the short to mid-term. Historically, November–December often brings portfolio rebalancing and policy easing cycles, both of which may serve as fuel for a potential gold rally into Q1 2026. ⚜️ MMFLOW Insight: “Accumulation isn’t waiting — it’s when big money quietly builds the next wave.”
OANDA:XAUUSDLong
by MMFlowTrading
SPX: Bear Markets and Complacency Oh boy, we are here, about to have “the talk”. Didn’t think this would come up until 2026, but alas we are. It’s a loaded talk so get ready. Bear markets, or less triggering, corrective markets. What about them, you may ask? I am going to talk about the prospects of a bear market for the S&P starting right now. Like today. Like November of all times. I am also going to talk a bit about complacency in markets which snagged me bad this week. So get ready for some theory, analysis, application and market lessons/reflection, all in one post! First off, bear markets. How do you identify them? This is the million-dollar question! How do you identify bear markets? The truth is, they are mostly impossible to determine reliably, even with the most robust fundamental and technical analysis combined! The approach I take to “preparing” for bear markets is usually on the fundamental side over everything else! It’s a bit of a hybrid, fundamental math, but traditionally what I use is simply the US money supply. It has served me well over the years and even prepared us for that correction we saw in early 2025, if you follow me and remember these posts: Essentially by analyzing how far the value of the S&P is over the US Money supply, and creating a cointegrated relationship. Traditionally, I would use R to do this, but in my mission to bring more statistics to Pinescript, I no longer need to rely on R to provide the analysis, as the Econometrica indicator now exists ( available here ). Using this indicator, we can take a look at SPY and SPX against the US money supply: We can see that historically SPX has traditionally corrected over-extension through reverting back to the US Money Supply mean, or more technically the cointegrated relationship that exists of SPX value over US money supply value. However, currently, SPX is the farthest it has ever been above the US money supply. Nuts! If we look at SPY: Nuts! Additionally, we know that this is still relevant because despite SPY and SPX being so far above the US money supply, the Correlation and, more importantly, the R2 remains really high. Indicating that a substantial degree of variance of SPY can be explained by the US Money supply. SPY and SPX can attempt to ignore it, but it will do so in vein because at the end of the day, the pair are two peas in a pod and inseparable. We know this from the strong correlation and R2 value of the cointegrated regression. If you don’t believe it, simply watch and read my previous ideas that were posted about a month or two before we saw SPY and SPX tank >20% in the span of a month! It generally works, its just, timing is difficult. Other, easier ways to identify bear markets: There is no other way I have found with statistical rigour. Some of the worst performing ways are using EMAs. For example, the average distance from the daily EMA 200 SPY and SPX will travel before a bear market starts is 7 to 9%. However, of the 7 to 9% distance, only 6% of these are true lead ins to bear markets. That’s because, SPY and SPX spend a great degree of time between 7 to 9% away from the EMA 200. Other ways like quantifying magnitude between bull and bear market cycles is more promising, though equally problematic. Studying magnitude between bear and bull markets (i.e. the percent gain from the bear market low to the bull market high prior to the next bear market) ranges from 4% to up to 100%, with the average being around 42%. Currently, SPY and SPX would be at 43.5% from its bear market/corrective cycle low: And peaked at about 10% away from the EMA 200: While these in silo are not helpful, seeing the confluence of signals does lend some potential rigour. In this case, we are incredibly over-extended from the US Money supply, we have surpassed the EMA threshold and we are >= the average bear – bull market cycle threshold. So there is that. The last way is by creating a time series model that calculates the mean, and analyzing behaviour at various distances from this mean historically. I have had hit or miss success with this. This is not so predictive of actual bear market onsets, but it is 100% reliable for target prices (again, if you follow me, the calling of the 481 target price on SPY during the crash was thanks to this approach). Lets talk about Bear markets in November They’re rare. Very rare. They have been known to happen but in extremely rare circumstances. This is because November seasonality is incredibly strong. November is one of the best performing months for the S&P and many stocks as a whole! If you ask some generic AI about bear markets starting in November, it will likely spit out 1980. Ah yes, the 80s. November 1980. While people were innocently doing aerobics while listening to Blondie, they never fathomed the -27% decline that awaited their markets, despite booming economies and AAPL coming to town (mind you, the big release was in 1984 when the market was healthy but apple still very much existed here). But why am I talking about this so much? Who cares about 1980. Well, yeah, that’s what I thought until I noticed something that peaked my interest. Let’s take a look at 1980: Notice anything? If not, don’t worry, here is it again with some reference: And if we are still not really feeling it: Interesting. I was intrigued by the similarity, so I had to test it mathematically to ensure that it wasn’t just a coincidence. To do this, I pulled monthly data from SPX and isolated January 1980 to November 1980. I then ran a regression on this data against January 2025 to November 2025 (bearing in mind November just begun). The results were: Correlation: 0.918 (Strong positive relationship, meaning that the trend is identical between the periods). R2: 0.843 (Meaning that 3/4s of the variance and movement of 2025 can be explained using 1980 monthly data). Comparing it against a random year (in my testing case, January 1984 to November 1984), I got a correlation of 0.468 and an R2 of 0.219, indicating no strong link and no explanation of variance. This verifies that this is not just some visual anomaly, there is actually some substance to this theory of the 80s. And why not? I mean, I see people rocking 80s hair cuts again on a daily basis, why not rock 80s markets while we are at it! So then the question that arises from this is, okay, larger timeframe, sure, it explains the data a bit. But does it really align on the smaller timeframe (i.e. Daily timeframe)? Does it align well when we narrow the picture? Well, for this, I tried it. And oh boy, buckle up. Because we are comparing tit for tat, side by side, same days etc. without missing data (i.e. for the monthly, we ran the analysis with most of November data missing), we have the following results: Correlation: 0.9444 R2: 0.8918 Its unreal. Had we known we could have predicted every single move SPX made this year! EVERY. SINGLE. MOVE. Hindsight is so annoying. Now, because I am not a fundamental analyst, as I like to say, its time to cite some AI. Gemini is my preferred. So lets ask him/her what they think about the results: “The strong correlation on the daily timeframe provides a high degree of confidence that the factors (macroeconomic, technical, or psychological) that drove the market trajectory in the first 214 trading days of 1980 are similar to those driving the 2025 market. This gives you a strong justification for using the remainder of the 1980 price data as a projection or probability model for the rest of 2025. ” So now my logical question is “ Well, how do the fundamentals of 1980 compare to today ”? And this is what Gemini has to say about that: The Central Theme: Inflation, Rates, and Recession Fear The S&P 500's price action in 1980 was fundamentally shaped by the confluence of three major forces, all of which have strong parallels today: 1. High and Volatile Inflation • 1980 Reality: This was the peak of the "Great Inflation" era. Inflation was incredibly high, peaking near 14% in the early part of the year, driven by oil price shocks following the 1979 energy crisis. This forced consumers and businesses to constantly adjust expectations. • 2025 Parallel: While not at 14%, the post-pandemic inflation shock has been the worst in four decades. Prices have remained sticky, particularly in services, and have proven difficult to bring down to the Fed's target, leading to persistent uncertainty. 2. Aggressive Monetary Policy • 1980 Reality: Paul Volcker, the Federal Reserve Chairman, was implementing radical, Volcker-shock policies to crush inflation. This involved driving interest rates to unprecedented levels (the Federal Funds Rate hit 20% in 1980). The market volatility reflected the uncertainty of whether the Fed would succeed and how much economic pain it would inflict. • 2025 Parallel: The Federal Reserve has conducted the most aggressive rate-hiking cycle in four decades. The debate has continuously centered on whether the Fed is "done," whether they will "pivot," and whether the current high rates are sufficient to induce the necessary slowdown without causing a severe recession. 3. Economic and Geopolitical Uncertainty • 1980 Reality: The economy was officially in a recession in the first half of 1980. Geopolitically, the Soviet invasion of Afghanistan and the Iranian hostage crisis created massive global instability, which directly impacted energy prices and market sentiment. • 2025 Parallel: While the economy has been resilient, the persistent fear of an imminent recession remains a dominant theme. Geopolitically, ongoing conflicts in Ukraine and the Middle East continue to pose supply chain risks and put upward pressure on energy and commodity prices, mirroring the external shocks of the 1980s. Oh man, where was AI many moons ago? So, what happens next? I want to assert something. I am not calling for a bear market here. I like to dabble in statistical analysis and I would be wrong to not have a discussion about this, in light of what I see and what is happening. That said, there are still reasons to be bullish: From a fundamental perspective, seasonality remains bullish and bear markets starting in November remain a rarity. We also have, according to my projections, a high probability target up at 710 on SPY leading us into the end of December, with a historic hit rate of 87%. We have, as well, the prospects of a Santa rally happening. If you recall my last idea on SPY, Santa rally’s happen on SPY around 75% of the time. But what can we do with the information about 1980? The simple answer, is we can observe and we can model. We can model an adjusted forecast based on the remainder of 1980 using current prices of SPX. And we can observe. We can observe the correlation and R square as time progresses to see if we are following the trajectory to the same degree and closeness as we are currently. For the first one, the forecast, I am sure you are wanting this and wanting to observe it with your own eyes, so I went ahead and did the forecast in R. Here are the results: As you can see, its mostly sideways. Though SPX made a new high after this point before coming down more. Timelines may be skewed however, which is why the R squared is 0.89 and not 1 (perfect). So, sell it? Maybe. I think, the key take away here, is exercise caution here. A Note on Complacency I want to give a quick note on the dangerous of complancency, even from the most experienced traders. I have been trading since 2018, and, for some reason, this year which has been incredibly bullish, I have just become complacent. Buying the dips and not thinking too much about it. Traditionally, I would analyze all options, pay attention to all metrics and weigh forecasts and statistics equally. However, this year I have massively slipped into just mindless, buy buy buy trading. This week was a wake up call for me, since it did not go as expected. It was also avoidable, since half of my stuff indicated the week was turning bearish. I chose to ignore in favour of being complacent and airing on the side of irrationality. Trading can and is a grind. Its is a job if not worse than a job. Its not always enjoyable. But the one thing that is different about a job is when you cut corners trading, you will for sure pay the price. Whereas, with a job, you may get off the hook. Be vigilant. Take breaks. And never corner cut! It’s a very important lesson for most! Don't be lazy, laziness breeds complacency. That’s it. This doesn’t count as my weekly post, so don’t worry because I didn’t share any analysis for next week haha. Safe trades everyone and thanks for reading!
SP:SPX
by Steversteves
5
Eth/Usd - Rejection Setup Targeting $3,250Ethereum is currently trading around the $3,435 zone, testing a strong resistance area between $3,450–$3,500. Price has previously rejected this zone multiple times, forming a clear double-top pattern. The support zone sits near $3,220–$3,260, where buyers have stepped in several times before. Unless ETH breaks above resistance with strong volume, a pullback toward the support zone remains likely. Bias: Bearish below $3,450 Target: $3,250 Invalidation: Break and close above $3,500
BINANCE:ETHUSDShort
by Hamza_Gold
USD/JPY Analysis — Short-Term Bearish CorrectionPersonal Trade Idea Fundamental: Despite Japan’s low interest rate (0.5%) versus the Fed’s 4%, which favors a stronger USD, the ongoing U.S. government shutdown has weakened dollar sentiment. Market confidence is slipping, creating room for a short-term bearish correction on USD/JPY while the broader trend remains fundamentally bullish. Technical: On the 4H timeframe, structure has turned bearish following a liquidity sweep and market structure shift (MSS). Price is now pulling back on lower timeframes (15M) toward a small Fair Value Gap (FVG) in 4H. A reaction from the marked zone on 3H TF could trigger the next bearish continuation leg. Outlook: Bias: Short-term bearish Key Zone: 3H AOI / 4H supply Setup: Wait for rejection confirmation before shorting
by SOL_FX
3
The Great Rising WedgeAltcoin market structure mirrors a macro rising wedge; the same bearish pattern that preceded the 2022 crash. A weak recovery after a sharp selloff, now forming on a higher timeframe, signals distribution before collapse. Technicals align with macro risk: • U.S. debt > $35T, credit cards and real estate at record highs. • Berkshire Hathaway sits on $350B in cash. • Michael Burry holds $1.1B in AI-related puts. • Open interest and leverage across markets are extreme. This setup reflects late-cycle euphoria; similar to 1999 (dot com) and 2008 (housing). The wedge is not just a chart pattern; it’s a symptom of systemic exhaustion. If history rhymes, we’re nearing a global liquidity event where “blood in the streets” becomes reality again.
CRYPTOCAP:OTHERSShort
by osamaadi
Zomdf bull thesis Zomdf is in a good spot to catch a bounce to .47. Then .82 ,gap at .99. Once this is over $1.00 it will squeeze to 2.08 which is my profit target. If you use MA's. This broke the reclaimed and just held the retest of the 200 day SMA. This capitulated in March with over 282 million is sale vol. Since then you have a rounded bottom. And recently the tech company that uses AI for you furry friends had great earnings. I believe that this is a $2 stock by mid next year. But DYOR.
OTC:ZOMDFLong
by moneyinthebank054
2
The continuous short positions in gold have ended perfectly!Whether gold can break through resistance levels in the near term depends on the convergence of three factors: First, whether the US dollar and US Treasury yields experience a more sustained decline, creating room for discounting; second, whether risk appetite strengthens the "insurance demand" for gold due to equity volatility and increased macroeconomic uncertainty; and third, whether net inflows of funds continue, especially whether passive funds and longer-term allocation funds enter the market simultaneously. If these three factors fail to move in tandem, the price will likely continue to consolidate within the $3930-$4000-$4050 range. If they move in unison, the resistance above these round numbers will weaken more smoothly. It's worth noting that the People's Bank of China suspended its 18-month gold purchase program in May 2024 but resumed it in November of the same year. The market currently expects a 67% probability of a Fed rate cut in December, up from around 60% the previous trading day. The Fed just cut rates last week, and Powell stated that this may be the last rate cut this year. The market's current focus is on macroeconomic data and when the US government shutdown will end—which is also driving safe-haven demand for gold. The congressional gridlock led to the longest government shutdown in U.S. history, forcing investors and the data-dependent Federal Reserve to rely on private economic indicators. Since gold does not generate interest income, it typically performs well in low-interest-rate environments and periods of economic uncertainty. Gold Technical Analysis: With the non-farm payroll data still pending, gold prices are likely to fluctuate little tonight, mainly consolidating. The battle between bulls and bears continues throughout the day. During the US session, gold rebounded to around 4027. We had already positioned short positions at 4015 and 4025, which subsequently fell back as expected, resulting in a profitable trade. This week's trading session has concluded perfectly, and we will not participate in the late-session trading. Our strategy remains to short below 4030. From a technical analysis perspective, key resistance and support levels need to be monitored. The upper resistance level to watch is the 4020-4030 area. If gold prices can break through this range and hold, the upward trend may continue in the short term, potentially challenging higher levels. Before this breakout, we have consistently emphasized against chasing highs and have provided a strategy and analysis for shorting in batches around the 4015-4030 area. Those who follow me should have seen this. Gold faces significant upward pressure, and unless there is a major positive news event to stimulate a breakout, we will continue to maintain a strategy of selling on rallies. Due to the lack of non-farm payroll data, gold prices will continue to be treated as oscillating. The lower support level is seen in the 3975-3960 area. If this support level is effectively broken, it may trigger a new round of declines, potentially opening up further downside potential.
OANDA:XAUUSDShort
by Daniel_PrimeFX
DXY ANALYSIS: TRADING WEEK 3 - 7 NOVEMBER 2025On this video i higlight the importance of the 101.800 area of resistance, a multi year resistance that on my view will be reached soon I have two possible scenarios for the DXY next week: - Test of the 101.800 during the first 2/3 trading days and pullback to the 97,700 area of support where the DXY would cover a gap left open 3 weeks ago and where the DXY will start rallying up again - Test of the 101.300 - 101.500 level of resistance during the first 2/3 trading days and pullback to the 98.500 - 98.400 area of support where the DXY will start rallying up again Data released through the week and the strength of the Index will ultimately confirm one of the two scenario I will update and follow up on this trading analysis - setup; please like, comment and share if you like this Trading Idea
TVC:DXYLong
by SalvoVaccaro