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Currencynerd

the market trinity ( power of 3 )The Hidden Phases of Smart Money: Accumulation, Manipulation, and Distribution Markets don’t move randomly, they move in cycles. Behind the price action, smart money (institutions, market makers, and big players) follow a playbook designed to take liquidity from retail traders. If you learn to spot these phases, you can stop trading against smart money and start aligning with it. The three key stages are: Accumulation, Manipulation, and Distribution. 🔹 1. The Accumulation Phase The Accumulation Phase is where smart money builds positions quietly. Price consolidates in a range, creating the illusion of indecision. To the untrained eye, this looks like “choppy sideways action,” but it’s a setup. What happens here? Price ranges sideways. Stop-losses build up below range lows (for bullish traders) and above range highs (for bearish traders). Liquidity pools form on both sides of the consolidation. Think of this phase as the “loading zone.” Institutions want to accumulate without driving price too high too quickly. The range traps traders into thinking the market is stagnant, while in reality, it’s building energy for the next move. 🔹 2. The Manipulation Phase Once enough orders are sitting around the range, smart money springs the trap. A false breakout occurs: If price breaks below the range → it triggers stop-losses of longs and tempts new shorts to enter. If price breaks above the range → it traps shorts and invites fresh longs to jump in. This is where retail traders get shaken out. The breakout looks convincing, but it’s engineered to harvest liquidity. Why does this happen? Markets need liquidity to move. By manipulating price beyond obvious levels, smart money collects the orders they need to fuel the real move. 🔹 3. The Distribution Phase After manipulation, the real direction of the market becomes clear. Smart money now drives price in the intended direction, often opposite to what retail traders expect. If the manipulation was a false downside break, the distribution phase will be a strong bullish rally. If the manipulation was a false upside break, distribution unfolds as a bearish decline. This is where the largest and cleanest moves happen. Retail traders who fell for the trap are either stopped out or forced to chase the market at worse prices, fueling the move further. 🎯 Why Understanding These Phases Matters Most traders lose because they trade the manipulation, not the distribution. They see a breakout and jump in exactly when smart money is unloading positions. If you want to flip the script: Identify Accumulation: Watch for tight ranges where liquidity builds. Anticipate Manipulation: Don’t get baited by the first breakout. Ride Distribution: Once the trap is set and reversed, that’s your chance to align with the smart money move. Nerdy Thoughts Trading isn’t just about indicators or chart patterns, it’s about psychology and liquidity. The Accumulation → Manipulation → Distribution cycle reveals the hidden structure behind price action. Next time you see a range, don’t just ask, “Which way will it break?” Instead, think, “Where is smart money likely to trap the crowd before the real move begins?” That shift in perspective could be the difference between trading against the tide and riding with it. 💡 Nerd Note: If you start spotting these cycles on multiple timeframes, you’ll notice how fractal the market really is, the same phases repeat inside bigger phases. The market is a story of traps within traps, and your job as a trader is to read the script, not fall for it. put together by : Pako Phutietsile as @currencynerd
COINBASE:BTCUSDEducation
by currencynerd
A Framework for Survival and GrowthTrading isn’t just about spotting patterns or indicators — it’s about survival, consistency, and growth. Without rules, the market will chew you up and spit you out. Trading is also simple but not easy. The market doesn’t owe you consistency, it rewards process. These seven rules are not motivational slogans: they’re operating principles you must turn into habits. Below each rule you’ll find why it matters, how to apply it, and concrete actions you can take on charts today. 1) Protect Your Capital First ( capital is king ) Why it matters Capital is your optionality. Lose it quickly and you cannot trade to recover. Bigger wins mean nothing if you’re repeatedly wiping accounts. Trading is a longevity game: the longer you survive, the more compounding edge you’ll capture. nerdy tip : Treat capital like ammo. Allocate risk so you can survive a losing streak. Define maximum drawdown limits for your account and stop trading if you exceed them. Avoid strategies that require frequent large bets or Martingale-style scaling. how to apply, example : Risk per trade: 0.5%–1% of account equity (conservative) or up to 2% (aggressive, but rare). Example calculation (step-by-step): account = $10,000; risk = 1% → risk amount = $10,000 × 0.01 = $100. If your stop is 40 pips, value per pip = $100 ÷ 40 = $2.50 per pip. Size your position so one pip equals $2.50. Set a daily-stop: e.g., if you lose 3% in a day ($300 on a $10k account), stop trading for the day. Reset, review, and return tomorrow. 2) Trade with a Plan ( Risk : Reward (R:R) — don’t trade where math is against you ) Why it matters Win rate and R:R together determine expectancy. You can be profitable with a low win rate if your winners are large enough; conversely, a high win rate with tiny winners and large occasional losses will still lose money. nerdy tip : Target trades with at least 1:2 R:R as a minimum. Better setups often give 1:3 or more. Use partial profits and trailing stops to convert large theoretical targets into realizable gains. how to apply : Expectancy example (clear math): Win rate = 40% (0.40), average winning trade = 2R, average losing trade = 1R. Expectancy per trade = (0.40 × 2R) − (0.60 × 1R) = 0.8R − 0.6R = 0.2R. That’s positive expectancy. Always calculate required move to hit your TP: if your stop = 40 pips and target = 80 pips, you have 1:2 R:R. Enter only if that setup is realistic given structure and volatility. 3) Stoploss = Lifeline Why it matters Stops are not bureaucratic—they’re your survival mechanism. Without a stop you trade with hope, not probability. The stop defines risk; the rest of your trade plan depends on that known value. nerdy tip : Place stops at structural invalidation points, not arbitrarily. The best stops say: “If price gets here, the trade idea is invalid.” Prefer volatility-aware stops (e.g., ATR-based) when markets are noisy; prefer structure-based stops when levels are clear. how to apply it : Use the Average True Range (ATR) to account for volatility. Formula: Stop distance = ATR(14) × multiplier (1.0–1.5) Example: If ATR(14) = 20 pips on EURUSD and you use a 1.2 multiplier → stop = 20 × 1.2 = 24 pips. This adapts to current volatility instead of using a fixed, unrealistic number like 75 pips in tight pairs. Buffer Stop (Anti-Stop Hunt) Add a small buffer (2–5 pips for majors, slightly more for volatile pairs) beyond obvious highs/lows. Purpose: avoid being wicked out by stop-hunts, but keep the risk controlled. Trailing Stop (Locking in Profits) As the trade moves in your favor, trail your stop to lock in gains without exiting too early. Methods: Fixed pip trail: e.g., move stop up by 15 pips once price is 20 pips in profit. ATR trail: dynamic — stop follows price at a distance of ATR(14) × multiplier (e.g., 1.0). Structure trail: move stop to below each new higher low in an uptrend (or above each lower high in a downtrend). 4) Trend — identify, respect, and choose how to engage it Why it matters Trading with the trend gives you tailwinds. Many retail losses come from “fighting the market.” A clear trend increases the probability that pullbacks will resume in the same direction. nerdy tip: Determine higher-timeframe (HTF) bias first. Use daily/4H for swing trades; 4H/1H for intraday. Label the HTF as bullish, bearish, or range. Trade in the direction of HTF bias when possible. In a strong trend, prefer pullback entries (trend-following). In ranges, prefer range strategies (fade the extremes). how to apply it : Trend identification checklist: HTF HH/HL = uptrend; LL/LH = downtrend. Confirm with a simple moving average slope or higher-timeframe structure break. Pullback entry rule in a bullish trend: wait for price to retrace to a confluence zone (moving average + prior support + demand zone) and show LTF rejection (reversal bar, bullish engulf, or momentum candle) before entering. If the market shows structure break on HTF, treat the trend as weakened and either reduce size or switch to structural reversal rules. 5) Kill Emotions — build systems so emotions cannot destroy logic Why it matters Fear and greed are predictable: fear causes premature exits; greed causes size creep; revenge trading follows losses with impulsive bets. Good process neutralizes emotion. nerdy tip : Replace feelings with rules. Create a pre-trade checklist and an emergency stop-trading rule (if you break rules/size, stop for the day). Use automation: limit orders, OCO orders (one-cancels-other), and predefined trade templates to avoid impulsive market orders. how to apply it : Pre-trade checklist (must be read aloud or checked): HTF bias? Setup valid? Entry level? Stop placed? Size correct? News window clear? If any “no” — don't trade. Emotional cooldown: after 2 consecutive losers, reduce size by 50% or stop for the session. After a big win, reduce size (to avoid overconfidence). Record emotional state with each trade in your journal — rating 1–5 — and track patterns (e.g., most mistakes happen at 9–11 PM). 6) Plan > Impulse (your plan is the only scalable edge) Why it matters Impulse destroys positive expectancy. A plan captures your edge; impulse leaks it away. Trading is not about how many ideas you have — it’s about disciplined execution of a few good rules. nerdy tip : Every trade must be part of a documented plan: bias → setup → entry → stop → targets → size → management → invalidation. Use simple, testable rules you can backtest or forward-test with a demo. how to apply it : Trade ticket template to fill BEFORE entry: Pair / Timeframe / HTF bias / Setup type / Entry price / Stop price / Position size / Target(s) / R:R / Reason to take trade. If you can’t complete it, don’t take the trade. Management plan examples: take 30% at 1R, move stop to breakeven on 50%, trail by ATR or swing lows afterward. Decide these before entry and stick to them. 7) Review & Evolve — data over ego Why it matters If you don’t measure, you can’t improve. The market changes; what worked last year may fail next. Regular review converts experience into repeatable improvements. nerdy tip : Keep a trade journal (yes, every trade). Analyze metrics monthly and iteratively adjust one variable at a time. Use quantitative metrics: win rate, average R per trade, expectancy, max drawdown, average hold time. how to apply it : Minimum journal fields: date, pair, timeframe, direction, entry, stop, size, R multiples (entered risk as R), outcome, notes, emotional state, lesson. Review ritual (weekly/monthly): calculate expectancy = (win rate × avg win) − (loss rate × avg loss). If expectancy is negative, stop and debug—don’t keep trading hoping it reverses. Evolve by A/B testing changes: e.g., change stop placement or time-of-day filter and run 50 live/demo trades to compare outcomes. Quick practical checklist ( BONUS SECTION ) : HTF bias labeled (✔) Setup aligns with bias (✔) Stop based on structure/volatility (✔) R:R ≥ 1:2 (or plan for partials) (✔) Position size aligns to risk% per trade (✔) Pre-trade checklist completed (✔) Post-trade journal entry made (✔) Final words : make these rules habits, not afterthoughts Rules alone don’t make you profitable; habits do. Turn each rule into a checklist, run the checklist before and after trades, and make the review process non-negotiable. Start by fixing one rule for 30 days — for example: “I will never risk more than 1% per trade.” Once that becomes habit, add another. Small persistent put together by : Pako Phutietsile as @currencynerd
OANDA:XAUUSDEducation
by currencynerd
market memory, the many faces of support and resistance.Every trader is introduced to support and resistance (S&R) early on. At first, it looks simple: support is where price stops falling, and resistance is where price stops rising. But the more screen time you log, the clearer it becomes that this tool is not just a “line on the chart.” It comes and is taught in many forms: sometimes sharp and obvious, other times hidden and subtle. The challenge for traders is to recognize which form the market is respecting at any given moment. Let’s go deeper into the different types of support and resistance, how they work, and why they matter. but first there is one golden rule of support and resistance, past support turns into resistance and vice versa, try to look closely at the chart examples i will present and watch how price reacts to the S&R zones and levels, and how this plays out... 1. Horizontal Support and Resistance – Market Memory in its Purest Form The most classic form of S&R is drawn horizontally at prior swing highs and lows. Price touches a level multiple times, and traders begin to see it as significant. Why it works: Markets are driven by collective memory. If price was rejected at 1.1000 three times before, traders naturally hesitate around that level again. Buy orders cluster below old lows, and sell orders cluster near old highs. How to trade: Bounce trade: Wait for price to retest the zone; enter on confirmation (pin bar, engulfing bar, volume spike). Place stop beyond the opposite edge of the zone or beyond the reaction candle wick. Break & retest: When a level breaks with conviction, wait for price to retest it from the other side. That retest becomes a new entry with confluence (volume, SMA, trendline). Use RR (reward:risk) based on the zone width. Don’t expect perfect fills — treat zones as areas. Pitfalls & pro tips: Fakeouts are common: institutional players sweep stops to gather liquidity. Expect occasional whipsaws. Vertical significance matters: daily/weekly horizontals are more reliable. Volume or momentum at the reaction adds conviction. A horizontal with no volume is weaker. chart example : the chart above is represented by candlesticks and for beginner traders it might be hard to spot the support and resistance levels from that chart but one hack is to use the line chart because the line chart shows only the closing price and candlestick shows extreme highs and lows that can be misleading. the chart below represents the same chart above but as a line chart. you want to plot your s&r levels around levels where price is making peaks and valleys like i have highlighted in the chart when you turn your chart type back to candlesticks after plotting on the line chart you are able to clearly see the levels.. on the recent above chart i have shown the resistance price reactions (support holding up) below is the same chart representing support another example is the golden rule i mentioned above being in play, here previous resistance later holds up as support chart example 2: highs and lows this shows how previous day high of day 1 acts as resistance on day 2 2. Trendline Support and Resistance – Dynamic Barriers in Motion Unlike horizontals, trendlines are angled. By connecting higher lows in an uptrend or lower highs in a downtrend, you create a slope the market respects. Why it works: In trending markets, buyers and sellers don’t step in at fixed prices—they react to rhythm. Trendlines capture that rhythm and act as visual guides for momentum. The nuance: Trendlines are highly subjective. Two traders may draw slightly different lines, and both might be “right.” The key is consistency—decide whether you draw them on candle bodies or wicks and stick to it. How to trade: Lean with the trend: buy touches of ascending trendline with tight confirmation. Channel trades: buy near lower band, target midline or upper band; sell vice versa. Breaks: a decisive break of a trendline with retest is often a momentum shift; trade the retest for continuation in the new direction. Pitfalls & pro tips: Lines are subjective — treat trendlines as a tool, not gospel. Re-draw only on new confirmed swings; avoid redrawing every candle. Combine with volume, moving averages or structure breaks for stronger signals. chart example : 4. Fibonacci Retracements & Extensions – Ratios of Market Psychology Fibonacci levels (38.2%, 50%, 61.8%, etc.) are not magical numbers; they are psychological checkpoints where traders expect pullbacks. Why it works: Fib levels are used globally, and like MAs, they become self-fulfilling. Many institutional algos also use ratios in trade planning, reinforcing their influence. How to identify: Choose structural swings—the most recent meaningful high and low. Treat levels as zones, not exact lines. Prefer Fib confluence: a Fib level that overlaps a horizontal, MA, or trendline is far more actionable. How to trade: Retracement entries: watch for price to pull into a Fib zone and show price-action confirmation (pin, absorbtion, heavy volume). Extensions as targets: use 127%/161.8% as extension targets once trend resumes. Combine with timeframe analysis: a 61.8% on the daily aligned with a weekly level is strong. Pitfalls & pro tips: Picking the wrong swing yields worthless Fib levels—choose structural points. Never trade Fib in isolation. It’s a confluence tool, not a standalone system. chart example identify high and low, because price was trading to the downside i will draw my fib levels from the high to the low i did not add the other fib levels because the chart did not look clear and only highlighted the significant level that price reacted to which is the 38.2% fib level. 3. Supply and Demand Zones – Where Imbalance Rules Supply and demand trading zooms out from single lines to zones. A sudden rally from a base suggests excess demand, while a sharp drop suggests excess supply. Why it works: Big players (banks, funds) often leave unfilled orders in these zones. When price returns, those orders trigger, causing strong reactions. Look for sharp moves with little overlap (big green/red candles leaving a base). Identify the base (consolidation) before the move and mark the zone from the high to the low of that base. Strong zones have speed and size in the move away (single big candle or sequence with increasing momentum). How to trade: Wait for retest: enter when price returns to the zone and shows absorption/buying interest. Use limit entries at the edge of the zone and stop beyond the zone’s opposite edge. Size position according to zone width — wide zones → larger stop → smaller position. Pitfalls & pro tips: Zones can be wide and ambiguous; tighten criteria by requiring a clean move away. Supply/Demand pairs well with orderflow or volume profile for institutional confirmation. chart example rally base rally, CP (continuation pattern) - demand chart 2 rally base drop - supply (PEAK) 4. Psychological and Round Numbers – Human Bias on the Chart Markets are human-driven, and humans love round numbers. EUR/USD at 1.2000, gold at $2000, Dow at 40,000—these levels attract attention. Why it works: Traders place stop-losses, take-profits, and pending orders around round figures. Liquidity clusters here, making them magnets for price. Round numbers are less about “holding” price and more about being zones where reactions happen. Price often overshoots before reversing, because stop-hunts occur just beyond these figures. How to identify: These are obvious: whole figures, halves, quarters (1.2000, 1.2500, 1.5000). Watch the tighter structural closeness: a round number that sits exactly on a daily swing is stronger. How to trade: Fade or follow: some traders fade the hesitation around a round number (fade the hesitation wick), others ride through on breakout if momentum is strong. Use round numbers as confluence, pair them with horizontal, Fib, or MA for stronger setups. Pitfalls & pro tips: Round numbers attract stop clusters; expect overshoots. Don’t assume a clean bounce every time. Big figures on high-liquidity pairs (EUR/USD) behave differently from lower-liquidity assets. chart example : resistance price : 3,700.000 support price : 3,680.000 Liquidity Pools – Advanced Market Microstructure liquidity pools to me are not levels but zones on a price chart where a large volume of pending buy stop-loss orders and sell stop-loss orders have accumulated. i identify them by connecting highs and lows / significant levels that are close together but not close to be connected by a singular line. Why it works: Institutions need liquidity to fill massive orders. They manipulate price into zones where retail traders’ stops sit. Once liquidity is captured, the real move begins. The nuance: Order blocks and liquidity pools require skill to read. They are not always obvious and can trap new traders who misinterpret them. Pitfalls & pro tips: This discipline is subtle; misreading an order block is common. Backtest and annotate many examples. chart example : The Bigger Picture – One Concept, Many Faces Support and resistance is not one tool, it is a family of tools. From clean horizontals to hidden liquidity pools, each type reflects a different aspect of market psychology. The real skill is not memorizing them all, but asking: Which type of support or resistance is the market respecting right now? When you start seeing markets this way, S&R stops being “lines on a chart” and becomes a living, breathing map of trader behavior. put together by : Pako Phutietsile as @currencynerd
OANDA:XAUUSDEducation
by currencynerd
when human error causes institutional chaos WHEN THE HOUSE OF CARDS FELL a concise look at history’s largest trading disasters. Intro Markets make fortunes, and erase them. Some of the largest drawdowns in modern financial history weren’t caused by market moves alone, but by human error, hubris, weak controls, or leverage run amok. Below are the most instructive episodes. 1) Nick Leeson — Barings Bank (1995) What was traded: Futures and options on the Nikkei 225 and other Asian equity derivatives (hidden in an error account). Losses: ~£827 million (the final number widely reported; Barings collapsed and was bought by ING). Why it happened: Unauthorized speculative bets, concealed losses in a hidden account, and complete breakdown of segregation between front and back office responsibilities. Lesson for traders: Always enforce separation of duties, log and reconcile trades daily, and respect position-size limits. Small hidden losses compound quickly when someone doubles down to "recover." 2) Long-Term Capital Management (LTCM) (1998) What was traded: Highly leveraged fixed-income arbitrage and complex derivatives (relative-value trades across bonds and swaps). Losses: About $4.6 billion in a few months and a near-collapse that required a $3.65 billion private-sector bailout organized under the Federal Reserve’s supervision. Why it happened: Massive leverage, concentrated positions, reliance on models that assumed low tail risk, and liquidity drying up after the 1997–98 crises. Lesson for traders: Models are only as good as their assumptions. Always stress-test for extreme events and never confuse historical volatility for guaranteed stability. 3) Amaranth Advisors — Brian Hunter (2006) What was traded: Natural gas futures and swaps (directional bets on gas prices). Losses: Around $6.6 billion (almost the entire fund). Why it happened: A massive one-way bet in a single commodity market, extreme exposure during a short time window, and insufficient risk checks on position concentrations. Lesson for traders: Diversify exposure, cap concentration per market, and use stop rules — particularly with volatile commodities. 4) Société Générale — Jérôme Kerviel (2008) What was traded: Large, unauthorized equity index and delta-hedging derivatives positions. Losses: €4.9 billion reported by the bank. Why it happened: A junior trader built enormous notional exposure hidden behind falsified trades and offsets; internal controls failed to detect the pattern early. Lesson for traders: Strong surveillance, automated alerts for notional buildup and mismatches between booking and market flows are mandatory. No trader should have the ability to both create and hide offsets. 5) JPMorgan Chase — "The London Whale" (2012) What was traded: Complex credit derivatives (CDS indices and related structured trades) booked by the Chief Investment Office. Losses: Approximately $6 billion (publicly reported as the headline figure). Why it happened: Large, illiquid positions taken under the guise of hedging; risk management misclassification and insufficient oversight of the desk’s activity. Lesson for traders: Question “official” hedges and track mark-to-market transparency. Size matters — large positions in illiquid markets behave unpredictably. 6) UBS — Kweku Adoboli (2011) What was traded: Equity derivatives and ETFs; fraudulent booking to hide true exposures. Losses: About $2.3 billion for UBS. Why it happened: Unauthorized trading far beyond limits, with fictitious trades used to mask losses. Lesson for traders: Controls matter: independent confirmations, reconciliation of booked trades with exchange/clearing records, and strong escalation procedures. 7) Sumitomo Corporation — Yasuo Hamanaka (1990s) What was traded: Copper futures and long-running attempts to corner the copper market. Losses/impact: Reported losses and claims ran into the billions (estimates vary), with major disruption to the LME and legal fallout. Why it happened: Single-commodity domination attempts, manipulation, and weak counterparty surveillance. Lesson for traders: Markets punish attempts to dominate a price. Avoid attempting to influence markets and respect regulatory/ethical boundaries. 8) Archegos Capital Management (2021) What was traded: Highly leveraged equity positions via total return swaps and prime broker financing. Losses: Bank losses linked to Archegos exceeded $10 billion across multiple counterparties. Why it happened: Extreme use of leverage through opaque swap structures, concentrated bets, and inadequate margining/aggregation across prime brokers. Lesson for traders: Leverage can be hidden — counterparties and traders must track true economic exposure. Concentration plus leverage is the most dangerous combination. Common themes across disasters Leverage + Concentration = Catastrophe. Almost every case involved outsized positions funded with borrowed money. Control failures matter more than market moves. Rogue behavior and poor internal controls are repeated patterns. Liquidity risk is underestimated. Markets that look liquid in calm times can evaporate in stress. Model humility. Models help, but they don’t replace common sense or scenario thinking. Actionable rules for retail traders (quick checklist) Limit leverage and set absolute position-size caps. Use stop losses and pre-defined exit rules. Reconcile trades daily with your broker statements. Stress-test your portfolio for extreme but plausible moves. Keep a trading log and review losing trades objectively. outro: memory from history Big losses make for great cautionary tales. Whether you trade FX, futures, or equities, the mechanics are the same: manage size, diversify, and build systems that work for you. put together by : Pako Phutietsile as @currencynerd
OANDA:XAUUSDEducation
by currencynerd
retail trading strategies **review**Intro : Over the past two decades retail forex traders have gathered around a handful of trading methods, some taught by personalities, other emerging from various trading online communities. These strategies range from rules-based technical systems to conceptual frameworks and mostly try to explain large institutional behavior. Most of these strategies are the ones that i have come across in my trading journey. What this is not : a promise of riches, holy grail system, It's a technical and practical review so you can evaluate, backtest, and adapt. 1) Beat the Market Maker — Steve Mauro (i) Overview: Popularized by Steve Mauro, this approach claims that major institutions (market makers) manipulate retail orderflow to generate liquidity. The method focuses on identifying accumulation/distribution phases and the ensuing directional move. Core ideas & rules: Identify periods of consolidation where "market makers" are believed to be accumulating. Look for shakeouts (false-breaks) designed to hit stop clusters, then trade the ensuing impulse move. Use support/resistance, liquidity pools (highs/lows), and structure breaks as confirmation. Key tools: structure (swing highs/lows), volume spikes (if using a data feed that shows volume), and range breakout fails. Strengths: Provides a narrative for why false breakouts occur and where liquidity sits. 2) ICT (Inner Circle Trader) Concepts — Michael Huddleston Overview: ICT is a comprehensive set of market concepts and tactics covering market structure, institutional orderflow, liquidity, and time-of-day edges (e.g., London Open, New York Open). It mixes SMC ideas with very specific rules (split tests, fair value gaps, breaker blocks). It also important to know it's always evolving. Core elements: Market structure shifts (MSH/MSL) Fair Value Gaps (FVG) — price imbalances to be filled Order blocks — candles/areas where institutions allegedly placed big orders Optimal trade entry (OTE) using Fibonacci retracements, often 61.8–79% Time-based edges and correlation analysis Strengths: Detailed playbook with clear confluence rules — useful for disciplined traders. 3) Smart Money Concepts (SMC) Overview: SMC is an umbrella term (overlapping heavily with ICT) used to describe approaches that try to model institutional behaviour: liquidity grabs, order blocks, fair value gaps, and structure breaks. Typical rules: Wait for liquidity sweeps (wick hunts) that break obvious swing highs/lows. Identify the return to an order block or imbalance as a high-probability entry. Only take trades in the direction of higher timeframe structure. Strengths: Emphasizes risk management and trading with institutional flow. 4) Supply and Demand Trading ( my personal favorite) Overview: Basically this is the imbalance between buyers and sellers, the greater the imbalance, the greater the move. A widely used retail approach that focuses on identifying institutional footprints. The idea is that price tends to revisit these levels because unfilled orders remain. Core ideas: Supply zones: areas where heavy selling originated, typically sharp moves away from consolidation. Demand zones: areas where aggressive buying originated. Trade the first return to these zones with stop-loss beyond the zone, with the entry being the proximal price and stop loss just a few pips from the distal price. Strengths: Provides clear areas of interest for entries/exits, often aligning with institutional footprints. 5) Price Action (Naked Trading) & Candlestick Patterns Overview: Pure price action traders use raw price and candle formations (pin bars, inside bars, engulfing patterns) rather than indicators. Core ideas: Read support/resistance structure Use rejected wicks/pin bars as entry signals Combine with orderflow context (higher timeframe structure) Strengths: Lightweight, transferable across markets, robust if rules are clear. 6) Wyckoff Method Overview: A classic institutional-style framework (dating earlier than 20 years but widely revived) focusing on accumulation, markup, distribution, and markdown phases. Core ideas: Identify phases (A–E) and spring/spring failures Volume and price structure show the footprints of large operators Strengths: Provides a stage-based map of market cycles; excellent for swing traders. 7) Order Flow / Volume Profile (Footprint-style thinking) Overview: Order-flow traders analyze where traded volume clusters and how price reacts to those clusters. In spot forex, exact volume data is limited, traders use tick volume or correlated markets. Core ideas: Volume Profile shows value areas, POC (point of control), and high-volume nodes Rejections from value areas often lead to directional moves Strengths: Gives a textured read of where supply/demand imbalance exists. 8) Trend-following & Moving Average Systems Overview: Simple, time-tested approach using moving averages, breakouts, and momentum to ride sustained trends. Core ideas: EMA crossovers (e.g., 8/21/55) or price above/below a long MA Use ADX or RSI to confirm trend strength Strengths: Low subjectivity, easy to automate, works well in trending markets. 9) Grid & Martingale (Controversial retail staples) Overview: Grid and martingale methods place multiple orders at fixed intervals or double down after losses. Core ideas: Grid: place buy/sell orders at intervals to capture mean reversion. Martingale: increase position size after losses to recover. Strengths: Can generate small, steady returns in low-volatility ranges. 10) Fibonacci & Harmonic Trading Overview: Fibonacci retracement/extension levels and harmonic patterns (Gartley, Bat, Butterfly) are price geometry approaches used for precision entries. Core ideas: Use Fibonacci retracement for pullback entries (38.2 / 50 / 61.8) Harmonic patterns require precise ratios to qualify, the same fib levels. Strengths: Clear entry/target geometry; widely taught, backed by math gods (hahaha) nerdy advice: Backtest before you believe. Use TradingView’s strategy tester or export historical bars for offline testing. Define objective rules. Ambiguity kills consistency; translate concepts (e.g., "order block" or "demand zone") into a reproducible rule set. Risk management is king. Use fixed fractional sizing, stop-loss placement based on structure, and stress-test for tail events. Simplicity beats complexity. Too many overlapping rules reduce clarity and make optimization fragile. Document setups. Save your @TradingView ideas with full annotation so you can later audit winners and losers. put together by : Pako Phutietsile as @currencynerd *** i also like supply and demand because most these strategies use supply and demand but under different titles, for example an ict trader calls supply and deand CP,s order blocks..
Education
by currencynerd
2
september effect: why markets seem to catch a cold every fall📉 The September Effect chart example: average monthly returns of the S&P500 since 1928 Every year, as summer ends and September rolls in, traders brace themselves. Why? Because the “September Effect” is notorious for turning even the steadiest markets into a rollercoaster. Understanding this seasonal quirk can make the difference between a smooth ride and a portfolio wipeout. 📊 What Is the September Effect? The September Effect is the observed tendency of financial markets to underperform during September. Historically, it’s one of the worst months for equities, currencies, and even commodities. Some reasons behind it: Institutional Moves: Big players return from summer breaks, recalibrating portfolios. Expect sudden spikes in activity and volatility. Quarter-End Adjustments: September marks the end of Q3, often triggering rebalancing or profit-taking. Economic Releases: Important data (jobs, inflation, trade figures) often drop in September, leading to sharp market reactions. 🌍 How It Hits Global Markets The effect isn’t just local—it ripples across the globe: Equities: Indices like the S&P 500 and FTSE historically trend lower more often in September than other months. Currencies: Pairs involving USD, EUR, and JPY can swing wildly as traders reposition ahead of data releases. Commodities: Gold, oil, and other commodities may see sudden shifts based on sentiment, hedging, or macroeconomic expectations. 🔍 Navigating September Without Panic You don’t have to fear September—it just requires smarter strategies: Tight Risk Management: Stop-losses, hedging, and diversification are your best friends. Stay Updated: Economic reports, geopolitical events, and central bank actions can set the tone. Chart Smarts: Technical patterns and indicators can guide better entries and exits amid the volatility. above chart shows the historical average of major indicies.. The Takeaway The September Effect is real, but it’s not a doom prophecy. Recognizing it allows traders to plan, protect, and even profit from seasonal swings. The markets may shiver in September—but with the right strategy, your portfolio doesn’t have to. put together by : @currencynerd
BITSTAMP:BTCUSDEducation
by currencynerd
8
timeline of GeniusThe Greatest Financial Minds Who Shaped the Trading Industry In trading, we often obsess over charts, entries, and exits, forgetting that the very foundation of our craft was built by great thinkers who saw beyond their time. These financial minds left behind legacies that continue to guide us every time we analyze a chart, hedge a risk, or speculate on a macro event. Let’s revisit some of these giants and unpack how they shaped the industry we trade in today. 1. Charles Dow – The Father of Technical Analysis Charles Dow wasn’t just a journalist; he was the architect of modern charting. By co-founding the Dow Jones & Company and creating the Dow Jones Industrial Average, he gave traders the first roadmap for analyzing price trends. His Dow Theory established concepts like market phases, primary vs. secondary trends, and the importance of volume. Without Dow, many of the indicators we use today would never exist. Impact: Every trader who draws a trendline, identifies a trend, or follows market cycles is echoing Dow’s work. Nerd Note: Dow didn’t just invent an index, he invented the idea of reading psychology through price. 2. Jesse Livermore – The Legendary Speculator Known as the "Boy Plunger," Jesse Livermore became one of the most famous traders of the early 20th century. He made (and lost) fortunes multiple times, most notably shorting the 1929 crash. His trading principles, cutting losses quickly, pyramiding into winners, and following the tape remain timeless. Impact: Livermore’s lessons on discipline and emotional control still serve as the blueprint for risk management today. Nerd Note: His trading diary might be 100 years old, but it still sounds like conversations on @TradingView today. 3. John Maynard Keynes – The Economist Who Traded Keynes wasn’t just an economist who reshaped government policy; he was also an active trader. He pioneered the idea that markets are not always rational famously saying, “The market can stay irrational longer than you can stay solvent.” His insights on market psychology and long-term investment influenced both central banks and portfolio managers. Impact: Keynes helped bridge economics and market behavior, reminding traders to respect liquidity and irrationality. Nerd Note: Keynes wasn’t just about theories, he pioneered diversification and professional portfolio management. 4. Paul Tudor Jones – The Modern Macro Trader Paul Tudor Jones became legendary for predicting and profiting from the 1987 crash. His trading style blends technical analysis with global macro themes, proving that successful trading is both art and science. He also emphasized risk management, famously never risking more than a small percentage of capital on one trade. Impact: His approach paved the way for today’s macro hedge funds and continues to inspire traders balancing fundamentals with charts. Nerd Note: PTJ is proof that charts + macro = a lethal combo. 5. Richard Dennis – The Turtle Trader Experiment Richard Dennis believed that trading could be taught. To prove it, he trained a group of novices later called the Turtle Traders and turned them into millionaires using a simple trend-following system. This experiment became proof that discipline and systemization can outperform emotion and intuition. Impact: Dennis democratized trading, showing that rules-based strategies could be replicated and mastered. Nerd Note: If you think rules-based trading is “too mechanical,” Dennis showed why systems often outperform emotions. 6. George Soros – The Man Who Broke the Bank of England Soros etched his name in history by shorting the British pound in 1992, making over $1 billion in a single trade. But his real genius was in reflexivity theory the idea that market participants’ biases can influence fundamentals, creating feedback loops. Impact: Soros expanded how we think about market psychology and global macro risk-taking. Nerd Note: Soros reminds us that market psychology isn’t just noise it’s a driver. 7. Edward Thorp – The Quant Pioneer A math professor turned investor, Edward Thorp applied probability theory to both blackjack and the stock market. His book Beat the Dealer revolutionized casinos, while Beat the Market introduced quantitative trading strategies. He was one of the first to use options pricing models profitably before Black-Scholes became mainstream. Impact: Thorp laid the foundation for quantitative trading and hedge funds, influencing everything from algorithmic trading to derivatives pricing. Nerd Note: Thorp’s legacy is alive every time an algo executes a trade in milliseconds. Outro The trading industry wasn’t built overnight it stands on the shoulders of visionaries who combined intellect, courage, and sometimes sheer audacity. Whether you’re drawing lines on a chart, running a trading bot, or hedging a portfolio, you’re applying principles these financial minds helped craft. As traders, we don’t just inherit their ideas we adapt them, test them, and carry them forward into the markets of tomorrow. Nerd’s final Take: Trading is not just about screens and signals; it’s a living history. Every trade you take is part science, part psychology, and part homage to the legends who paved the way. Which of these financial giants do you think shaped trading the most and who should we as traders study harder today? put together by : Pako Phutietsile as @currencynerd
BITSTAMP:BTCUSDEducation
by currencynerd
separating Myth from MethodTrendlines: The Most Misused Tool in Trading If I had a pip for every time a trader got faked out by a “trendline breakout,” I’d probably have more profits than most retail traders combined. Trendlines are one of the simplest, oldest, and most powerful tools in technical analysis yet they’re also one of the most misused. Most traders rely on what they’ve been taught in books, courses, or quick YouTube tutorials without putting in the hours of backtesting and screen time. And as every trader eventually learns: theory is a different game than practice. A book may say: Buy the breakout of a bearish trendline. But in practice? Price fakes out, you get stopped, and frustration builds. Or: Sell at the touch of a bearish trendline. Then price rallies and breaks the line. Again, stopped out. The problem? Markets love to trap traders here. False breakouts, wicks, and algo-driven liquidity hunts chew up traders who rely only on “trendline piercing.” If that’s your main strategy, you’re not trading the market, the market is trading you. But here’s the truth: trendlines aren’t the problem. The way traders use them is. This doesn’t mean the trendline is invalid. It means the application is shallow. For me, trendlines are non-negotiable when analysing. But I don’t take trades just because of a line. I use them in specific, tested ways that give structure to my trading and reduce false signals. Here are the two core methods I use trendlines in my trading: 1. Trendlines as a Measure of Momentum Momentum is the speed of price, not just the price itself. And trendlines can act as leading indicators of momentum shifts. For example: A break of a bullish trendline doesn’t instantly mean “sell.” It means momentum has shifted from bullish to bearish. That’s my cue to look for sell setups that align with my strategy. As long as price respects a bullish trendline, it signals buyers are in control, and I look for buy setups. Vice versa for bearish lines. Think of trendline breaks not as signals but as context for setups. They tell you where the wind is blowing, not when to set sail. For me, a trendline break means nothing unless a full OHCL candle (Open, High, Close, Low) forms entirely above or below the line. Why? Because a wick through a trendline is just noise, it’s the market testing liquidity, not shifting momentum. A confirmed close beyond the trendline signals that the crowd has moved, and the trend’s character is changing. This approach drastically reduces false signals. Instead of jumping at the first poke through the line, I wait for commitment. Think of it like waiting for the market to sign the contract rather than just flirt with the idea. chart example : 2. Trendlines as Dynamic Support & Resistance The second use is less about breakouts and more about reaction levels. A clean, well-respected trendline acts like a dynamic S/R zone, guiding how price reacts when tested. In uptrends, I look for bounces off the rising trendline as opportunities to join the momentum. In downtrends, I treat the falling trendline as overhead resistance a zone to fade rallies or time entries. What makes trendlines powerful here is context: they’re not static like horizontal levels but move with the market’s rhythm adapting as price makes new highs or lows. When combined with volume, candlestick structure, or confluence with horizontals, they create highly reliable zones. Yes, false breaks happen but this is where order flow, confluence, and top-down analysis come in. The more aligned factors you stack with a trendline, the higher the probability of a valid setup. chart example : the other great thing about this is that the law for support and resistance also applies here where previous support acts as resistance and vice versa chart example : nerdy conclusion : trendlines alone won’t make you money. They aren’t buy or sell signals by themselves. But used correctly, they’re an incredibly powerful map of momentum and dynamic structure. Most importantly, don’t throw them out just because a few breakouts failed. That’s not the trendline’s fault, it’s the method. The smarter nerdy approach is: Wait for full OHCL confirmation beyond the line before calling it a momentum shift. Use trendlines as dynamic support/resistance to trade with structure, not noise. put together by : Pako Phutietsile as @currencynerd courtesy of : @TradingView
BITSTAMP:BTCUSDEducation
by currencynerd
from Rice to Robots, evolution of TA The History and Origin of Technical Analysis Every chart we study today. Every candlestick, moving average, or RSI indicator is built on centuries of market wisdom. While many believe technical analysis began with Charles Dow in the 1800s, its origins reach much further back, to Amsterdam’s bustling spice markets in the 1600s and Japan’s rice exchanges in the 1700s. Let’s take a journey through time and see how technical analysis evolved into the powerful tool traders and investors use today. 17th Century: The First Signs of Charting 1. Dutch East India Company Traders (1602) The Dutch East India Company, established in Amsterdam in 1602, became the first publicly traded company. Its shares were bought and sold on the world’s first stock exchange, the Amsterdam Stock Exchange. Early traders began tracking price fluctuations in simple graphical forms — the very first steps toward technical analysis. 2. Joseph de la Vega (1650–1692) A Spanish diamond merchant and philosopher, Joseph de la Vega, authored Confusión de Confusiones (1688), the earliest known book on stock markets. He described investor behavior, speculative patterns, and even outlined concepts resembling modern puts, calls, and pools. His insights captured both the psychology of markets and the primitive beginnings of technical analysis. 18th Century: Japan’s Candlestick Revolution Homma Munehisa (1724–1803) In Osaka’s Dōjima Rice Exchange, Japanese rice merchant Homma Munehisa created what remains one of the most widely used charting methods in history: the Japanese Candlestick (then called Sakata Charts). His book The Fountain of Gold – The Three Monkey Record of Money detailed not only price charts but also market psychology, emotions, and crowd behavior. Today, candlestick patterns remain a cornerstone of technical analysis worldwide. Late 19th & Early 20th Century: The Modern Foundations Charles Dow (1851–1902) Often called the father of modern technical analysis, Charles Dow co-founded Dow Jones & Company and The Wall Street Journal in 1889. His market observations led to: The Dow Jones Industrial Average and Transportation Average The Dow Theory, which identified three types of trends: primary, secondary, and minor. Dow believed markets reflect the overall health of the economy, and his work inspired generations of analysts, including William Hamilton, Robert Rhea, George Schaefer, and Richard Russell. Ralph Nelson Elliott (1871–1948) Building on Dow’s ideas, Elliott studied 75 years of stock market data and developed the Elliott Wave Theory, arguing that markets move in recurring wave patterns driven by crowd psychology. In March 1935, he famously predicted a market bottom and the Dow Jones indeed hit its lowest point the following day, cementing his theory’s credibility. 20th Century: The Rise of Indicators The computer era supercharged technical analysis. Mathematically driven technical indicators were developed to analyze price, volume, and momentum on a scale that manual charting could never achieve. Example: RSI (Relative Strength Index) Developed by J. Welles Wilder Jr. in 1978, RSI measures the speed and magnitude of price changes on a scale of 0–100. Above 70 = Overbought (potential sell signal) Below 30 = Oversold (potential buy signal) Other popular indicators soon followed, such as Moving Averages, MACD, and Bollinger Bands, giving traders an expanding toolbox to forecast market movements. 21st Century: From Charts to Algorithms and AI Today, technical analysis has evolved far beyond hand-drawn charts: Algorithmic Trading: Automated systems use indicators and strategies to execute trades at lightning speed. AI Trading Bots: Artificial intelligence combines both technical and fundamental analysis, processing massive datasets to generate signals and even execute trades. Platforms like TradingView: Empower traders worldwide to build custom indicators, test strategies and share insights, democratizing access to advanced market tools. nerdy thoughts From Amsterdam’s first stock traders to Osaka’s candlestick pioneers, from Charles Dow’s theories to AI-powered trading bots, technical analysis has always been about one thing: decoding price to understand human behavior in markets. It’s a discipline born from centuries of observation, innovation, and adaptation, one that continues to evolve every day. “Life is a moving, breathing thing. We have to be willing to constantly evolve. Perfection is constant transformation.” put together by: Pako Phutietsile ( @currencynerd ) courtesy of : @TradingView this is inspired by a publication i once posted this is the revamped edition...
PEPPERSTONE:XAUUSDEducation
by currencynerd
when Jerome says spike, the markets asks how low/high"Watch what they do, but also how they say it." In the high-stakes world of central banking, few things move markets like the subtle wording of a Fed statement, But beyond the headlines and soundbites, one market absorbs this information faster—and with greater clarity—than almost any other: the bond market. 💬 What Is "Fed Speak"? "Fed speak" refers to the nuanced and often deliberately vague language used by U.S. Federal Reserve officials when communicating policy expectations. It includes: FOMC statements Dot plot projections Press conferences Individual speeches from Fed officials nerdy tip: the Fed aims to influence expectations without committing to specific outcomes, maintaining flexibility while steering market psychology. 📈 The Bond Market as a Decoder The bond market, particularly the U.S. Treasury market, is where real-time interpretation of Fed policy plays out. Here's how it typically reacts: 1. Short-Term Yields (2Y, 3M) = Fed Expectation Barometer These are the most sensitive to near-term interest rate expectations. If the Fed sounds hawkish (more rate hikes), short-term yields jump. If dovish (hinting cuts), they fall. At the May 7, 2025 FOMC meeting, the 2-year Treasury yield (US02Y) experienced a modest but clear reaction: Just before the release, yields were hovering around 3.79%. In the first hour following the 2:00 PM ET (20:00 UTC+2) statement, the yield ticked up by approximately +8 basis points, temporarily reaching about 3.87%. Later that day, it eased back to around 3.79%, ending the day roughly unchanged—a sharp, immediate spike followed by a reversion. 2. Long-Term Yields (10Y, 30Y) = Growth + Inflation Expectations Longer-dated yields reflect how the market sees the economy unfolding over time. After a Fed speech: Rising long-term yields = stronger growth/inflation expected Falling yields = fears of recession, disinflation, or policy over-tightening 3. The Yield Curve = Market's Policy Verdict One of the best tools to read the bond market's verdict is the yield curve—specifically, the spread between 10Y and 2Y yields. Steepening curve → Market thinks growth is picking up (Fed may be behind the curve) Flattening or Inversion → Market believes the Fed is too aggressive, risking a slowdown or recession 📉 Example: After Jerome Powell’s hawkish Jackson Hole speech in 2022, the 2Y-10Y spread inverted deeply—markets were pricing in recession risks despite a strong Fed tone. 🧠 Why Traders Must Watch Bonds After Fed Speak 🪙 FX Traders: Higher yields = stronger USD (carry trade advantage) Falling yields = weaker USD (lower return for holding) 📈 Equity Traders: Rising yields = pressure on tech/growth stocks (higher discount rates) Falling yields = relief rally in risk assets 📊 Macro Traders: The MOVE Index (bond volatility) often spikes around FOMC events Forward guidance shifts = big rotation opportunities (e.g., bonds > gold > dollar) (BONUS NERDY TIP) 🔍 How to Analyze Fed Speak Through Bonds ✅ Step 1: Watch the 2Y Yield First responder to new rate expectations. ✅ Step 2: Check the Fed Funds Futures Compare market pricing pre- and post-statement. ✅ Step 3: Look at Yield Curve Movement Steepening or inversion? That’s the market’s macro take. ✅ Step 4: Track TLT or 10Y Yield on Your Chart Bond ETFs or Treasury yields reveal sentiment instantly. 🧭 Final Nerdy Thought : Bonds React First, Talk Later When the Fed speaks, don't just read the words. Read the yields. The bond market is often the first to interpret what the Fed really means—and the first to price in what comes next. So next FOMC meeting, instead of watching only Powell’s facial expressions or CNBC pundits, open a chart of the 2Y and 10Y. That’s where the smart money’s listening. put together by : @currencynerd as Pako Phutietsile courtesy of : @TradingView
COINBASE:BTCUSDEducation
by currencynerd
the markets are a very emotional cry babyIf you've ever asked, “Why is the market going up on bad news?” or “Why did it dump after great earnings?”, you're not alone. Markets may seem logical—economic data in, price action out—but in reality, they’re driven by human emotion, crowd psychology, and reflexive feedback loops. The charts don’t lie, but the reasons behind the moves? Often irrational. Let’s break down why markets are emotional—and how traders can use that to their advantage. 🧠 1. Markets Are Made of People (and People Aren’t Rational) Even in the age of algorithms, human behaviour sets the tone. Fear, greed, FOMO, panic—all of it shows up on charts. Fear leads to irrational selling Greed fuels bubbles and euphoria Uncertainty causes volatility spikes—even with no new information 📉 Example: The 2020 COVID crash saw massive capitulation. Then came one of the fastest bull markets ever—driven by stimulus and FOMO. another example 📊 S&P 500 in 2020 with VIX, the S&P 500 crashed and the VIX went up, When the VIX (CBOE Volatility Index) goes up, it means that traders/investors expect a greater likelihood of price fluctuations in the S&P 500 over the next 30 days. This generally indicates increased fear as shown on the chart below 📈 2. Price Doesn’t Reflect Facts—It Reflects Belief The market is not a thermometer. It’s a barometer of expectations. When traders believe something will happen—whether true or not—price adjusts. If the Fed is expected to cut rates, assets may rally before it actually happens. 💡 Nerd Tip: Reality matters less than consensus expectations. Chart Idea to visit: 💬 USD Index vs. Fed rate expectations (2Y yield or futures pricing) 🪞 3. Reflexivity: Belief Becomes Reality Coined by George Soros, reflexivity explains how beliefs can influence the system itself. Traders bid up assets, creating bullish momentum That momentum attracts more buyers, reinforcing the trend Eventually, fundamentals “catch up” (or the bubble bursts) 📌 Insight: The market creates its own logic—until it doesn’t. 😬 4. Emotional Extremes Create Opportunity When markets overreact, they offer setups for rational traders. Capitulation = Bottom Fishing Euphoria = Caution Disbelief = Strongest rallies 🧠 Pro Tip: Watch sentiment indicators, not just price. Fear & Greed Index, put/call ratios, or COT data reveal what the crowd is feeling. Chart Example: 📊 Bitcoin 2022 bottom vs. Fear & Greed Index.. on the chart above the index score close to zero (RED) indicating extreme fear this was because in november 2022 crypto cybercrimes grew new level and investors lost confidence, these cyber crimes included the bankruptcy of FTX as the owners were allegedly misusing customer funds. 💡 5. How to Trade Rationally in an Irrational Market a. Have a plan. Pre-define entries, exits, and invalidation levels. b. Expect overreaction. Markets often go further than they “should.” c. Use sentiment tools. Divergences between price and emotion are gold. d. Don’t fight the crowd—until it peaks. Fade extremes, not momentum. e. Zoom out. 5-minute panic means nothing on a weekly trendline. 🎯Nerd Takeaway: Markets aren’t efficient—they’re emotional. But that emotion creates mispricing, and mispricing = opportunity. You don’t need to predict emotion—you just need to recognize it, and trade on the reversion to reason. 💬 Have you ever traded against the crowd and nailed it? Or got caught up in the hype? Drop your chart and your story—let’s learn from each other. put together by : @currencynerd as Pako Phutietsile
BINANCE:BTCUSDEducation
by currencynerd
7
Trade Wars, Tariffs & Currencies: The Connection Explained📊 What Are Tariffs & Why Should Traders Care? 💱 Tariffs are taxes imposed by a country on imported goods. Think of them as the "price of entry" foreign products must pay to access domestic markets. 🔍 Why Governments Use Them: Protect domestic industries from cheaper foreign goods Retaliate in trade disputes Raise revenue (less common today) 🧠 Why Traders Should Watch Tariffs: Tariffs don’t just hit companies—they ripple through economies and currency markets. Here’s how: 📉 1. Currency Impact Tariffs can lead to currency depreciation in the targeted country as trade volumes fall and foreign demand drops. Example: When the U.S. imposed tariffs on China, the Yuan weakened to offset the blow. 📈 2. Inflation Pressure Tariffs make imports more expensive, fueling inflation. Central banks may respond with rate hikes—which moves markets. 🌐 3. Risk Sentiment Tariff wars increase global uncertainty = risk-off sentiment. Traders flee riskier currencies (like EMFX) for safe havens like the USD, CHF, or JPY. 🔄 4. Trade Balance Shifts Tariffs can affect a country's trade balance, influencing long-term currency valuation. 💡 Trading Tip: Watch for tariff announcements or trade tension headlines—they often precede volatility spikes in major pairs. Combine with sentiment tools and fundamentals for best results.
Education
by currencynerd
Unlocking the Power of TradingViewWhether you're a forex newbie or a seasoned trader, having the right tools can make or break your trading success. One platform that consistently stands out is @TradingView charting powerhouse packed with features designed to give you an edge. I @currencynerd I'm all about helping traders stay smart and stay sharp, so here’s a look at @TradingView features that can enhance your trading game. 1. Advanced Charting Tools TradingView's clean, responsive charts are one of its strongest features. You can customize everything—from chart types (like Heikin Ashi, Renko, or Line Break) to timeframes (including custom ones like 3-minute or 8-hour charts). Multiple chart layouts allow you to view several pairs or timeframes side by side—perfect for multi-timeframe analysis. Pro Tip: Use the “Replay” feature to practice backtesting and understand market behavior in real-time. 2. Built-in Technical Indicators TradingView offers hundreds of built-in indicators (RSI, MACD, Bollinger Bands) and community-created ones. You can also stack multiple indicators on the same pane for cleaner setups. my is Favorite: “Pako Phutietsile's <50%”, which is an automatic indicator that detects and marks basing candles on the chart. A basing candle is a candle with body length less than 50% of its high-low range. This is essential for supply and demand traders. 3. Pine Script for Custom Strategies If you're serious about systematizing your edge, Pine Script lets you build and backtest custom indicators and strategies. Even with basic coding knowledge, you can automate entry/exit rules, alerts, and more. Nerdy Bonus: Many user-generated indicators are open source. Tweak them to fit your style. 4. Smart Alerts Set price, indicator, or drawing-based alerts that trigger via popup, email, or even webhook. This means you don’t need to watch the chart all day—TradingView becomes your eyes on the market. Example: Get an alert when RSI crosses below 30 on GBP/USD or when price hits a key Fibonacci level. 5. Economic Calendar & News Integration Stay ahead of market-moving events with TradingView's built-in Economic Calendar and News Feed. You can filter by currency or event impact to focus only on what matters to your trades. 6. Community & Script Library TradingView’s social side is underrated. Thousands of traders share ideas, scripts, and trade setups. It’s a great way to test your biases or discover new strategies. Tip: Follow high-reputation contributors in the trading/investing space and learn from their setups. 7. Multi-device Access & Cloud Sync Access your charts and watchlists from anywhere. Whether you're on desktop, tablet, or phone, everything stays synced in the cloud. You can start charting at home and get alerts on your phone while you're out. Final Thoughts: @TradingView isn’t just a charting tool—it’s a full-fledged trading assistant. Whether you're looking to simplify your workflow, test strategies, or get real-time alerts, the platform can enhance every part of your trading process. If you haven’t explored these features yet, give them a try. And if you're already using TradingView like a pro, let us know your favorite features in the comments! Stay sharp, stay nerdy. — @currencynerd
PEPPERSTONE:BTCUSDEducation
by currencynerd
The World’s Financial PowerhousesMoney never sleeps — and in certain cities, it practically runs the show. These financial capitals aren't just centers of wealth; they're the beating hearts of global finance, moving trillions every single day. Today, let's take a quick tour through the cities that move markets, set trends, and shape economies. 🌍 1. New York City: The Global Titan Nickname: The City That Never Sleeps Key Institutions: New York Stock Exchange (NYSE) NASDAQ Wall Street banks (Goldman Sachs, JP Morgan, Morgan Stanley) Why It Matters: New York is the world's largest financial center by market cap, volume, and influence. If you trade stocks, currencies, or commodities, you’re feeling New York’s pulse — even if you don’t realize it. 🔔 Trading Fact: The NYSE alone handles over $20 trillion in listed market cap! 🌍 2. London: The Forex King Nickname: The Old Lady of Threadneedle Street (referring to the Bank of England) Key Institutions: London Stock Exchange (LSE) Bank of England Hundreds of forex and investment firms Why It Matters: London is the epicenter of forex trading — commanding nearly 40% of the global forex market turnover. Its time zone also bridges Asia and North America, making it crucial for liquidity during major sessions. 🔔 Trading Fact: The 4 PM London Fix is a major reference point for institutional forex traders worldwide. 🌍 3. Tokyo: The Asian Anchor Nickname: The Gateway to the East Key Institutions: Tokyo Stock Exchange (TSE) Bank of Japan (BOJ) Why It Matters: Tokyo sets the tone for Asian markets — and often for global risk appetite during the Asian session. The Japanese yen (JPY) is the third most traded currency globally, often acting as a safe-haven barometer during market turmoil. 🔔 Trading Fact: Japan is also home to massive institutional players known as the "Japanese real money accounts" — pension funds, insurers, and mega-banks. 🌍 4. Hong Kong & Singapore: The Dual Dragons Nicknames: Hong Kong: Asia’s World City Singapore: The Lion City Why They Matter: Hong Kong: Gateway for global money flowing into China and emerging Asian markets. Singapore: Major hub for forex trading, wealth management, and commodity trading. Both cities are fiercely competitive, tech-driven, and strategically vital for accessing Asia’s fast-growing economies. 🔔 Trading Fact: Singapore is now ranked among the top 3 global forex trading hubs, catching up fast to London and New York. 🌍 5. Zurich: The Quiet Giant Nickname: The Bank Vault of Europe Key Institutions: Swiss National Bank (SNB) Swiss private banking giants (UBS, Credit Suisse) Why It Matters: Zurich represents stability, security, and discretion. It's a powerhouse in private banking, wealth management, and gold trading. The Swiss franc (CHF) is another classic safe-haven currency — and Zurich's influence is a big reason why. 🔔 Nerdy Fact: Despite its small size, Switzerland punches way above its weight in forex and commodity markets. 🗺️ Why These Cities Matter to Your Trading Liquidity: Big cities = Big volumes = Tighter spreads and faster executions. Market Movements: Economic reports, policy decisions, and corporate news from these capitals can spark global volatility. Session Overlaps: New York–London overlap? Tokyo–London handoff? Understanding when these cities are active helps you time your trades better. Final Thoughts : You don't have to live in New York or Tokyo to trade like a pro. But you do need to understand where the big moves are born. Follow the money. Watch the capitals. Trade smarter. Markets may seem chaotic — but behind the noise, the world’s financial capitals keep the rhythm steady. put together by : @currencynerd as Pako Phutietsile
Education
by currencynerd
one of the most underrated charts : M2(money supply)When it comes to forex and macro trading, it's easy to get lost in charts, indicators, and economic calendars. But one of the most overlooked—and incredibly powerful—macro indicators is the M2 Money Supply. In this post, we’ll break down what M2 really is, why it matters, and how traders like you can use it to get an edge. 💰 What Is M2 Money Supply? M2 represents the total amount of money in circulation in an economy, including: M1 (physical cash + checking deposits) Savings deposits Money market securities Time deposits (under $100,000) In simple terms: M2 tracks how much money is sloshing around in the system. 🧠 Why Traders Should Care About M2 When M2 goes up significantly, it often signals that a central bank is easing monetary policy—i.e., printing more money, keeping interest rates low, or using QE (quantitative easing). Conversely, when M2 contracts or slows, it suggests tightening, and could signal reduced liquidity, higher rates, or a slower economy. M2 = Macro Liquidity Meter And liquidity drives markets—especially currencies. ⚙️ How to Use M2 in Your Trading Strategy Here are 3 ways you can incorporate M2 into your macro trading toolkit: 1. Gauge Inflation & Currency Value When a country expands its money supply rapidly (like the U.S. did during COVID), the purchasing power of its currency often declines, especially against currencies with tighter monetary policy. ✅ Watch for divergences: If M2 is growing fast in one country and flat in another, that’s a potential FX opportunity. 📉 Example: USD weakened sharply post-COVID when M2 surged. 2. Confirm Trends in Interest Rates M2 often leads or confirms central bank policy. Shrinking M2 → Tighter conditions → Rising rates → Currency bullish Expanding M2 → Easier policy → Lower rates → Currency bearish Use it alongside yield curve analysis and central bank projections. 3. Identify Risk-On/Risk-Off Regimes A rising M2 usually supports risk assets like equities and EM currencies. Falling M2 can trigger liquidity squeezes, flight to safety, and stronger demand for USD or JPY. Use M2 as a macro filter for your risk appetite. Watch for turning points in M2 to anticipate market regime shifts. 🔎 How to Track M2 on @TradingView Open a new chart and search for: 🔍 FRED:M2SL – U.S. M2 Money Stock (seasonally adjusted) You can also compare this against: DXY (US Dollar Index) USDJPY, EURUSD, or other major FX pairs U.S. 10-Year Yields (US10Y) or Fed Funds Rate (FEDFUNDS) Add M2 as an overlay or sub-chart for macro context. Use the "Compare" tool to visualize divergences with currency pairs. 📌 Final Thoughts M2 might not give you minute-by-minute trade signals like an RSI or MACD, but it offers something far more powerful: macro context. When used with other indicators, it can help traders: Anticipate currency trends Understand shifts in monetary policy Position for regime changes in risk appetite Remember: the smartest traders aren’t just charting price—they’re charting liquidity. And M2 is the ultimate liquidity map. put together by : @currencynerd
FRED:M2SLEducation
by currencynerd
3
From Gut to Algorithm: How AI Is Changing the Game for TradersArtificial Intelligence isn't just changing tech — it’s rewriting the rules of trading and investing. What used to be the domain of seasoned floor traders and intuition-driven bets is now increasingly dominated by algorithms, machine learning models, and predictive analytics. Here is how AI changing the markets — and what it means for traders like you. 📈 AI in Action: How It’s Used in Markets AI impacts trading in ways both seen and unseen. Here’s how: Algorithmic Trading: High-frequency trading (HFT) firms use AI to make thousands of trades per second, exploiting tiny inefficiencies. Sentiment Analysis: AI scans news articles, social media, and earnings calls to gauge market mood before humans even blink. Predictive Analytics: Machine learning models digest millions of data points to forecast stock movements, currency fluctuations, and market trends. Portfolio Management: Robo-advisors like Betterment or Wealthfront use AI to automatically rebalance portfolios — making decisions humans might overthink. Risk Management: Banks and hedge funds use AI to predict and manage market risks faster than traditional risk teams ever could. 🤖 Why AI Is a Game-Changer for Traders AI isn’t just about speed. It's about edge. ✅ Processing Power: AI can analyze complex patterns across decades of historical data — something a human could never do in a lifetime. ✅ Emotionless Trading: AI doesn’t panic, get greedy, or revenge trade. It executes the plan — consistently. ✅ Adaptive Strategies: Machine learning models evolve over time, adjusting to changing market conditions without needing a human hand. ⚠️ The Dark Side: Risks and Challenges AI isn’t magic. It introduces new risks into markets: Flash Crashes: Algorithms can amplify volatility — causing sudden, violent moves like the 2010 Flash Crash. Overfitting: AI models might "learn" patterns that don’t actually exist, leading to disastrous real-world trades. Market Homogenization: If everyone uses similar AI models, trading strategies become crowded — making the market more fragile. Ethical Concerns: Who is accountable if an AI trader manipulates a market unintentionally? Regulators are still catching up. 🧠 What This Means for You Whether you’re a day trader, swing trader, or long-term investor, understanding AI is becoming a competitive necessity. Retail traders are starting to access AI-powered tools once reserved for institutions. Custom indicators, predictive models, and smart portfolio managers are more available than ever. But remember: AI is a tool, not a crystal ball. Human judgment, risk management, and emotional discipline still matter. In the end, the best traders will be those who can combine machine intelligence with human intuition. in conclution: Markets have always rewarded those who adapt. AI isn’t replacing traders — it’s changing what trading looks like. The future belongs to those who can learn faster, adapt smarter, and trade sharper. Stay curious. Stay strategic. Stay ahead. put together by: @currencynerd courtesy of: @TradingView
NASDAQ:PLTREducation
by currencynerd
From Tulips to Tech: The Evolution of Financial Bubbles 🎯 Introduction: financial/economic bubbles are a recurring theme in economic history, this is often when a particular financial asset goes to unrealistic price levels often making money for early investors but usually these high price levels do not match their fundamental value this is then followed by a large public participation who also want a piece of the pie eventually with the price collapsing or sharply declining blowing or living investors in a large financial loss.. From 17th-century tulip gardens to 21st-century crypto manias, one thing has remained constant: Humans never learn. Every generation thinks this time is different — but the pattern of bubbles keeps repeating. Here's the crash course in 400 years of financial euphoria, panic, and pain. 🧠 Section 1: 1637 — Tulip Mania 🌷 The original bubble. In the Netherlands, rare tulip bulbs were worth more than houses. Prices exploded... then collapsed 90% in a matter of weeks. Lesson: Speculation + FOMO is not new. Humans were flipping flowers before they flipped crypto. Mini Nerd Tip: "When people stop caring about value and only care about price rising, watch out." 🧠 Section 2: 1720 — South Sea Bubble 📜 Britain’s South Sea Company promised massive profits trading with South America (but barely did any business). Politicians and aristocrats pumped the stock price. Collapsed spectacularly → ruined many fortunes (including Isaac Newton himself: "I can calculate the motion of heavenly bodies, but not the madness of men.") Mini Nerd Tip: "If a bubble needs government help to stay alive, it's already dying." 🧠 Section 3: 1929 — Wall Street Crash 🏛️ Roaring 20s: endless optimism, cheap margin loans, "stocks only go up!" 1929: Stock market crashed, triggering the Great Depression. People were buying stocks with 10% down and gambling recklessly. Mini Nerd Tip: "When leverage is everywhere, the smallest panic causes waterfalls." 🧠 Section 4: 2000 — Dotcom Bubble 💻 Everyone thought the internet would change everything (it did — but slower and differently). Companies with no profits were valued in billions. "Eyeballs" were treated as real revenue. NASDAQ lost 78% from top to bottom. Mini Nerd Tip: "Innovation creates real value... but hype inflates fake value faster." 🧠 Section 5: 2008 — Housing Bubble 🏡 Banks handed out mortgages to anyone. Financial engineering (CDOs, synthetic MBS) created the illusion of safety. US housing prices collapsed → global financial crisis. "Too Big to Fail" became the famous phrase. Mini Nerd Tip: "If everyone is getting rich easily, someone is lying or blind." 🧠 Section 6: 2017/2021 — Crypto & Meme Stocks 🚀 Gamestop, Dogecoin, NFTs, Shiba Inu — the wildest "everyone’s a genius" market since the 1920s. Social media + free apps = amplified bubble speed. Massive rises, insane collapses. Mini Nerd Tip: "Technology changes, human emotion doesn’t." 🧠 Final Section: Why Bubbles Will Never End Greed, fear, and FOMO are timeless. Every era dresses up bubbles in new clothes (flowers, sea companies, internet, crypto). Smart traders understand this pattern — and use it to survive and thrive. "**Bubbles don't pop because of bad assets. They pop because confidence disappears put together by : Pako Phutietsile as @currencynerd courtesy of : @TradingView
PEPPERSTONE:XAUUSDEducation
by currencynerd
trailblazing women who took Wall Street by storm these incredible women have paved a way for female investors and traders around the world showing great resilience and fearless mentality despite facing gender discrimination going on to achieve great things in the financial field, motivating the future generation of young women that they too can achieve the unthinkable. 1. HETTY GREEN the witch of wall street also referred to as "the woman who loved money" born November 21, 1834 and also believed to have been the richest woman in America before the time of her passing, Hetty Green started her financial/business journey from a young age through the influence of her father who was a successful agent, oil manufacturer, and Quaker, who encouraged her to read and study financial texts when she was a young girl, he believed that even women needed to understand the dealings of money, business and overall how the financial world operates. She is best known for turning an inheritance of between 3 - 7 million to 100 million U.S dollars approximately $2.5 billion in today's money. She did this by investing in U.S government bonds, stocks, real estate and railroads and providing financial support during crises, most especially the Panic of 1907, making her a reputable investor and financier, using a buy low, sell high strategy and impeccable psychology facing markets militantly and unafraid even in times of panic. 2. VICTORIA WOODHALL the first woman to run for presidency born September 23, 1838, Victoria came from a very poor background, with the influence of their father she and her sister sold herbs and potions posing as spiritualists and healers they caused them to live a on the run from one place to another due to unsatisfied customers/patients. Their nomadic lifestyle led them to Manhattan were they caught the attention of railroad magnate Cornelius Vanderbilt, who it was believed they helped him keep in contact with his dead wife he in return offered them financial advice and through this connection they were able to open the first female owned brokerage in wall street in 1870 called WOODHULL, CLAFLIN and CO with clients of high society women, rich widows and high value prostitutes, this become a success earning them over $700 000 about 2million today. She used this money to further her goals and fund her campaign to run for presidency. 3. ISABEL BENHAM madam railroad born 1909, in the 1920s Isabel enrolled at a women only college called Bryn Mawr in Pennsylvania, with a strong desire to study economics and work in wall street it has a great tragedy to find that the school offered no economics courses but Isabel insisted the college offer economics studies and made history by being 1 of 5 women to graduate from the college with a degree in economics. after graduation, living in times of the great depression also facing daily gender discrimination this did not stop her from pursuing her dreams to work in wall street, she started a side hustle by selling magazine subscriptions and later landed a job as a bond strategist on wall street bond house R.W Pressprich and Co. and due to her resilience and hard work providing accurate reports of the railroad industry became their first female partner and first woman as a partner of a wall street bond house and first woman to be appointed Board of Directors for a railroad. 4. MURIEL SIEBERT the first lady of finance born 1928 without graduating from any college her finance career started by being a finance research trainee and grew her expertise by working in various brokerages. through hard work and determination by year 1967, despite numerous failed attempts and rejection she became the first woman to have a seat on the BYSE being the only woman among 1,365 men which was a remarkable achievement. she went on to co-found Siebert and Co a broker- dealer in 1969 and when the the NYSE jettisoned it's 183 year old tradition allowing it's members to negotiate broker commissions her company became America's first discount brokerage also being owned by a woman. by year 1977 she hit another incredible career milestone by being appointed superintendent of Banks for New York state, overseeing all NEW YORK banks with no banks failing in her 5 year term. 5. GERALDINE WEISS grand dame of dividents considered one of the best female investors/ traders of the 20th century, learning about investing by reading investing texts like Security Analysis by BENJAMIN GRAHAM and studying business and finance earning a degree at the University Of California. with her advanced knowledge about investing she was still unable to get any job position higher than secretary due to gender discrimination in the male dominated industry but this did not put out her fuel and and undying desire to become be involved in the investment community and by age 40 she started her investment newsletter called "Investment Quality Trends" under a pseudonym "G. Weiss" to hide her gender as at the time many believed no woman can make successful investments and did this for a decade with her subscribers thinking she is a male it was only in 1977 when she appeared on TV program "wall street with Louis Rukeyser" that she revealed her gender this now with her newsletter being a success with accurate analysis asserting that dividend yield is a key valuation measure that how she got her nickname. hope this inspires more women to be more active in the trading world. Whatever women do they must do twice as well as men to be thought half their inferior. Luckily, this is not difficult. – Charlotte Whitton put together by : Pako Phutietsile as currencynerd
OANDA:XAUUSDEducation
by currencynerd
4
if you use technical analysis you owe a lot to these individualsTHE HISTORY AND ORIGIN OF TECHNICAL ANALYSIS I am a firm believer that as investors/traders we need to know the historic and major events that have occurred in this magnificent field of ours that have shaped how it is today. Today i want to shed light of knowledge on the history/origin of technical analysis as this is a widely used concept that is used by majority of traders/investors to analyse/predict future market moves through the evaluation of historic market data especially price, volume and implied volatility and many have made a living and good returns on the financial markets using the various technical analysis tools and concepts but not knowing where it all started. many do believe that technical analysis was initiated by Charles Dow in the 1800s but this is not true as evidence of Technical Analysis dates far back as to the 17th century from basic and underdeveloped methods as compared to the more evolved ones used in Morden-day times. Let's get straight into it: 17th CENTURY -- 1. the Dutch east India Company traders The Dutch East India Company which was formed in the Dutch Republic, Amsterdam in 1602 which is known to be the first publicly traded company, trading mainly in spices, Indigo and cotton, which gave way to the first financial market the Amsterdam Stock Exchange. Here is when the earliest forms of technical analysis came to show when the Dutch traders would graph record/keep track of the various price fluctuations of their stock but in a basic form. 2. José or Joseph Penso de la Vega still in the 17th century a Spanish diamond merchant, philosopher and poet best known also as Joseph de la Vega, born 1650 in Spain also considered one of the earliest financial market expert published a marvellous financial read called "Confusion De Confusiones" which provided detailed awareness of how the Dutch financial market participants operated focusing on their illogical behaviour and price patterns they used further more hinting on technical analysis with his descriptions of technical analysis concepts such as puts, calls and pools which are still relevant in Morden-day technical analysis and how he used these in the Amsterdam Stock Exchange. 18th CENTURY Homma Munehisa Homma Munehisa, born 1724 in Sakata, Japan a Japanese rice merchant trading in Dōjima Rice Exchange developed what i consider the most popular form of technical analysis which proved high standards of acceptance as traders/investors world-wide still use it in modern-day times, he initiated the Japanese Candlestick/ K-Line (primarily known as Sakata Charts), which is a price chart that's represents the open, close, high and low prices of a security for a specific time period which was introduced in his book "THE FOUNTAIN OF GOLD- THE THREE MONKEY RECORD OF MONEY" which also shared insights about chart patterns, markets trends and traders human emotions. LATE 19TH AND EARLY 20TH CENTURY Charles Henry Dow considered father of technical analysis born 1851 Charles Dow is the one that first to induct modern-day technical analysis in the United States Of America, he was an American journalist who co-founded Dow Jones and Company which is a publishing firm along ide Edward Davis Jones and Charles Bergstresser. He also co-founded The Wall Street Journal which its first publication was on July 8, 1889 which became the the most reputed financial publication and first of it's kind which was a series of texts that discussed his observations of the U.S stock market especially the industrial and transportation stocks listed in the U.S stock market this gave way to the Dow Jones Industrial Average and Dow Jones Transportation Average, he also held a strong believe that "the stock market as a whole was a reliable measure of overall business conditions within the economy" he also developed the Dow Jones Theory which states that the market has 3 trend phases which was a significant breakthrough in technical analysis as this theory aids traders/investors in identifying the major, intermediate and minor trends in the market. after his passing many other technical analysis developers came from studying his work/publications which include the likes of William Hamilton who later become the editor of the wall street journal, others notable followers of his work include Robert Rhea, George Shaefer and Richard Russel. another prominent figure in the development of modern-day technical analysis is Ralph Nelson Elliot born 1871 whose financial career started as an accountant, Mr. Elliot was famously known for studying 75 years of historical stock market data and recording his research and findings manually as computerized systems where limited which i believe is very outstanding. his work is based on a theory that market movements are not random and that the markets moves in specific trends and patterns (waves) which are influenced by traders/investors psychology. his wave theory gained traction in March 13, 1935 when he stated that the the market will make a bottom and indeed the following trading day the Dow Jones Industrial Average made it's lowest closing price, which proved his Elliot Wave Theory to be a significant technical anaysis concept. 20th CENTURY Technical Indicators with the aid of computerized systems technical analysis evolved into technical indicators which are computer systems backed by mathematical calculations of price data which apply these calculations to analyse large volumes of market data incorporated by algorithms which overlap on charts to forecast future price movements. hope you have a fun read and learned something new. “In learning you will teach, and in teaching you will learn.” Phil Collins put together by Pako Phutietsile as @currencynerd
COINBASE:BTCUSDEducation
by currencynerd
BTC to run out by year 2140, who is the biggest whale?bitcoin whales are individuals or entities that hold/own the most amount of the digital XAU, to achieve this financial status one has to own at least 1000 BTC, with the coin's supply being infinite to 21 million (also known as HARD CAP), meaning that only 21 million bitcoins can ever be created. it's important to know who the big players are in the market also to keep track of the left supply. one of the important reasons i think why the supply was capped at 21 million was to ensure no risk of inflation even though the Bitcoin creator 'SATOSHI NAKAMOTO' disclosed once that him capping it at 21 million was just an "educated guess" in order to control supply, there is what is called Bitcoin halving which is the process by which the reward for mining BTC by half hence the term halving. the first ever halving was November 28, 2012 this was the start of a historic run of BTC as a deflationary asset and the most recent was this year APRIL 19, with the reward for mining a single block cut from 6.25 BTC to 3.125 BTC. this event happens when 210,000 are added to the blockchain. this also reduces the rate at which new coins are created maintaining scarcity which results in an increase in value. with all that said, WH0 OWNS THE MOST BITCOIN? top 5 public cooperation's that hold most Bitcoin * MICROSTRATEGY - U.S company - holds 214,400 est. Value - $13.5B * MARATHON DIGITAL - U.S company - hold 17,631 est. Value - $1.1B * TESLA - U.S company - holds 9,720 est. Value - $600M * HUT 8 - CANADA company - holds 9,109 est. Value - $574.1M * COINBASE - U.S company - holds 9,000 est. Value - $567.2M top 5 countries that hold most Bitcoin * USA - holds 207,189 est. Value - GETTEX:13B * CHINA - holds 194,000 est. Value - $12.2B * UK - holds 61,000 est. Value - $3.8B * GERMANY - holds 50,000 est. Value - $3.1B * UKRAIN - holds 46,351 est. Value - $2.9B top 5 private companies that hold most Bitcoin * Mt. Gox - holds 200,000 est. Value - $12.6B * Block.one - holds 140,000 est. Value - $8.8B * Tether holdings - holds 75,354 est. Value - $4.7B * Xapo Bank - holds 38,931 est. Value - $2.4B * BitMEX - holds 36,794 est. Value - $2.3B then there are other investors that are involved in the BITCOIN market without directly purchasing it but through bitcoin related assets. these are : *Grayscale Bitcoin Trust holds 291,802 est. Value - $18.3B *iShares Bitcoin Trust holds 274,322 est. Value - $17.2B *Fidelity Wise Origin Bitcoin Fund holds 152,880 est. Value - $9.6B *CoinShares/XBT Provider holds 48,466 est. Value SEED_TVCODER77_ETHBTCDATA:3B *ARK 21Shares Bitcoin ETF holds 43,470 est Value - $2.7B top individuals that hold the most BTC. *SATOSHI NAKAMOTO 1.1MILLION BTC *THE WINKLEVOSS TWINS 70,000 BTC *TIM DRAPER 29,500 BTC *MICHAEL SAYLOR 17,732 BTC researched and put together by : Pako Phutietsile as @currencynerd
COINBASE:BTCUSDEducation
by currencynerd
A Long "short"i analyzed this a while back and completely forgot about. but when i opened the price chart i noticed that price is reacting off significant market price structures. basically, on the Monthly price chart... price is reacting to liquidity pool covering price areas from 0.91000 to 0.90600 which is based off monthly supply of proximal price 0.91000 and prev. demand Continuous Proximal PRICE of 0.90600. and price on smaller timeframes is trading below parallel bullish price channel but i am waiting specifically for the 4HR candlestick to form a full OCHL below the channel to indicate changing market momentum to bearish. with targets @ previous swing valley around price areas of 0.89400 and 0.89000! always remember, the market never forgets significant price areas.. used up/not. put together by : Pako Phutietsile as @currencynerd
Short
by currencynerd
Fib Retracement - better/important than most believeFibonacci. introduced by Italian mathematician "father of the Fibonacci sequence" Leonardo Da Pasa (born around A.D. 1170) in 1202 in his book Liber Abaci "book of calculations" which he handwrote as the printing was not yet invented, which also became the first book to be introduced to the Hindu-Arabic numeral system as it was a new way to write numbers and do calculations. Fibonacci in trading. the most important/popular fib tool in the trading/investing community is the Fibonacci Retracement applied from the Fibonacci sequence which is a set of steadily increasing numbers where each number is the sum of the preceding 2 numbers. Fibonacci retracement, is derived based on high and low price/ valley and peak in supply and demand terms. The most important Fibonacci ratios/percentage of the retracement measure is - 23.6%, 38.2%, 50%, 61.8%, 100%, with the ratio/percentage being represented by horizontal lines on the price chart. calculated by : in bull market, high price - (high price-low price) x percentage in bear market, low price + (high price-low price) x percentage Significance of Fib Retracement. these are very important too traders as the indicate significant price levels/areas like : - support and resistance - liquidity pool - using rectangle drawing tool to connect two fib retracement levels together as a zone not a singular ratio level. based on current market conditions and trading criteria. - price targets, exit price (Take Profit) - Stop Loss - stop and limit orders (set and forget for supply and demand traders) Fibonacci retracement also compliments other trading tool and indicators well and can be used by all sorts of traders, from position traders to scalpers. it works best on trending market conditions to identify reversals, corrections, pullbacks continuation moves. important note : - Leonardo did not invent Fibonacci, it was actually used and known to Indian mathematicians since the 6th century. - the 50% is not really a Fibonacci number instead is taken from Dow theory that assets usually retrace half their prior move. put together by : Pako Phutietsile as @currencynerd
OANDA:XAUUSDEducation
by currencynerd
Top Trading BooksLiterature is one of the best ways to share and spread knowledge and information around the world, here are my top picks of the most informative, knowledge packed trading books that can help improve and transform your trading approach for the better. 1. Market Wizards - by Jack Schwager, 1989. this consists of a series of interviews from a couple of the world's renowned traders including Paul Tudor James, Bruce Kovner, Richard Dennis and several others as they share tips and insights on what makes them the best from the rest. It reveals to traders/investors some of the traits it takes to become a successful trader. "the elements of good trading are (i) cutting losses, (ii) cutting losses, (iii) cutting losses. 2. Trading In The Zone : master the markets with confidence, discipline and a winning attitude - by Mark Douglas, 2000. this is mostly a trading psychology book that explores the significance of the right mindset when pursuing trading success as well as ways to maintain and gain emotional intelligence in the fast-paced trading environment and how emotional control is an essential part in any trading plan. "do not let past loses influence your future" 3. Reminiscence Of A Stock Operator - by Edwin Lefèvre, 1923. published almost 100 years ago, inspired by the life of stock trader Jesse Livermore. This book highlights tons of experience he gained in the stock market from the failures to success that even present day traders face. "there is nothing like losing all you have in the world for teaching you what not to do, and when you know what not to do in order not to lose money, you begin to learn what to do in order to win" 4. Technical Analysis Of The Financial Markets : a comprehensive guide to trading methods and applications - by John Murphy, 1999. given the name "the bible of technical analysis" updated from his landmark best seller "technical analysis of the future markets" if you want to learn how to track market behavior this is the book for you. if also offers from basic trading concepts to advanced trading concepts covering also different technical indicators and over 400 chart illustrating different market techniques. after reading i am sure you will be able to create a trading system that fits oneself. "it should be stressed here again, however that basic trend analysis is still the overriding consideration" 5. One Up On Wall Street - by Peter Lynch, John Rothchild, 1989. this book focuses more on the importance of research, study and analysis to go from beginner to expert trader as well as the different investment opportunities in our everyday life's that expert investors are not even aware of. Most importantly the effective investment techniques, strategies and guidelines that aided Peter to become one of the best fund mangers of all time. "the trick is not to learn to trust your gut feeling, but rather to discipline yourself to ignore them" 6. When Genius Failed - by Roger Lowenstein, 2000. this book tells the story of the rise and fall of one of the most impressive hedge funds Long-Term Capital Management which has more than $120 Billion under management before its downfall in 1998. The book is written in 2 sections, the first focuses on the 'genius' business model of the hedge fund that delivered more than 40% between 1994 and 1998 and the second segment explores the firm's downfall. "investors long for steady waters, but paradoxically the opportunities are richest when the markets turn turbulent" but together by : Pako Phutietsile ( @currencynerd )
OANDA:XAUUSDEducation
by currencynerd
2