{"id":370402,"date":"2025-09-03T13:36:19","date_gmt":"2025-09-03T13:36:19","guid":{"rendered":"https:\/\/pocketoption.com\/blog\/news-events\/data\/blockchain-analysis\/"},"modified":"2025-09-03T13:38:46","modified_gmt":"2025-09-03T13:38:46","slug":"blockchain-analysis","status":"publish","type":"post","link":"https:\/\/pocketoption.com\/blog\/en\/knowledge-base\/markets\/blockchain-analysis\/","title":{"rendered":"Blockchain On-Chain Analysis for Crypto Trading"},"content":{"rendered":"<div id=\"root\"><div id=\"wrap-img-root\"><\/div><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":249045,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[2567],"class_list":["post-370402","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-markets","tag-trading"],"acf":{"h1":"Blockchain On-Chain Analysis for Crypto Trading","h1_source":{"label":"H1","type":"text","formatted_value":"Blockchain On-Chain Analysis for Crypto Trading"},"description":"Analysis of blockchain data for cryptocurrency trading decisions and market insights","description_source":{"label":"Description","type":"textarea","formatted_value":"Analysis of blockchain data for cryptocurrency trading decisions and market insights"},"intro":"In the ever-evolving world of cryptocurrency, having an edge often means going beyond traditional price charts and indicators. On-chain analysis\u2014a method of examining data directly from blockchain networks\u2014has emerged as a powerful tool for understanding market behavior at a granular level. It offers traders insights into the actual usage, movement of assets, and behavioral patterns of participants that price action alone cannot reveal.","intro_source":{"label":"Intro","type":"text","formatted_value":"In the ever-evolving world of cryptocurrency, having an edge often means going beyond traditional price charts and indicators. On-chain analysis\u2014a method of examining data directly from blockchain networks\u2014has emerged as a powerful tool for understanding market behavior at a granular level. It offers traders insights into the actual usage, movement of assets, and behavioral patterns of participants that price action alone cannot reveal."},"body_html":"Whether you're tracking large wallet movements, monitoring token inflows to exchanges, or evaluating the health of a blockchain ecosystem, on-chain metrics provide a unique window into what's happening behind the scenes. For binary options and spot traders alike, integrating blockchain analysis into your strategy can improve timing, sharpen risk assessment, and uncover signals missed by conventional technical tools.\r\n\r\nThis guide explores the essential metrics, frameworks, and practical strategies for leveraging on-chain data to make smarter trading decisions in crypto markets.\r\n<h2>What Is On-Chain Analysis?<\/h2>\r\nOn-chain analysis refers to the examination of data recorded directly on public blockchains. Unlike technical analysis, which interprets historical price movements, or fundamental analysis, which evaluates project viability, on-chain analysis dives into the real-time behavior of users, miners, and network validators. It uses data such as wallet balances, transaction flows, exchange inflows\/outflows, and smart contract activity to assess the health and sentiment of a crypto asset.\r\n\r\nBecause blockchain data is transparent and immutable, traders can observe the exact movements of large holders (often referred to as \u201cwhales\u201d), analyze network activity spikes, or detect early signs of capitulation or accumulation. This makes it particularly valuable in highly speculative markets like crypto, where news cycles and emotional trading often distort the true picture.\r\n\r\nModern on-chain platforms allow users to track these metrics visually and apply them contextually to their strategies. As institutional adoption increases, so does the value of on-chain data as a way to interpret crowd psychology, anticipate volatility, and refine entries and exits.\r\n<h2>\u2714 Essential On-Chain Metrics: What They Reveal<\/h2>\r\nMastering on-chain trading begins with decoding the raw data written on blockchains. These aren\u2019t just numbers \u2014 they\u2019re behavioral signals, showing what different market participants are doing in real time. Here\u2019s how to read the most telling metrics:\r\n<h3>\u2714 Unique Active Wallets<\/h3>\r\nThis reflects how many addresses are participating in transactions daily. A rise may indicate user growth, adoption, or speculative activity. A sharp drop? Possible disengagement or declining demand.\r\n<h3>\u2714 Exchange Wallet Movements<\/h3>\r\nWhen large sums flow into exchanges, it often means traders are preparing to sell \u2014 a potential bearish flag. Outflows, especially during dips, can suggest accumulation and a bullish outlook.\r\n<h3>\u2718 Large Holder Transfers<\/h3>\r\nBig wallets (aka whales) tend to move quietly but leave massive footprints. Noticing consistent buys from these addresses often precedes price rallies. Spotting distribution? Might be time to tighten risk.\r\n<h3>\u2714 NVT (Network Value to Transactions)<\/h3>\r\nThink of it as a crypto version of the P\/E ratio. If market cap balloons but transaction volume doesn\u2019t follow \u2014 the asset might be overpriced relative to real usage.\r\n<h3>\u2718 Gas Fees and Congestion<\/h3>\r\nSkyrocketing transaction fees, particularly on networks like Ethereum, hint at a frenzy \u2014 NFT launches, hype-driven DeFi projects, or panic selling. High fees = network stress = volatility.\r\n<h2>MVRV (Market Value vs. Realized Value)<\/h2>\r\nThis metric compares the current market cap to the aggregate price users paid for their coins. High MVRV values may suggest profit-taking zones; low values can flag oversold conditions.\r\n\r\nIndividually, these metrics are useful \u2014 but together, they paint a high-resolution image of market psychology.\r\n<h2>5 Whale Tracking and Behavioral Patterns<\/h2>\r\nIn the world of crypto, not all wallets are created equal. A small group of high-capital entities \u2014 often referred to as \u201cwhales\u201d \u2014 can significantly sway markets. On-chain analysis gives traders a rare chance to observe their movements in real time, revealing powerful sentiment signals.\r\n<h3>Exchange Inflows from Whales<\/h3>\r\nWhen large wallets transfer assets to centralized exchanges, it\u2019s often a preparation for liquidation. Tracking these inflows can help anticipate selling pressure before it hits the charts.\r\n<h3>Cold Wallet Accumulation<\/h3>\r\nIf whales are consistently moving funds from exchanges to cold storage, it suggests long-term conviction and reduced short-term selling risk \u2014 a bullish signal, especially during price consolidation phases.\r\n<h3>\u201cSmart Money\u201d Distribution<\/h3>\r\nSudden transfers from multiple large wallets to exchanges during pumps may point to coordinated exits. Recognizing these shifts early can help retail traders avoid buying into tops.\r\n<h3>Wallet Labeling Tools<\/h3>\r\nModern on-chain platforms like Nansen and Arkham Intelligence help identify wallet owners or behavioral patterns by tagging exchange wallets, institutional players, and active DeFi participants. These tools enable traders to monitor whale behavior with greater precision.\r\n<h3>Example:<\/h3>\r\nA notable case occurred before Bitcoin\u2019s drop in May 2021 \u2014 several whale wallets began sending BTC to exchanges in unusually high volumes days before the price decline, signaling insider exits.\r\n\r\nUnderstanding how whales move their assets is like reading the footprints of market-moving players. These insights often come before price reacts, giving on-chain analysts a distinct advantage.\r\n<h2>Protocol-Level Data Interpretation<\/h2>\r\nBeyond wallet activity, each blockchain protocol generates a wealth of internal metrics that reflect its health, user engagement, and economic activity. These protocol-specific insights can be invaluable when evaluating both short-term sentiment and long-term potential.\r\n<h2>Staking Participation and Governance<\/h2>\r\nFor proof-of-stake chains, the proportion of tokens staked often signals network confidence. A rising staking ratio implies user commitment and belief in network security. Additionally, high governance participation (e.g., votes on DAO proposals) can indicate an active, invested community.\r\n<h3>Fee Revenue and Gas Utilization<\/h3>\r\nBlockchains like Ethereum or Solana generate protocol fees \u2014 a direct indicator of usage. Surging gas fees during peak periods reflect demand pressure. Tracking fee trends helps distinguish hype from sustainable utility.\r\n<h2>TVL (Total Value Locked)<\/h2>\r\nIn DeFi ecosystems, TVL measures how much capital is actively engaged in smart contracts. A growing TVL, especially on newer protocols, shows rising market trust. But if TVL climbs without matching user activity or volume, it may indicate unsustainable incentives.\r\n<h2>Developer Activity<\/h2>\r\nDevelopment metrics from GitHub or blockchain-specific tools (e.g., Electric Capital reports) provide context on protocol maturity. Consistent code commits and ecosystem upgrades signal innovation \u2014 key for identifying long-term holds.\r\n<h3>Example:<\/h3>\r\nDuring the 2021 bull run, Avalanche\u2019s TVL exploded, driven by strong staking incentives. However, a simultaneous rise in developer activity and consistent wallet growth confirmed that the interest wasn\u2019t purely mercenary.\r\n\r\nProtocol-level data offers a window into the real engine of a blockchain \u2014 its infrastructure, usage, and sustainability. Traders who dig deeper than price often spot winning trends early.\r\n<h2>Transaction Volume and Velocity Metrics<\/h2>\r\nUnderstanding how funds move through a blockchain is essential to identifying shifts in market sentiment, liquidity cycles, and the emergence of new trends. Transaction volume and velocity are two key indicators that offer deep insight into the flow of capital.\r\n<h3>Transaction Volume: Real vs. Wash<\/h3>\r\nTotal transaction volume measures the raw throughput on a network. However, traders must differentiate between\u00a0<strong>organic volume<\/strong>\u00a0and\u00a0<strong>wash trading<\/strong>\u00a0or automated activity.\r\n<ul>\r\n \t<li><strong>Organic volume<\/strong>\u00a0(e.g., user transfers, DEX trades, NFT sales) shows healthy user engagement.<\/li>\r\n \t<li><strong>Suspiciously high volume<\/strong>\u00a0without user growth can signal manipulation \u2014 common in low-liquidity altcoins.<\/li>\r\n<\/ul>\r\n<h3>Velocity of Money<\/h3>\r\nVelocity refers to how quickly tokens change hands. A high velocity implies active usage and trading, while low velocity suggests hoarding or long-term holding.\r\n<ul>\r\n \t<li><strong>Rising velocity<\/strong>\u00a0during a price rally can suggest retail speculation or short-term trading interest.<\/li>\r\n \t<li><strong>Falling velocity<\/strong>\u00a0while price climbs may indicate accumulation by whales or institutions.<\/li>\r\n<\/ul>\r\n<h3>\u2611 Metric Interplay Example:<\/h3>\r\nIn early 2023, BNB Chain saw declining velocity but rising price and volume \u2014 a sign of accumulation by large holders ahead of ecosystem upgrades.\r\n<h3>\ud83d\udccd Layer 2s and Bridges<\/h3>\r\nWith cross-chain infrastructure and rollups becoming common, it\u2019s important to also track transaction flow between chains. A surge in volume moving from Ethereum to Arbitrum, for example, often signals upcoming trading activity on the L2.\r\n<h2>\ud83d\udd17 Whale Watching and Token Concentration<\/h2>\r\nIn decentralized markets, large holders\u2014often called \u201cwhales\u201d\u2014can significantly sway price movements. Monitoring their behavior is a critical component of on-chain analysis.\r\n<h3>\ud83d\ude80\ufe0f Whale Wallet Tracking<\/h3>\r\nWhales are wallets holding large amounts of a specific token (typically top 1\u20135% by holdings). By tracking their actions, traders can anticipate large inflows\/outflows before they impact price.\r\n<ul>\r\n \t<li><strong>Accumulation:<\/strong>\u00a0If whales are steadily increasing holdings during a dip, this may signal a reversal or long-term bullish expectation.<\/li>\r\n \t<li><strong>Distribution:<\/strong>\u00a0Rapid outflows from top wallets near local tops often precede sharp corrections.<\/li>\r\n<\/ul>\r\n<h3>\ud83d\ude80\ufe0f Token Distribution Metrics<\/h3>\r\nToken concentration offers a window into market stability or fragility.\r\n<ul>\r\n \t<li><strong>High concentration<\/strong>\u00a0= more control by a few entities (e.g., insider-driven or VC-heavy projects).<\/li>\r\n \t<li><strong>Low concentration<\/strong>\u00a0= more decentralization and potentially more organic growth.<\/li>\r\n<\/ul>\r\n<h3><strong><em>Metric Tip:<\/em><\/strong><\/h3>\r\nTools like Nansen or Lookonchain allow real-time tracking of labeled wallets (e.g., exchanges, funds, insiders).\r\n<h2>\ud83d\udcb7 Case Example:<\/h2>\r\nBefore the 2021 Shiba Inu rally, a handful of wallets began accumulating billions of tokens over a two-week period. The price exploded shortly after, validating the whale behavior as a lead indicator.\r\n<h2>\ud83c\udf40 Caution:<\/h2>\r\nNot all large wallets are whales \u2014 some are exchanges, staking pools, or bridge contracts. Proper tagging and attribution are vital to avoid misreading the data.\r\n<h2>\ud83c\udf40 Exchange Flows and Wallet Movements<\/h2>\r\nExchange inflows and outflows are powerful real-time indicators of market sentiment. They reflect traders\u2019 intent to sell, hold, or accumulate based on the behavior of funds moving on- and off-exchange.\r\n<h2>\ud83c\udf40 Exchange Inflows<\/h2>\r\nLarge amounts of crypto being sent to exchanges often signal potential sell pressure. Traders or whales might be preparing to realize profits, cut losses, or rotate capital.\r\n<ul>\r\n \t<li>Sudden spikes in inflows during rallies may precede local tops<\/li>\r\n \t<li>Consistent inflows during downtrends often correlate with panic selling<\/li>\r\n<\/ul>\r\n<h2>\ud83d\udcb7 Exchange Outflows<\/h2>\r\nConversely, large outflows (especially to new or cold wallets) indicate accumulation or long-term holding intentions.\r\n<ul>\r\n \t<li>Outflows after price corrections may suggest whale buy zones<\/li>\r\n \t<li>Decreasing exchange reserves across multiple platforms often correlate with\u00a0<strong>bullish momentum<\/strong><\/li>\r\n<\/ul>\r\n<h2>Tracking Tools<\/h2>\r\n<ul>\r\n \t<li><strong>CryptoQuant, Glassnode, Santiment<\/strong>\u00a0\u2014 for exchange balance dashboards<\/li>\r\n \t<li><strong>LookIntoBitcoin<\/strong>\u00a0\u2014 historical overlays of exchange flows with price charts<\/li>\r\n<\/ul>\r\n<h2>Smart Strategy Use:<\/h2>\r\nDuring market uncertainty, monitor stablecoin exchange inflows too. A spike in USDT or USDC deposits might front-run buying pressure for major assets like BTC or ETH.\r\n<h3>Watch Out For:<\/h3>\r\n<ul>\r\n \t<li><strong>Internal exchange transfers<\/strong>\u00a0or\u00a0<strong>maintenance flows<\/strong>\u00a0can create noise.<\/li>\r\n \t<li><strong>Rely on aggregated data across exchanges<\/strong>\u00a0to filter out anomalies.<\/li>\r\n<\/ul>\r\n<h2>Network Value and Economic Throughput<\/h2>\r\nUnderstanding the underlying\u00a0<strong>economic activity<\/strong>\u00a0on a blockchain is key to identifying true utility, adoption trends, and whether price action is backed by real fundamentals.\r\n<h3>NVT Ratio (Network Value to Transactions)<\/h3>\r\nThe\u00a0<strong>NVT ratio<\/strong>\u00a0compares a crypto asset\u2019s market cap to the total USD volume transmitted on-chain. It\u2019s often dubbed the \"P\/E ratio\" of crypto.\r\n<ul>\r\n \t<li><strong>High NVT<\/strong>\u00a0= potentially overvalued (price rising faster than usage)<\/li>\r\n \t<li><strong>Low NVT<\/strong>\u00a0= potentially undervalued (network activity is outpacing price)<\/li>\r\n<\/ul>\r\n<h3>Example:<\/h3>\r\nWhen Bitcoin\u2019s NVT rises while price rallies, it might hint at an overheated move lacking on-chain support.\r\n<h3>Adjusted Transaction Volume<\/h3>\r\nRaw transaction counts can be misleading (spam, small transfers). Instead, we look at:\r\n<ul>\r\n \t<li><strong>Adjusted TX volume<\/strong>\u00a0(filtering out self-sends)<\/li>\r\n \t<li><strong>Value-adjusted activity<\/strong>\u00a0(considering USD value of each transaction)<\/li>\r\n<\/ul>\r\nThese metrics reflect\u00a0<strong>true network usage<\/strong>\u00a0and capital throughput.\r\n<h2>Tools:<\/h2>\r\n<ul>\r\n \t<li><strong>Glassnode<\/strong>\u00a0\u2014 NVT, Adjusted TX Volume, Velocity charts<\/li>\r\n \t<li><strong>IntoTheBlock<\/strong>\u00a0\u2014 Value moved by transaction size tiers (e.g. whale volume vs. retail)<\/li>\r\n<\/ul>\r\n<h2>Strategic Takeaway:<\/h2>\r\nCombine NVT with volume delta and trend filters to validate whether a breakout is supported by real capital flow or driven by speculation alone.\r\n<h2>Whale Tracking and Wallet Clustering<\/h2>\r\nIn crypto markets,\u00a0<strong>whale behavior<\/strong>\u00a0often precedes major price movements. Monitoring large wallet addresses and clustering related wallets offers a deep edge for directional bias and risk-on\/risk-off shifts.\r\n<h3>Who Are the Whales?<\/h3>\r\nWhales typically include:\r\n<ul>\r\n \t<li>Early investors<\/li>\r\n \t<li>Hedge funds and institutions<\/li>\r\n \t<li>Large OTC traders<\/li>\r\n \t<li>Protocol treasuries<\/li>\r\n<\/ul>\r\nTheir actions\u2014accumulation, distribution, long dormancy\u2014can\u00a0<strong>telegraph intent<\/strong>\u00a0before it\u2019s reflected in the market.\r\n<h2>Wallet Clustering<\/h2>\r\nBlockchain analysis tools can\u00a0<strong>group addresses<\/strong>\u00a0that likely belong to the same entity based on:\r\n<ul>\r\n \t<li>Input co-spending<\/li>\r\n \t<li>Behavioral patterns<\/li>\r\n \t<li>Heuristic linking<\/li>\r\n<\/ul>\r\nExample: A cluster of addresses consistently sending coins to a known exchange wallet may indicate a coordinated sell.\r\n<h2>Key Metrics to Track<\/h2>\r\n<div>\r\n<table>\r\n<thead>\r\n<tr>\r\n<th>Metric<\/th>\r\n<th>Insight<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>Whale accumulation zones<\/td>\r\n<td>Areas where large players consistently buy<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Exchange inflows\/outflows<\/td>\r\n<td>Whales moving funds to\/from CEXs<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Dormant supply shift<\/td>\r\n<td>Long-held tokens becoming active<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\n<h2>Tools:<\/h2>\r\n<ul>\r\n \t<li><strong>Whalemap.io<\/strong>\u00a0\u2013 Real-time whale cluster zones<\/li>\r\n \t<li><strong>Santiment<\/strong>\u00a0\u2013 On-chain social + whale flow combo<\/li>\r\n \t<li><strong>Nansen<\/strong>\u00a0\u2013 Entity tagging, smart money dashboards<\/li>\r\n<\/ul>\r\n<h2>Strategic Takeaway:<\/h2>\r\nLook for divergence between retail activity and whale flows. For example, if whales are quietly accumulating while retail is fearful, it may signal a hidden bottom.\r\n<h2>Transaction Analysis and Flow Mapping<\/h2>\r\nTo go beyond surface-level metrics,\u00a0<strong>transaction flow mapping<\/strong>\u00a0allows traders to trace the origin, destination, and intent behind major on-chain movements. It\u2019s a forensic approach to understanding capital behavior.\r\n<h2>Key Concepts<\/h2>\r\n<ul>\r\n \t<li><strong>Transaction Clustering:<\/strong>\u00a0Grouping related transfers to identify pattern behavior (e.g., whale-to-exchange-to-DEX swap).<\/li>\r\n \t<li><strong>Temporal Flow Analysis:<\/strong>\u00a0Studying the timing of inflows\/outflows to forecast\u00a0<strong>liquidity cycles<\/strong>\u00a0and\u00a0<strong>event-driven trading<\/strong>.<\/li>\r\n \t<li><strong>Smart Contract Interaction:<\/strong>\u00a0Detecting how tokens move through DeFi protocols, staking contracts, or automated market makers (AMMs).<\/li>\r\n<\/ul>\r\n<h2>What to Watch<\/h2>\r\n<div>\r\n<table>\r\n<thead>\r\n<tr>\r\n<th>Type of Flow<\/th>\r\n<th>Implication<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>Wallet \u2192 Exchange<\/td>\r\n<td>Possible sell pressure incoming<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Exchange \u2192 Wallet<\/td>\r\n<td>Accumulation, long-term holding<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>Wallet \u2192 DeFi Protocol<\/td>\r\n<td>Yield farming, leveraged positioning<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>DEX Swap (Token A \u2192 B)<\/td>\r\n<td>Rotation or hedging strategy<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\n<h2>\u2715 Tools for Flow Analysis<\/h2>\r\n<ul>\r\n \t<li><strong>Arkham Intelligence<\/strong>\u00a0\u2013 Entity identification &amp; visual flow charts<\/li>\r\n \t<li><strong>DeBank &amp; Zapper<\/strong>\u00a0\u2013 Wallet-level DeFi movement<\/li>\r\n \t<li><strong>Dune Analytics<\/strong>\u00a0\u2013 Custom flow queries (e.g., whale transactions before major events)<\/li>\r\n<\/ul>\r\n<h2>\u2611 Strategy in Action<\/h2>\r\nBefore the Curve Finance exploit in 2023, flow analysis revealed a spike in stablecoin movement from Curve LPs to centralized exchanges \u2014 a precursor to the liquidity crunch that followed.\r\n<h2>\ud83d\udcc5 Common Mistakes<\/h2>\r\n<ul>\r\n \t<li>Misinterpreting bridge activity as sell pressure<\/li>\r\n \t<li>Ignoring gas-efficient batch transfers (used by whales or funds)<\/li>\r\n<\/ul>\r\n[cta_green text=\"Start trading\"]\r\n\r\n&nbsp;\r\n<h2>\ud83d\udcdd Conclusion<\/h2>\r\nOn-chain analysis has emerged as a critical tool in modern cryptocurrency trading. By dissecting blockchain activity\u2014transaction flows, wallet behavior, and network metrics\u2014traders gain a real-time view of market dynamics often hidden from traditional chart-based analysis. When combined with social sentiment and technical strategies, on-chain data offers a robust edge in a volatile and often speculative market. For serious traders, developing a workflow that integrates on-chain signals is no longer optional\u2014it's a competitive necessity.\r\n\r\nKeep testing, stay curious, and remember: the blockchain never lies.\r\n<h2>\ud83d\udd0d Sources<\/h2>\r\n<ul>\r\n \t<li style=\"list-style-type: none;\">\r\n<ul>\r\n \t<li>QuantInsti \u2013 Machine Learning for Trading<\/li>\r\n \t<li>CBOE \u2013 Understanding Market Microstructure<\/li>\r\n \t<li>BIS \u2013 Algorithmic Trading Practices<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>","body_html_source":{"label":"Body HTML","type":"wysiwyg","formatted_value":"<p>Whether you&#8217;re tracking large wallet movements, monitoring token inflows to exchanges, or evaluating the health of a blockchain ecosystem, on-chain metrics provide a unique window into what&#8217;s happening behind the scenes. For binary options and spot traders alike, integrating blockchain analysis into your strategy can improve timing, sharpen risk assessment, and uncover signals missed by conventional technical tools.<\/p>\n<p>This guide explores the essential metrics, frameworks, and practical strategies for leveraging on-chain data to make smarter trading decisions in crypto markets.<\/p>\n<h2>What Is On-Chain Analysis?<\/h2>\n<p>On-chain analysis refers to the examination of data recorded directly on public blockchains. Unlike technical analysis, which interprets historical price movements, or fundamental analysis, which evaluates project viability, on-chain analysis dives into the real-time behavior of users, miners, and network validators. It uses data such as wallet balances, transaction flows, exchange inflows\/outflows, and smart contract activity to assess the health and sentiment of a crypto asset.<\/p>\n<p>Because blockchain data is transparent and immutable, traders can observe the exact movements of large holders (often referred to as \u201cwhales\u201d), analyze network activity spikes, or detect early signs of capitulation or accumulation. This makes it particularly valuable in highly speculative markets like crypto, where news cycles and emotional trading often distort the true picture.<\/p>\n<p>Modern on-chain platforms allow users to track these metrics visually and apply them contextually to their strategies. As institutional adoption increases, so does the value of on-chain data as a way to interpret crowd psychology, anticipate volatility, and refine entries and exits.<\/p>\n<h2>\u2714 Essential On-Chain Metrics: What They Reveal<\/h2>\n<p>Mastering on-chain trading begins with decoding the raw data written on blockchains. These aren\u2019t just numbers \u2014 they\u2019re behavioral signals, showing what different market participants are doing in real time. Here\u2019s how to read the most telling metrics:<\/p>\n<h3>\u2714 Unique Active Wallets<\/h3>\n<p>This reflects how many addresses are participating in transactions daily. A rise may indicate user growth, adoption, or speculative activity. A sharp drop? Possible disengagement or declining demand.<\/p>\n<h3>\u2714 Exchange Wallet Movements<\/h3>\n<p>When large sums flow into exchanges, it often means traders are preparing to sell \u2014 a potential bearish flag. Outflows, especially during dips, can suggest accumulation and a bullish outlook.<\/p>\n<h3>\u2718 Large Holder Transfers<\/h3>\n<p>Big wallets (aka whales) tend to move quietly but leave massive footprints. Noticing consistent buys from these addresses often precedes price rallies. Spotting distribution? Might be time to tighten risk.<\/p>\n<h3>\u2714 NVT (Network Value to Transactions)<\/h3>\n<p>Think of it as a crypto version of the P\/E ratio. If market cap balloons but transaction volume doesn\u2019t follow \u2014 the asset might be overpriced relative to real usage.<\/p>\n<h3>\u2718 Gas Fees and Congestion<\/h3>\n<p>Skyrocketing transaction fees, particularly on networks like Ethereum, hint at a frenzy \u2014 NFT launches, hype-driven DeFi projects, or panic selling. High fees = network stress = volatility.<\/p>\n<h2>MVRV (Market Value vs. Realized Value)<\/h2>\n<p>This metric compares the current market cap to the aggregate price users paid for their coins. High MVRV values may suggest profit-taking zones; low values can flag oversold conditions.<\/p>\n<p>Individually, these metrics are useful \u2014 but together, they paint a high-resolution image of market psychology.<\/p>\n<h2>5 Whale Tracking and Behavioral Patterns<\/h2>\n<p>In the world of crypto, not all wallets are created equal. A small group of high-capital entities \u2014 often referred to as \u201cwhales\u201d \u2014 can significantly sway markets. On-chain analysis gives traders a rare chance to observe their movements in real time, revealing powerful sentiment signals.<\/p>\n<h3>Exchange Inflows from Whales<\/h3>\n<p>When large wallets transfer assets to centralized exchanges, it\u2019s often a preparation for liquidation. Tracking these inflows can help anticipate selling pressure before it hits the charts.<\/p>\n<h3>Cold Wallet Accumulation<\/h3>\n<p>If whales are consistently moving funds from exchanges to cold storage, it suggests long-term conviction and reduced short-term selling risk \u2014 a bullish signal, especially during price consolidation phases.<\/p>\n<h3>\u201cSmart Money\u201d Distribution<\/h3>\n<p>Sudden transfers from multiple large wallets to exchanges during pumps may point to coordinated exits. Recognizing these shifts early can help retail traders avoid buying into tops.<\/p>\n<h3>Wallet Labeling Tools<\/h3>\n<p>Modern on-chain platforms like Nansen and Arkham Intelligence help identify wallet owners or behavioral patterns by tagging exchange wallets, institutional players, and active DeFi participants. These tools enable traders to monitor whale behavior with greater precision.<\/p>\n<h3>Example:<\/h3>\n<p>A notable case occurred before Bitcoin\u2019s drop in May 2021 \u2014 several whale wallets began sending BTC to exchanges in unusually high volumes days before the price decline, signaling insider exits.<\/p>\n<p>Understanding how whales move their assets is like reading the footprints of market-moving players. These insights often come before price reacts, giving on-chain analysts a distinct advantage.<\/p>\n<h2>Protocol-Level Data Interpretation<\/h2>\n<p>Beyond wallet activity, each blockchain protocol generates a wealth of internal metrics that reflect its health, user engagement, and economic activity. These protocol-specific insights can be invaluable when evaluating both short-term sentiment and long-term potential.<\/p>\n<h2>Staking Participation and Governance<\/h2>\n<p>For proof-of-stake chains, the proportion of tokens staked often signals network confidence. A rising staking ratio implies user commitment and belief in network security. Additionally, high governance participation (e.g., votes on DAO proposals) can indicate an active, invested community.<\/p>\n<h3>Fee Revenue and Gas Utilization<\/h3>\n<p>Blockchains like Ethereum or Solana generate protocol fees \u2014 a direct indicator of usage. Surging gas fees during peak periods reflect demand pressure. Tracking fee trends helps distinguish hype from sustainable utility.<\/p>\n<h2>TVL (Total Value Locked)<\/h2>\n<p>In DeFi ecosystems, TVL measures how much capital is actively engaged in smart contracts. A growing TVL, especially on newer protocols, shows rising market trust. But if TVL climbs without matching user activity or volume, it may indicate unsustainable incentives.<\/p>\n<h2>Developer Activity<\/h2>\n<p>Development metrics from GitHub or blockchain-specific tools (e.g., Electric Capital reports) provide context on protocol maturity. Consistent code commits and ecosystem upgrades signal innovation \u2014 key for identifying long-term holds.<\/p>\n<h3>Example:<\/h3>\n<p>During the 2021 bull run, Avalanche\u2019s TVL exploded, driven by strong staking incentives. However, a simultaneous rise in developer activity and consistent wallet growth confirmed that the interest wasn\u2019t purely mercenary.<\/p>\n<p>Protocol-level data offers a window into the real engine of a blockchain \u2014 its infrastructure, usage, and sustainability. Traders who dig deeper than price often spot winning trends early.<\/p>\n<h2>Transaction Volume and Velocity Metrics<\/h2>\n<p>Understanding how funds move through a blockchain is essential to identifying shifts in market sentiment, liquidity cycles, and the emergence of new trends. Transaction volume and velocity are two key indicators that offer deep insight into the flow of capital.<\/p>\n<h3>Transaction Volume: Real vs. Wash<\/h3>\n<p>Total transaction volume measures the raw throughput on a network. However, traders must differentiate between\u00a0<strong>organic volume<\/strong>\u00a0and\u00a0<strong>wash trading<\/strong>\u00a0or automated activity.<\/p>\n<ul>\n<li><strong>Organic volume<\/strong>\u00a0(e.g., user transfers, DEX trades, NFT sales) shows healthy user engagement.<\/li>\n<li><strong>Suspiciously high volume<\/strong>\u00a0without user growth can signal manipulation \u2014 common in low-liquidity altcoins.<\/li>\n<\/ul>\n<h3>Velocity of Money<\/h3>\n<p>Velocity refers to how quickly tokens change hands. A high velocity implies active usage and trading, while low velocity suggests hoarding or long-term holding.<\/p>\n<ul>\n<li><strong>Rising velocity<\/strong>\u00a0during a price rally can suggest retail speculation or short-term trading interest.<\/li>\n<li><strong>Falling velocity<\/strong>\u00a0while price climbs may indicate accumulation by whales or institutions.<\/li>\n<\/ul>\n<h3>\u2611 Metric Interplay Example:<\/h3>\n<p>In early 2023, BNB Chain saw declining velocity but rising price and volume \u2014 a sign of accumulation by large holders ahead of ecosystem upgrades.<\/p>\n<h3>\ud83d\udccd Layer 2s and Bridges<\/h3>\n<p>With cross-chain infrastructure and rollups becoming common, it\u2019s important to also track transaction flow between chains. A surge in volume moving from Ethereum to Arbitrum, for example, often signals upcoming trading activity on the L2.<\/p>\n<h2>\ud83d\udd17 Whale Watching and Token Concentration<\/h2>\n<p>In decentralized markets, large holders\u2014often called \u201cwhales\u201d\u2014can significantly sway price movements. Monitoring their behavior is a critical component of on-chain analysis.<\/p>\n<h3>\ud83d\ude80\ufe0f Whale Wallet Tracking<\/h3>\n<p>Whales are wallets holding large amounts of a specific token (typically top 1\u20135% by holdings). By tracking their actions, traders can anticipate large inflows\/outflows before they impact price.<\/p>\n<ul>\n<li><strong>Accumulation:<\/strong>\u00a0If whales are steadily increasing holdings during a dip, this may signal a reversal or long-term bullish expectation.<\/li>\n<li><strong>Distribution:<\/strong>\u00a0Rapid outflows from top wallets near local tops often precede sharp corrections.<\/li>\n<\/ul>\n<h3>\ud83d\ude80\ufe0f Token Distribution Metrics<\/h3>\n<p>Token concentration offers a window into market stability or fragility.<\/p>\n<ul>\n<li><strong>High concentration<\/strong>\u00a0= more control by a few entities (e.g., insider-driven or VC-heavy projects).<\/li>\n<li><strong>Low concentration<\/strong>\u00a0= more decentralization and potentially more organic growth.<\/li>\n<\/ul>\n<h3><strong><em>Metric Tip:<\/em><\/strong><\/h3>\n<p>Tools like Nansen or Lookonchain allow real-time tracking of labeled wallets (e.g., exchanges, funds, insiders).<\/p>\n<h2>\ud83d\udcb7 Case Example:<\/h2>\n<p>Before the 2021 Shiba Inu rally, a handful of wallets began accumulating billions of tokens over a two-week period. The price exploded shortly after, validating the whale behavior as a lead indicator.<\/p>\n<h2>\ud83c\udf40 Caution:<\/h2>\n<p>Not all large wallets are whales \u2014 some are exchanges, staking pools, or bridge contracts. Proper tagging and attribution are vital to avoid misreading the data.<\/p>\n<h2>\ud83c\udf40 Exchange Flows and Wallet Movements<\/h2>\n<p>Exchange inflows and outflows are powerful real-time indicators of market sentiment. They reflect traders\u2019 intent to sell, hold, or accumulate based on the behavior of funds moving on- and off-exchange.<\/p>\n<h2>\ud83c\udf40 Exchange Inflows<\/h2>\n<p>Large amounts of crypto being sent to exchanges often signal potential sell pressure. Traders or whales might be preparing to realize profits, cut losses, or rotate capital.<\/p>\n<ul>\n<li>Sudden spikes in inflows during rallies may precede local tops<\/li>\n<li>Consistent inflows during downtrends often correlate with panic selling<\/li>\n<\/ul>\n<h2>\ud83d\udcb7 Exchange Outflows<\/h2>\n<p>Conversely, large outflows (especially to new or cold wallets) indicate accumulation or long-term holding intentions.<\/p>\n<ul>\n<li>Outflows after price corrections may suggest whale buy zones<\/li>\n<li>Decreasing exchange reserves across multiple platforms often correlate with\u00a0<strong>bullish momentum<\/strong><\/li>\n<\/ul>\n<h2>Tracking Tools<\/h2>\n<ul>\n<li><strong>CryptoQuant, Glassnode, Santiment<\/strong>\u00a0\u2014 for exchange balance dashboards<\/li>\n<li><strong>LookIntoBitcoin<\/strong>\u00a0\u2014 historical overlays of exchange flows with price charts<\/li>\n<\/ul>\n<h2>Smart Strategy Use:<\/h2>\n<p>During market uncertainty, monitor stablecoin exchange inflows too. A spike in USDT or USDC deposits might front-run buying pressure for major assets like BTC or ETH.<\/p>\n<h3>Watch Out For:<\/h3>\n<ul>\n<li><strong>Internal exchange transfers<\/strong>\u00a0or\u00a0<strong>maintenance flows<\/strong>\u00a0can create noise.<\/li>\n<li><strong>Rely on aggregated data across exchanges<\/strong>\u00a0to filter out anomalies.<\/li>\n<\/ul>\n<h2>Network Value and Economic Throughput<\/h2>\n<p>Understanding the underlying\u00a0<strong>economic activity<\/strong>\u00a0on a blockchain is key to identifying true utility, adoption trends, and whether price action is backed by real fundamentals.<\/p>\n<h3>NVT Ratio (Network Value to Transactions)<\/h3>\n<p>The\u00a0<strong>NVT ratio<\/strong>\u00a0compares a crypto asset\u2019s market cap to the total USD volume transmitted on-chain. It\u2019s often dubbed the &#8220;P\/E ratio&#8221; of crypto.<\/p>\n<ul>\n<li><strong>High NVT<\/strong>\u00a0= potentially overvalued (price rising faster than usage)<\/li>\n<li><strong>Low NVT<\/strong>\u00a0= potentially undervalued (network activity is outpacing price)<\/li>\n<\/ul>\n<h3>Example:<\/h3>\n<p>When Bitcoin\u2019s NVT rises while price rallies, it might hint at an overheated move lacking on-chain support.<\/p>\n<h3>Adjusted Transaction Volume<\/h3>\n<p>Raw transaction counts can be misleading (spam, small transfers). Instead, we look at:<\/p>\n<ul>\n<li><strong>Adjusted TX volume<\/strong>\u00a0(filtering out self-sends)<\/li>\n<li><strong>Value-adjusted activity<\/strong>\u00a0(considering USD value of each transaction)<\/li>\n<\/ul>\n<p>These metrics reflect\u00a0<strong>true network usage<\/strong>\u00a0and capital throughput.<\/p>\n<h2>Tools:<\/h2>\n<ul>\n<li><strong>Glassnode<\/strong>\u00a0\u2014 NVT, Adjusted TX Volume, Velocity charts<\/li>\n<li><strong>IntoTheBlock<\/strong>\u00a0\u2014 Value moved by transaction size tiers (e.g. whale volume vs. retail)<\/li>\n<\/ul>\n<h2>Strategic Takeaway:<\/h2>\n<p>Combine NVT with volume delta and trend filters to validate whether a breakout is supported by real capital flow or driven by speculation alone.<\/p>\n<h2>Whale Tracking and Wallet Clustering<\/h2>\n<p>In crypto markets,\u00a0<strong>whale behavior<\/strong>\u00a0often precedes major price movements. Monitoring large wallet addresses and clustering related wallets offers a deep edge for directional bias and risk-on\/risk-off shifts.<\/p>\n<h3>Who Are the Whales?<\/h3>\n<p>Whales typically include:<\/p>\n<ul>\n<li>Early investors<\/li>\n<li>Hedge funds and institutions<\/li>\n<li>Large OTC traders<\/li>\n<li>Protocol treasuries<\/li>\n<\/ul>\n<p>Their actions\u2014accumulation, distribution, long dormancy\u2014can\u00a0<strong>telegraph intent<\/strong>\u00a0before it\u2019s reflected in the market.<\/p>\n<h2>Wallet Clustering<\/h2>\n<p>Blockchain analysis tools can\u00a0<strong>group addresses<\/strong>\u00a0that likely belong to the same entity based on:<\/p>\n<ul>\n<li>Input co-spending<\/li>\n<li>Behavioral patterns<\/li>\n<li>Heuristic linking<\/li>\n<\/ul>\n<p>Example: A cluster of addresses consistently sending coins to a known exchange wallet may indicate a coordinated sell.<\/p>\n<h2>Key Metrics to Track<\/h2>\n<div>\n<table>\n<thead>\n<tr>\n<th>Metric<\/th>\n<th>Insight<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Whale accumulation zones<\/td>\n<td>Areas where large players consistently buy<\/td>\n<\/tr>\n<tr>\n<td>Exchange inflows\/outflows<\/td>\n<td>Whales moving funds to\/from CEXs<\/td>\n<\/tr>\n<tr>\n<td>Dormant supply shift<\/td>\n<td>Long-held tokens becoming active<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h2>Tools:<\/h2>\n<ul>\n<li><strong>Whalemap.io<\/strong>\u00a0\u2013 Real-time whale cluster zones<\/li>\n<li><strong>Santiment<\/strong>\u00a0\u2013 On-chain social + whale flow combo<\/li>\n<li><strong>Nansen<\/strong>\u00a0\u2013 Entity tagging, smart money dashboards<\/li>\n<\/ul>\n<h2>Strategic Takeaway:<\/h2>\n<p>Look for divergence between retail activity and whale flows. For example, if whales are quietly accumulating while retail is fearful, it may signal a hidden bottom.<\/p>\n<h2>Transaction Analysis and Flow Mapping<\/h2>\n<p>To go beyond surface-level metrics,\u00a0<strong>transaction flow mapping<\/strong>\u00a0allows traders to trace the origin, destination, and intent behind major on-chain movements. It\u2019s a forensic approach to understanding capital behavior.<\/p>\n<h2>Key Concepts<\/h2>\n<ul>\n<li><strong>Transaction Clustering:<\/strong>\u00a0Grouping related transfers to identify pattern behavior (e.g., whale-to-exchange-to-DEX swap).<\/li>\n<li><strong>Temporal Flow Analysis:<\/strong>\u00a0Studying the timing of inflows\/outflows to forecast\u00a0<strong>liquidity cycles<\/strong>\u00a0and\u00a0<strong>event-driven trading<\/strong>.<\/li>\n<li><strong>Smart Contract Interaction:<\/strong>\u00a0Detecting how tokens move through DeFi protocols, staking contracts, or automated market makers (AMMs).<\/li>\n<\/ul>\n<h2>What to Watch<\/h2>\n<div>\n<table>\n<thead>\n<tr>\n<th>Type of Flow<\/th>\n<th>Implication<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Wallet \u2192 Exchange<\/td>\n<td>Possible sell pressure incoming<\/td>\n<\/tr>\n<tr>\n<td>Exchange \u2192 Wallet<\/td>\n<td>Accumulation, long-term holding<\/td>\n<\/tr>\n<tr>\n<td>Wallet \u2192 DeFi Protocol<\/td>\n<td>Yield farming, leveraged positioning<\/td>\n<\/tr>\n<tr>\n<td>DEX Swap (Token A \u2192 B)<\/td>\n<td>Rotation or hedging strategy<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h2>\u2715 Tools for Flow Analysis<\/h2>\n<ul>\n<li><strong>Arkham Intelligence<\/strong>\u00a0\u2013 Entity identification &amp; visual flow charts<\/li>\n<li><strong>DeBank &amp; Zapper<\/strong>\u00a0\u2013 Wallet-level DeFi movement<\/li>\n<li><strong>Dune Analytics<\/strong>\u00a0\u2013 Custom flow queries (e.g., whale transactions before major events)<\/li>\n<\/ul>\n<h2>\u2611 Strategy in Action<\/h2>\n<p>Before the Curve Finance exploit in 2023, flow analysis revealed a spike in stablecoin movement from Curve LPs to centralized exchanges \u2014 a precursor to the liquidity crunch that followed.<\/p>\n<h2>\ud83d\udcc5 Common Mistakes<\/h2>\n<ul>\n<li>Misinterpreting bridge activity as sell pressure<\/li>\n<li>Ignoring gas-efficient batch transfers (used by whales or funds)<\/li>\n<\/ul>\n<div class=\"po-container po-container_width_article\">\n   <div class=\"po-cta-green__wrap\">\n      <a href=\"https:\/\/pocketoption.com\/en\/register\/\" class=\"po-cta-green\">Start trading\n         <span class=\"po-cta-green__icon\">\n            <svg width=\"24\" height=\"24\" fill=\"none\" aria-hidden=\"true\">\n               <use href=\"#svg-arrow-cta\"><\/use>\n            <\/svg>\n         <\/span>\n      <\/a>\n   <\/div>\n<\/div>\n<p>&nbsp;<\/p>\n<h2>\ud83d\udcdd Conclusion<\/h2>\n<p>On-chain analysis has emerged as a critical tool in modern cryptocurrency trading. By dissecting blockchain activity\u2014transaction flows, wallet behavior, and network metrics\u2014traders gain a real-time view of market dynamics often hidden from traditional chart-based analysis. When combined with social sentiment and technical strategies, on-chain data offers a robust edge in a volatile and often speculative market. For serious traders, developing a workflow that integrates on-chain signals is no longer optional\u2014it&#8217;s a competitive necessity.<\/p>\n<p>Keep testing, stay curious, and remember: the blockchain never lies.<\/p>\n<h2>\ud83d\udd0d Sources<\/h2>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li>QuantInsti \u2013 Machine Learning for Trading<\/li>\n<li>CBOE \u2013 Understanding Market Microstructure<\/li>\n<li>BIS \u2013 Algorithmic Trading Practices<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n"},"faq":[{"question":"What are the most important on-chain metrics for traders?","answer":" The most relevant on-chain metrics include active addresses, transaction volume, exchange inflow\/outflow, realized cap, and MVRV ratio. These indicators offer insight into market participation, sentiment, and investor behavior."},{"question":"Can whale tracking predict market moves?","answer":"\u00a0While not a guarantee, whale movements can serve as strong market signals. Large inflows to exchanges may precede selling pressure, while withdrawals often indicate accumulation or long-term holding."},{"question":"How reliable is on-chain data for short-term trading?","answer":"On-chain data is generally more suited for medium- to long-term analysis. For short-term strategies, combining it with technical indicators or real-time sentiment data yields better results."},{"question":"Are there risks to relying too much on on-chain data?","answer":"Yes. On-chain data can lag, and interpreting it without broader context may lead to false conclusions. It should be used as part of a multi-dimensional trading approach."},{"question":"Which platforms offer the best on-chain analytics?","answer":"Notable platforms include Glassnode, CryptoQuant, Santiment, and Nansen. Each offers a unique blend of metrics, dashboards, and custom alerts."}],"faq_source":{"label":"FAQ","type":"repeater","formatted_value":[{"question":"What are the most important on-chain metrics for traders?","answer":" The most relevant on-chain metrics include active addresses, transaction volume, exchange inflow\/outflow, realized cap, and MVRV ratio. These indicators offer insight into market participation, sentiment, and investor behavior."},{"question":"Can whale tracking predict market moves?","answer":"\u00a0While not a guarantee, whale movements can serve as strong market signals. Large inflows to exchanges may precede selling pressure, while withdrawals often indicate accumulation or long-term holding."},{"question":"How reliable is on-chain data for short-term trading?","answer":"On-chain data is generally more suited for medium- to long-term analysis. For short-term strategies, combining it with technical indicators or real-time sentiment data yields better results."},{"question":"Are there risks to relying too much on on-chain data?","answer":"Yes. On-chain data can lag, and interpreting it without broader context may lead to false conclusions. It should be used as part of a multi-dimensional trading approach."},{"question":"Which platforms offer the best on-chain analytics?","answer":"Notable platforms include Glassnode, CryptoQuant, Santiment, and Nansen. Each offers a unique blend of metrics, dashboards, and custom alerts."}]}},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.8 (Yoast SEO v27.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Blockchain On-Chain Analysis for Crypto Trading<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pocketoption.com\/blog\/en\/knowledge-base\/markets\/blockchain-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Blockchain On-Chain Analysis for Crypto Trading\" \/>\n<meta property=\"og:url\" content=\"https:\/\/pocketoption.com\/blog\/en\/knowledge-base\/markets\/blockchain-analysis\/\" \/>\n<meta property=\"og:site_name\" content=\"Pocket Option blog\" \/>\n<meta property=\"article:published_time\" 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