Insight Data Issue 02｜OKX & CoinGlass: How to Mine Valuable Data and Develop a Mature Trading Mindset?
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Insight Data Issue 02｜OKX & CoinGlass: How to Mine Valuable Data and Develop a Mature Trading Mindset?
Jointly discussed by the OKX strategy team and CoinGlass Research Institute, covering data dimensions relevant to various trading scenarios, including capturing trading opportunities and cultivating a scientific trading mindset.
Navigating Web3 tides with focused insightsSummary: In the cryptocurrency market, data has always been a crucial factor in making trading decisions. How can we cut through the fog of data to uncover effective insights that optimize our trading strategies? This is an ongoing topic of interest for the market. On this occasion, OKX has specially launched the "Insights on Data" column, collaborating with leading data platforms such as CoinGlass and AICoin, starting from common user needs, aiming to develop a more systematic methodology around data use for reference and learning by the broader market.
Below is the second installment, jointly prepared by the OKX Strategy Team and the CoinGlass Research Institute, discussing the different dimensions of data relevant across various trading scenarios—ranging from capturing trading opportunities to cultivating scientific trading thinking—with the hope of being helpful to you.
CoinGlass: CoinGlass is a global cryptocurrency data analytics platform dedicated to providing users with comprehensive market monitoring and in-depth data interpretation services. CoinGlass offers real-time market data, depth analysis, futures and options positions, funding rates, liquidation data, and other tools to help traders better understand market dynamics and risk conditions. Through intuitive charts and regular market reports, CoinGlass has become an essential tool for analyzing the global crypto market.
OKX Strategy Team: The OKX Strategy Team consists of a group of experienced professionals committed to advancing innovation in the field of global digital asset strategies. Drawing expertise from market analysis, risk management, and financial engineering, the team provides solid support for OKX's strategic development based on deep professional knowledge and extensive practical experience.
1. For novice users, which data dimensions are most valuable?
CoinGlass: Novice users typically lack trading experience and professional knowledge, so they tend to prefer simple, intuitive, and easy-to-understand data indicators. These indicators often have high reference value because they quickly reflect market sentiment and trends. For example, the Fear & Greed Index, long/short ratio, ETF fund inflows/outflows, and CME open interest changes are all metrics that beginners can grasp easily. These indicators clearly reflect market sentiment and trader behavior, helping users rapidly understand market movements and make informed decisions.
So how can they quickly learn to interpret these simple data points? Here are some tips:
First, regularly monitor key indicators such as ETF fund flows, the Fear & Greed Index, and long/short ratios. When these indicators change, use charting tools to visually analyze their relationship with price movements.
Second, review the historical trends of these indicators and compare them with price charts to understand how indicator shifts correspond to market movements.
Third, learn foundational analytical methods, including mastering basic technical analysis and market sentiment analysis principles and techniques.
Fourth, follow market news and expert commentary to accumulate more market knowledge and experience, which helps deepen understanding of market context and directional trends.
Finally, practice via simulated trading and conduct post-trade reviews using data to enhance your ability to interpret and apply data. With consistent effort, users can gradually improve their data literacy and application skills, enabling more confident and sound decision-making.
OKX Strategy Team: We summarize the following four aspects along with corresponding analytical tips for user reference:
First, price trend data. Current price, historical price trends, moving averages (MA), Relative Strength Index (RSI), Bollinger Bands, etc., fall into this category. These data help users understand the general market direction and identify optimal entry and exit points. Regarding moving averages (MA), when price is above MA, the market may be in an uptrend; when below MA, it may be in a downtrend; and when a short-term MA crosses above a long-term MA, it could signal a trend reversal. As for RSI, if RSI exceeds 70, the market may be overbought and a sell might be considered; if RSI falls below 30, the market may be oversold and a buy considered. With Bollinger Bands, when price approaches the upper band, resistance may occur and a sell signal emerge; when approaching the lower band, support may appear and suggest a buying opportunity; and when the bandwidth narrows, it may indicate an imminent breakout.
Second, volume data. Volume reflects market activity and helps assess the strength and sustainability of trends. The core principle of volume-price analysis is: rising volume with rising price suggests continued upward momentum, while rising volume with falling price may indicate deeper declines or trend reversals. In volume patterns, if the market was previously sluggish with low volume and price, but volume gradually increases alongside a slow price rise, this may signal large capital beginning to enter, potentially forming a new bullish trend. Increased trading activity means more participants, possibly signaling a trend shift. A surge in volume after a sharp decline may mean selling pressure is easing and buyers are entering, indicating potential stabilization—though not necessarily immediate rebound. Counter-trend volume spikes in individual coins during broad market downturns may reflect unique factors requiring fundamental analysis to judge sustainability and future direction.
Third, fundamental data. Project announcements, partnerships, technological progress, tokenomics, and regulatory developments all belong to fundamental data. These provide insight into a project’s long-term potential and risks, supporting more informed trading decisions. Users should pay attention to major announcements and assess their potential impact on development; track technical milestones to evaluate feasibility; analyze tokenomics including supply mechanisms, inflation rates, and utility; and monitor regulatory changes for their implications.
Lastly, market sentiment data. Social media mentions, Fear & Greed Index, and derivatives funding rates are examples. These reflect traders’ psychological states and help identify potential reversal points. A sudden spike in social media buzz may foreshadow short-term volatility, while sustained high热度 may indicate excessive hype. On the Fear & Greed Index, extreme fear (0–25) may present buying opportunities, whereas extreme greed (75–100) may signal selling time. Regarding funding rates, persistently high positive rates indicate strong bullish sentiment and potential correction; persistently negative rates suggest bearish dominance and possible rebounds.
2. For advanced users, diversified asset allocation is important—how should it be approached effectively?
CoinGlass: We recommend advanced users focus on the following dimensions:
First, promising coin screening. Filter coins based on criteria like price, market cap, circulating supply, and exchange listings to identify those with growth potential for precise positioning. This method helps traders find higher-potential assets and achieve better returns.
Second, portfolio construction. The key lies in correlation analysis—selecting assets with low correlations to diversify risk, thereby improving overall stability and return. Low-correlation assets ensure that when some assets fall, others may rise, balancing total performance.
Third, derivative arbitrage opportunities. Use funding rate arbitrage calculators to discover and execute funding rate arbitrage, increasing overall yield. Funding rate arbitrage is a relatively low-risk strategy that generates stable returns amid market fluctuations.
Fourth, portfolio monitoring. Portfolio monitoring tools allow testing of different trading scenarios' profit and risk profiles, enabling periodic review and adjustment to optimize allocation strategies. This helps traders stay aware of portfolio performance and adapt promptly to changing markets.
Fifth, risk management tools. Utilize various tools and techniques such as stop-loss orders and hedging strategies to control trading risk. Effective risk management is essential for preserving capital amid market volatility.
OKX Strategy Team: From our observations, strategic product selection is critical for this group. Commonly used tools include dollar-cost averaging (DCA), portfolio arbitrage, and large-order splitting. DCA reduces average holding cost through periodic purchases; portfolio arbitrage lowers risk via hedging; large-order splitting minimizes market impact and transaction costs by breaking big orders into smaller ones. Combining these strategies according to their characteristics enables large-capital users to conduct diversified allocation more efficiently and achieve steady trading goals.
Dollar-Cost Averaging (multi-coin combination, regular purchases) is a strategy that lowers average holding cost through periodic buying. Continuously purchase at lower prices during downturns and take profits during rebounds, repeating cyclically to capture incremental gains.
Portfolio Arbitrage is a strategy designed to hedge and reduce trading risk. It allows simultaneous execution across different or identical coins/markets, automatically locking in profits by exploiting price spreads and market oscillations. This strategy effectively reduces potential losses due to future market uncertainty.
Large-Order Splitting is a convenient trading strategy for high-volume traders. It breaks large orders into smaller chunks for gradual placement. Thanks to intelligent algorithmic settings, this strategy minimizes market impact while maintaining a relatively high average fill price, significantly reducing trading costs for large transactions.
3. Timing is key to success—how can traders identify optimal trading opportunities?
CoinGlass: Timing is crucial. In the previous question, we introduced several key data dimensions that play a vital role in identifying ideal buy/sell moments. Below, we briefly outline the data and analytical methods applicable during position entry and profit-taking/stopping phases.
During Position Entry:
Liquidation heatmaps show that when liquidation intensity concentrates around a specific price range, price tends to move toward that zone—traders can enter positions in the direction of concentrated liquidation levels. If there is substantial ETF inflow—for instance, BTC ETF daily inflows far exceeding average levels—it indicates growing market interest in BTC, suggesting opportunities to initiate or add to positions. Long-term Bitcoin funding rates below the benchmark (0.01%) usually signal consolidation or near-bottom conditions, suitable for accumulating positions. A significant increase in open interest suggests fresh capital entering the market, boosting activity—often preceding an uptrend. For example, a sudden 10% rise in CME Bitcoin futures open interest implies institutional confidence in future market direction, warranting consideration of opening or holding positions.
Prolonged low volume often indicates consolidation or bottoming, making it favorable for accumulation. Rising spot inflows reflect increased buying demand—a bullish signal—and justify initiating positions to capture upside potential. A low long/short ratio means bears dominate, which may trigger short covering and subsequent price rises—an ideal time to build positions. A Fear & Greed Index persistently below 20 signals extreme fear and depressed prices, offering bottom-fishing opportunities—gradual accumulation is advisable.
During Profit-Taking and Stop-Loss Phases:
Liquidation heatmaps help traders locate optimal profit-taking and stop-loss points—setting them just before dense liquidation zones enhances safety in locking profits. Increasing ETF outflows—e.g., BTC ETF daily outflows greatly exceeding averages—may signal deteriorating sentiment, prompting position reduction or stop-loss actions. High funding rates serve as warning signs; for example, Bitcoin futures funding rates above 0.1% indicate excessive bullishness, and prolonged highs may lead to corrections or even collapse.
Conversely, persistently low funding rates suggest overly pessimistic sentiment, possibly leading to overselling and unexpected reversals—creating potential trading opportunities. For instance, a sudden drop of over 10% in Bitcoin contract open interest reflects weakening confidence, calling for reduced exposure or profit-taking/stops. A rapid price plunge triggering massive liquidations may lead to a quick rebound—traders can re-enter once the market stabilizes. Rising spot outflows indicate mounting selling pressure, serving as signals for profit-taking or stop-losses. Heavy selling may drive further downside—profit-taking locks gains ahead of declines, while stops prevent larger losses.
Significant shifts in long/short ratio typically indicate extreme market sentiment swings and likely volatile price moves—traders should stay alert, adjust positions accordingly, and set proper take-profit and stop-loss levels. A Fear & Greed Index consistently above 80 reflects extreme greed and inflated prices—suggesting gradual position reduction or profit-taking due to looming correction risks.
These data dimensions help traders enter at opportune times and adjust strategies timely for improved returns and risk control. However, it must be emphasized that optimal timing requires integrating multiple indicators—this holistic approach enables more accurate predictions, reduces misleading signals from single metrics, and improves decision accuracy and efficiency.
OKX Strategy Team: On this topic, we recommend traders integrate holdings bias, basis, technical indicators, and risk/reward tools to accurately determine optimal entry and exit points and objectively manage profit-taking and stop-loss timing.
• Holdings Bias (Long Short Ratio):
Holdings bias reflects the balance between long and short market participants. A high long ratio typically indicates optimistic sentiment and a tendency to buy; a high short ratio reflects pessimism and a tendency to sell. Analyzing holdings bias helps users gauge prevailing market trends and sentiment, guiding optimal entry timing.
• Basis:
Basis refers to the difference between futures contract price and spot price. It can be positive (futures > spot) or negative (futures < spot). Basis reflects market expectations about future price movements. A positive basis usually indicates expectations of rising prices (contango); a negative basis suggests expectations of falling prices (backwardation). Basis can be used to monitor sentiment and design arbitrage strategies. For example, rapidly rising basis may indicate bullish sentiment, while sharp declines suggest bearish bias.
• Technical Indicators – Overbought/Oversold:
Using technical indicators such as RSI and Stochastic Oscillator, users can determine whether the market is overbought or oversold. When RSI exceeds 70, the market may be overbought and due for a pullback; when below 30, it may be oversold and ripe for a rebound. These tools help users time entries during periods of extreme sentiment.
• Risk/Reward Tools:
This tool helps users visualize and manage the potential gain and risk of each trade. By setting take-profit and stop-loss levels, users can calculate the risk-reward ratio per trade and formulate rational exit strategies. Using this tool enhances risk control and ensures optimal returns amid market volatility.
4. Overall, are there any undervalued data indicators?
CoinGlass: Different traders have varying trading styles, risk tolerances, and objectives, so their choice of analytical metrics differs. Market conditions and cycles also influence the relevance of certain indicators—some may be highly meaningful at certain times but less so at others.
While every indicator has its unique function, relying solely on one often fails to fully capture market reality.
Therefore, we recommend traders consider multiple data dimensions comprehensively, conducting integrated analysis for more accurate assessment of market trends and opportunities. Combining fundamental, technical, and sentiment indicators helps traders gain a fuller picture, reduce biases from single metrics, and improve decision accuracy and efficiency.
OKX Strategy Team: The following data dimensions may be underappreciated in the crypto market, yet carry relatively high value for market analysis and trading decisions:
• ETF Fund Flows:
ETF fund inflows and outflows reflect institutional traders’ market sentiment. Large inflows typically signal institutional optimism, while outflows may indicate weakening confidence. Analyzing ETF flows helps users assess medium- to long-term trends.
• Options Market Data:
Options data includes implied volatility, call/put open interest, etc. These reflect market expectations for future price volatility. Options data offers forward-looking sentiment signals. For example, rising implied volatility may precede sharp price moves; growing call options may indicate bullish expectations.
• Stablecoin Flows:
The movement of stablecoins (e.g., USDT, USDC) reflects capital flows and traders’ risk appetite. When large amounts flow into exchanges, traders may be preparing to buy crypto; outflows may signal cashing out. Tracking stablecoin flows provides clues about capital movements.
• Network Effect Metrics:
Metrics such as active user count, developer activity, and social media engagement reflect a blockchain project’s network effects and ecosystem health. Strong network effects imply greater stickiness and growth potential, valuable for medium- to long-term decisions.
• DeFi Activity Metrics:
Including Total Value Locked (TVL), number of users on DeFi protocols, lending and liquidity provision activity. These reflect the health and growth potential of decentralized finance. High TVL and active participation signal strong demand and expansion potential in DeFi.
5. How to cultivate a more scientific trading mindset?
CoinGlass: Cultivating a scientific trading mindset requires systematic learning and practice. First, maintaining objectivity and rationality is crucial. Develop a detailed trading plan and adhere to it strictly to avoid being swayed by market emotions—though easier said than done. Second, mastering data analysis and risk management is essential. Learn technical and fundamental analysis tools, and practice setting stop-loss and take-profit levels to better navigate volatility and ensure sustainable trading growth.
Of course, accumulating trading experience is key to success. Record the rationale, process, and outcome of every trade, then summarize and reflect—this helps continuously refine your strategy. Given the ever-changing market, staying open-minded is necessary. Keep up with industry news and expert views to continually update your knowledge and stay in tune with market rhythms.
Additionally, establishing clear trading rules and strictly following them helps avoid poor decisions driven by greed or fear. Simulated trading allows thorough preparation and strategy validation before live trading, reducing risks and losses in real markets.
Finally, regularly reviewing and adjusting your trading strategy is key to continuous improvement. Optimize your approach based on market conditions and personal experience to ensure it remains effective and adaptive. Through persistent effort, you can gradually build a more scientific trading mindset, enhancing both success rate and efficiency.
OKX Strategy Team: Based on our experience, becoming a mature trader requires strengthening three key capabilities:
First, master foundational data and indicators. Understanding macro trends is key—this includes grasping basic economic indicators (e.g., GDP, inflation, interest rates) and their market impacts, tracking geopolitical events and major developments affecting crypto, and understanding crypto market cycles and long-term trends. Price and technical analysis are equally essential—deepen your use of common indicators (e.g., MA, RSI, MACD, Bollinger Bands), master identification of trendlines, support/resistance levels, and learn to recognize and analyze market structure (e.g., highs, lows, trend channels). Additionally, strengthen fundamental analysis—study project whitepapers, team backgrounds, roadmaps, deeply understand tokenomics (supply mechanisms, inflation/deflation models, use cases), and stay updated on industry innovations and regulatory changes.
Second, develop analytical and decision-making skills. Critical thinking is central—learn to question and verify information sources, especially market “hype” on social media; cultivate multi-angle thinking by considering opposing viewpoints; learn to identify emotional extremes and overreactions; and foster independent judgment rather than blindly following so-called “experts.” Build systematic trading strategies—create clear plans aligned with personal risk tolerance and goals; define precise entry/exit rules including stop-loss and take-profit levels; learn to use various order types (limit, market, conditional orders) effectively. Establish strict trading discipline—develop pre-trade checklist habits to avoid impulsive trades; rigorously follow predetermined plans and risk rules; learn emotional control, especially during large wins or losses; maintain a trading journal documenting rationale, outcomes, and emotional states for each trade.
Third, practice and continuous improvement. Conduct systematic post-trade reviews and optimization—regularly revisit trade records to analyze successes and failures; use quantitative metrics (e.g., Sharpe ratio, max drawdown) to assess strategy performance; continuously refine strategies based on market changes and review findings; treat every loss as a learning opportunity. Maintain a learning mindset and market sensitivity—follow insights from top industry analysts while building independent verification skills; keep pace with emerging fintech developments like DeFi, NFTs, cross-chain tech; and learn cross-market analysis to understand linkages between traditional finance and crypto markets.
Conclusion
The above is the second edition of OKX’s “Insights on Data” column, focusing on different data dimensions relevant to various user scenarios, aiming to provide systematic data methodologies for traders of all experience levels—helping them better sense market rhythms and make smarter trading decisions. In future installments, we will continue exploring practical data usage and analytical methods, offering valuable references for traders’ learning journeys.
Risk Warning and Disclaimer
This article is for informational purposes only. The content represents the authors’ opinions and does not reflect the views of OKX. This article is not intended to provide (i) investment advice or recommendations; (ii) offers or solicitations to buy, sell, or hold digital assets; or (iii) financial, accounting, legal, or tax advice. Holding digital assets (including stablecoins and NFTs) involves high risk and prices may fluctuate significantly. You should carefully consider whether trading or holding digital assets is suitable for you based on your financial situation. Please consult your legal/tax/investment professionals regarding your specific circumstances. You are solely responsible for understanding and complying with applicable local laws and regulations.
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