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# Market Order Count **Overview:**\ \ A market order is an order to buy or sell at the market's current best available price. Primary goal of submitting a market order is to ensure immediate execution of a trade. However, it does not guarantee a specified price.\ \ These participants are known as market takers or aggressive orders.\ \ Market and limit orders are constantly being placed at all times during market hours. Studying executed orders can help users understand activity at different price levels whereas resting orders can help identify future potential interest.\ \ In this section we will be focusing on executed orders (orderflow). For more information on resting orders you can look at our [Orderbook](/indicators/orderbook) section.\ \ **Indicator Description:**\ \ The market order count is a technical analysis tool that shows the number of trades that occurred during a specific time period (candlestick).\ \ You can access the indicator on the Main Chart product under the Orderflow & Open Interest.
# Participation Ratio ## Introduction In the fast-paced world of cryptocurrency trading, the "Participation Ratio" indicator emerges as a key tool for traders. It offers a unique perspective on market dynamics by analyzing the relationship between volume and open interest. This indicator helps traders gauge the level of new participation in the market, which can be pivotal in understanding market sentiment and potential price movements. ## What is the "Participation Ratio" Indicator? ### **Overview** The "Participation Ratio" measures the percentage of trading volume represented by the change in Open Interest (OI). It is calculated as the Open Interest Delta divided by the Volume. ### **Concept** The essence of this indicator lies in differentiating between the volume that results from new market participants entering (or exiting) and the volume from ongoing trading activities. * Very high (positive) participation ratio indicates a significant portion of the trading volume involves new participants * Very low (negative) participation ratio indicates a significant portion of the trading volume involves participant exiting * Flat (close to 0) value suggests existing market players dominate the volume ### **Example** Consider a situation where the open interest increases by 2 million contracts and the total trading volume is 20 million contracts. The participation ratio here would be 10%, indicating that 10% of the trading volume involves new participants entering the market. ## Why is it Important? ### **Insight into Market Participation** Understanding the participation ratio is crucial for traders as it provides insights into whether new players are entering (or exiting) the market, or if the trading is predominantly by existing participants. ### **Market Sentiment Indicator** The participation ratio can serve as a barometer for market sentiment. A rising ratio might indicate growing interest, whereas a falling ratio could suggest waning interest. ## How Can it be Used in Markets? **Identifying Market Trends** A consistently high participation ratio during a market rally can signal strong buying interest from new participants, possibly reinforcing the uptrend. Conversely, during market declines, a low participation ratio might indicate that the sell-off is mainly driven by existing participants, hinting at a potential bottom formation. **Trading Volume Analysis** By analyzing participation ratio alongside trading volume, traders can distinguish between volume spikes caused by new entrants versus those by existing participants. This distinction is crucial in evaluating the strength of price movements. ## Specific Use Cases ### Transfer of Contracts During High Volume Periods **Scenario: Transfer of Contracts** In scenarios where the trading volume is high over a short time frame, yet the Participation Ratio remains flat, a significant transfer of contracts can occur. This happens when one set of market participants is entering positions while an approximately equal number of participants are exiting, leading to a balanced transfer of contracts. **How It Works** * **Balanced Entry and Exit:** In this scenario, for every trader or group of traders entering the market (buying contracts), there is an approximately equal number of traders exiting the market (selling contracts). This balance results in high trading volume but little net change in open interest. * **Example:** Imagine within a 5-minute window, a group of traders purchases 500,000 contracts of a cryptocurrency, while another group simultaneously sells an equal amount. The trading volume spikes due to these transactions, but the open interest remains largely unchanged since the total number of open contracts doesn't increase or decrease significantly. **Implications** * **Market Sentiment Analysis:** This kind of transfer can be a key indicator of market sentiment. For instance, if the price remains stable or increases during this period, it might suggest that the selling pressure is being absorbed by new buyers, which could be a bullish sign. Conversely, if the price declines, it may indicate that buyers are not sufficiently absorbing the selling pressure, potentially a bearish signal. * **Liquidity and Price Stability:** Such balanced transfers often contribute to liquidity and can lead to price stability. They are essential in markets, especially in high-volatility periods, as they allow traders to enter and exit positions without causing significant price disruptions. * **Strategic Positioning:** Understanding this dynamic can be crucial for traders looking to enter or exit the market. Recognizing a transfer of contracts can help in timing the trades better, especially in anticipating potential resistance or support levels. ### **Bullish and Bearish Engagements** A surge in the participation ratio amidst a price rally could imply strong bullish engagement, as more new buyers enter the market. In contrast, an increase during a downturn might signal bearish sentiment, with new participants entering short positions. ### **Sentiment Shift Detection** Sudden changes in the participation ratio can indicate sentiment shifts. For instance, a sharp increase after a prolonged downtrend might signal a reversal as new buyers start to enter, suggesting a potential market turnaround.
# Previous Day, Week, and Month Technical Levels ## Introduction In trading, particularly in the volatile cryptocurrency market, understanding historical levels is crucial. Previous day, week, and month levels — including open, high, low, and equilibrium (average of high and low) — are key technical indicators that traders often use as potential support and resistance levels. These levels can provide high reward-to-risk opportunities and help traders make informed decisions. ## What are Previous Day, Week, and Month Levels? ### **Overview** These levels refer to the open, high, low, and equilibrium (EQ) points from the previous trading day, week, and month. The equilibrium is calculated as the average of the high and low prices. ### **Concept** The rationale behind using these levels lies in their ability to highlight significant price points that have previously acted as either support or resistance. They are often closely watched by a large number of traders, thereby increasing their relevance. #### **Calculation** * **Daily Levels:** Calculated from the previous day's trading data. * **Weekly Levels:** Derived from the last week's trading range. * **Monthly Levels:** Based on the previous month's price action. ## Why are They Important? ### **Psychological Significance** These levels often hold psychological importance for traders and can influence market behavior. For instance, a previous month's high can act as a psychological barrier or target. ### **Decision-Making Tool** They serve as a guide for placing entry and exit points, setting stop-loss orders, and identifying potential reversal points in the market. ## How Can They be Used? ### **Support and Resistance** These levels can act as support in a rising market or resistance in a falling market. Traders might look for buying opportunities near the previous day's low or selling opportunities near the previous day's high. ### **Breakout and Reversal Trading** A breakout above a previous high or a drop below a previous low can signal a strong market move. Conversely, a failure to break these levels might indicate a potential reversal. ## Specific Use Cases ### **Trend Confirmation** * **Bullish Scenario:** If the price consistently closes above the previous day's or week's high, it might indicate a strong bullish trend. * **Bearish Scenario:** Conversely, closing below the previous day's or week's low could signal a bearish trend. ### **High Reward-to-Risk Trade Setups** * Traders might find high reward-to-risk opportunities near these levels. For example, entering a long position near the previous week's low with a tight stop-loss can offer a favorable risk-reward ratio if the level holds as support. ### **Intraday Pivot Points** * For intraday traders, previous day levels can act as pivot points. Trading strategies might involve buying near the previous day's EQ level or selling near it, depending on the market's overall trend. ### **Swing Trading** * Swing traders might use previous week or month levels to set longer-term trade targets. For instance, buying near a previous month's low with an aim to sell near the high, or vice versa. # Anchored CVD ## Definition Anchored CVD is a specialized variation of the Cumulative Volume Delta (CVD) indicator that resets its calculation at predefined anchor points, such as the start of a day, 4-hour period, or 1-hour period. Like traditional CVD, it tracks the difference between buy volume and sell volume to reveal buying or selling pressure in the market. By anchoring to a specific point (ie. daily open), it highlights intraday shifts in market sentiment more clearly. This helps traders compares buying or selling momentum on a day-to-day basis. **Key Features:** * **Reset Points:** The cumulative calculation starts fresh at each anchor point (e.g., daily, 4-hour, or 1-hour intervals). * **Comparative Analysis:** Enables clearer comparisons of buying and selling behavior across different timeframes. * **Trend Identification:** Highlights shifts in market sentiment more precisely by isolating periods of activity. This variation helps traders analyze intraday momentum, spot trend reversals, and compare market pressure across multiple time intervals. # Anchored Open Interest (OI) ## Definition Anchored Open Interest (OI) is a specialized variation of the traditional Open Interest indicator that resets its calculation at predefined anchor points, such as the start of a day, 4-hour period, or 1-hour period. Open Interest measures the total number of outstanding derivative contracts (e.g., futures or options) that have not been settled. **Key Features:** * **Reset Points:** The cumulative calculation starts fresh at each anchor point (e.g., daily, 4-hour, or 1-hour intervals). * **Comparative Analysis:** Facilitates clearer comparisons of position buildup and reduction across different timeframes. * **Market Sentiment Insights:** Highlights periods of significant position changes, providing deeper insight into directional biases and potential reversals. This variation helps traders analyze intraday changes in market positioning, track how open interest evolves during key periods, and identify patterns of accumulation or distribution. # Buy Sell Trade Count Ratio ## Definition Measures the relative proportion of executed buy trade count (both market and limit) versus sell trade count (both market and limit) within a given period. A higher ratio indicates stronger buy-side activity, while a lower ratio points to increased sell-side pressure. \ \ By tracking changes in this ratio over time, traders can gain insights into emerging or fading market momentum on either side of the order flow. # Slippage ## Definition Slippage refers to the difference between the expected execution price of a market order and the actual price at which the order is filled. In the context of price slippage, it specifically measures the price impact caused by executing a market order that consumes multiple levels of available liquidity from the order book. **Example:**\ If you market buy BTC and your order is filled across multiple limit sell orders ranging from $90,000 to $90,002, the slippage is **$2** — representing the difference between the initial price level and the highest execution price within your order.\ \ These individual slippage values are then combined to provide three key metrics: 1. **Maximum Slippage:** The largest price deviation recorded in a single trade. 2. **Total Slippage:** The sum of all price deviations across trades. 3. **Average Slippage:** The average price deviation per trade. These metrics are broken down into four categories: * **Buy:** Slippage from buy trades. * **Sell:** Slippage from sell trades. * **Total:** Combined slippage from all trades (buy + sell). * **Delta:** The difference between buy and sell slippage (buy - sell). **Key Factors Influencing Slippage:** * **Order Size:** Larger orders are more likely to consume liquidity at multiple price levels. * **Market Liquidity:** Thin order books with low liquidity often result in higher slippage. * **Market Volatility:** Rapid price movements can amplify slippage. Slippage is a critical metric for assessing trade execution quality and understanding the cost associated with market orders, particularly in volatile or low-liquidity environments. # Volume Ratio ## Definition The **Volume Ratio** measures the **relative dominance of buy volume versus sell volume** from executed market orders within a specific timeframe. It provides insight into **order flow imbalance** by comparing the net difference between buy and sell volumes against their combined total. $$ \textbf{Volume Ratio} = \frac{\textbf{Buy Volume} - \textbf{Sell Volume}}{\textbf{Buy Volume} + \textbf{Sell Volume}} $$ #### **Key Components:** * **Buy Volume:** The total volume of market **buy orders** executed during the timeframe. * **Sell Volume:** The total volume of market **sell orders** executed during the timeframe. * **Ratio Range:** The ratio is typically **bounded between -1 and +1**, where: * **+1:** 100% buy volume dominance (only buy orders). * **-1:** 100% sell volume dominance (only sell orders). * **0:** Equal buy and sell volumes, indicating balance. # Market Order Count Ratio ## Definition The **Market Order Count Ratio** measures the **relative dominance of buy market orders versus sell market orders** by comparing the difference in their counts against their combined total. It highlights the **imbalance in the frequency of market buy and sell orders.** $$ \textbf{Market Order Count Ratio} = \frac{\textbf{Market Order Buy Count} - \textbf{Market Order Sell Count}}{\textbf{Market Order Buy Count} + \textbf{Market Order Sell Count}} $$ #### **Key Components:** * **Market Order Buy Count:** The total number of **market buy orders** executed during a specific timeframe. * **Market Order Sell Count:** The total number of **market sell orders** executed during a specific timeframe. * **Ratio Range:** The ratio is typically **bounded between -1 and +1**, where: * **+1:** 100% buy order dominance (only buy orders). * **-1:** 100% sell order dominance (only sell orders). * **0:** Equal buy and sell order counts, indicating balance. # Limit Order Count Ratio ## Definition The **Limit Order Count Ratio** measures the **relative dominance of executed limit buy orders versus executed limit sell orders** by comparing the difference in their counts against their combined total. It highlights the **imbalance in the frequency of executed limit buy and sell orders**, providing insight into liquidity absorption and market behavior. $$ \textbf{Limit Order Count Ratio} = \frac{\textbf{Limit Order Buy Count} - \textbf{Limit Order Sell Count}}{\textbf{Limit Order Buy Count} + \textbf{Limit Order Sell Count}} $$ #### **Key Components:** * **Limit Order Buy Count:** The total number of **executed limit buy orders** during a specific timeframe (orders resting on the book, filled by market sell orders). * **Limit Order Sell Count:** The total number of **executed limit sell orders** during a specific timeframe (orders resting on the book, filled by market buy orders). * **Ratio Range:** The ratio is typically **bounded between -1 and +1**, where: * **+1:** 100% buy-side dominance (only limit buy orders were executed). * **-1:** 100% sell-side dominance (only limit sell orders were executed). * **0:** Equal buy and sell limit order counts, indicating balance. # Liquidity Indicators # Top Trader Average Leverage Used ### What is leverage? Leverage is an important function in the crypto market and some even say it's at the heart of derivatives trading. Most crypto exchanges offer leverage to their users. Leverage allows traders to borrow funds in order to enter a position larger than their own funds permit. Traders who trade with leverage are doing so with the goal of capturing larger gains but also at the risk of being "liquidated", or losing all or nearly all of their Initial Margin. Initial Margin is basically the amount of money coming from the traders pocket. If this trader wants to enter a $5000 trade with 10x leverage, then $500 is the Initial Margin and the remaining $4500 are borrowed funds. Exchanges cannot allow a trader to lose borrowed funds and therefore close out the position as soon as position losses reach the initial margin. When entering a trade with leverage, most exchanges provide the price at which the trade would be liquidated otherwise known as the liquidation level. ### Why is leverage a useful data point? If we know the amount of aggregate leverage being taken out by users, then we can also understand how risk-on or risk-off the current market is. For example, if we know that on average, longs are using 12x leverage while shorts are using 2x leverage, this is useful information. It can increase the likelihood of a long squeeze (as price drops, it may trigger a cascade of liquidations, quite common in crypto). Similarly, a market (or trend) may be considered “healthy” if the amount of leverage taken out is low. ### What is this indicator actually showing? This indicator shows the average leverage taken out by “top traders” (larger accounts), separated by long leverage and short leverage. So if long leverage is 5.6, it implies that longs are taking out 5.6x leverage on average.  Hyblock users can track not only the current amount of leverage used but also in which direction leverage is trending. {% hint style="info" %} Note: Top Traders does not mean the best or sharpest traders, it is just a particular segment of the entire population. Each exchange has their own definition of “top traders”, but in all cases it is just a portion of all accounts either by size of account, volume etc. {% endhint %} ### Top Trader Average Leverage Delta Users can also look at the "gap" between average long leverage and average short leverage, known as the *delta.* In other words, Top Trader Average Leverage Delta is the difference between leverage used by long and leverage used by shorts. This can be used to track when leverage on one side is significantly offside, identify any spikes in leverage, and monitor which direction leverage is building (trending) toward. # LiqLevels Liquidation Levels are estimates of potential price levels where long or short liquidation events may occur. These predictions are based on factors such as leverage, position size, entry price, and margin requirements, offering insights into areas of potential liquidity concentration before they are triggered. #### **Key Components:** 1. **Leverage Tiers:**\ Predicted liquidation levels are categorized by the leverage used in positions: * **High Leverage:** Positions with high leverage, most sensitive to small price movements. * **Medium Leverage:** Positions with moderate leverage, balancing risk and exposure. * **Low Leverage:** Positions with lower leverage, requiring significant price moves to trigger liquidation. 2. **Size Tiers:** Predicted liquidation levels are divided into three tiers based on position size: **Tier 1** (small retail positions), **Tier 2** (medium-sized positions), and **Tier 3** (large positions). **LiqLevel Indicators:** * **LiqLevels - Long \[High Leverage]** * **LiqLevels - Long \[Medium Leverage]** * **LiqLevels - Long \[Low Leverage]** * **LiqLevels - Short \[High Leverage]** * **LiqLevels - Short \[Medium Leverage]** * **LiqLevels - Short \[Low Leverage]** # LiqLevelsCount **LiqLevelsCount** represents the total number of predicted liquidation levels that are either **opening** or **closing** within a specific timeframe. It provides a numerical overview of liquidation activity, highlighting how many potential liquidation points are being created (opened) or hit/liquidated (closed) as market conditions change. **LiqLevelCount Indicators:** * **LiqLevelsCount - Longs** * **LiqLevelsCount - Longs Cumulative** * **LiqLevelsCount - Shorts** * **LiqLevelsCount - Shorts Cumulative** * **LiqLevelsCount - Delta** * **LiqLevelsCount - Delta Cumulative** * **LiqLevelsCount - Total** # LiqLevelsSize **LiqLevelsSize** represents the total size of predicted liquidation levels that are either **opening** or **closing** within a specific timeframe. It provides a numerical overview of the volume tied to liquidation activity, highlighting the total value of positions associated with potential liquidation points being created (opened) or liquidated (closed) as market conditions change. **LiqLevelSize Indicators:** * **LiqLevelSize - Longs** * **LiqLevelSize - Longs Cumulative** * **LiqLevelSize - Shorts** * **LiqLevelSize - Shorts Cumulative** * **LiqLevelSize - Delta** * **LiqLevelSize - Delta Cumulative** * **LiqLevelSize - Total** # Anchored LiqLevelsCount #### **1. Anchored LiqLevelsCount** This indicator displays the **cumulative sum** of **predicted long liquidation levels** and **predicted short liquidation levels** within anchored timeframes (e.g., daily, 4-hour, or 1-hour). * **Visualization:** Represented as **two separate lines** on the same chart: * **Long Liq Levels Line:** Tracks the cumulative count of predicted long liquidation levels. * **Short Liq Levels Line:** Tracks the cumulative count of predicted short liquidation levels. **Purpose:** * Compare the buildup of long vs. short liquidation levels over time. * Identify imbalances between long and short liquidation activity. * Highlight directional market stress points. #### **2. Anchored LiqLevelsCount - Delta Cumulative** This indicator calculates the **difference** between the cumulative predicted **long liquidation levels** and **short liquidation levels** during the same anchored interval: Delta= (Long Liq Levels Count) − (Short Liq Levels Count) * **Visualization:** Represented as a **bar graph**, where: * **Positive Delta:** Long liquidation levels exceed short liquidation levels. * **Negative Delta:** Short liquidation levels exceed long liquidation levels. **Purpose:** * Highlight the net directional bias of liquidation levels. * Identify periods where one side (long or short) dominates liquidation activity. * Provide signals for potential reversals or continuation trends based on liquidation imbalances. *** #### **Why They Matter:** * **Market Sentiment Analysis:** Understand whether long or short liquidation levels dominate during specific intervals. * **Liquidity Insights:** Identify key periods where large-scale liquidation events may trigger significant market moves. * **Comparative Analysis:** Analyze liquidation trends across multiple anchored periods for clearer insights into market behavior. Together, **Anchored LiqLevelsCount** and **Anchored LiqLevelsCount Delta Cumulative** provide a comprehensive view of liquidation activity, helping traders make informed decisions based on directional imbalances and cumulative liquidation trends. # Anchored LiqLevelsSize #### **1. Anchored LiqLevelsSize** This indicator displays the **cumulative sum** of the **predicted long liquidation size** and **predicted short liquidation size** within anchored timeframes (e.g., daily, 4-hour, or 1-hour). * **Visualization:** Represented as **two separate lines** on the same chart: * **Long Liq Levels Size Line:** Tracks the cumulative size of predicted long liquidation levels. * **Short Liq Levels Size Line:** Tracks the cumulative size of predicted short liquidation levels. **Purpose:** * Compare the scale of long vs. short liquidation levels over time. * Identify imbalances in liquidation size between long and short positions. * Highlight areas where significant capital is at risk of liquidation. *** #### **2. Anchored LiqLevelsSize - Delta Cumulative** This indicator calculates the **difference** between the cumulative predicted **long liquidation size** and **short liquidation size** during the same anchored interval: Delta= (Long Liq Levels Size) − (Short Liq Levels Size) * **Visualization:** Represented as a **bar graph**, where: * **Positive Delta:** Long liquidation size exceeds short liquidation size. * **Negative Delta:** Short liquidation size exceeds long liquidation size. **Purpose:** * Highlight the net bias of liquidation levels. * Identify periods where one side (long or short) carries a larger liquidation risk. * Provide signals for potential market stress points or volatility based on size imbalances. *** #### **Why They Matter:** * **Market Risk Analysis:** Understand whether long or short positions carry a larger risk of liquidation. * **Liquidity Insights:** Identify high-risk zones where significant liquidation events could impact market stability. * **Comparative Analysis:** Analyze trends across multiple anchored periods to better understand market positioning. Together, **Anchored LiqLevelsSize** and **Anchored LiqLevelsSize Delta Cumulative** provide a comprehensive view of the **magnitude** behind predicted liquidation levels, helping traders assess capital exposure and prepare for potential market moves driven by liquidation events. # Liquidations The **Liquidation** measures the **actual amount of long and short liquidations** that occurred within a specific timeframe (e.g., candle period). It captures the total value of positions forcefully closed due to insufficient margin, providing insights into real-time liquidation activity rather than predicted price levels. #### **Key Components:** * **Long Liquidations:** The total value of long positions forcefully closed during the timeframe. * **Short Liquidations:** The total value of short positions forcefully closed during the timeframe. * **Delta Liquidations:** The difference between long positions and short positions forcefully closed during the timeframe. * **Total Liquidations:** The combined value of long and short liquidations within the period. **Trade Size Buckets** Liquidations can be displayed for various size buckets. Users can choose from ranges like 0 to 100, 1k to 100k, and so on, up to 'Infinity'. This feature allows traders to analyze market behavior in different segments: * **0 to 100 (Smallest)** * **100 to 1k (Smaller)** * **1k to 10k (Small)** * **10k to 100k (Medium)** * **100k to 1m (Large)** * **1m to 10m (Larger)** * **10m to Infinity (Largest)** # Longs & Shorts Indicators # Binance Longs & Shorts Indicators based on tracking longs and shorts on Binance exchange. Binance provides 3 separate indicators that help identify long (and short) direction. 1\) **Global Longs & Shorts Accounts:** This measures the total number of \*accounts\* that are long (or short) on Binance. So for example, if there are 1million accounts on Binance and 600k of them are net long, then the global accounts long% is 60% (and short% = 40%). Each account gets one "vote" 2\) **Top Trader Longs & Shorts Accounts**: This measures the total number of \*top trader accounts\* that are long (or short) on Binance. Note, top traders do not necessarily mean the best traders or those with the highest profits, but rather Binance classifies top traders as accounts with the top20% in margin (or balance). This indicator is similar to Global Long Accounts with the only difference being that it focuses on the top 20% accounts. 3\) **Top Trader Longs & Shorts Positions:** This measures the total number of \*top trader positions\* that are long (or short) on Binance. The key difference here is that instead of looking at accounts, it instead looks at positions. For example, let's say there are 10 accounts that make up top traders and these positions are the following: | Trader | Side | Size | | ------ | ----- | -------- | | 1 | Long | 100k | | 2 | Long | 200k | | 3 | Long | 100k | | 4 | Short | 500k | | 5 | Long | 100k | | 6 | Short | 1million | | 7 | Long | 200k | | 8 | Short | 500k | | 9 | Long | 200k | | 10 | Long | 100k | So in total, we have 7 accounts that are long and 3 accounts that are short. This mean 70% of \*accounts\* are long. However, in terms of positions (or size), 1m positions are long and 2m positions are short, implying that 33% \*positions\* are long. We use top trader positions as a proxy to whale positions and global accounts as a proxy to retail. Traders and researchers can use these indicators to understand where the majority of positions lie and how larger positions diverge or converge with the majority of accounts (retail). Combining these indicators with open interest can often explain a lot on how the market participants are positioning themselves. # Bitmex Net Longs & Shorts Some exchanges provide long and short data in some capacity (like Binance). Bitmex, unfortunately, does not. So we went ahead and tried to approximate this data using a combination of Open Interest, Buy/Sell Volume and a couple other metrics. The general idea derives from the following combinations: | Price Change | Open Interest (OI) Change | Result | | --------------- | ------------------------- | --------------- | | Price goes up | OI goes up | longs entering | | Price goes down | OI goes up | shorts entering | | Price goes up | OI goes down | shorts closing | | Price goes down | OI goes down | longs closing | However, there are two flaws to the above approach. 1. The assumption is that price going up means that there is more buying than selling, hence more net buying with an increase in OI = longs entering. Similarly, price going down would mean more selling than buying. However, this is not always the case, as price can go up with more selling than buying (due to an imbalance in orderbook). Hence, one must look at buy volume and sell volume in combination with OI, rather than price. 2. When we say “longs entering”, this can be confusing. If OI goes up by 1million, this means 1 million longs entered and 1 million shorts entered. The number of longs and shorts in total are always the same. What “longs entering” really means is longs entering via market (aggressive) orders. Buy Volume and Sell Volume is based on market orders.Since buy volume and sell volume is used as a key ingredient in net longs & net shorts data, we are actually estimating what the aggressive orders are doing. Some assume that this market data is more representative of retail data as retail is more likely to pay a larger fee for their orders. #### Why do we use OI as another metric in estimating net longs and shorts? A key concept to understand is that buy volume increasing does not automatically mean longs entering (or short volume increasing does not mean shorts entering). If we know that a market buy led to an increase in open interest, then yes, that market buy is likely associated with longs opening. However, if that market buy is coupled with open interest decreasing, then likely that market buy is longs closing. Below is a table explaining all the combinations and *why* open interest is important to this estimation. | Market Order Type | Open Interest Change | Result | | ----------------- | -------------------- | --------------- | | Market Buy | OI Increase | Longs entering | | Market Sell | OI Increase | Shorts entering | | Market Buy | OI Decrease | Shorts exiting | | Market Sell | OI Decrease | Longs exiting | # Whale vs Retail Delta Our whale vs retail delta indicator (WRD) *for binance* is used throughout many of the hyblock products including the main charts, probability histogram, coin screener, etc. The concept of this indicator is to try to identify large gaps between retail long% and whale long%. So for example, if retail is constantly long and increasing their long% over time, while whales are heavier on the short side (and/or reducing their long exposure), the whale vs retail delta will display this. This indicator ranges from -100 to 100, with 0 representing whales and retail positioned exactly the same. Very high (or positive) values of WRD indicate that whales having higher long exposure than retail while low (or negative) values indicate retail has more long exposure than whales. It is also important to identify the directionality of WRD and which way the indicator is trending. For example, if WRD has a value of -30 and then starts increasing to -10, this can indicate that whales are increasing their long exposure (or reducing short exposure), while retail are doing the opposite (despite the value being negative). More often than not when whales are taking the opposite side of retail, it is the whale that are usually right (note: like everything in trading, nothing is 100%). Finding these divergences early can help spot a breakout trade or even periods of accumulation / distribution. # True Retail Longs & Shorts ## Definition The **True Retail Longs & Shorts** indicator tracks the percentage of **retail accounts** on Binance that are holding long versus short positions. Unlike volume-weighted metrics, this indicator assigns **equal weight to each retail account**, ensuring that every account contributes **one vote**, regardless of position size. #### **Key Components:** * **True Retail Longs (%):** The percentage of retail accounts currently holding long positions. * **True Retail Shorts (%):** The percentage of retail accounts currently holding short positions. * **Equal Weighting:** Each account contributes equally, preventing large positions from skewing the data. #### **Why It Matters:** * **Retail Sentiment:** Offers a clear view of market sentiment among retail traders. * **Directional Bias:** Highlights whether retail traders are leaning more bullish (long) or bearish (short). * **Market Psychology:** Provides insight into crowd behavior, which is often a key driver of short-term market moves. This indicator helps traders and analysts better understand **retail positioning trends**, offering valuable signals about potential market sentiment shifts or herd mentality behavior in trading activity. # Anchored Binance Longs & Shorts Ratios ## Definition These **anchored indicators** are a specialized variation of the traditional binance long short indicators that resets its calculation at predefined anchor points, such as the start of a day, 4-hour period, or 1-hour period. **Key Features:** * **Reset Points:** The cumulative calculation starts fresh at each anchor point (e.g., daily, 4-hour, or 1-hour intervals). * **Comparative Analysis:** Facilitates clearer comparisons of position buildup and reduction across different timeframes. * **Market Sentiment Insights:** Highlights periods of significant position changes, providing deeper insight into directional biases and potential reversals. These **indicators** provide insights into trader behavior and positioning across different account types on Binance:\ \ **Anchored Long Short Indicators:** **1. Anchored Global Longs and Shorts Accounts (Binance)**\ **2. Anchored Top Trader Longs and Shorts Accounts (Binance)**\ **3. Anchored Top Trader Longs and Shorts Positions (Binance)**\ **4. Anchored Whale vs Retail (Binance)** *** #### # Cumulative Net Longs & Shorts (CLS & CLSD) ## Definition #### **Cumulative Net Longs & Shorts** The **Cumulative Net Longs & Shorts (CLS)** indicator tracks the **net difference between long and short positions** over time, providing insight into the overall directional bias of market participants. It aggregates the total net positioning from longs and shorts across a given timeframe (e.g., daily, 4-hour, or 1-hour), offering a dynamic view of market sentiment and positioning trends. *** #### **Key Components:** 1. **Cumulative Net Longs:** The aggregated total of long positions after subtracting closed long positions over time. 2. **Cumulative Net Shorts:** The aggregated total of short positions after subtracting closed short positions over time. 3. **Cumulative Net Longs & Shorts Delta (CLSD):** The difference between **Cumulative Net Longs** and **Cumulative Net Shorts**, calculated as: Delta = (Cumulative Net Longs) − (Cumulative Net Shorts) * **Positive Delta:** Indicates that long positions dominate net positioning. * **Negative Delta:** Indicates that short positions dominate net positioning. *** #### **Visualization:** * **Cumulative Net Longs & Shorts:** Typically displayed as two separate lines on a chart: * **Net Longs Line:** Represents the cumulative total of long positions. * **Net Shorts Line:** Represents the cumulative total of short positions. * **Cumulative Net Longs & Shorts Delta:** Displayed as a **bar graph** to visualize the net difference between longs and shorts. *** #### **Why It Matters:** * **Directional Bias:** Highlights imbalances between long and short positioning trends. * **Trend Confirmation:** Persistent dominance of longs or shorts can indicate strong directional conviction. * **Reversal Signals:** Sudden shifts in delta values may signal potential trend reversals. The **Cumulative Net Longs & Shorts** indicator, along with the **Cumulative Net Longs & Shorts Delta**, provides a comprehensive view of market positioning dynamics, helping traders identify sentiment trends, potential reversals, and key liquidity zones. # Anchored CLS & CLSD ## Definition These two indicators provide insights into **net long and short positioning** over **anchored time intervals** (e.g., daily, 4-hour, or 1-hour), offering a standardized view of market sentiment and directional bias. *** #### **1. Anchored Cumulative Net Long Short (Anchored CLS)** **Anchored CLS** calculates the **cumulative net difference between long and short positions** within a predefined anchored timeframe, resetting at regular intervals (e.g., daily, 4-hour, or 1-hour). **Key Features:** * **Reset Points:** Calculation starts fresh at each anchor point (e.g., daily, 4-hour, or 1-hour). * **Longs:** Tracks the total net long positions within the anchored period. * **Shorts:** Tracks the total net short positions within the anchored period. **Visualization:** Represented as two separate lines: * **Anchored Net Longs Line:** Tracks the cumulative total of net long positions. * **Anchored Net Shorts Line:** Tracks the cumulative total of net short positions. **Why It Matters:** * Provides clarity on net positioning trends within anchored timeframes. * Highlights periods of sustained long or short dominance. * Identifies positioning shifts across standardized time intervals. *** #### **2. Anchored Cumulative Net Long Short Delta (Anchored CLSD)** **Anchored CLSD** calculates the **difference between Anchored Net Longs and Anchored Net Shorts** within the same predefined anchor points. Delta = (Anchored Net Longs) − (Anchored Net Shorts) **Key Features:** * **Positive Delta:** Long positions dominate during the anchored timeframe. * **Negative Delta:** Short positions dominate during the anchored timeframe. **Visualization:** Represented as a **bar graph**, where: * **Positive Bars:** Indicate net long dominance. * **Negative Bars:** Indicate net short dominance. **Why It Matters:** * Highlights directional bias within anchored periods. * Identifies imbalances in positioning that may signal market trends or reversals. * Provides clear comparisons of long vs. short sentiment across multiple anchored intervals. *** #### **Why These Indicators Matter Together:** * **Market Sentiment Analysis:** Clearly distinguish between long and short positioning trends. * **Directional Insights:** Understand whether long or short traders dominate during specific anchored intervals. * **Comparative Analysis:** Consistent anchor points allow for trend analysis across different timeframes. * **Risk Management:** Identify potential market stress points caused by extreme long or short dominance. Together, **Anchored CLS** and **Anchored CLSD** offer traders a structured, time-anchored view of market positioning, helping to identify trends, imbalances, and potential turning points in trader sentiment. # Trader Sentiment Gap The **Trader Sentiment Gap** measures the **difference in sentiment between top traders and retail traders**, offering insight into how these two groups are positioned relative to each other. It highlights the divergence or alignment in market outlook between **large-scale traders** and **smaller, retail-focused participants**. Extreme values can signal differing expectations or strategies between these two groups. # Whale Position Dominance ## Definition **Whale Position Dominance** measures the **relative influence of the largest traders within the top trader group** by analyzing their l**ong% positioning**. It highlights whether market positioning is driven more by the **largest whales** or distributed across **medium-sized traders**. #### **Key Insights:** * **Higher Values:** Indicate that the largest whales are exerting greater dominance in **Long% positioning**. * **Lower Values:** Suggest that medium-sized traders, or in some cases even smaller participants, are playing a more significant role in **Long% positioning**. #### **Why It Matters:** * **Market Behavior Analysis:** Understand whether **Long% positioning** is concentrated among a few dominant players or distributed across a broader group of traders. * **Liquidity Insights:** Large whale dominance can signal concentrated capital flows and stronger directional conviction. * **Trend Strength:** Higher dominance values may reinforce directional trends, while lower values suggest distributed sentiment and potentially weaker directional bias. This indicator provides valuable insights into **capital concentration and Long% positioning within top traders**, offering a clearer view of market dynamics and the role of large-scale participants in driving price movements. # Sentiment # Twitter - Cashtag Count The world of cryptocurrency is fast-paced and ever-changing. With new developments and trends emerging daily, traders and investors need real-time information to stay ahead of the curve. Social media platforms, especially Twitter, have become critical sources of information and sentiment analysis in the crypto community. At Hyblock, we recognize the importance of incorporating social media data into our platform, and we're excited to announce the integration of Twitter data! As part of this integration, we're launching our first-ever Twitter-based metric: the **Twitter - Cashtag count** for $BTC. ## What is the Twitter - Cashtag count? The "Twitter - Cashtag count" is an innovative metric that collects and displays the number of tweets mentioning the cashtag "$BTC." To ensure accuracy and minimize noise, we exclude tweets with fewer than 20 characters, effectively filtering out spam and irrelevant content. This metric provides valuable insights into the sentiment and activity surrounding Bitcoin on Twitter.
$BTC tweets spike at the start of every hour
Local Bottom marked by spike in $BTC tweets (1min timeframe)
# Margin Lending Ratio \[Okx] Margin Trading allows investors to borrow cryptocurrencies and leverage their trading position to potentially increase returns. For example, traders may borrow tether (usdt) to increase exposure to BTC. ### Definition OKx provides ratio known as Margin Lending Ratio and define it as "This indicator shows the ratio of cumulative data value between BTC/USDT leverage quote currency (USDT) and underlying asset (BTC) over a given period of time." This may sound confusing so let's simplify. The BTC margin lending ratio shows how much USDT is borrowed versus how much BTC is borrowed (quoted in USDT) when trading BTC/USDT margin. If 1000 USDT is borrowed and 500 USDT (in BTC) is borrowed, then the ratio is 1000/500 = 2. ### Concept If the ratio is increasing (let's say from 15 to 25), then this means more USDT is being borrowed in comparison to BTC. Generally, USDT is usually borrowed to increase exposure to BTC and reflects a bullish sentiment. On the other hand, if the ratio is decreasing, then this means more BTC is being borrowed in comparison to USDT. Generally, BTC is borrowed too short and reflects a bearish sentiment. The lending ratio provides more edge when compared with how price has behaved over that same time period of borrowing: * USDT is being heavily borrowed (to potentially buy BTC) + price action is flat / decreasing -> leverage traders are in a loss and underwater. This will likely force deleveraging and can create bearish continuation in BTC/USDT price. * BTC is being heavily borrowed (presumingly to short BTC) + price action is flat / increasing -> traders are in a loss and underwater. This will likely force deleveraging and can create bullish continuation (ie. to close a short they have to buy back BTC, creating buy pressure). * Large increases in leverage can also be indication of future volatility. Similar to retail long/short ratios, what we often see is that when the market has a bullish sentiment, price action becomes bearish and vice versa. So an increasing margin lending ratio may imply that the market is more bullish (since they are borrowing more USDT than BTC, to presumingly buy more BTC), which could lead to bearish price action due to the above reasons. ### Where can I find this? The Margin Lending Ratio \[Okx] is found in our main charting application (Tools -> Charts). Within our main charting application, it is found in the Indicators Sentiment Section (as per the image). It is currently available for BTC and ETH across 6 timeframes (1min, 5min, 15min, 1hr, 4hr, 1day).
# BVOL & DVOL ## Introduction Volatility plays a pivotal role in shaping market dynamics. The "BVOL" (Binance Volatility Index) and "DVOL" (Deribit Implied Volatility Index) are essential tools for traders and investors, allowing them to gauge market expectations of future price movements and make informed decisions based on this crucial data. ## What is BVOL - Binance Volatility Index? ### **Overview** BVOL, or the Binance Volatility Index, is a derivative financial tool designed to measure the implied volatility of the cryptocurrency market. It offers real-time insights into market sentiment and expectations regarding future price fluctuations. ### **Calculation** BVOL is calculated using a formula that takes into account the weighted average of the implied volatility of specific crypto options contracts. These contracts are derived from the Binance Options market's crypto trades, including assets like BTC and ETH. ### **Significance** * **Market Sentiment:** BVOL provides a real-time measure of the market's expectation of future volatility. A high BVOL suggests significant price changes are anticipated, while a low BVOL indicates minor price fluctuations are expected. * **Risk Management:** Traders use BVOL to improve risk management strategies by adjusting their positions and trade sizes based on anticipated volatility. * **Informed Decisions:** BVOL helps traders make more informed decisions by providing a forward-looking view of potential price movements. ## What is DVOL - Deribit Implied Volatility Index? ### **Overview** DVOL, or the Deribit Implied Volatility Index, offers simple exposure to pure implied volatility in the cryptocurrency market. It is based on tradable futures on a volatility index and is a valuable instrument for traders seeking to understand market dynamics. ### **Calculation** DVOL uses the implied volatility smile of relevant expiries to output a single number, representing a gauge of the 30-day annualized implied volatility. It provides a forward-looking expectation of volatility in the market. ### **Significance** * **Forward-Looking Volatility:** DVOL is forward-looking and provides insights into the 30-day annualized expectation of volatility, making it a crucial tool for traders. * **Market "Fear and Greed" Gauge:** Unlike traditional markets, where volatility is often seen as a "fear gauge," in the crypto world, it can also indicate market "action" or "fear and greed." DVOL helps traders understand the dynamics of the crypto market. * **Trading Strategies:** DVOL facilitates various trading strategies, including hedging volatility exposure, mean reversion, and momentum strategies. ## How Can They be Used in Crypto Markets? ### **Risk Management** * Both BVOL and DVOL help traders manage risk by providing insights into expected price movements. Traders can adjust their positions and exposure accordingly. ### **Trading Strategies** * Traders can employ volatility-based trading strategies, such as options trading, to take advantage of expected price volatility. ### **Sentiment Analysis** * BVOL and DVOL serve as indicators of market sentiment. High volatility expectations might indicate uncertainty or upcoming price swings. ### **Volatility Trading** * Traders can use BVOL and DVOL to engage in volatility trading, which involves taking positions based on expected market volatility. ## Specific Use Cases **1. Options Trading** * Traders can use BVOL and DVOL to inform their options trading strategies, particularly when deciding on strike prices and expiration dates. **2. Risk Mitigation** * Investors can use these indicators to assess and mitigate risk in their cryptocurrency portfolios, especially during periods of heightened volatility. **3. Volatility-Linked Investments** * Traders seeking exposure to cryptocurrency market volatility can utilize BVOL and DVOL in creating tailored investment strategies. # Fear & Greed Index ## Introduction The Fear & Greed Index, developed by alternative.me, is a critical tool for understanding the emotional dynamics of the cryptocurrency market. This index provides a measure of the prevailing sentiment among investors, ranging from "Extreme Fear" to "Extreme Greed." Understanding this sentiment can offer valuable insights for trading decisions in the often volatile crypto market. ## What is the Fear & Greed Index? ### **Overview** The Fear & Greed Index is a gauge of market sentiment in the crypto space. It assigns a numerical value from 0 to 100 to represent the collective emotional state of the market, where 0 indicates "Extreme Fear" and 100 signifies "Extreme Greed." ### **Purpose** * **Emotional Check:** The index aims to save investors from their own emotional overreactions, such as FOMO (Fear of Missing Out) or panic selling in response to falling prices. * **Market Opportunities:** It operates under two primary assumptions: Extreme fear could indicate a potential buying opportunity, while extreme greed might signal an impending market correction. ## How is the Fear & Greed Index Calculated? #### **Data Sources** The index aggregates data from five key sources to represent sentiment accurately: 1. **Volatility (25%):** Measures Bitcoin's current volatility and maximum drawdowns, comparing them to 30-day and 90-day averages. 2. **Market Momentum/Volume (25%):** Combines current volume and market momentum against recent averages. 3. **Social Media (15%):** Analyzes interactions on Twitter related to Bitcoin, evaluating public interest and sentiment. 4. **Surveys (15%):** Gathers public opinion through polls, although currently paused. 5. **Dominance (10%):** Observes Bitcoin's market cap dominance as a sign of investor sentiment towards risk. 6. **Trends (10%):** Pulls data from Google Trends on Bitcoin-related queries, interpreting changes in search volumes. ## Why Measure Fear and Greed? ### **Market Behavior Insights** The index offers insights into the market's emotional state, helping to identify extremes that might signify market turning points. ### **Strategy Development** Traders use the index to refine their strategies, potentially taking contrarian positions when extreme sentiment levels are reached. ## How Can it be Used in Crypto Markets? ### **Identifying Market Extremes** * Traders can use the index to spot potential tops (extreme greed) or bottoms (extreme fear) in the market. ### **Contrarian Trading Strategies** * The index serves as a tool for contrarian strategies, where traders might buy during extreme fear or sell during extreme greed. ### **Complementary Analysis** * The index can complement technical and fundamental analyses, adding a sentiment layer to trading decisions. ## Specific Use Cases **1. Market Entry and Exit Points** * Traders might consider entering the market when the index shows extreme fear, suggesting a potential bottom, and exiting when extreme greed is indicated. **2. Risk Management** * The index can inform risk management decisions, particularly in adjusting position sizes based on market sentiment. **3. Portfolio Diversification** * Investors might use the index to time diversification moves, such as shifting to altcoins when Bitcoin dominance decreases (indicating greed towards riskier assets). # Funding Rate ## Definition The **Funding Rate** is a periodic fee exchanged between traders in perpetual futures contracts to ensure that the contract price stays close to the spot price of the underlying asset. It reflects the balance between long and short positions in the market and serves as an incentive mechanism to maintain price alignment. #### **Key Points:** * **When Positive:** Long traders pay short traders * **When Negative:** Short traders pay long traders * **Frequency:** Funding rates are typically exchanged at regular intervals (e.g., every 8 hours) and vary depending on market conditions. # USDT & USDC P2P Premium \[OKX] The **USDT & USDC P2P Premium** on OKX refers to the difference between the price of USDT (Tether) and USDC (USD Coin) traded in peer-to-peer (P2P) markets and their official market prices (typically pegged at $1). This premium reflects the willingness of buyers and sellers to transact these stablecoins at prices higher or lower than their market value. #### **Key Insights:** * **Positive Premium:** USDT or USDC is trading above $1 in the P2P market, indicating strong demand or limited supply. * **Negative Premium:** USDT or USDC is trading below $1 in the P2P market, indicating weaker demand or excess supply. # User-Bot Ratio \[BitMEX] ## Definition The **User-Bot Ratio** on BitMEX provides insight into the proportion of trading activity driven by human traders (users) versus algorithmic trading systems (bots) on the platform. It consists of three key metrics: 1. **User Count:** The total number of human traders actively connected. 2. **Bot Count:** The total number of algorithmic trading systems actively connected. 3. **User-Bot Ratio:** Calculated as **Bots / (Bots + Users)**, this ratio represents the share of bots relative to the combined total of bots and users. #### **Key Insights:** * **High User Count:** Suggests increased participation from retail or discretionary traders, often driven by sentiment or market events. * **High Bot Count:** Indicates significant activity from automated strategies, often focused on arbitrage, market-making, or high-frequency trading. * **User-Bot Ratio Trends:** A rising ratio signals increasing dominance of bots in market activity, while a falling ratio indicates higher participation from human traders. #### **Why It Matters:** The User-Bot Ratio helps traders and analysts: * Understand the balance between human-driven and algorithmic trading activity. * Identify periods of heightened bot dominance, which may impact liquidity and market behavior. * Adjust trading strategies based on the observed market participant composition. This metric serves as a valuable tool for assessing market dynamics, liquidity conditions, and potential volatility on BitMEX. # wBTC Mint & Burn wBTC Mint & Burn refers to the process of creating (“minting”) and destroying (“burning”) Wrapped Bitcoin (wBTC) tokens on the Ethereum network. Each wBTC token is backed 1:1 by real BTC held in custody, ensuring that every minted token corresponds to an equivalent amount of BTC locked up, and every burn reduces that supply accordingly.\ \ **Key Insights** 1. 1:1 Backing: Minting increases the wBTC supply and requires locking the same amount of BTC as collateral, while burning releases BTC from custody. 2. Bridging Ecosystems: wBTC allows Bitcoin holders to participate in Ethereum-based DeFi, combining BTC’s liquidity with smart contract functionality. 3. Supply & Demand Signals: A rise in minting can indicate growing demand for DeFi participation, whereas increased burning may reflect a shift back to native BTC holdings. # Orderbook # Bids & Asks Bids and Asks are fundamental to how an orderbook is constructed. ## **What is it?** ### Definition A bid (or limit buy) is a “passive” buyer who advertises the price and size they would like to buy at. An asks (or limit sell) is a “passive” seller who advertises the price and size they would like to sell at. ### Concept Trading markets at their core consist of buyers and sellers. There are two types of buyers (or sellers): passive and aggressive. * Aggressive --> are those that buy/sell at the current price. * Passive --> are those that are patiently waiting for price to arrive at a price level that they are interested in. Without these passive participants, trading markets as they are defined today could not exist. Price would fail to increase or decrease because there would be no one on the other side (passive buyer/seller) willing to take that order -- price would forever remain at the same level. Price only increases and decreases when there are no longer passive buyers (or sellers) at the current price level and the aggressive (market) order triggers a passive order at a different price. ### Example Let’s dive into an example: If the current price of BTC is 30,000 and Joe wants to buy $100 at 29,000 he can place a limit buy order of $100 at 29,000. This order is displayed to all participants in the orderbook. Similar to Joe, there are other traders who are interested in buying at various price levels. Let’s say Jillian wants to buy $50 at price level 28,000 and Jack is willing to buy $25 at 27,500. Now the buy side of the orderbook looks like this: 30,000 → Current Price\ 29,000 → $100 \ 28,000 → $50 \ 27,500 → $25 Users do not know the exact size and price level of every single participant, rather the aggregate at each price level. Now let’s say Alice also wants to buy $25 at 27,500. The orderbook now changes to: 30,000 → Current Price\ 29,000 → $100\ 28,000 → $50\ 27,500 → $50 \[we add $25 to the same price level]. Similar to the limit buys (bids), we have limit sells (asks). \ \- Matt wants to sell $200 at 30,100. \ \- Molly also wants to sell $100 at 30,100. \ \- Mary is willing to sell $50 at 30,200 and another $50 at 30,300. \ \- Finally, Mike is interested in selling $100 at 31,000. Now the full orderbook is: 31,000 → $100\ 30,300 → $50\ 30,200 → $50\ 30,100 → $300\ 30,000 → Current Price\ 29,000 → $100\ 28,000 → $50\ 27,500 → $50 Technically, the current price of $30,000 means this is the last price a transaction occurred. Since there are no bids or asks at 30,000, the next aggressive (market) order will triggered a new price level. If it is a market buy order, it will hit 30100 and it is a market sell order it will trigger 29000. Let’s say Trader X market buys $250, this then changes the orderbook to: 31,000 → $100\ 30,300 → $50\ 30,200 → $50\ 30,100 → $50 → \[300 -250 = 50. Also now the current price]\ 29,000 → $100\ 28,000 → $50\ 27,500 → $50 Trader Y also market buys $75. The orderbook is now: 31,000 → $100\ 30,300 → $50\ 30,200 → $25 \[$50 at 30100 is all taken and the remaining 25 is subtracted from 30200. Also the new Current Price].\ 29,000 → $100\ 28,000 → $50\ 27,500 → $50 The interaction of market and limit buys is how markets ultimately move and knowing the activity of limit buyers and sells can provide a great deal of insight into the markets. ## **How can it be used?** Bids & Asks data can be used in a myriad of ways. ### Supply/Demand We’ll start with the simplest way: supply and demand. Bids represent demand and asks represent supply. Let’s say we sum up all the bids (from 0 to the current price) and that sum is $10million. The sum of all asks (from current price to infinity) is $5m. This means there is more demand than supply. In fact, there is twice as much demand than supply, which could indicate bullish pressure. Why? For price to go down, you require twice as much force than for price to go up. Now of course, like most things in trading, it’s not as simple as this and we’ll get into why things can get complex. But for now, it’s important to understand that bids and asks can represent demand and supply.  ### Bid & Ask Walls (Support / Resistance) If let’s say a new participant, Trader X, enters the market and wants to buy $500 million at 29,500… suddenly, there is massive buy pressure (demand). Trader X is actually executing their orders and the current price (say 30,000), and is willing to wait until price drops. Price may never reach 29500 and Trader X’s order may never get executed, but the demand has been advertised to the market as everyone now knows that there is a $500million limit buy order(s) at 29,500. This leads to buy pressure in two ways: Price drops from 30000 to 29500 but for it to drop further, we need 500million in aggressive sell orders to eat through Trader X’s order. This is a lot of supply required and creates friction for price to further drop – in a way acting like support. As mentioned above, since the market knows that there is 500million worth of demand at 29500, they start buying realizing there is a massive imbalance in the markets. This causes the price to rise and it never reaches the 29500 level. In both cases, the 500million bid creates direct or indirect buy pressure. Traders often refer to these extremely large limit buys/sells as “walls” (bid wall / ask wall).  ### Spoofs (“Fake Orders”) We mentioned earlier that using bids as a proxy for demand and asks as a proxy for supply comes with a caveat. That caveat is spoofs or fake orders. Traders have the ability to cancel their limit orders. There are many reasons traders may want to cancel their orders before price reaches that level. Perhaps they simply changed their mind, or received new data which made them lower their bid, or found a better opportunity elsewhere. These are all valid reasons a limit order can be canceled, however, another reason is to simply create fake buying or selling pressure without ever having the intention of executing that order. In other words, that $500 million order at 29500 we mentioned earlier – well imagine if price starts to drop from 30000 reaches 29550 and suddenly that 500 million disappears. If trader X placed this large limit buy order with the intention of never wanting to buy, then this is known as a spoof. Manipulating the markets like this can be common as it is hard to truly identify whether the order was a spoof or canceled due to the other reasons mentioned above. We often see that when a large limit order is canceled or a wall is removed, it can lead to price volatility as other participants have to readjust with this new information.  ### Filtering the Orderbook One can get a better understanding of supply / demand by breaking it up into tranches and also potentially filtering out spoofs. Let’s go back to the same example where there is a 500 million buy order at 29500 and the current price is 30000. If we filter the orderbook within 1% of the current price: 29700 to 30300 and then take the sum of bids and asks, this can paint a completely different picture of where supply demand is since prices further away from current price (like the one at 29500) are no longer included. The following filters are currently available: Quote, 1%, 2%, 5%, 10%, 20%, and full orderbook. Quote is the best (nearest) bid price and ask price. Often this can be a good way to filter out potential spoofs as the likelihood of faking an order so close to price is low. In addition, looking at the quote level can also show market maker (MM) activity as they tend to make up a bulk of the quote bid/ask market share.   ### Exchange Comparisons The orderbook indicator can be displayed in aggregated mode which is the sum of all bids and asks on exchanges selected by the user. Like other indicators that are aggregated – one can drill down to individual exchanges. In some cases, viewing the fully aggregated data can be useful as it can remove noise on one particular exchange. In other cases, investigating the activity of certain exchanges could be useful. One example of this is TWAP. Suppose, we have a large player who wants to enter a position. An efficient way to do this is to slowly bid the price and average over a period of time (TWAP or time weighted average price). Often, this can be spotted by an increase in the bids. When the TWAP is complete, the bids may drop back to normal levels. On an aggregated basis, this may be hard to spot but by drilling into each exchange one may be able to identify such patterns. ## **Where can I find this?** Orderbook data is currently available on our TradingView Charting Application. From charts, users can go to Indicators → Orderbook (Beta). Bids & Asks indicator is available in this orderbook suite.    # Bid & Ask Ratio ## Background An order book contains a list of buy and sell orders for a particular asset, such as a BTCUSDT. Each order specifies the price at which a trader is willing to buy or sell a certain quantity of the asset. When you select a range of 0-1% in the order book, you are asking to see only the bids or asks that are within 0-1% of the current market price. For example, if the current market price for a BTCUSDT is $100, then bids within the 0-1% range would be between $99 and $100 ($100 minus 1%). Asks within the 0-1% range would also be between $100 and $101 ($100 plus 1%) By looking at bids and asks within a specific percentage range, you can get a better idea of the supply and demand for the asset at different price levels, which can help inform your trading decisions. ## What is it? The bid/ask ratio is a measure of the relationship between the number of buy orders (bids) and sell orders (asks) in an order book for a particular asset. To calculate the bid/ask ratio, you take the difference in total bids and total asks and divide the result by the total number of bids and asks. $$bidAskRatio = (bids - asks) / (bids + asks)$$ The resulting ratio ranges between -1 and 1, with 0 indicating an equal number of buy and sell orders in the order book. * A bid/ask ratio that is greater than 0 indicates that there are more buy orders than sell orders in the order book, which could suggest that there is greater demand for the asset at the current price level. * Conversely, a ratio less than 0 indicates that there are more sell orders than buy orders, which could suggest that there is greater supply of the asset at the current price level. ## Where can I find it? To start using the "Bid & Ask Ratio" on the Hyblock platform, follow these simple steps: 1. Go to "Charts." 2. Select "Indicators." 3. Navigate to the "Orderbook" section. 4. Locate and select the "Bid & Ask Ratio" from the list of available indicators.
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# Combined Books ## Definition **Combined Books** represent the **total liquidity available in the order book** across multiple exchanges, encompassing both **bids** (limit buy orders) and **asks** (limit sell orders) at various **depth levels**. These depth levels typically include: * **Quote:** Best bid and ask prices. * **1%, 2%, 5%, 10%, 20% Depth:** Liquidity within a percentage range from the mid-price. * **Full Book:** Entire visible order book liquidity, covering all price levels. #### **Key Insights:** * **Total Market Liquidity:** Measures the aggregated buying and selling power across exchanges. * **Depth Analysis:** Highlights liquidity concentration at different price ranges. #### **Why It Matters:** * **Market Stability:** Higher liquidity generally indicates more stable price movements and reduced slippage. * **Volatility Risk:** Thin liquidity at key depth levels may signal potential price swings. The **Combined Books** indicator provides a comprehensive view of **aggregated market liquidity**, enabling traders to make more informed decisions about entry, exit, and risk management based on order book dynamics. # Bid Ask Spread ## Definition The **Bid-Ask Spread** is the **difference between the best ask price and the best bid price** in an order book. It represents the **cost of immediate execution** in the market and serves as a key indicator of **liquidity and market efficiency**. Bid Ask Spread = Best Ask Price − Best Bid Price *** **Parameters:** 1. **Average:** * Measures the **average spread value** over a specific timeframe. * Calculated by taking the **average of the bid-ask spread** every time it changes within the given period. * **Purpose:** Provides a smoothed-out view of the spread, reducing noise from momentary spikes. 2. **Max:** * Tracks the **highest recorded bid-ask spread** within a specific timeframe. * **Purpose:** Highlights periods of extreme liquidity imbalance or market stress. *** #### **Key Insights:** * **Narrow Average Spread:** Indicates consistently high liquidity and lower trading costs. * **Wide Average Spread:** Suggests persistent liquidity issues or reduced market participation. * **High Max Spread:** Signals moments of market stress, volatility spikes, or low liquidity periods. #### **Why It Matters:** * **Execution Costs:** Wider spreads increase costs for market orders. * **Market Liquidity:** Narrow spreads imply deeper liquidity, while wider spreads suggest thin order books. * **Volatility Signals:** High max spreads can indicate sudden price movements or temporary market imbalances. Together, **Average Bid-Ask Spread** and **Max Bid-Ask Spread** provide a more nuanced understanding of **liquidity conditions** and **market stability**, helping traders make informed decisions about trade execution and risk management. # Bid & Ask Cumulative Delta ## Definition **Bid & Ask Cumulative Delta** tracks the **cumulative difference between resting buy (bid) and sell (ask) orders** on the order book over a specific timeframe. It measures the **net liquidity imbalance** between passive buy and sell orders, offering insight into the **supply and demand dynamics** waiting to be executed. #### **Key Concept:** * **Bid Liquidity:** The total volume of passive buy (bid) orders resting in the order book. * **Ask Liquidity:** The total volume of passive sell (ask) orders resting in the order book. * **Delta:** The difference between bid liquidity and ask liquidity at each point in time. * **Cumulative Delta:** The running total (cumulative sum) of these differences over time. Cumulative Delta=∑(Bid Liquidity−Ask Liquidity) #### **Depth Parameters:** The **Bid & Ask Cumulative Delta** is analyzed across various **order book depth levels**, each representing a range of liquidity from the mid-price: * **Quote:** Best bid and ask prices. * **1% Depth:** Orders within 1% of the mid-price. * **2% Depth:** Orders within 2% of the mid-price. * **5% Depth:** Orders within 5% of the mid-price. * **10% Depth:** Orders within 10% of the mid-price. * **20% Depth:** Orders within 20% of the mid-price. * **Full Book:** All visible liquidity across the entire order book. Each depth level provides a unique perspective on **liquidity concentration and imbalance**, offering clarity on market sentiment across varying price ranges. # Best Bid & Ask ## Definition The **Best Bid & Ask** represents the **highest available buy price (Best Bid)** and the **lowest available sell price (Best Ask)** in the order book at any given moment. These two prices form the **immediate liquidity boundary** where buy and sell orders are most likely to be executed. #### **Key Concepts:** * **Best Bid:** The **highest price** a buyer is willing to pay for an asset. * **Best Ask:** The **lowest price** a seller is willing to accept for an asset. #### **Visualization:** * **Best Bid Line:** Displays the price level of the highest buy order over time. * **Best Ask Line:** Displays the price level of the lowest sell order over time. #### **Key Insights:** * **Price Boundaries:** The gap between these two lines forms the [**Bid-Ask Spread**](https://academy.hyblockcapital.com/indicators/orderbook/bid-ask-spread), indicating the cost of immediate execution. * **Liquidity Dynamics:** Changes in the best bid and ask prices reflect shifting supply and demand. * **Market Sentiment:** Persistent upward movement in the Best Bid suggests buying pressure, while downward movement in the Best Ask suggests selling pressure. The **Best Bid & Ask** lines provide a **real-time snapshot of market liquidity boundaries**, helping traders track price discovery, assess market efficiency, and identify immediate buying and selling pressures. # Bids & Asks Delta ## Definition **Bid-Ask Delta** measures the **net difference between buy-side liquidity (bids) and sell-side liquidity (asks)** within the order book at specific **depth levels**. It highlights the **imbalance between passive buy and sell orders**, offering insight into supply and demand dynamics across different price ranges. Bid-Ask Delta = Total Bids − Total Asks #### **Depth Parameters:** The **Bid-Ask Delta** can be calculated across multiple **order book depth levels**, each representing a specific range from the mid-price: * **Quote:** Best bid and ask prices. * **1% Depth:** Orders within 1% of the mid-price. * **2% Depth:** Orders within 2% of the mid-price. * **5% Depth:** Orders within 5% of the mid-price. * **10% Depth:** Orders within 10% of the mid-price. * **20% Depth:** Orders within 20% of the mid-price. * **Full Book:** All visible orders in the order book. Each depth level offers a unique perspective on liquidity imbalances, with smaller ranges reflecting short-term orderbook and larger ranges showing broader liquidity trends. #### **Key Insights:** * **Positive Delta:** Indicates more buy-side liquidity (bids exceed asks), suggesting stronger demand. * **Negative Delta:** Indicates more sell-side liquidity (asks exceed bids), suggesting stronger supply. * **Depth Variance:** Imbalances at deeper levels may indicate hidden liquidity or strategic positioning. The **Bid-Ask Delta** serves as a **powerful tool for assessing liquidity imbalances across multiple depth levels**, helping traders and analysts identify market sentiment, liquidity zones, and potential price pressure points. # Products {% content-ref url="/pages/-MQYhW0E9cRKqTTJYyib" %} [Liquidation Levels](/tools/liquidation-levels) {% endcontent-ref %} {% content-ref url="/pages/-MQYmzcR84VJ8FIhUTt3" %} [Net Positions Heatmap](/tools/net-positions-heatmap) {% endcontent-ref %} {% content-ref url="/pages/-MQYn3foibZJaKaOfHJk" %} [Open Interest Profile](/tools/oi-profile) {% endcontent-ref %} {% content-ref url="/pages/-MQYhbWeBWXYGxnDV1HI" %} [Coin Screener](/tools/coin-screener) {% endcontent-ref %} {% content-ref url="/pages/-MRQe4lMn64B-MSOWBjz" %} [Probability Histograms](/tools/probability-histograms) {% endcontent-ref %} # Liquidation Levels Estimated price levels predicting where liquidation events may occur {% embed url="
 {% endtab %} {% endtabs %} In the tabs above, there are five distributions, each representing a separate coin with a unique shape. Each distribution tells a different story about the pattern in retail longs. * *Distribution 1*: Majority of the time the percentage of accounts that are net long lies between 55% - 70%, there are a few rare instances where they are between 35% - 50%. This is known as left-skewed distribution (or negative skewness) where the "tail" is longer to the left. * *Distribution 2*: Similar to distribution 1, this is also left skewed with a tail longer to the left. However, unlike distribution 1, this distribution has a more "normal" distribution with three peaks: 57% - 58%, 63% - 64%, and 66% - 67%. * *Distribution 3*: In this distribution both extremes are relatively the same with peaks around 55% and 70%, representing something close to a bimodal distribution. * *Distribution 4*: This is close to a normal distribution where both the mean and median would be close to each other. In addition, we can see that the majority of time, the long% lies in the center. * *Distribution 5*: Finally, this distribution is very similar to distribution 3 which could imply that these coins move similarly. ## How do traders use this? This tool can be used in a variety of ways from simple data exploration to advanced techniques like finding divergences. ### Identifying Divergences For example, in the below chart for QTUMUST, the retail long% (top graph) is at 81.4% while the whale long% (third graph from top) is at 49.22%. While 49.22% might not seem like an extreme value, it is in fact an outlier. Only 2.59% of the time has whale long% been lower – in other words, \~98% of the time whale long% is above the current value of 49.22%. Similarly, 81.4% retail long percentage is also a massive outlier. 99.719% of all historical values have been lower than the current long%. Clearly, whales are more short than they normally are while retail is more long than they normally are signaling a strong divergence. Generally traders view this is a bearish sign.  ### Finding Confluence In our next example (image below), we see how to use the probability histograms to find confluence. Retail long% is at 51% and while this on the lower side relative to all historical values, it is not an extreme outlier. However, Top Trader Positions (whales) are significantly more long than usual. In addition, the funding rate is at -0.0236 and by using the histogram we know this does not happen too often –- only 4.08% of the time has the funding rate been lower. Whales taking a heavier long position than usual and funding rate being lower than usual is generally a bullish sign as both signals are in confluence.  # Coin Screener {% embed url="
We display custom indicators from alternative datasets or proprietary calculated metrics such as liquidation levels and all of these indicators update in real-time.  Over 40 custom indicators, from the following categories: {% tabs %} {% tab title="Orderflow and Open Interest" %}  {% endtab %} {% tab title="Longs & Shorts" %}  {% endtab %} {% tab title="Liquidity" %}  {% endtab %} {% tab title="Sentiment" %}  {% endtab %} {% tab title="Technical Indicators" %}  {% endtab %} {% endtabs %} # FAQ ### **What constitutes a "top trader" for the long & short indicators?** The criteria varies from exchange to exchange. * Okex defines “top traders” as the top 100 traders. * Binance defines “top traders” as the top 20% of traders by margin balance. * Huobi defines top traders are those part of exclusive, invite-only club meant for quantitative, institutional investors and other elite level traders participating in Huobi’s platform. ### **What constitutes a "whale" for the Retail vs Whale indicator \[Binance]?** Binance provides two types of top trader long% indicators: top trader accounts and top trader positions. We do not consider top trader accounts to be whales, but rather *assume top trader positions are the "whales"* Why? Because generally whales have the largest positions, while retail make up majority of the accounts (even in the top20% of accounts by size). For a further breakdown of this, please see our [Binance Long & Shorts section](https://academy.hyblockcapital.com/indicators/longs-and-shorts-indicators/binance-longs-and-shorts). ### **I was wondering do I need different subscription for alpha and beta?** No, as a premium member, you receive access to both alpha and beta. If your account does not have access to both, please DM me. ### **What is heatmap type on the coin screener?** Suppose funding rate is 0.00034 for BTC. 1. 1\. Is this high or low relative to the market? 2. Is this high or relative to bitcoins historical funding? (Itself) *relative to market* compares the coin to the rest of the coins (market) -- answering question1 *relative to itself* compares the coin to its own past (or historical data) -- answering question2 ### **What is the refund policy?** We deal with every refund on a case-by-case basis. The sooner we hear from you, the more chance we have in rectifying any issues that may have arisen. You may cancel your Paid Account at any time. If you're located in a region where we're legally required to issue a refund on an early cancellation or you have any questions about cancellations or refunds, please contact us at
