SF - Margin levels
Advanced margin zone model predicts stoploss order accumulation levels and liquidations with high accuracy
Last updated
Advanced margin zone model predicts stoploss order accumulation levels and liquidations with high accuracy
Last updated
To add the "Margin levels" tool to your workspace, first click on the "Widget menu" button in the platform header. Then click on the button of the same name in the "Microstructure" section.
The margin zone map visualizes price areas where hidden liquidity from liquidations and stoploss orders is concentrated.
Margin levels represents a glass with potential margin liquidations and has numerical and color identification by levels:
Red is the projected margin level for SHORT positions;
Green is the projected margin level for LONG positions;
White - current price level.
At the bottom of the tool is a scale of the volume of potential margin levels in dollars.
When you hover over a level with the cursor, there is clarifying information about the price level and dollar volume of potential liquidations.
At the top of the tool is a search box that allows you to navigate to a specific ticker.
Like all tools SpreadFighter, Margin Levels has the ability to synchronize with other tools marked with the same color.
One of the features of the derivatives market is the ability to open leveraged or margined positions. Any such margin position will have a liquidation price. As soon as the price of the underlying asset reaches the liquidation price level, the exchange will forcibly close the trader's position at a loss to prevent the client's balance from going into the negative zone.
Stoploss orders are pending orders that traders place on exchanges to stop losses if the price moves against an open position. On the exchange, stoploss orders and liquidations are implemented using pending orders.
Single liquidations and stoploss orders do not carry any interest, as their influence on the market is insignificant. However, the accumulation of such orders can significantly affect the price and provoke a jump in volatility. The accumulation of pending orders is otherwise called a margin zone.
Ordinary users do not have access to information about them - such high-level data is available only to exchanges (and usually to some affiliated persons conducting trading activities related to the exchange's cryptocurrency assets). However, current quantitative models in the field of market microstructure allow us to calculate marginal zones with sufficiently high accuracy.
Based on the data analyzed using a dynamic neural network, we identified regularities in the placement of margin zones taking into account the peculiarities of the behavior of a particular asset and built a corresponding model that depicts the accumulations of pending orders.
An important part of our miscalculation algorithm is data obsolescence, which allows us to level out "hung" clusters.
Prices are different for large participants. Therefore, knowing the location of liquidity in the market is valuable information for large market participants.
It is also important to note that the exchanges charge additional penalty fees on liquidations (funds are typically redistributed to insurance funds and others).
As martket move to liqudity is known - the market moves for liquidity. Accordingly, the accumulation of pending orders is a point of attraction for the price, as margin zones are the point of volume concentration.
We can suggest the following uses:
Directional trading. Prices often gravitate toward liquidity accumulations. Identifying these zones can help you evaluate potential price movement in conjunction with other tools.
Finding pivot points. Often prices reverse after pending orders are executed.
Risk Management. Using Maring Levels, a trader can more accurately place his stoploss and take profit orders, avoid false outs and lock in profits at the most favorable prices.
Solving the liquidity problem. Traders with significant capital can use predictive pending orders as a source of liquidity to open and close their positions, thereby avoiding significant risk.
Volatility trading. Maring levels allow you to make more accurate volatility forecasts due to more correct estimation of market depth. The simplest example is buying an option with a strike in front of a margin zone cluster.
