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Profit and Loss

7 months ago

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MCS, MyCoinStory, 마이코인스토리, 무기한계약, derivatives trading, 손익계산, pnl

   

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Welcome to MCS, the world-class derivatives trading platform where traders ALWAYS come first.

The topic of this post is "how to calculate profit and loss" in MCS.

First, there are two types of profit and loss: 'Realized Profit and Loss (RPNL)' and 'Unrealized Profit and Loss (UPNL)'.

       

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The RPNL is the actual profit or loss that arises when the position is actually closed (liquidated) partially or wholly, and this can be calculated using the trader's position exit price and the entry price. The RPNL can be found in the 'Closed PNL':

     

     

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The UPNL is the possible profit and loss of trader's open position.

When a trader holds a position, trader can check two types of the UPNL: one based on the mark price, and one with last traded price.

The UPNL can be found in the 'Position & Open Orders'. If the icon beside "Unrealized PNL" column is M → L, it indicates that the UPNL being displayed is based on the mark price. If the icon is L → M, the UPNL is based on the last traded price. By clicking the icon, traders can set the default UPNL they want to refer to.

       

   

Realized Profit and Loss Calculation

The RPNL can easily be found by substituting values to the following formulas. A long position and a short position have slightly different formulas, so stay focused!

   

<Long Position>

RPNL = (1 / Average Entry Price - 1 / Average Exit Price) x Contract Size

Let me give you an example to help you understand better.

David enters a long position of 10,000 contract at 5,000 USDT and decides to close all 10,000 contracts when the BTC price reaches 10,000 USDT.

The RPNL can be calculated as follows:
RPNL = (1 / 5,000 – 1 / 10,000) x 10,000 = 1 BTC

Thus, David makes the RPNL of 1 BTC in this transaction.

   

<Short Position>

RPNL = (1 / Average Exit Price - 1 / Average Entry Price) x Contract Size

   

Have you noticed the difference between the formulas of the long and the short positions?

In the long position, 1/Average Entry Price comes first; whereas in the short position, 1/Average Exit Price comes first.

   

Let us continue to an example for the short position.

   

David enters a short position of 10,000 contract at 5,000 USDT and decides to close all 10,000 contracts when the BTC price reaches 4,000 USDT.

The RPNL can be calculated as follows:
RPNL = (1 / 4,000 – 1 / 5,000) x 10,000 = 0.5 BTC

Thus, David makes the RPNL of 0.5 BTC in this time.

   

Now that we understand the RPNL, it is the time to visit the UPNL. If a trader wants to know the total of their profit and loss at the current price point, he or she can calculate the UPNL using either the last traded price or the mark price.

   

         

Unrealized Profit and Loss using the Last Traded Price

Just like the RPNL, the difference between the long and the short is the order in using the Entry price. So, I will only be covering a long position case this time.

   

<Long Position>

UPNL = ( 1 / Average Entry Price - 1 / Last Traded Price ) x Contract Size

   

David enters a long position of 10,000 contract at 5,000 USDT and the last traded price of BTC at the point is 8,000 USDT.

UPNL = (1 / 5,000 – 1 / 8,000) x 10,000 = 0.75 BTC

Thus, David makes the UPNL of 0.75 BTC using the last traded price.

           

     

Unrealized Profit and Loss using the Mark Price

We are almost there! I will calculate the UPNL using the mark price, and for a long position again.

   

<Long Position>

UPNL = (1 / Average Entry Price - 1 / Mark Price) x Contract Size

 

David enters a long position of 10,000 contract at 5,000 USDT and the mark price of BTC is 8,000 USDT.

UPNL = (1 / 5,000 – 1 / 8,000) x 10,000 = 0.75 BTC

Thus, David makes the UPNL of 0.75 BTC using the mark price.

   

We hope this post is helpful to all traders when placing an order. You can now compare the target profit and loss with either the UPNL using the mark price or the UPNL using the last traded price.

   

MCS will consider traders at the first.

Thank you.

   

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Published 7 months ago