π Neocart AI Agent Trading Results
π Period: March 30 β April 5
π° Total Realized PNL: +5.78%
π€ Total Client Profit: +2.89%
π Daily Results:
β’ March 30 β +0.52%
β’ March 31 β +0.76%
β’ April 1 β +0.66%
β’ April 2 β +1.63%
β’ April 3 β +0.50%
β’ April 4 β +0.54%
β’ April 5 β +1.17%
π Period: March 30 β April 5
π° Total Realized PNL: +5.78%
π€ Total Client Profit: +2.89%
π Daily Results:
β’ March 30 β +0.52%
β’ March 31 β +0.76%
β’ April 1 β +0.66%
β’ April 2 β +1.63%
β’ April 3 β +0.50%
β’ April 4 β +0.54%
β’ April 5 β +1.17%
π5π₯4β€2
Why the Profitability Differs Between the Pool and API Accounts
The difference in profitability between the overall strategy (the pool) and accounts connected via API arises due to several technical and strategic factors.
1. Balance Dynamics in the Pool
In the pool, one of the key factors is the constant change in the active balance (including participants connecting or disconnecting). This leads to the following effects:
β’ Existing open positions may be additionally scaled in (averaged).
β’ The total position size can increase.
β’ The average entry price may improve.
As a result, when the same take-profit level is reached:
β’ The realized PNL may differ.
β’ In many cases it may be higher due to a better average entry price.
β’ However, the opposite can also happen during unfavorable market movements.
2. More Active Trading by the AI Agent
Within the pool, the AI agent operates more aggressively:
β’ Approximately 30% more trades are executed.
β’ The strategy reacts to market movements faster.
β’ The averaging mechanism is used more actively.
All of this directly affects the final profitability.
3. Extended Capabilities of the Exchange Account
The pool operates through a broker account on the Gate exchange, which provides additional advantages:
β’ Higher limits
β’ More flexible volume management
β’ The ability to average positions more efficiently
β’ Overall better execution of the strategy
4. Exchange Management via Client API
When trading through a clientβs API account, a more conservative model is used:
β’ The number of averaging steps is limited.
β’ Position entry sizes are reduced.
β’ Risk control is stricter.
β’ The number of simultaneously open positions is optimized.
β’ No extended limits are available β the strategy operates under the standard exchange conditions of the clientβs account.
Additionally, this mode must consider external exchange constraints (limits, liquidity, API conditions), which directly affects both the strategy execution and its profitability potential.
The difference in profitability between the overall strategy (the pool) and accounts connected via API arises due to several technical and strategic factors.
1. Balance Dynamics in the Pool
In the pool, one of the key factors is the constant change in the active balance (including participants connecting or disconnecting). This leads to the following effects:
β’ Existing open positions may be additionally scaled in (averaged).
β’ The total position size can increase.
β’ The average entry price may improve.
As a result, when the same take-profit level is reached:
β’ The realized PNL may differ.
β’ In many cases it may be higher due to a better average entry price.
β’ However, the opposite can also happen during unfavorable market movements.
2. More Active Trading by the AI Agent
Within the pool, the AI agent operates more aggressively:
β’ Approximately 30% more trades are executed.
β’ The strategy reacts to market movements faster.
β’ The averaging mechanism is used more actively.
All of this directly affects the final profitability.
3. Extended Capabilities of the Exchange Account
The pool operates through a broker account on the Gate exchange, which provides additional advantages:
β’ Higher limits
β’ More flexible volume management
β’ The ability to average positions more efficiently
β’ Overall better execution of the strategy
4. Exchange Management via Client API
When trading through a clientβs API account, a more conservative model is used:
β’ The number of averaging steps is limited.
β’ Position entry sizes are reduced.
β’ Risk control is stricter.
β’ The number of simultaneously open positions is optimized.
β’ No extended limits are available β the strategy operates under the standard exchange conditions of the clientβs account.
Additionally, this mode must consider external exchange constraints (limits, liquidity, API conditions), which directly affects both the strategy execution and its profitability potential.
In just 2 weeks, our bot has attracted a strong number of interested users β we now have over 140 people with us!
Thatβs a great result in such a short time. Weβre committed to continuously improving and supporting our trading agent to deliver better performance and a more ΡΠ΄ΠΎΠ±Π½ΡΠΉ experience for our users.
Thank you for being with us!
Thatβs a great result in such a short time. Weβre committed to continuously improving and supporting our trading agent to deliver better performance and a more ΡΠ΄ΠΎΠ±Π½ΡΠΉ experience for our users.
Thank you for being with us!
π8π₯4β€3
π Neocart AI Agent Trading Results
π Period: April 13 β April 19
π° Total Realized PNL: +3.92%
π€ Total Client Profit: +1.96%
π Daily Results:
β’ April 13 β +0.62%
β’ April 14 β +0.82%
β’ April 15 β +1.06%
β’ April 16 β -1.46%
β’ April 17 β +1.56%
β’ April 18 β -0.88%
β’ April 19 β +2.20%
π Period: April 13 β April 19
π° Total Realized PNL: +3.92%
π€ Total Client Profit: +1.96%
π Daily Results:
β’ April 13 β +0.62%
β’ April 14 β +0.82%
β’ April 15 β +1.06%
β’ April 16 β -1.46%
β’ April 17 β +1.56%
β’ April 18 β -0.88%
β’ April 19 β +2.20%
β€6π6π3