FAQ

How does the bot decide when to enter and exit a trade?

The EASY Trendopedia Bot employs a sophisticated, multi-step process to decide when to enter and exit trades, ensuring that each decision is based on rigorous analysis and strategic alignment with the prevailing market conditions. Here’s a detailed breakdown of the decision-making logic:

Step 1: Signal Generation

Data Collection: The bot begins by collecting real-time tick data from the market. This data includes every price change, transaction volume, and the exact time of each tick, providing a detailed snapshot of market activity.

Initial Pattern Analysis: Using a sophisticated algorithm, the bot analyzes the tick data to detect patterns that could indicate potential trading opportunities. This involves comparing current market data against historical patterns to identify similarities that have historically led to profitable outcomes.

Min pp Similarity Check: The bot applies the “Min pp similarity” parameter, ensuring that the patterns it identifies closely match those that have historically been successful. This step is crucial for enhancing the accuracy of the signals, as it minimizes the risk of false positives by adhering closely to proven patterns.

Step 2: Signal Validation

Max Signal Deviation Checks:

In Pips: The bot ensures that the current market price has not deviated from the signal price by more than a specified number of pips, which helps prevent execution during excessive price slippage.
In Seconds: The bot also checks that the signal is acted upon within a specific time frame to ensure the trade’s timeliness and relevance.

Spread Check: Before proceeding, the bot verifies that the current market spread is within acceptable limits. This is crucial to avoid trading during high spread conditions, which can unfavorably impact trade entry and exit points.

Step 3: Additional Confirmation

Confirmation Model Application: If the initial signal passes the deviation and spread checks, the bot then applies an additional confirmation model. This model uses different or supplementary criteria to confirm the validity of the initial trading signal, further validating the signal’s strength and potential for success.

Min Number of Confirmation in pp: The bot requires a minimum number of subsequent price points to confirm the signal before executing the trade. This helps to ensure that the signal is robust and reduces the likelihood of executing based on a false signal.

Step 4: Trade Execution

MM Mode Application: Depending on the selected Money Management (MM) mode:

Fixed: A pre-determined lot size is used.
% SL Level: The lot size is calculated based on a percentage of the account balance and the predefined stop-loss level.
Fixed Margin: The trade uses a specified portion of the account’s margin.

Trade Placement: Once all conditions and confirmations are met, and the trade size is determined based on the MM Mode, the trade is executed. This involves opening a position at the current market price under the conditions that have been validated as favorable.

Step 5: Balance Protection and Risk Management

Max Profit/Loss Day Checks: After the trade is executed, the bot monitors accumulated profits or losses against the day’s limits set by “Max Profit Day” and “Max Loss Day”. If these limits are reached, trading is halted for the day to protect the balance and either secure profits or limit losses.

Continuous Monitoring: The bot continues to monitor market conditions and adjusts open positions accordingly. It employs stop-loss, take-profit, and possibly trailing stops (if configured) to manage ongoing trades, ensuring that each position is closed at the optimal time to maximize gains or minimize losses.

This comprehensive approach allows the EASY Trendopedia Bot to make well-informed trading decisions that are not only based on real-time market data but are also corroborated by historical evidence and additional validation mechanisms, providing a robust framework for profitable and risk-averse trading.