KOL Performance Metrics
KOL performance metrics is the indicators that helps justify how good a KOL is on the matter of he/she giving the signal to their followers on their Twitter.KOL Performance Metrics are key indicators designed to evaluate the effectiveness of Key Opinion Leaders (KOLs) in guiding their followers on platforms like Twitter. These metrics provide FlashX users with a concise overview of a KOL's historical performance regarding the trading signals they promote. Metrics include:
Alpha: The number of signals promoted by the Twitter ID that has been tracked through FlashX users.
Alpha Followers: The number of followers actively engaging with the Alpha through FlashX.
Average ROI (Return on Investment): The average return generated by following the KOL's signals.
Win Rate: The percentage of signals that resulted in profitable outcomes.
The primary goal of these metrics is to assist users in quickly assessing the past performance of KOLs, aiding in more informed decision-making. KOLs with strong historical ROI and win rates are more likely to provide profitable signals in the future. It is important to note that a "good" signal is one that has historically helped users achieve positive trading outcomes, with higher ROI being preferable.
While we strive for accuracy, these metrics are not infallible and may evolve over time. We welcome your feedback to enhance their precision and relevance.
2.1 Accountability
Scope of Measurement: We only measure transactions executed through FlashX by clicking on the KOL's signal indicator that FlashX overlays next to the call..Trades completed outside of FlashX on other DEXs or trading platforms are not included.
Timeframe Considerations: Accurately timing a trade in relation to a KOL's signal is critical; however, establishing a perfect timeframe is challenging as KOL strategies can vary from short to long-term. Therefore, we track ROI across an indefinite timeframe to accommodate different trading strategies.
Token Transfers: ROI calculations are only accurate for tokens initially purchased on FlashX. Transfers from external wallets are excluded, as they do not provide a clear measure of ROI from the platform-specific activity.
Multiple Signal Tracking: In cases where tokens are bought and sold based on signals from different KOLs, we attribute the purchase to the first KOL's signal. Subsequent sales influenced by other KOLs are not factored into this KOL’s performance metrics.
2.2 How ROI is calculated
ROI = (Average Sell Price - Average Buy Price) x Number of Tokens Sold
2.2.1 Average Sell price
To calculate the Average Sell Price, we use the following formula:
Here’s how you can break it down:
Total Sell Revenue: This is the total amount of money you received from selling the tokens. It is calculated by summing up the revenue from each sale.
Number of Tokens Sold: This is the total number of tokens that were sold.
Average sell price =
Example:
Sale 1: Sold 100 tokens at $50 each.
Sale 2: Sold 150 tokens at $55 each.
Number of Tokens Sold = 100 + 150 = 250Average Sell Price = 13250/250 = 53So, the Average Sell Price is $53 per token.
You can use this method to calculate the average sell price based on your sales data.
2.2.2 Average Buy Price
To calculate the Average Buy Price, you would use a similar formula as for the Average Sell Price:
Total Buy Cost: This is the total amount of money you spent to purchase the tokens. It is calculated by summing up the cost from each purchase.
Number of Tokens Bought: This is the total number of tokens that were bought.
Formula:
Average Buy Price =
Example:
Purchase 1: Bought 200 tokens at $45 each.
Purchase 2: Bought 300 tokens at $48 each.
Total Buy Cost =
Number of Tokens Bought = 200 + 300 = 500
Average Buy Price = 23400/500 = 46.8
So, the Average Buy Price is $46.80 per token.
This method allows you to determine the average price at which you acquired your tokens, which is crucial for calculating your ROI.
Alpha follower: is the number of people who have swapped on the tweet line of that KOL. We only record it if a swap is made. Therefore, the minimum number of Alpha followers here is 1.
Alpha: is the number of calls that have been promoted that had FlashX user swap.
ROI for each call : The ROI for each KOL call is the highest ROI achieved by any user. For example:
KOL named Santi shills a buy signal for PEPE and has 3 users, A profits 10%, B profits 80%, and C profits 200%. We will calculate the ROI for the PEPE call as 200% (the highest ROI).
Santi shills another call for DOGE, where Mr. A profits 40%, Mr. E profits 50%, and Mr. F profits 300%. We will calculate the ROI for the DOGE call as 300% (the highest ROI).
In cases where the ROI for each call is negative, we take the smallest negative number. For example, Kabu shills a meme call SHARO: User A -100%, user B -200%. Thus, we select -100% as the ROI for that call.
Avg ROI: is the average ROI of the deals. KOL Santi above has 2 call, one at 200% and one at 300%. Thus, the AvgROI for this KOL is (200% + 300%) / 2 = 250%.
Win rate: is the ratio of deals with positive ROI to the total number of deals.
The method described for calculating KOL performance metrics, while insightful, has several limitations that could impact the accuracy and usefulness of the data. Here are some key limitations:
Dependence on User Actions: The metrics rely solely on actions taken (swaps) directly through tweets, which may not capture the full influence of a KOL. Users may take action based on a KOL's advice without performing the swap in the immediate context of the tweet, leading to underreporting of a KOL’s true impact.
Selection of Highest ROI Only: Calculating ROI based on the highest return achieved by any user might skew the perceived success of a KOL. This method overlooks the average performance experienced by the majority of followers and may amplify outlier successes that are not reflective of typical outcomes.
Negative ROI Handling: In the case of negative ROIs, choosing the smallest negative number might not accurately reflect the potential financial impact on followers. This approach minimizes the appearance of loss, potentially misleading about the risks involved.
ROI Calculation from Initial Purchases Only: The restriction to calculate ROI only for tokens bought directly on FlashX excludes a broader assessment of a KOL's recommendations, particularly if followers are using multiple platforms or transferring pre-owned tokens.
Lack of Contextual Data: The methodology does not account for external factors that might influence trading outcomes, such as market volatility or unforeseen economic events, which can affect the performance metrics independently of a KOL’s influence.
Win Rate Simplification: Determining the win rate solely on the basis of positive returns might not provide a complete picture of a KOL’s performance. This metric fails to consider the magnitude of gains or losses, which can be crucial for understanding investment outcomes.
Average ROI Calculation: Averaging the ROIs of all deals might not adequately represent the variability and risk associated with a KOL’s recommendations, especially if the results are highly skewed by a few highly successful or poor trades.
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