Trader Grades

Trader Grades 📈

The Trader Grade endpoint empowers traders to make informed buy and sell decisions by calculating grades for a specific crypto asset using a combination of Technical Analysis, Quantitative-Driven Performance Metrics, and Onchain Metrics. The endpoint offers a comprehensive overview of price movements through the TM Trader Grade, which combines all other grades in the endpoint.

Parameters: TOKEN_ID, START_DATE, END_DATE, SYMBOL, CATEGORY, EXCHANGE, MARKETCAP, VOLUME, FDV, TRADER GRADE, TRADER GRADE PERCENT CHANGE

Datapoints:

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TOKEN_ID

Token ID for identifying each cryptocurrency (e.g., the Token ID of BTC is 3375).

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NAME

The name of the crypto asset (e.g., Bitcoin).

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DATE

The date of calculation of the grades.

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SYMBOL

The symbol of the crypto asset (e.g., BTC).

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TA_GRADE

The Token Metrics TA grade is based on Technical Analysis. It primarily focuses on price moves and trading indicators and indicates price momentum.

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QUANT_GRADE

The Token Metrics Quant Grade is based on Quantitative-Driven Performance Metrics. It primarily focuses on historical price statistics and provides indications on historical performance.

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TM_TRADER_GRADE_24H_PCT_CHANGE

Represents the 24h percentage change in the Token Metrics Trader grade.

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TM_TRADER_GRADE

The short-term Token Metrics Trader Grade comprises all of the aforementioned indicators.

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Visualize on Token Metrics Application:

Go to the Token Metrics Ratings Page. This gives a bird's eye view of the whole market while applying the TM Trader Grade. This page can be sorted by the highest-lowest Trader Grades or vice versa.

Screenshot from Token Metrics Application: Tokens sorted by Token Metrics Trader Grade high to low.

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Example Use Case:

A trader can use the Token Metrics Trading Indicator to identify potential buying and selling opportunities. Token Metrics Grades are generated by a machine learning model and provide short-term price predictions for a given token. If the grade is high, it signals that the model predicts the token's price is likely to increase. On the other hand, if the grade is low, the model predicts that the token's price may decrease. This information can be used by traders to make informed decisions about when to buy and sell, or to create automated trading strategies that respond to changes in the grade. Additionally, traders can track the accuracy and historical performance of the Token Metrics Trading Indicator to evaluate its effectiveness.