Crypto Basics

What Indicators Should I Use for Technical Crypto Analysis?

Discover the top indicators for crypto technical analysis—RSI, MACD, moving averages, and more. Learn how Token Metrics uses AI to combine indicators for smarter trading.
Token Metrics Team
8 min
MIN

If you’re serious about trading cryptocurrency, technical analysis (TA) is an essential skill. It helps you understand price movements, predict trends, and identify high-probability entry and exit points.

But with hundreds of technical indicators available, one common question is: “Which indicators should I use for technical analysis?”

In this guide, we’ll break down the most effective indicators for crypto trading, explain how they work, and show you how Token Metrics combines them with AI-driven insights to help you trade smarter.

Why Use Technical Indicators in Crypto?

Unlike traditional stocks, cryptocurrency markets trade 24/7, are more volatile, and are largely driven by sentiment and speculation.

Technical indicators help you:

  • Identify trends (bullish or bearish).

  • Pinpoint support and resistance levels.

  • Detect overbought or oversold conditions.

  • Find entry and exit points with better timing.

The key is not using one indicator in isolation but combining multiple tools for confirmation—which is exactly what Token Metrics does with its AI-driven trading signals.

The Most Important Indicators for Technical Analysis

Here are the must-know indicators for crypto traders:

1. Moving Averages (MA & EMA)

What they do:
Moving averages smooth out price data to help you identify overall market direction.

  • Simple Moving Average (SMA): Calculates the average closing price over a set period (e.g., 50-day, 200-day).

  • Exponential Moving Average (EMA): Gives more weight to recent prices, making it more responsive.

How to use them:

  • Golden Cross: When the 50-day MA crosses above the 200-day MA → bullish signal.

  • Death Cross: When the 50-day MA crosses below the 200-day MA → bearish signal.

Best for:
Spotting long-term trends and momentum.

2. Relative Strength Index (RSI)

What it does:
RSI measures price momentum and identifies overbought (70+) or oversold (30-) conditions.

How to use it:

  • Above 70: Asset may be overbought → possible pullback.

  • Below 30: Asset may be oversold → potential bounce.

Best for:
Finding reversal points and confirming trend strength.

3. Moving Average Convergence Divergence (MACD)

What it does:
MACD measures the relationship between two EMAs (usually 12-day and 26-day) and generates buy/sell signals based on crossovers.

How to use it:

  • Bullish crossover: MACD line crosses above the signal line.

  • Bearish crossover: MACD line crosses below the signal line.

Best for:
Spotting trend changes early.

4. Bollinger Bands

What they do:
Bollinger Bands create a price channel around an asset using a moving average plus/minus two standard deviations.

How to use them:

  • Price near upper band: Potential overbought condition.

  • Price near lower band: Potential oversold condition.

  • Band squeeze: Indicates upcoming volatility.

Best for:
Predicting volatility and identifying breakout opportunities.

5. Volume Indicators (OBV & VWAP)

What they do:
Volume indicators confirm price movements and help spot trend strength.

  • On-Balance Volume (OBV): Tracks buying/selling pressure.

  • VWAP (Volume-Weighted Average Price): Shows average price relative to volume.

Best for:
Confirming whether a trend is supported by strong trading volume.

6. Fibonacci Retracement

What it does:
Identifies key support and resistance levels based on Fibonacci ratios (23.6%, 38.2%, 50%, 61.8%, etc.).

How to use it:

  • Place retracement levels between swing highs and lows to find potential pullback or breakout zones.

Best for:
Setting targets and identifying price zones for entries/exits.

7. Stochastic Oscillator

What it does:
Measures price momentum by comparing closing prices to recent price ranges.

How to use it:

  • Above 80: Overbought.

  • Below 20: Oversold.

  • Use crossovers for potential buy/sell signals.

Best for:
Short-term traders looking for momentum shifts.

8. Ichimoku Cloud

What it does:
Provides a complete view of trend, momentum, and support/resistance levels in one indicator.

How to use it:

  • Price above cloud: Bullish.

  • Price below cloud: Bearish.

  • Cloud crossovers: Signal trend reversals.

Best for:
Swing traders who need multi-factor confirmation in one tool.

How Token Metrics Combines Indicators with AI

Instead of manually tracking dozens of indicators, Token Metrics uses AI to analyze 80+ technical, fundamental, and sentiment-based data points for each asset—giving you actionable insights without the guesswork.

Here’s how:

1. AI-Powered Bullish & Bearish Signals

Our system combines RSI, MACD, MAs, and more to generate real-time buy/sell signals.

2. Trader & Investor Grades

  • Trader Grade: Helps short-term traders focus on cryptos with strong technical setups.

  • Investor Grade: Identifies long-term investment opportunities with strong fundamentals.

3. Narrative Detection

Token Metrics tracks emerging narratives (AI tokens, DeFi, etc.) so you can spot trends before they explode.

4. AI-Managed Indices

Don’t want to analyze charts? Our AI-driven indices automatically rebalance portfolios using technical indicators and market conditions.

How to Combine Indicators Effectively

The most successful traders don’t rely on one indicator. Instead, they combine them for confirmation.

Example:

  • Use RSI to spot oversold conditions.

  • Confirm with MACD bullish crossover.

  • Check volume to ensure strong buying pressure.

When multiple indicators align, your trade has a higher probability of success—and Token Metrics does this automatically.

Advanced Tips for Using Indicators

  1. Don’t Overload: Use 3–5 indicators for clarity.

  2. Adjust for Volatility: Crypto is more volatile than stocks—shorten timeframes for faster signals.

  3. Combine With Fundamentals: Use Token Metrics Investor Grades to pair TA with project fundamentals.

  4. Practice Risk Management: Even the best indicators fail—always use stop-loss orders.

Final Thoughts

So, what indicators should you use for technical analysis?

Start with moving averages, RSI, MACD, Bollinger Bands, and Fibonacci levels—then add volume indicators and advanced tools like the Ichimoku Cloud as you gain experience.

But here’s the truth: indicators are only as good as the trader using them. That’s why Token Metrics simplifies the process by combining dozens of technical indicators with AI-powered analysis, giving you clear, actionable insights for smarter trades.

Whether you’re a day trader or a long-term investor, Token Metrics helps you use technical indicators strategically—not emotionally.

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AI Agents in Minutes, Not Months
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Token Metrics Team
Token Metrics Team

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Research

APIs Explained: What an API Does and Why It Matters

Token Metrics Team
5
MIN

APIs power much of the modern software economy, but the term can feel abstract. This guide breaks down what an API is, how APIs work in practice, common types you’ll encounter, and practical frameworks for evaluating or integrating an API into your projects.

What is an API? A concise definition

An API, or application programming interface, is a set of rules and protocols that lets different software components communicate. Think of an API as a contract: one system exposes specific operations (endpoints) and data structures, and other systems call those operations to request services or information. The API hides internal complexity and provides a predictable interface for developers.

At its core, an API specifies:

  • The actions available (e.g., read data, submit a transaction, trigger a process).
  • The input and output formats (often JSON or XML for web APIs).
  • The transport protocol and authentication methods (HTTP, gRPC, OAuth, API keys).

How APIs work — protocols, endpoints, and flows

APIs can be implemented with different technologies, but common patterns include REST, GraphQL, and RPC (gRPC). A typical web API flow involves a client sending an HTTP request to an endpoint URL, the server processing that request, and then returning a structured response. Key components to understand:

  • Endpoint: A specific URL that performs an action or returns data.
  • Method: HTTP verbs such as GET, POST, PUT, DELETE indicate intent.
  • Payload: The data sent with requests (body) or returned (response).
  • Authentication: Controls access — API keys, OAuth tokens, or signed requests.
  • Rate limits: Servers often limit calls per minute to protect resources.

Understanding these pieces helps you design predictable integrations and debug issues like unexpected latencies or malformed responses.

Common API types and real-world examples

Different APIs serve different needs. Here are common categories and examples:

  • Public / Open APIs: Accessible to external developers. Examples: public weather APIs, mapping APIs.
  • Private APIs: Used internally within an organization to modularize services.
  • Partner APIs: Shared with specific partners under contract.
  • Web APIs (REST/GraphQL): Most common for web and mobile apps. REST APIs expose resources via endpoints; GraphQL exposes a flexible query schema.
  • Streaming / WebSocket APIs: Real-time data feeds such as live market prices or chat messages.

Practical examples: integrating a payment processor via its REST API, pulling exchange rates from a crypto API for display, or using a mapping API to embed location features.

Evaluating and integrating APIs: a practical checklist

When researching or choosing an API, apply a short framework: compatibility, cost, reliability, and security (CCRS).

  1. Compatibility: Does the API support the required protocols and data formats? Is client SDK support available for your stack?
  2. Cost: Understand pricing tiers, rate limits, and overage fees. Check if a free tier or trial exists for testing.
  3. Reliability: Review historical uptime, SLAs, and status page transparency. Look for rate limit details and failover options.
  4. Security: Evaluate authentication models, data encryption, and compliance notes (e.g., GDPR, SOC2 where relevant).

Additional integration tips: use sandbox environments for testing, log API requests/responses for troubleshooting, and build retry/backoff logic to handle transient failures.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

FAQ: Common questions about APIs

What is the difference between REST and GraphQL?

REST defines endpoints that return fixed data structures, which can result in over- or under-fetching. GraphQL exposes a query language where clients request exactly the fields they need, reducing extra data transfer but adding schema complexity on the server side.

How do API keys differ from OAuth tokens?

API keys are simple credentials often used for server-to-server authentication or identifying an app. OAuth is an authorization framework that enables delegated access (user consents) and typically issues short-lived access tokens with refresh mechanics for better security.

Are APIs secure by default?

No. Security depends on implementation: use HTTPS, validate and sanitize inputs, enforce proper authentication/authorization, rotate keys periodically, and monitor for unusual activity. Treat APIs as a potential attack surface and apply standard security controls.

What are typical API rate limits and how should I handle them?

Rate limits vary widely: some services allow thousands of requests per minute, others are stricter. Implement client-side throttling, exponential backoff on retries, and caching where appropriate to reduce request volume and avoid hitting limits.

How can AI and analytics help when working with APIs?

AI-driven tools can help parse API responses, detect anomalies, prioritize endpoints by value, and synthesize insights from multiple data feeds. Platforms such as Token Metrics use AI to aggregate on-chain and market data, which can speed evaluation when integrating crypto-related APIs.

What are common pitfalls when building with third-party APIs?

Common issues include unexpected breaking changes, insufficient error handling, underestimating rate limits, hidden costs, and lack of observability. Mitigate these by reading docs thoroughly, using versioned endpoints, and automating monitoring and alerts.

Disclaimer: This article is for educational and informational purposes only. It explains technical concepts and practical frameworks related to APIs and does not provide investment, legal, or professional advice. Evaluate services independently and consult appropriate experts for decision-making.

Research

APIs Explained: How They Power Web & Crypto Apps

Token Metrics Team
5
MIN

APIs — short for Application Programming Interfaces — are the invisible wiring that connects software, data, and services. From mobile apps fetching weather to crypto platforms streaming on-chain data, APIs turn discrete systems into interoperable ecosystems. This guide explains what an API is, how it works, common types and protocols, practical evaluation criteria, and how AI-driven tools can help you research and integrate APIs safely and effectively.

What is an API? A practical definition

An API is a set of rules and conventions that lets one software program request services or data from another. Think of it as a contract: the provider exposes endpoints and documented inputs/outputs, and the consumer sends requests and receives structured responses. APIs abstract complexity, enforce consistency, and enable modular development.

At a high level, an API specifies:

  • Available operations (endpoints) and the expected parameters
  • Data formats for requests and responses (JSON, XML, etc.)
  • Authentication and authorization methods (API keys, OAuth)
  • Rate limits, error handling, and versioning policies

How APIs work: endpoints, methods and data flow

Most modern web APIs operate over HTTP. A consumer makes a request to a URL (endpoint) using an HTTP method such as GET, POST, PUT, or DELETE. The server processes the request and returns a response payload plus status codes that signal success or error.

Core concepts:

  • Endpoint: A URI representing a resource or action (e.g., /prices/bitcoin).
  • Request: Includes method, headers (authentication, content-type), query or body parameters.
  • Response: Status code (200, 404, 500) and structured data (commonly JSON).
  • Idempotency: Whether repeated requests have the same effect (important for retries).

Understanding these mechanics helps you design integrations, debug issues, and interpret API documentation efficiently.

Common API types and protocols

Not all APIs are built the same. Choosing the right style depends on use case, performance needs, and client ecosystem.

  • REST APIs: Resource-based, conventionally using HTTP verbs and stateless interactions. Popular due to simplicity and broad tooling support.
  • GraphQL: Query language that lets clients request exactly the fields they need. Useful when clients need flexible, efficient queries across related data.
  • WebSockets: Persistent, bidirectional socket connections ideal for real-time updates (chat, market feeds).
  • gRPC: High-performance RPC framework using Protocol Buffers—good for microservices and low-latency systems.
  • SOAP: Legacy, XML-based protocol with strict standards—still used in some enterprise environments.

Each approach has trade-offs: REST is simple but may require multiple round-trips, GraphQL reduces over-fetching but adds server complexity, and WebSockets enable streaming but require connection management.

Security, authentication, and operational governance

APIs often provide access to valuable data and functionality, so security and governance are paramount. Key considerations include:

  • Authentication: API keys, OAuth 2.0, JWTs. Choose methods that match risk and user flows.
  • Authorization: Enforce least privilege—limit which endpoints and operations each credential can access.
  • Rate limits and quotas: Protect infrastructure from overload and abusive usage.
  • Encryption & TLS: Always use HTTPS for data in transit; consider encryption at rest for sensitive payloads.
  • Auditing & monitoring: Log access patterns, errors, and anomalies for forensic and operational visibility.
  • Versioning: Maintain backward compatibility with explicit versioning strategies to avoid breaking consumers.

Operational SLAs, clear error codes, and robust documentation reduce integration friction and surface potential risks early.

How to evaluate and integrate an API: a practical checklist

When assessing a third-party API, use a structured framework:

  1. Documentation quality: Are endpoints, schemas, examples, and rate limits clearly described?
  2. Sandbox & test keys: Is there a sandbox for dry runs without impacting production data?
  3. Latency & throughput: Does the API meet your performance requirements under expected load?
  4. Reliability: Check status pages, historical uptime, and incident response practices.
  5. Cost model: Understand pricing tiers, overage fees, and whether free tiers suffice for initial development.
  6. Security posture: What authentication methods, encryption, and compliance certifications are provided?

For proofs of concept, use API testing tools (Postman, curl) and programmatic SDKs where available. Track metrics during integration and plan for retries, backoff strategies, and graceful degradation.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

FAQ: What is an API?

An API (Application Programming Interface) is a defined set of rules and endpoints that allows one software system to request data or services from another. It standardizes how data is exchanged and operations are invoked between systems.

FAQ: REST vs GraphQL — when to use each?

REST is simple and widely supported, ideal for straightforward resource-based access. GraphQL excels when clients need flexible, aggregated queries and want to reduce over-fetching. Choice depends on client needs and server complexity tolerance.

FAQ: How do APIs stay secure?

Security relies on strong authentication (API keys, OAuth), encryption (HTTPS/TLS), authorization controls, rate limiting, input validation, and monitoring. Regular audits and threat modeling help identify and mitigate risks.

FAQ: What are common API use cases?

APIs power mobile and web apps, payment processing, identity providers, data feeds (market, weather, maps), IoT device control, and integrations between enterprise systems or blockchain nodes.

FAQ: How do I test an API safely?

Use sandbox environments and test keys where available. Employ tools like Postman for exploratory testing, write automated integration tests, validate edge cases and error handling, and verify rate-limit behaviors under load.

Disclaimer

This article is for educational and informational purposes only. It explains technical concepts and evaluation frameworks but does not constitute professional, legal, or investment advice. Always perform your own due diligence when selecting or integrating APIs.

Research

APIs Explained: How They Work and Why They Matter

Token Metrics Team
5
MIN

APIs sit at the center of modern software. Whether a mobile app fetches weather data, a dashboard queries on-chain activity, or an AI agent calls a language model, an API is the bridge that enables machines to communicate. This article breaks down what an API is, how it works, common types and use cases, and practical steps to evaluate and use one safely and effectively.

What Is an API?

An API (Application Programming Interface) is a defined set of rules and protocols that allow software components to communicate. It specifies the methods available, the expected inputs and outputs, and the underlying conventions for transport and encoding. In web development, APIs typically include endpoints you can call over HTTP, request and response formats (commonly JSON), and authentication rules.

Think of an API as a contract: the provider promises certain functionality (data, computations, actions) and the consumer calls endpoints that adhere to that contract. Examples include a weather API returning forecasts, a payment API creating transactions, or a blockchain data API exposing balances and transactions.

How APIs Work: The Technical Overview

At a technical level, most web APIs follow simple request/response patterns:

  • Client issues an HTTP request to an endpoint (URL).
  • Request includes a method (GET, POST, PUT, DELETE), headers, authentication tokens, and optionally a body.
  • Server processes the request and returns a response with a status code and a body (often JSON).

Key concepts to understand:

  • HTTP methods: indicate intent—GET to read, POST to create, PUT/PATCH to update, DELETE to remove.
  • Authentication: can use API keys, OAuth tokens, JWTs, or mutual TLS. Authentication defines access and identity.
  • Rate limits: providers throttle calls per unit time to protect infrastructure.
  • Versioning: APIs use versioned endpoints (v1, v2) so changes don’t break consumers.
  • Webhooks: push-style endpoints that let providers send real-time events to a consumer URL.

Types of APIs and Common Use Cases

APIs come in many shapes tailored to different needs:

  • REST APIs: resource-oriented, use HTTP verbs and stateless requests. Widely used for web services.
  • GraphQL: provides a flexible query layer so clients request exactly the fields they need.
  • gRPC: high-performance, binary protocol ideal for internal microservices.
  • WebSocket/APIs for streaming: support continuous two-way communication for real-time data.

Use cases span industries: integrating payment gateways, building mobile backends, connecting to cloud services, feeding analytics dashboards, and powering crypto tools that stream price, order book, and on-chain data. AI systems also consume APIs—calling models for text generation, embeddings, or specialized analytics.

How to Build, Evaluate and Use an API

Whether you are a developer integrating an API or evaluating a provider, use a systematic approach:

  1. Read the docs: good documentation should include endpoints, example requests, error codes, SDKs, and usage limits.
  2. Test quickly: use tools like curl or Postman to make basic calls and inspect responses and headers.
  3. Check authentication and permissions: ensure tokens are scoped correctly and follow least-privilege principles.
  4. Evaluate performance and reliability: review SLA information, latency benchmarks, and historical uptime if available.
  5. Understand pricing and quotas: map expected usage to cost tiers and rate-limits to avoid surprises.
  6. Security review: watch for sensitive data exposure, enforce transport encryption (HTTPS), and rotate keys regularly.

For domain-specific APIs, such as those powering crypto analytics or trading signals, additional considerations include data freshness, source transparency (e.g., direct node reads vs. indexers), and on-chain coverage. Tools that combine data feeds with AI analytics can speed research—one example of a platform in that space is Token Metrics, which layers model-driven insights on top of market and on-chain inputs.

Build Smarter Crypto Apps & AI Agents with Token Metrics

Token Metrics provides real-time prices, trading signals, and on-chain insights all from one powerful API. Grab a Free API Key

FAQ — What Is an API?

Q: What is the difference between an API and an SDK?

A: An API is a set of rules for communicating with a service. An SDK (Software Development Kit) is a bundled set of tools, libraries, and often an API wrapper that helps developers integrate with that service more easily in a specific programming language.

FAQ — REST vs GraphQL: Which to use?

Q: When is GraphQL preferable to REST?

A: GraphQL is useful when clients need flexible queries and want to avoid over- or under-fetching data. REST remains a strong default for simple, cache-friendly resource-based services and broad interoperability.

FAQ — API Security

Q: What are basic security best practices for APIs?

A: Require HTTPS, enforce strong authentication (OAuth, signed tokens), validate and sanitize inputs, implement rate limits, use scopes for permissions, and log access for auditability. Rotate credentials and monitor anomalous usage.

FAQ — Using Crypto APIs

Q: How do I get started with crypto or market data APIs?

A: Begin by identifying the data you need (prices, order books, on-chain events), locate providers with clear documentation and sample code, test endpoints in a sandbox, and account for latency and historical coverage. Combining raw feeds with analytics tools can help accelerate research.

FAQ — API Keys and Rate Limits

Q: What is an API key and why are rate limits important?

A: An API key is a token that identifies and authenticates a client. Rate limits prevent abuse and keep shared services stable—exceeding limits typically returns 429 errors and may incur additional costs or temporary blocks.

Disclaimer

This content is for informational and educational purposes only. It does not constitute investment, legal, tax, or professional advice. Evaluate tools, APIs, and services according to your own research and risk tolerance.

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