Back to blog
Research

Generating Passive Income with Token Metrics AI Indices: Beyond Capital Appreciation to Consistent Yield

Explore how Token Metrics AI Indices enable passive crypto income, blending staking, DeFi, and risk management for consistent yield beyond capital appreciation.
Token Metrics Team
10 min read
Want Smarter Crypto Picks—Free?
See unbiased Token Metrics Ratings for BTC, ETH, and top alts.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
 No credit card | 1-click unsubscribe

The landscape of cryptocurrency investing is changing. For many years, the focus remained solely on speculation and price appreciation—the legendary 'number go up' mindset.

Now, innovative protocols and platforms are turning crypto into an income-generating asset class, creating new opportunities for systematic, sustainable yield. Understanding this shift is crucial for anyone seeking more than just capital gains from their crypto portfolios.

Understanding Cryptocurrency Passive Income Sources

Staking is one primary way to earn crypto income. It involves locking up tokens to support a blockchain network's operation and security.

Stakers receive newly minted tokens in return, with yields depending on each network.

Major stakable cryptocurrencies include:

• Ethereum (post-Merge), yielding roughly 3-5% annually
• Cardano (ADA), with 4-6% rewards
• Solana (SOL), at 6-8% yields
• Polkadot (DOT), returning 10-14%
• Cosmos (ATOM), providing 15-20% rewards

Staking provides predictable returns and aligns incentives for network security. There’s also no risk of impermanent loss, unlike liquidity provision.

However, stakers face lock-up periods, possible slashing due to validator misbehavior, and variable yields based on participation rates.

For DeFi lending, platforms like Aave, Compound, and MakerDAO allow crypto holders to lend tokens, earning interest like a traditional bond.

Stablecoins typically generate 2-8% annually, while more volatile assets could see 1-4%, climbing higher during periods of high demand.

Flexible liquidity, diversified asset options, and auto-reinvesting are benefits. Risks include smart contract vulnerabilities, liquidity crunches, and protocol insolvency.

Liquidity provision lets users earn trading fees for supplying pairs to AMMs such as Uniswap, SushiSwap, or PancakeSwap.

Major trading pairs could earn 5-20% annually, but more exotic token pools might offer far higher returns—alongside greater risks.

The largest risk is impermanent loss, which can sometimes outpace fee earnings during high volatility.

Yield aggregators (like Yearn Finance) enable hands-off income by algorithmically finding the highest DeFi yields and managing strategies on users' behalf.

This brings optimization and gas savings but also adds further smart contract risk and possible tax complexity.

Building a Passive Income Strategy with Token Metrics

Constructing an income-oriented portfolio means balancing yield generation, capital preservation, and growth.

A typical allocation through Token Metrics might use 40-50% in staking assets (such as ETH, ADA, SOL, DOT), 30-40% in stablecoin lending, 10-20% in liquidity provision, and a modest 0-10% in higher-risk yield farming.

This strategy emphasizes stability and sustainability while still benefiting from capital gains and yield variety.

Yield stacking is a tactic where investors combine multiple yield streams from a single holding, such as staking ETH, then lending staked ETH derivatives for an added yield layer.

This can boost total income but may add complexity or stacked risk, so each layer should be carefully evaluated.

Sustainable yields are derived from real economic activity. In contrast, 'unsustainable' yields are often backed only by new token issuance, which can erode value over time.

Token Metrics AI distinguishes between these by analyzing protocol revenues, yield sources, and token supply dynamics.

Risk Management for Income-Generating Strategies

Smart contract risk is inherent in DeFi income opportunities.

Token Metrics emphasizes diversification across multiple audited protocols, focusing on established providers, and monitoring for new vulnerabilities.

Even with robust precautions, only risk amounts you are prepared to lose entirely in DeFi protocols.

Counterparty and protocol risk also merit attention. Market disruptions can challenge protocol solvency, especially during periods of stress or volatile price swings.

Token Metrics mitigates these exposures by selecting over-collateralized protocols, monitoring reserve funds, managing exposure, and stress-testing scenarios.

Impermanent loss is a key risk for liquidity providers.

The platform favors strategies with highly correlated pairs, sustainable fee offsets, and appropriate allocation size to contain exposure.

Crypto income also brings complex tax obligations. Each yield event (staking, lending, fees) typically triggers a taxable moment, and detailed record-keeping is critical.

Get Started For Free

Token Metrics Indices for Income Generation

Large-Cap Staking Indices:
Token Metrics offers indices focused on leading Proof-of-Stake assets, blending potential appreciation with steady yields. These strategies spotlight established networks, optimize staking selections, and help manage liquidity and risk.

For income-oriented investors, these can provide stable 4-8% annual yields with less downside than purely growth-weighted options—but still more volatility than many traditional products.

DeFi Yield Indices:
Specifically designed to capture lending, liquidity, and aggregation yield opportunities, these indices diversify across protocols and systematically rebalance for optimal results.

They suit those comfortable with DeFi risks and desiring enhanced yield potential (10-20%+ in favorable markets).

Balanced Income and Growth Indices:
Balancing income generators with growth tokens, these indices typically split allocations—for example 60% in appreciation assets, 40% in income-producing holdings.

Moderate yields (3-7%) are common, combining growth upside and consistent cash flow.

Practical Implementation: From Strategy to Income

Calculating the yield required for income goals is a vital first step. For example, a $1,000,000 portfolio targeting $50,000 annual income requires a 5% yield, while a $500,000 portfolio would require an unsustainable 10%.

Staking can be approached through:

• Direct staking (most technical, highest yields)
• Delegated staking (third-party validators for ease)
• Liquid staking (protocols like Lido for flexibility)

Token Metrics provides tailored advice to optimize staking approach by asset, reflecting yields, lock-up, and user preferences.

Cash flow and reinvestment must be planned systematically—decide withdrawal frequency, reinvestment amounts, tax withholding, and rebalance as life stages shift.

Most investors reinvest during accumulation, then increase withdrawals for retirement or income phases. Token Metrics indices can adapt dynamic allocations accordingly.

Ongoing monitoring is essential. Quarterly reviews of protocol health, comparative yield checks, and timely rebalancing help maintain income sustainability.

Token Metrics’ analytics automate much of this ongoing assessment, flagging notable changes for user action.

Real-World Income Scenarios

Scenario 1 – Supplemental Income:
An employed professional with $300,000 in crypto seeks $1,000-$2,000 monthly and moderate risk. The strategy could include 60% large-cap staking, 30% stablecoin lending, and 10% conservative DeFi, targeting a blended 5-7% annual return.

Scenario 2 – Early Retirement:
A 50-year-old with $1,500,000 in crypto aims for $75,000 per year in five years, with moderate/aggressive risk. A balanced index (50%), DeFi yield index (30%), and large-cap staking (20%) could target a 6-8% yield, blended with capital withdrawals if necessary.

Scenario 3 – Financial Independence:
A 35-year-old with $750,000 targets future independence and a $100,000 annual income. Aggressive growth indices (70%) and DeFi yield indices (30%) may be optimal, directing all current income back into the portfolio for compounding.

Avoiding Passive Income Pitfalls

Chasing extremely high yields—especially anything above 100%—is the most common misstep among crypto income investors.

Token Metrics systematically screens out these unsustainable offers, instead prioritizing protocols delivering steady, real-economic yields within a safer range.

Focusing excessively on yield without regard to principal protection is another risk. A high yield does not compensate if the asset’s underlying value declines sharply. Total return—combining appreciation and income—is always the bigger picture.

DeFi risks are often correlated. What appears diversified may not truly diversify portfolio risk if protocols are tightly connected.

Token Metrics manages this by combining blockchains (e.g., Ethereum, Solana, Avalanche), different income methods, and balancing DeFi with non-DeFi assets for true diversification.

Building Sustainable Passive Income Through Intelligent Crypto Strategies

The maturation of crypto investing delivers new paths toward passive income, not just speculative growth. Thoughtful strategy and risk management are key.

Focus on yields from genuine activity, diversify smartly, and continuously revisit portfolio allocations as conditions change.

Token Metrics AI Indices offer systematic portfolio tools and research for pursuing income. The platform's AI filters opportunities by sustainability, automates complex allocations, and keeps investors informed about evolving protocols and industry risk.

Whether you aim for supplemental income, long-term wealth, or full financial independence, smart use of these tools now puts the future of passive crypto income within reach.

FAQ: Passive Income with Crypto Indices

What is the difference between staking and DeFi lending?

Staking means locking tokens to support a network and earn newly minted rewards, usually tied to Proof-of-Stake blockchains.

DeFi lending involves providing assets to protocols where borrowers pay interest. Staking supports network operations, while lending acts like digital banking for earners.

Are crypto passive income yields guaranteed?

No, crypto yields are never guaranteed.

Returns depend on protocol economics, market demand, and potential risks, including smart contract issues and overall market volatility.

How can Token Metrics help manage income risk?

Token Metrics evaluates and monitors thousands of protocols, rates their risk, analyzes yield sources, and helps users systematically diversify across many strategies to lessen risk.

What tax documentation does generating crypto income require?

Each yield event (staking, lending, liquidity provision) may trigger taxable income, which must be reported where required by law.

Keeping careful records and seeking guidance from a crypto-specialized tax expert is strongly advised.

Which income strategies are most sustainable?

Sustainable income derives from real network use like transaction fees, security rewards, or legitimate borrowing. The most sustainable avenues are usually staking on established blockchains and selectively vetted lending platforms.

Very high yields backed by token inflation, rather than real use, are generally less sustainable.

Get Started For Free

Disclaimer

This blog is for educational and informational purposes. It does not constitute financial, investment, or tax advice.

Cryptocurrency markets are volatile and carry risk. Always conduct your own due diligence and seek independent advice before acting on any information provided herein.

Build Smarter Crypto Apps &
AI Agents in Minutes, Not Months
Real-time prices, trading signals, and on-chain insights all from one powerful API.
Grab a Free API Key
About Token Metrics
Token Metrics: AI-powered crypto research and ratings platform. We help investors make smarter decisions with unbiased Token Metrics Ratings, on-chain analytics, and editor-curated “Top 10” guides. Our platform distills thousands of data points into clear scores, trends, and alerts you can act on.
30 Employees
analysts, data scientists, and crypto engineers
Daily Briefings
concise market insights and “Top Picks”
Transparent & Compliant
Sponsored ≠ Ratings; research remains independent
Want Smarter Crypto Picks—Free?
See unbiased Token Metrics Ratings for BTC, ETH, and top alts.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
 No credit card | 1-click unsubscribe
Token Metrics Team
Token Metrics Team

Recent Posts

Research

Support and Resistance API: Auto-Calculate Smart Levels for Better Trades

Token Metrics Team
4

Most traders still draw lines by hand in TradingView. The support and resistance API from Token Metrics auto-calculates clean support and resistance levels from one request, so your dashboard, bot, or alerts can react instantly. In minutes, you’ll call /v2/resistance-support, render actionable levels for any token, and wire them into stops, targets, or notifications. Start by grabbing your key on Get API Key, then Run Hello-TM and Clone a Template to ship a production-ready feature fast.

What You’ll Build in 2 Minutes

A minimal script that fetches Support/Resistance via /v2/resistance-support for a symbol (e.g., BTC, SOL).

  • A one-liner curl to smoke-test your key.
  • A UI pattern to display nearest support, nearest resistance, level strength, and last updated time.

Next Endpoints to add

  • /v2/trading-signals (entries/exits)
  • /v2/hourly-trading-signals (intraday updates)
  • /v2/tm-grade (single-score context)
  • /v2/quantmetrics (risk/return framing)

Why This Matters

Precision beats guesswork. Hand-drawn lines are subjective and slow. The support and resistance API standardizes levels across assets and timeframes, enabling deterministic stops and take-profits your users (and bots) can trust.

Production-ready by design. A simple REST shape, predictable latency, and clear semantics let you add levels to token pages, automate SL/TP alerts, and build rule-based execution with minimal glue code.

Where to Find

Need the Support and Resistance data? The cURL request for it is in the top right of the API Reference for quick access.

👉 Keep momentum: Get API Key • Run Hello-TM • Clone a Template

How It Works (Under the Hood)

The Support/Resistance endpoint analyzes recent price structure to produce discrete levels above and below current price, along with strength indicators you can use for priority and styling. Query /v2/resistance-support?symbol=<ASSET>&timeframe=<HORIZON> to receive arrays of level objects and timestamps.

Polling vs webhooks. For dashboards, short-TTL caching and batched fetches keep pages snappy. For bots and alerts, use queued jobs or webhooks (where applicable) to avoid noisy, bursty polling—especially around market opens and major events.

Production Checklist

  • Rate limits: Respect plan caps; add client-side throttling.
  • Retries/backoff: Exponential backoff with jitter for 429/5xx; log failures.
  • Idempotency: Make alerting and order logic idempotent to prevent duplicates.
  • Caching: Memory/Redis/KV with short TTLs; pre-warm top symbols.
  • Batching: Fetch multiple assets per cycle; parallelize within rate limits.
  • Threshold logic: Add %-of-price buffers (e.g., alert at 0.3–0.5% from level).
  • Error catalog: Map common 4xx/5xx to actionable user guidance; keep request IDs.
  • Observability: Track p95/p99; measure alert precision (touch vs approach).
  • Security: Store API keys in a secrets manager; rotate regularly.

Use Cases & Patterns

  • Bot Builder (Headless): Use nearest support for stop placement and nearest resistance for profit targets. Combine with /v2/trading-signals for entries/exits and size via Quantmetrics (volatility, drawdown).
  • Dashboard Builder (Product): Add a Levels widget to token pages; badge strength (e.g., High/Med/Low) and show last touch time. Color the price region (below support, between levels, above resistance) for instant context.
  • Screener Maker (Lightweight Tools): “Close to level” sort: highlight tokens within X% of a strong level. Toggle alerts for approach vs breakout events.
  • Risk Management: Create policy rules like “no new long if price is within 0.2% of strong resistance.” Export daily level snapshots for audit/compliance.

Next Steps

  • Get API Key — generate a key and start free.
  • Run Hello-TM — verify your first successful call.
  • Clone a Template — deploy a levels panel or alerts bot today.
  • Watch the demo: Compare plans: Scale confidently with API plans.

FAQs

1) What does the Support & Resistance API return?

A JSON payload with arrays of support and resistance levels for a symbol (and optional timeframe), each with a price and strength indicator, plus an update timestamp.

2) How timely are the levels? What are the latency/SLOs?

The endpoint targets predictable latency suitable for dashboards and alerts. Use short-TTL caching for UIs, and queued jobs or webhooks for alerting to smooth traffic.

3) How do I trigger alerts or trades from levels?

Common patterns: alert when price is within X% of a level, touches a level, or breaks beyond with confirmation. Always make downstream actions idempotent and respect rate limits.

4) Can I combine levels with other endpoints?

Yes—pair with /v2/trading-signals for timing, /v2/tm-grade for quality context, and /v2/quantmetrics for risk sizing. This yields a complete decide-plan-execute loop.

5) Which timeframe should I use?

Intraday bots prefer shorter horizons; swing/position dashboards use daily or higher-timeframe levels. Offer a timeframe toggle and cache results per setting.

6) Do you provide SDKs or examples?

Use the REST snippets above (JS/Python). The docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.

7) Pricing, limits, and enterprise SLAs?

Begin free and scale as you grow. See API plans for rate limits and enterprise SLA options.

Disclaimer

This content is for educational purposes only and does not constitute financial advice. Always conduct your own research before making any trading decisions.

Research

Quantmetrics API: Measure Risk & Reward in One Call

Token Metrics Team
5

Most traders see price—quants see probabilities. The Quantmetrics API turns raw performance into risk-adjusted stats like Sharpe, Sortino, volatility, drawdown, and CAGR so you can compare tokens objectively and build smarter bots and dashboards. In minutes, you’ll query /v2/quantmetrics, render a clear performance snapshot, and ship a feature that customers trust. Start by grabbing your key at Get API Key, Run Hello-TM to verify your first call, then Clone a Template to go live fast.

What You’ll Build in 2 Minutes

  • A minimal script that fetches Quantmetrics for a token via /v2/quantmetrics (e.g., BTC, ETH, SOL).
  • A smoke-test curl you can paste into your terminal.
  • A UI pattern that displays Sharpe, Sortino, volatility, max drawdown, CAGR, and lookback window.

Next Endpoints to Add

  • /v2/tm-grade (one-score signal)
  • /v2/trading-signals
  • /v2/hourly-trading-signals (timing)
  • /v2/resistance-support (risk placement)
  • /v2/price-prediction (scenario planning)

Why This Matters

Risk-adjusted truth beats hype. Price alone hides tail risk and whipsaws. Quantmetrics compresses edge, risk, and consistency into metrics that travel across assets and timeframes—so you can rank universes, size positions, and communicate performance like a professional.

Built for dev speed

A clean REST schema, predictable latency, and easy auth mean you can plug Sharpe/Sortino into bots, dashboards, and screeners without maintaining your own analytics pipeline. Pair with caching and batching to serve fast pages at scale.

Where to Find

The Quant Metrics cURL request is located in the top right of the API Reference, allowing you to easily integrate it with your application.

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

How It Works (Under the Hood)

Quantmetrics computes risk-adjusted performance over a chosen lookback (e.g., 30d, 90d, 1y). You’ll receive a JSON snapshot with core statistics:

  • Sharpe ratio: excess return per unit of total volatility.
  • Sortino ratio: penalizes downside volatility more than upside.
  • Volatility: standard deviation of returns over the window.
  • Max drawdown: worst peak-to-trough decline.
  • CAGR / performance snapshot: geometric growth rate and best/worst periods.

Call /v2/quantmetrics?symbol=<ASSET>&window=<LOOKBACK> to fetch the current snapshot. For dashboards spanning many tokens, batch symbols and apply short-TTL caching. If you generate alerts (e.g., “Sharpe crossed 1.5”), run a scheduled job and queue notifications to avoid bursty polling.

Production Checklist

  • Rate limits: Understand your tier caps; add client-side throttling and queues.
  • Retries & backoff: Exponential backoff with jitter; treat 429/5xx as transient.
  • Idempotency: Prevent duplicate downstream actions on retried jobs.
  • Caching: Memory/Redis/KV with short TTLs; pre-warm popular symbols and windows.
  • Batching: Fetch multiple symbols per cycle; parallelize carefully within limits.
  • Error catalog: Map 4xx/5xx to clear remediation; log request IDs for tracing.
  • Observability: Track p95/p99 latency and error rates; alert on drift.
  • Security: Store API keys in secrets managers; rotate regularly.

Use Cases & Patterns

  • Bot Builder (Headless): Gate entries by Sharpe ≥ threshold and drawdown ≤ limit, then trigger with /v2/trading-signals; size by inverse volatility.
  • Dashboard Builder (Product): Add a Quantmetrics panel to token pages; allow switching lookbacks (30d/90d/1y) and export CSV.
  • Screener Maker (Lightweight Tools): Top-N by Sortino with filters for volatility and sector; add alert toggles when thresholds cross.
  • Allocator/PM Tools: Blend CAGR, Sharpe, drawdown into a composite score to rank reallocations; show methodology for trust.
  • Research/Reporting: Weekly digest of tokens with Sharpe ↑, drawdown ↓, and volatility ↓.

Next Steps

  • Get API Key — start free and generate a key in seconds.
  • Run Hello-TM — verify your first successful call.
  • Clone a Template — deploy a screener or dashboard today.
  • Watch the demo: VIDEO_URL_HERE
  • Compare plans: Scale with API plans.

FAQs

1) What does the Quantmetrics API return?

A JSON snapshot of risk-adjusted metrics (e.g., Sharpe, Sortino, volatility, max drawdown, CAGR) for a symbol and lookback window—ideal for ranking, sizing, and dashboards.

2) How fresh are the stats? What about latency/SLOs?

Responses are engineered for predictable latency. For heavy UI usage, add short-TTL caching and batch requests; for alerts, use scheduled jobs or webhooks where available.

3) Can I use Quantmetrics to size positions in a live bot?

Yes—many quants size inversely to volatility or require Sharpe ≥ X to trade. Always backtest and paper-trade before going live; past results are illustrative, not guarantees.

4) Which lookback window should I choose?

Short windows (30–90d) adapt faster but are noisier; longer windows (6–12m) are steadier but slower to react. Offer users a toggle and cache each window.

5) Do you provide SDKs or examples?

REST is straightforward (JS/Python above). Docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.

6) Polling vs webhooks for quant alerts?

Dashboards usually use cached polling. For threshold alerts (e.g., Sharpe crosses 1.0), run scheduled jobs and queue notifications to keep usage smooth and idempotent.

7) Pricing, limits, and enterprise SLAs?

Begin free and scale up. See API plans for rate limits and enterprise SLA options.

Disclaimer

All information provided in this blog is for educational purposes only. It is not intended as financial advice. Users should perform their own research and consult with licensed professionals before making any investment or trading decisions.

Research

Crypto Trading Signals API: Put Bullish/Bearish Calls Right in Your App

Token Metrics Team
4

Timing makes or breaks every trade. The crypto trading signals API from Token Metrics lets you surface bullish and bearish calls directly in your product—no spreadsheet wrangling, no chart gymnastics. In this guide, you’ll hit the /v2/trading-signals endpoint, display actionable signals on a token (e.g., SOL, BTC, ETH), and ship a conversion-ready feature for bots, dashboards, or Discord. Start by creating a key on Get API Key, then Run Hello-TM and Clone a Template to go live fast.

What You’ll Build in 2 Minutes

  • A minimal script that fetches Trading Signals via /v2/trading-signals for one symbol (e.g., SOL).
  • A copy-paste curl to smoke-test your key.
  • A UI pattern to render signal, confidence/score, and timestamp in your dashboard or bot.

Endpoints to add next

  • /v2/hourly-trading-signals (intraday updates)
  • /v2/resistance-support (risk placement)
  • /v2/tm-grade (one-score view)
  • /v2/quantmetrics (risk/return context)

Why This Matters

Action over analysis paralysis. Traders don’t need more lines on a chart—they need an opinionated call they can automate. The trading signals API compresses technical momentum and regime reads into Bullish/Bearish events you can rank, alert on, and route into strategies.

Built for dev speed and reliability. A clean schema, predictable performance, and straightforward auth make it easy to wire signals into bots, dashboards, and community tools. Pair with short-TTL caching or webhooks to minimize polling and keep latency low.

Where to Find

You can find the cURL request for Crypto Trading Signals in the top right corner of the API Reference. Use it to access the latest signals!

Live Demo & Templates

  • Trading Bot Starter: Use Bullish/Bearish calls to trigger paper trades; add take-profit/stop rules with Support/Resistance.
  • Dashboard Signal Panel: Show the latest call, confidence, and last-updated time; add a history table for context.
  • Discord/Telegram Alerts: Post signal changes to a channel with a link back to your app.

How It Works (Under the Hood)

Trading Signals distill model evidence (e.g., momentum regimes and pattern detections) into Bullish or Bearish calls with metadata such as confidence/score and timestamp. You request /v2/trading-signals?symbol=<ASSET> and render the most recent event, or a small history, in your UI.

For intraday workflows, use /v2/hourly-trading-signals to update positions or alerts more frequently. Dashboards typically use short-TTL caching or batched fetches; headless bots lean on webhooks, queues, or short polling with backoff to avoid spiky API usage.

Production Checklist

  • Rate limits: Know your tier caps; add client-side throttling and queues.
  • Retries/backoff: Exponential backoff with jitter; treat 429/5xx as transient.
  • Idempotency: Guard downstream actions (don’t double-trade on retries).
  • Caching: Memory/Redis/KV with short TTLs for reads; pre-warm popular symbols.
  • Webhooks & jobs: Prefer webhooks or scheduled workers for signal change alerts.
  • Pagination/Bulk: Batch symbols; parallelize with care; respect limits.
  • Error catalog: Map common 4xx/5xx to clear fixes; log request IDs.
  • Observability: Track p95/p99 latency, error rate, and alert delivery success.
  • Security: Keep keys in a secrets manager; rotate regularly.

Use Cases & Patterns

  • Bot Builder (Headless): Route Bullish into candidate entries; confirm with /v2/resistance-support for risk and TM Grade for quality.
  • Dashboard Builder (Product): Add a “Signals” module per token; color-code state and show history for credibility.
  • Screener Maker (Lightweight Tools): Filter lists by Bullish state; sort by confidence/score; add alert toggles.
  • Community/Discord: Post signal changes with links to token pages; throttle to avoid noise.
  • Allocator/PM Tools: Track signal hit rates by sector/timeframe to inform position sizing (paper-trade first).

Next Steps

  1. Get API Key — create a key and start free.
  2. Run Hello-TM — confirm your first successful call.
  3. Clone a Template — deploy a bot, dashboard, or alerting tool today.

FAQs

1) What does the Trading Signals API return?

A JSON payload with the latest Bullish/Bearish call for a symbol, typically including a confidence/score and generated_at timestamp. You can render the latest call or a recent history for context.

2) Is it real-time? What about latency/SLOs?

Signals are designed for timely, programmatic use with predictable latency. For faster cycles, use /v2/hourly-trading-signals. Add caching and queues/webhooks to reduce round-trips.

3) Can I use the signals in a live trading bot?

Yes—many developers do. A common pattern is: Signals → candidate entry, Support/Resistance → stop/targets, Quantmetrics → risk sizing. Always backtest and paper-trade before going live.

4) How accurate are the signals?

Backtests are illustrative, not guarantees. Treat signals as one input in a broader framework with risk controls. Evaluate hit rates and drawdowns on your universe/timeframe.

5) Do you provide SDKs and examples?

You can integrate via REST using JavaScript and Python snippets above. The docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.

6) Polling vs webhooks for alerts?

Dashboards often use cached polling. For bots/alerts, prefer webhooks or scheduled jobs and keep retries idempotent to avoid duplicate trades or messages.

7) Pricing, limits, and enterprise SLAs?

Begin free and scale as you grow. See API plans for allowances; enterprise SLAs and support are available.

Choose from Platinum, Gold, and Silver packages
Reach with 25–30% open rates and 0.5–1% CTR
Craft your own custom ad—from banners to tailored copy
Perfect for Crypto Exchanges, SaaS Tools, DeFi, and AI Products