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Market Cap Weighting vs Equal Weight: Why Top 100 Indices Outperform in Volatile Markets

Explore why market cap-weighted Top 100 crypto indices consistently outperform equal-weighted approaches in volatile markets—using data-driven insights, index construction fundamentals, and practical analysis.
Token Metrics Team
10
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Crypto markets are famous for their rapid swings and unpredictable conditions, making how you construct a portfolio especially critical. The debate between market cap weighting and equal weighting in constructing crypto indices has grown louder as the number of digital assets surges and volatility intensifies. Understanding these methodologies isn’t just academic—it fundamentally affects how portfolios respond during major upswings and downturns, and reveals why broad Top 100 indices consistently deliver different results than more concentrated or equally weighted approaches.

Introduction to Index Weighting

Index weighting determines how an index or portfolio reflects the value and performance of its constituents. Market cap weighting assigns higher weights to larger assets, closely mirroring the aggregate value distribution in the market—so leading tokens like Bitcoin and Ethereum impact the index more significantly. In contrast, equal weighting grants every asset the same allocation, regardless of size, offering a more democratized but risk-altered exposure. Recognizing these differences is fundamental to how risk, diversification, and upside potential manifest within an index, and to how investors participate in the growth trajectory of both established and up-and-coming crypto projects.

Market Cap Weighting Explained: Following Market Consensus

Market cap weighting is a methodology that allocates index proportions according to each asset’s market capitalization—bigger assets, by value, represent a greater portion in the index. For instance, in a Top 100 market cap-weighted index, Bitcoin could make up more than half the portfolio, followed by Ethereum, while the remaining tokens are weighted in line with their market caps.

This approach naturally adjusts as prices and sentiment shift: assets rising in value get larger weights, while those declining are reduced automatically. It removes subjective bias and reflects market consensus, because capitalization is a product of price and token supply, responding directly to market dynamics.

Token Metrics’ TM Global 100 Index is a strong example of advanced market cap weighting tailored to crypto. This index goes beyond mere size by filtering for quality through AI-derived grades—evaluating momentum and long-term fundamentals from over 80 data points. Each week, the index rebalances: new leaders enter, underperformers exit, and proportions adapt, ensuring continuous adaptation to the current market structure. The result is a strategy that, like broad-based indices in traditional equities, balances widespread exposure and efficient updates as the crypto landscape evolves.

Equal Weighting Explained: Democratic Allocation

Equal weighting gives the same allocation to each index constituent, regardless of its market cap. Thus, in an equal-weighted Top 100 index, a newly launched token and a multi-billion-dollar asset both make up 1% of the portfolio. The intention is to provide all assets an equal shot at impacting returns, potentially surfacing emerging opportunities that traditional weighting may overlook.

This approach appeals to those seeking diversification unconstrained by market size and is featured in products like the S&P Cryptocurrency Top 10 Equal Weight Index. In traditional finance and crypto alike, equal weighting offers a different pattern of returns and risk, putting more emphasis on smaller and emerging assets and deviating from market cap heavy concentration.

The Volatility Performance Gap: Why Market Cap Wins

Empirical research and live market experience reveal that during high volatility, Top 100 market cap-weighted indices tend to outperform equal-weighted alternatives. Key reasons include:

  • Automatic Risk Adjustment: As prices fall, particularly for small caps, their market cap—and thus their weight—shrinks. The index reduces exposure naturally, mitigating the impact of the worst performers. Equal weighting, conversely, maintains exposure through rebalancing, meaning losses from declining assets can be compounded.
  • Liquidity Focus: In turbulent periods, trading activity and liquidity typically concentrate in larger assets. Market cap indices concentrate exposure where liquidity is highest, avoiding excessive trading costs. Equal-weighted strategies must buy and sell in less liquid assets, exposing portfolios to higher slippage and trading costs.
  • Volatility Drag: Equal weighting can lock portfolios into frequent reallocations and face "volatility drag," where assets with wild swings undermine cumulative returns. Market cap approaches allow losers and winners to move more organically, reducing forced transactions.
  • Correlation Surge: As overall market stress increases, assets move more in sync, reducing the theoretical diversification benefit of equal weighting. Analytical data—including insights from Token Metrics—shows that correlation spikes increase downside risk in equal-weighted portfolios that hold more high-volatility assets.

The Top 100 Advantage: Breadth Without Excessive Complexity

Why use 100 constituents? The Top 100 format achieves a practical balance between breadth and manageability. It captures a full cross-section of the crypto universe, allowing exposure to leading narratives and innovations, from AI tokens to Real-World Assets (RWAs), as demonstrated repeatedly throughout recent crypto cycles.

Research from Token Metrics highlights that Top 100 indices regularly outperform more concentrated Top 10 indices, thanks in large part to diversified participation in mid-caps following current narratives. The structure enables timely adaptation as capital and attention shift, while the weekly rebalance limits excessive trading.

Operationally, equal weighting becomes logistically complex with 100 assets—it demands near-constant buying and selling as each asset’s price changes. Market cap weighting, meanwhile, achieves most rebalancing automatically via price movement, minimizing execution costs and slippage risk.

Active Factor Risk Consideration

Active factor risk describes how certain characteristics—such as size, sector, or style—can disproportionately impact portfolio returns. Market cap weighting naturally leans toward large caps and leading sectors, making portfolios sensitive to concentration in just a few dominant names. Equal weighting dilutes this, granting more space to smaller, sometimes riskier assets, and can help offset sector concentration. Understanding these dynamics helps portfolio builders balance the trade-offs between diversification, risk, and performance objectives, and highlights the importance of methodological transparency in index design.

When Equal Weighting Makes Sense: The Exception Cases

While market cap weighting often excels in volatile conditions, equal weighting can be appropriate in specific situations:

  • Small, Stable Universes: Indexes tracking just a couple of mega-cap assets (e.g., Bitcoin and Ethereum) can use equal weighting to avoid over-concentration without rebalancing becoming unwieldy.
  • Conviction in Mid-Caps: If analysts strongly believe that mid-cap assets are poised to outperform, equal weighting can intentionally overweight them compared to a cap-weighted approach, though this is an active rather than passive bet.
  • Bull Market Rallies: In sustained, high-correlation upswings, equal weighting may capture upside from small and mid-caps that experience outsized gains. However, these periods are less common in crypto’s turbulent history.

It is crucial to recognize that equal weighting is not fundamentally lower in risk—it simply shifts risk to different parts of the token universe.

Token Metrics’ Intelligent Implementation

Token Metrics integrates multiple layers of process innovation into the market cap weighted paradigm:

  • AI-Powered Filtering: Projects receive scores for both short-term momentum and long-term fundamentals, excluding assets with artificially inflated caps or dubious quality.
  • Regime Switching: Proprietary indicators identify macro bull or bear phases, adapting the index’s allocation towards risk-off assets when appropriate.
  • Optimized Rebalancing: Weekly updates balance responsiveness and cost efficiency, unlike daily or bi-weekly schemes that may increase trading expenses.
  • Transparency: Users can view holdings, rebalancing logs (including associated fees), and methodology, supporting operational clarity and trust.

The Mathematical Reality: Expected Value in Volatile Markets

Market cap weighting’s core advantage is its mathematical fit for volatile markets:

  • Compounding Winners: Assets on a growth trajectory automatically gain additional index weight, reinforcing positive momentum and compounding returns.
  • Reducing Losers: Projects declining in value are swiftly de-prioritized, reducing their drag on the overall portfolio and sidestepping repeated reinvestment in underperformers.
  • Lower Transaction Costs: Because market cap indices require fewer forced trades, especially amid volatility, the cost of index maintenance is consistently reduced compared to equal-weighted alternatives.

Practical Implications for Investors

For those seeking systematic exposure to the digital asset market—regardless of whether they adopt an active or passive approach—the data leans toward broad, market cap-weighted Top 100 methodologies. These strategies enable:

  • Risk-Adjusted Performance: Improved Sharpe ratios, as exposure aligns with the risk-reward profiles present in the market ecosystem.
  • Operational Simplicity: Fewer required adjustments, manageable trade sizes, and streamlined operational execution.
  • Behavioral Discipline: Avoiding emotional rebalancing or systematic reinvestment in declining assets.
  • Scalability: The model accommodates growth in assets under management without running into liquidity barriers posed by small-cap constituents.

The TM Global 100 Index by Token Metrics embodies these features—melding market cap logic with quality assessment, modern rebalancing, regime-aware management, and transparency for users of all expertise levels. Parallels with traditional equity indexing further validate these approaches as effective in a range of asset classes.

Conclusion: Methodology Matches Market Reality

The consistent outperformance of market cap-weighted Top 100 indices is the result of a methodology attuned to crypto’s structural realities. By tracking consensus, managing drawdowns, enabling liquidity, and reducing unnecessary trading, market cap weighting provides a systematic defense against the chaos of volatile markets.

Contemporary implementations, such as those from Token Metrics, optimize these benefits through AI-backed analytics, smart rebalancing, and rigorous quality metrics—delivering robust and scalable exposure for institutional and retail users alike. In crypto, where sharp volatility and fast-evolving narratives are the norm, index construction methodology truly determines which approaches endure through all market cycles.

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FAQ: What is market cap weighting in crypto indices?

Market cap weighting means each constituent’s index representation is proportional to its market value. In practice, this gives larger, more established crypto assets greater influence over index returns. This approach tracks aggregate market sentiment and adjusts automatically as prices move.

FAQ: How does equal weighting differ from market cap weighting?

Equal weighting assigns each asset the same index share, no matter its relative size. While this offers exposure to smaller projects, it increases both diversification and the risk associated with less-established, and often more volatile, tokens. Unlike market cap weighting, it does not adjust based on market value dynamics.

FAQ: Why do market cap-weighted Top 100 indices outperform in volatile markets?

In volatile conditions, market cap weighting reduces portfolio exposure to sharply declining, illiquid, or high-risk tokens, while equal weighting requires ongoing investments in assets regardless of their decline. This difference in automatic risk reduction, transaction costs, and compounding effect yields stronger downside protection and risk-adjusted results.

FAQ: Does equal weighting ever outperform market cap weighting?

Equal weighting can outperform during certain sustained bull markets or in small, stable universes where concentrated risk is a concern. However, over longer periods and during volatility spikes, its frequent rebalancing and mid-cap emphasis usually result in higher risk and potentially lower net returns.

FAQ: How does Token Metrics enhance crypto index construction?

Token Metrics blends market cap weighting with AI-based quality filtering, adaptive rebalancing based on market regimes, and full transparency on holdings and methodology. This modern approach aims to maximize exposure to high-potential tokens while managing drawdown and operational risks.

Disclaimer

This article is for informational and educational purposes only and does not constitute investment, financial, or trading advice. Cryptocurrency markets are highly volatile and subject to rapid change. Readers should conduct their own research and consult professional advisors before making any investment decisions. Neither the author nor Token Metrics guarantees the accuracy, completeness, or reliability of the information provided herein.

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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.
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Recent Posts

Research

Python Quick-Start with Token Metrics: The Ultimate Crypto Price API

Token Metrics Team
10 min

If you’re a Python developer looking to build smarter crypto apps, bots, or dashboards, you need two things: reliable data and AI-powered insights. The Token Metrics API gives you both. In this tutorial, we’ll show you how to quickly get started using Token Metrics as your Python crypto price API, including how to authenticate, install the SDK, and run your first request in minutes.

Whether you’re pulling live market data, integrating Trader Grades into your trading strategy, or backtesting with OHLCV data, this guide has you covered.

🚀 Quick Setup for Developers in a Hurry

Install the official Token Metrics Python SDK:

pip install tokenmetrics

Or if you prefer working with requests directly, no problem. We’ll show both methods below.

🔑 Step 1: Generate Your API Key

Before anything else, you’ll need a Token Metrics account.

  1. Go to app.tokenmetrics.com/en/api
  2. Log in and navigate to the API Keys Dashboard
  3. Click Generate API Key
  4. Name your key (e.g., “Development”, “Production”)
  5. Copy it immediately — keep it secret.

You can monitor usage, rate limits, and quotas right from the dashboard. Track each key’s status, last used date, and revoke access at any time.

📈 Step 2: Retrieve Crypto Prices in Python

Here’s a simple example to fetch the latest price data for Ethereum (ETH):

import requests

API_KEY = "YOUR_API_KEY"

headers = {"x-api-key": API_KEY}

url = "https://api.tokenmetrics.com/v2/daily-ohlcv?symbol=ETH&startDate=<YYYY-MM-DD>&endDate=<YYYY-MM-DD>"

response = requests.get(url, headers=headers)

data = response.json()

for candle in data['data']:

    print(f"Date: {candle['DATE']} | Close: ${candle['CLOSE']}")

You now have a working python crypto price API pipeline. Customize startDate or endDate to get specific range of historical data.

📊 Add AI-Powered Trader Grades

Token Metrics’ secret sauce is its AI-driven token ratings. Here’s how to access Trader Grades for ETH:

grade_url = "https://api.tokenmetrics.com/v2/trader-grades?symbol=ETH&limit=30d"

grades = requests.get(grade_url, headers=headers).json()['data']

for day in grades:

    print(f"{day['DATE']} — Trader Grade: {day['TA_GRADE']}")

Use this data to automate trading logic (e.g., enter trades when Grade > 85) or overlay on charts.

🔁 Combine Data for Backtesting

Want to test a strategy? Merge OHLCV and Trader Grades for any token:

import pandas as pd

ohlcv_df = pd.DataFrame(data['data'])

grades_df = pd.DataFrame(grades)

combined_df = pd.merge(ohlcv_df, grades_df, on="DATE")

print(combined_df.head())

Now you can run simulations, build analytics dashboards, or train your own models.

⚙️ Endpoint Coverage for Python Devs

  • /daily-ohlcv: Historical price data
  • /trader-grades: AI signal grades (0–100)
  • /trading-signals: Bullish/Bearish signals for short and long positions.
  • /sentiment: AI-modeled sentiment scores
  • /tmai: Ask questions in plain English

All endpoints return structured JSON and can be queried via requests, axios, or any modern client.

🧠 Developer Tips

  • Each request = 1 credit (tracked in real time)
  • Rate limits depend on your plan (Free = 1 req/min)
  • Use the API Usage Dashboard to monitor and optimize
  • Free plan = 5,000 calls/month — perfect for testing and building MVPs

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You can reduce your API bill by up to 35% by staking and paying with Token Metrics’ native token, $TMAI. Available via the settings → payments page.

🌐 Final Thoughts

If you're searching for the best python crypto price API with more than just price data, Token Metrics is the ultimate choice. It combines market data with proprietary AI intelligence, trader/investor grades, sentiment scores, and backtest-ready endpoints—all in one platform.

✅ Real-time & historical data
✅ RESTful endpoints
✅ Python-ready SDKs and docs
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Start building today → tokenmetrics.com/api

Looking for SDK docs? Explore the full Python Quick Start Guide

Research

Crypto API to Google Sheets in 5 Minutes: How to Use Token Metrics API with Apps Script

Token Metrics Team
6 min

If you're a trader, data analyst, or crypto enthusiast, chances are you've wanted to pull live crypto data directly into Google Sheets. Whether you're tracking prices, building custom dashboards, or backtesting strategies, having real-time data at your fingertips can give you an edge.

In this guide, we'll show you how to integrate the Token Metrics API — a powerful crypto API with free access to AI-powered signals — directly into Google Sheets in under 5 minutes using Google Apps Script.

📌 Why Use Google Sheets for Crypto Data?

Google Sheets is a flexible, cloud-based spreadsheet that:

  • Requires no coding to visualize data
  • Can be shared and updated in real time
  • Offers formulas, charts, and conditional formatting
  • Supports live API connections with Apps Script

When combined with the Token Metrics API, it becomes a powerful dashboard that updates live with Trader Grades, Bull/Bear Signals, historical OHLCV data, and more.

🚀 What Is Token Metrics API?

The Token Metrics API provides real-time and historical crypto data powered by AI. It includes:

  • Trader Grade: A score from 0 to 100 showing bullish/bearish potential
  • Bull/Bear Signal: A binary signal showing market direction
  • OHLCV: Open-High-Low-Close-Volume price history
  • Token Metadata: Symbol, name, category, market cap, and more

The best part? The free Basic Plan includes:

  • 5,000 API calls/month
  • Access to core endpoints
  • Hourly data refresh
  • No credit card required

👉 Sign up for free here

🛠️ What You’ll Need

  • A free Token Metrics API key
  • A Google account
  • Basic familiarity with Google Sheets

⚙️ How to Connect Token Metrics API to Google Sheets

Here’s how to get live AI-powered crypto data into Sheets using Google Apps Script.

🔑 Step 1: Generate Your API Key

  1. Visit: https://app.tokenmetrics.com/en/api
  2. Click “Generate API Key”
  3. Copy it — you’ll use this in the script

📄 Step 2: Create a New Google Sheet

  1. Go to Google Sheets
  2. Create a new spreadsheet
  3. Click Extensions > Apps Script

💻 Step 3: Paste This Apps Script

const TOKEN_METRICS_API_KEY = 'YOUR_API_KEY_HERE';

async function getTraderGrade(symbol) {

  const url = `https://api.tokenmetrics.com/v2/trader-grades?symbol=${symbol.toUpperCase()}`;

  const options = {

    method: 'GET',

    contentType: 'application/json',

    headers: {

      'accept': 'application/json',

      'x-api-key': TOKEN_METRICS_API_KEY,

    },

    muteHttpExceptions: true

  };

  

  const response = UrlFetchApp.fetch(url, options);

  const data = JSON.parse(response.getContentText() || "{}")

  

  if (data.success && data.data.length) {

    const coin = data.data[0];

    return [

      coin.TOKEN_NAME,

      coin.TOKEN_SYMBOL,

      coin.TA_GRADE,

      coin.DATE

    ];

  } else {

    return ['No data', '-', '-', '-'];

  }

}

async function getSheetData() {

  const sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();

  const symbols = sheet.getRange('A2:A').getValues().flat().filter(Boolean);

  const results = [];

  results.push(['Name', 'Symbol', 'Trader Grade', 'Date']);

  for (const symbol of symbols) {

    if (symbol) {

      const row = await getTraderGrade(symbol);

      results.push(row);

    }

  }

  sheet.getRange(2, 2, results.length, results[0].length).setValues(results);

}

🧪 Step 4: Run the Script

  1. Replace 'YOUR_API_KEY_HERE' with your real API key.
  2. Save the project as TokenMetricsCryptoAPI.
  3. In your sheet, enter a list of symbols (e.g., BTC, ETH, SOL) in Column A.
  4. Go to the script editor and run getSheetData() from the dropdown menu.

Note: The first time, Google will ask for permission to access the script.

✅ Step 5: View Your Live Data

After the script runs, you’ll see:

  • Coin name and symbol
  • Trader Grade (0–100)
  • Timestamp

You can now:

  • Sort by Trader Grade
  • Add charts and pivot tables
  • Schedule automatic updates with triggers (e.g., every hour)

🧠 Why Token Metrics API Is Ideal for Google Sheets Users

Unlike basic price APIs, Token Metrics offers AI-driven metrics that help you:

  • Anticipate price action before it happens
  • Build signal-based dashboards or alerts
  • Validate strategies against historical signals
  • Keep your data fresh with hourly updates

And all of this starts for free.

🏗️ Next Steps: Expand Your Sheet

Here’s what else you can build:

  • A portfolio tracker that pulls your top coins’ grades
  • A sentiment dashboard using historical OHLCV
  • A custom screener that filters coins by Trader Grade > 80
  • A Telegram alert system triggered by Sheets + Apps Script + Webhooks

You can also upgrade to the Advanced Plan to unlock 21 endpoints including:

  • Investor Grades
  • Smart Indices
  • Sentiment Metrics
  • Quantitative AI reports
  • 60x API speed

🔐 Security Tip

Never share your API key in a public Google Sheet. Use script-level access and keep the sheet private unless required.

🧩 How-To Schema Markup (for SEO)

{

  "@context": "https://schema.org",

  "@type": "HowTo",

  "name": "Crypto API to Google Sheets in 5 Minutes",

  "description": "Learn how to connect the Token Metrics crypto API to Google Sheets using Google Apps Script and get real-time AI-powered signals and prices.",

  "totalTime": "PT5M",

  "supply": [

    {

      "@type": "HowToSupply",

      "name": "Google Sheets"

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    {

      "@type": "HowToSupply",

      "name": "Token Metrics API Key"

    }

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  "tool": [

    {

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      "name": "Google Apps Script"

    }

  ],

  "step": [

    {

      "@type": "HowToStep",

      "name": "Get Your API Key",

      "text": "Sign up at Token Metrics and generate your API key from the API dashboard."

    },

    {

      "@type": "HowToStep",

      "name": "Create a New Google Sheet",

      "text": "Open a new sheet and list crypto symbols in column A."

    },

    {

      "@type": "HowToStep",

      "name": "Add Apps Script",

      "text": "Go to Extensions > Apps Script and paste the provided code, replacing your API key."

    },

    {

      "@type": "HowToStep",

      "name": "Run the Script",

      "text": "Execute the getSheetData function to pull data into the sheet."

    }

  ]

}

✍️ Final Thoughts

If you're serious about crypto trading or app development, integrating live market signals into your workflow can be a game-changer. With the Token Metrics API, you can get institutional-grade AI signals — right inside Google Sheets.

This setup is simple, fast, and completely free to start. Try it today and unlock a smarter way to trade and build in crypto.

👉 Get Your API Key & Start for Free

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Token Metrics Team
5 min

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