Research

Tracking Bitcoin’s Rise as a Macro Hedge with Token Metrics – The #1 Crypto Analytics Platform in 2025

Explore Bitcoin’s evolving role as a macro hedge in 2025 amid global uncertainty. Learn how crypto research tools like Token Metrics help investors track this shift.
Token Metrics Team
8 min
MIN

Bitcoin’s Role in a Shifting Global Financial Order

Bitcoin's relevance in global finance continues to evolve. In 2025, this evolution is accelerating as geopolitical tensions and economic uncertainties challenge traditional systems. While Bitcoin was once viewed as a fringe digital asset, it is increasingly being positioned as a strategic hedge—one that could play a central role in a future where fiat currencies, particularly reserve currencies, face structural strain.

This blog explores how current global dynamics are elevating Bitcoin’s role, not as a speculative trade, but as a macroeconomic signal.

Rising Geopolitical Tensions

Recent developments in the Middle East have drawn increased attention to the intersection of geopolitics and financial markets. Conflicts involving Iran, Israel, and broader regional tensions are no longer localized issues—they have global implications, especially when supply chains and energy flows are involved.

A scenario some analysts are exploring is a prolonged conflict that could last several years. If oil exports are disrupted, global inflation could spike. History tells us that war economies tend to create volatility, both in commodity markets and in currencies.

In such environments, hard assets often perform well. Gold has traditionally filled that role. But Bitcoin, with its fixed supply and decentralized infrastructure, is increasingly being viewed in a similar light.

Game Theory and the Incentive to Escalate

Several geopolitical analysts have recently applied game theory to understand current alignments. The thesis: multiple nations involved in ongoing conflicts have internal and external incentives that make prolonged conflict more likely than resolution.

From a market perspective, that introduces risk into the global economy—risk that can erode trust in fiat systems or centralized monetary authorities.

Bitcoin, by design, offers an alternative. It operates on a predictable schedule, outside the reach of any single government or bank. In times of instability, that predictability becomes an asset in itself.

Flight to Bitcoin in a Crisis?

The concept of a “flight to safety” is typically associated with sovereign bonds or gold. However, during recent events, Bitcoin has at times rallied when traditional risk assets fell—especially when the conflict narrative intersects with economic concerns.

In the event of a long-term geopolitical crisis, particularly one affecting the global reserve currency system, Bitcoin could see a significant re-rating. The logic is simple: a decentralized, non-sovereign asset becomes a hedge against sovereign instability.

This doesn’t mean Bitcoin is without risk—it remains volatile and speculative compared to traditional assets. But in extreme scenarios, such as currency devaluation or prolonged stagflation, Bitcoin’s use case as a financial escape valve becomes more compelling.

Bitcoin vs. the US Dollar

Some strategists now openly discuss the possibility that the dollar’s dominance may be structurally weakened in the years ahead. That doesn’t imply imminent collapse, but it does suggest the global financial order may be recalibrating.

Central bank digital currencies (CBDCs), the rise of alternative payment networks, and multipolar geopolitical tensions all point toward a future where reserve status is contested.

Bitcoin, by virtue of being neutral, borderless, and digitally native, offers a counterweight. While it’s unlikely to “replace” fiat in the near term, its role as a counter-reserve asset may expand.

Institutional Alignment Around Bitcoin

In parallel to these global developments, institutional alignment around Bitcoin continues. Several major financial entities have integrated Bitcoin exposure into their portfolios, launched products like ETFs, and begun building custody and trading infrastructure.

This shift is not ideological—it’s pragmatic. Institutions are increasingly treating Bitcoin not as a gamble, but as an uncorrelated hedge with asymmetric upside in macro-uncertain environments.

The key takeaway is that Bitcoin’s narrative is evolving from risk-on speculation to macro hedge. That shift changes how it's traded, valued, and held.

2026 and the Timing of a Possible PEAK

Interestingly, the projected peak of the current crypto cycle aligns with the timing of several geopolitical forecasts. Some macro analysts predict that major disruptions to the global economy could materialize by early 2026—just as Bitcoin historically tends to peak 12–18 months post-halving.

This alignment isn’t deterministic, but it’s suggestive. If geopolitical conflict escalates and monetary regimes are questioned, Bitcoin could benefit not from hype, but from its underlying design.

In such a scenario, estimates of Bitcoin reaching $250,000 or more—while speculative—are not purely fantasy. They reflect what could happen if Bitcoin becomes a globally recognized monetary hedge during a systemic macro reset.

Implications for Portfolio Construction

If these scenarios play out, they carry implications for crypto portfolios. Altcoins, which rely more on risk appetite and speculative narratives, may underperform in a risk-off, conflict-driven environment.

Bitcoin, conversely, may outperform as capital concentrates in the most liquid, battle-tested asset.

This doesn’t suggest abandoning altcoins entirely—but it does support the idea that Bitcoin may deserve a larger allocation than in previous cycles, especially as macro risks rise.

Risk, Resilience, and Reality

It’s important to acknowledge the counterarguments. Bitcoin’s volatility, regulatory uncertainty, and still-limited real-world use cases are valid concerns. No asset is invulnerable, and Bitcoin’s rise is not guaranteed.

Yet, amid systemic uncertainty, few assets offer the combination of digital mobility, fixed supply, and decentralization that Bitcoin does.

Whether or not a macro crisis unfolds as predicted, the world is clearly entering a phase where economic assumptions are being questioned. In that context, Bitcoin becomes not just an asset—but a signal.

Conclusion

Bitcoin’s role in the global economy is far from settled. But in 2025, it is clear that the asset is evolving beyond its original use case. No longer just a curiosity for early adopters, Bitcoin is increasingly part of the conversation among serious investors, analysts, and policymakers.

If the world moves toward greater uncertainty, more conflict, and more questioning of existing monetary systems, Bitcoin may be one of the few assets positioned to benefit—not because of speculation, but because of structural design.

To navigate this evolving landscape, investors need access to accurate, real-time macro signals—and that’s where tools like Token Metrics become indispensable. As a leading crypto research and analytics platform, Token Metrics helps investors track sentiment shifts, macro trends, and on-chain dynamics that may signal Bitcoin’s strengthening role in global finance.

It is not a prediction. It’s a possibility. One worth understanding—and preparing for with the right tools.

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
Token Metrics Team
Token Metrics Team

Recent Posts

Token Metrics API

Price Prediction API: Model Moon/Base/Bear Scenarios in Minutes

Sam Monac
5 min
MIN

Every trader wonders: how high could this token really go? The price prediction API from Token Metrics lets you explore Moon, Base, and Bear scenarios for any asset—grounded in market-cap assumptions like $2T, $8T, $16T and beyond. In this guide, you’ll call /v2/price-prediction, render scenario bands (with editable caps), and ship a planning feature your users will bookmark. Start by creating a key at 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 Price Predictions via /v2/price-prediction for any symbol (e.g., BTC, SUI).

  • A simple UI pattern showing Moon / Base / Bear ranges and underlying market-cap scenarios.

  • Optional one-liner curl to smoke-test your API key.

  • Endpoints to add next: /v2/tm-grade (quality context), /v2/trading-signals / /v2/hourly-trading-signals (timing), /v2/resistance-support (stop/target placement), /v2/quantmetrics (risk/return framing).

Why This Matters

Scenario planning beats guessing. Prices move, narratives change, but market-cap scenarios provide a common yardstick for upside/downside. With the price prediction API, you can give users transparent, parameterized ranges (Moon/Base/Bear) and the assumptions behind them—perfect for research, allocation, and position sizing.

Build investor trust. Pair scenario ranges with TM Grade (quality) and Quantmetrics (risk-adjusted performance) so users see both potential and risk. Add optional alerts when price approaches a scenario level to turn curiosity into action—without promising outcomes.

Where to Find 

Find the cURL request for Price Predictions in the top right corner of the API Reference. Use it to easily pull up predictions for your project.

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

Live Demo & Templates

  • Scenario Planner (Dashboard): Select a token, choose caps (e.g., $2T / $8T / $16T), and display Moon/Base/Bear ranges with tooltips.

  • Portfolio Allocator: Pair scenario bands with Quantmetrics and TM Grade to justify position sizes and rebalances.

  • Alert Bot (Discord/Telegram): Ping when price approaches a scenario level; link to the dashboard for context.

Fork a scenario planner or alerting template, plug in your key, and deploy. Confirm your environment by Running Hello-TM, and when you’re scaling users or need higher limits, review API plans.

How It Works (Under the Hood)

The Price Prediction endpoint maps market-cap scenarios to implied token prices, then categorizes them into Bear, Base, and Moon bands for readability. Your inputs can include a symbol and optional market caps; the response returns a scenario array you can plot or tabulate.

A common UX path is: Token selector → Scenario caps input → Prediction bands + context. For deeper insight, link to TM Grade (quality), Trading Signals (timing), and Support/Resistance (execution levels). This creates a complete plan–decide–act loop without overpromising outcomes.

Polling vs webhooks. Predictions don’t require sub-second updates; short-TTL caching and batched fetches work well for dashboards. If you build alerts (“price within 2% of Base scenario”), use a scheduled job and make notifications idempotent to avoid duplicates.

Production Checklist

  • Rate limits: Understand your tier caps; add client throttling and worker queues.

  • Retries & backoff: Exponential backoff with jitter for 429/5xx; capture request IDs.

  • Idempotency: De-dup alerts and downstream actions (e.g., avoid repeat pings).

  • Caching: Memory/Redis/KV with short TTLs; pre-warm popular symbols.

  • Batching: Fetch multiple symbols per cycle; parallelize within rate limits.

  • User controls: Expose caps (e.g., $2T/$8T/$16T) and save presets per user.

  • Display clarity: Label Bear/Base/Moon and show the implied market cap next to each price.

  • Compliance copy: Add a reminder that scenarios are not financial advice; historical outcomes don’t guarantee future results.

  • Observability: Track p95/p99 latency and error rate; log alert outcomes.

  • Security: Store API keys in secrets managers; rotate regularly.

Use Cases & Patterns

  • Bot Builder (Headless): Size positions relative to scenario distance (smaller size near Moon, larger near Bear) while confirming timing with /v2/trading-signals.

  • Dashboard Builder (Product): Add a Predictions tab on token pages; let users tweak caps and export a CSV of bands.

  • Screener Maker (Lightweight Tools): Rank tokens by upside to Base or distance to Bear; add alert toggles for approach thresholds.

  • PM/Allocator: Create policy rules like “increase weight when upside-to-Base > X% and TM Grade ≥ threshold.”

  • Education/Content: Blog widgets showing scenario bands for featured tokens; link to your app’s detailed page.

Next Steps

FAQs

1) What does the Price Prediction API return?
A JSON array of scenario objects for a symbol—each with a market cap and implied price, typically labeled Bear, Base, and Moon for clarity.

2) Can I set my own scenarios?
Yes, you can pass custom market caps (e.g., $2T, $8T, $16T) to reflect your thesis. Store presets per user or strategy for repeatability.

3) Is this financial advice? How accurate are these predictions?
No. These are scenario estimates based on your assumptions. They’re for planning and research, not guarantees. Always test, diversify, and manage risk.

4) How often should I refresh predictions?
Scenario bands typically don’t need real-time updates. Refresh on page load or at a reasonable cadence (e.g., hourly/daily), and cache results for speed.

5) Do you offer SDKs and examples?
REST is straightforward—see the JavaScript and Python snippets above. The docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.

6) How do I integrate predictions with execution?
Pair predictions with TM Grade (quality), Trading Signals (timing), and Support/Resistance (SL/TP). Alert when price nears a scenario and route to your broker logic (paper-trade first).

7) Pricing, limits, and SLAs?
Start free and scale up as you grow. See API plans for rate limits and enterprise SLA options.

Token Metrics API

Moonshots API: Discover Breakout Tokens Before the Crowd

Sam Monac
5 min
MIN

The biggest gains in crypto rarely come from the majors. They come from Moonshots—fast-moving tokens with breakout potential. The Moonshots API surfaces these candidates programmatically so you can rank, alert, and act inside your product. In this guide, you’ll call /v2/moonshots, display a high-signal list with TM Grade and Bullish tags, and wire it into bots, dashboards, or screeners in minutes. Start by grabbing your key at Get API Key, then Run Hello-TM and Clone a Template to ship fast.

What You’ll Build in 2 Minutes

  • A minimal script that fetches Moonshots via /v2/moonshots (optionally filter by grade/signal/limit).

  • A UI pattern to render symbol, TM Grade, signal, reason/tags, and timestamp—plus a link to token details.

  • Optional one-liner curl to smoke-test your key.

  • Endpoints to add next: /v2/tm-grade (one-score ranking), /v2/trading-signals / /v2/hourly-trading-signals (timing), /v2/resistance-support (stops/targets), /v2/quantmetrics (risk sizing), /v2/price-prediction (scenario ranges).

Why This Matters

Discovery that converts. Users want more than price tickers—they want a curated, explainable list of high-potential tokens. The moonshots API encapsulates multiple signals into a short list designed for exploration, alerts, and watchlists you can monetize.

Built for builders. The endpoint returns a consistent schema with grade, signal, and context so you can immediately sort, badge, and trigger workflows. With predictable latency and clear filters, you can scale to dashboards, mobile apps, and headless bots without reinventing the discovery pipeline.

Where to Find 

The Moonshots API cURL request is right there in the top right of the API Reference. Grab it and start tapping into the potential!

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

Live Demo & Templates

  • Moonshots Screener (Dashboard): A discover tab that ranks tokens by TM Grade and shows the latest Bullish tags and reasons.

  • Alert Bot (Discord/Telegram): DM when a new token enters the Moonshots list or when the signal flips; include S/R levels for SL/TP.

  • Watchlist Widget (Product): One-click “Follow” on Moonshots; show Quantmetrics for risk and a Price Prediction range for scenario planning.

Fork a screener or alerting template, plug your key, and deploy. Validate your environment with Hello-TM. When you scale users or need higher limits, compare API plans.

How It Works (Under the Hood)

The Moonshots endpoint aggregates a set of evidence—often combining TM Grade, signal state, and momentum/volume context—into a shortlist of breakout candidates. Each row includes a symbol, grade, signal, and timestamp, plus optional reason tags for transparency.

For UX, a common pattern is: headline list → token detail where you render TM Grade (quality), Trading Signals (timing), Support/Resistance (risk placement), Quantmetrics (risk-adjusted performance), and Price Prediction scenarios. This lets users understand why a token was flagged and how to act with risk controls.

Polling vs webhooks. Dashboards typically poll with short-TTL caching. Alerting flows use scheduled jobs or webhooks (where available) to smooth traffic and avoid duplicates. Always make notifications idempotent.

Production Checklist

  • Rate limits: Respect plan caps; batch and throttle in clients/workers.

  • Retries & backoff: Exponential backoff with jitter on 429/5xx; capture request IDs.

  • Idempotency: De-dup alerts and downstream actions (e.g., don’t re-DM on retries).

  • Caching: Memory/Redis/KV with short TTLs; pre-warm during peak hours.

  • Batching: Fetch in pages (e.g., limit + offset if supported); parallelize within limits.

  • Sorting & tags: Sort primarily by tm_grade or composite; surface reason tags to build trust.

  • Observability: Track p95/p99, error rates, and alert delivery success; log variant versions.

  • Security: Store keys in a secrets manager; rotate regularly.

Use Cases & Patterns

  • Bot Builder (Headless):


    • Universe filter: trade only tokens appearing in Moonshots with tm_grade ≥ X.

    • Timing: confirm entry with /v2/trading-signals; place stops/targets with /v2/resistance-support; size via Quantmetrics.

  • Dashboard Builder (Product):


    • Moonshots tab with Badges (Bullish, Grade 80+, Momentum).

    • Token detail page integrating TM Grade, Signals, S/R, and Predictions for a complete decision loop.

  • Screener Maker (Lightweight Tools):


    • Top-N list with Follow/alert toggles; export CSV.

    • “New this week” and “Graduated” sections for churn/entry dynamics.

  • Community/Content:


    • Weekly digest: new entrants, upgrades, and notable exits—link back to your product pages.

Next Steps

FAQs

1) What does the Moonshots API return?
A list of breakout candidates with fields such as symbol, tm_grade, signal (often Bullish/Bearish), optional reason tags, and updated_at. Use it to drive discover tabs, alerts, and watchlists.

2) How fresh is the list? What about latency/SLOs?
The endpoint targets predictable latency and timely updates for dashboards and alerts. Use short-TTL caching and queued jobs/webhooks to avoid bursty polling.

3) How do I use Moonshots in a trading workflow?
Common stack: Moonshots for discovery, Trading Signals for timing, Support/Resistance for SL/TP, Quantmetrics for sizing, and Price Prediction for scenario context. Always backtest and paper-trade first.

4) I saw results like “+241%” and a “7.5% average return.” Are these guaranteed?
No. Any historical results are illustrative and not guarantees of future performance. Markets are risky; use risk management and testing.

5) Can I filter the Moonshots list?
Yes—pass parameters like min_grade, signal, and limit (as supported) to tailor to your audience and keep pages fast.

6) Do you provide SDKs or examples?
REST works with JavaScript and Python snippets above. Docs include quickstarts, Postman collections, and templates—start with Run Hello-TM.

7) Pricing, limits, and enterprise SLAs?
Begin free and scale up. See API plans for rate limits and enterprise options.

Token Metrics API

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

Sam Monac
5 min
MIN

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.

  • Endpoints to add next: /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

Live Demo & Templates

  • SL/TP Alerts Bot (Telegram/Discord): Ping when price approaches or touches a level; include buffer %, link back to your app.

  • Token Page Levels Panel (Dashboard): Show nearest support/resistance with strength badges; color the latest candle by zone.

  • TradingView Overlay Companion: Use levels to annotate charts and label potential entries/exits driven by Trading Signals.

Kick off with our quickstarts—fork a bot or dashboard template, plug your key, and deploy. Confirm your environment by Running Hello-TM. When you’re scaling or need webhooks/limits, review API plans.

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

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.

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