惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

The Hacker News
The Hacker News
GbyAI
GbyAI
雷峰网
雷峰网
罗磊的独立博客
WordPress大学
WordPress大学
博客园_首页
Hugging Face - Blog
Hugging Face - Blog
The Cloudflare Blog
云风的 BLOG
云风的 BLOG
F
Full Disclosure
Google DeepMind News
Google DeepMind News
C
Cyber Attacks, Cyber Crime and Cyber Security
NISL@THU
NISL@THU
S
Schneier on Security
T
Tor Project blog
C
Cybersecurity and Infrastructure Security Agency CISA
Recent Announcements
Recent Announcements
酷 壳 – CoolShell
酷 壳 – CoolShell
C
Check Point Blog
P
Palo Alto Networks Blog
C
CERT Recently Published Vulnerability Notes
S
Secure Thoughts
Application and Cybersecurity Blog
Application and Cybersecurity Blog
Last Week in AI
Last Week in AI
T
Threatpost
I
Intezer
Y
Y Combinator Blog
G
GRAHAM CLULEY
MyScale Blog
MyScale Blog
阮一峰的网络日志
阮一峰的网络日志
T
The Exploit Database - CXSecurity.com
Scott Helme
Scott Helme
A
Arctic Wolf
Martin Fowler
Martin Fowler
Hacker News: Ask HN
Hacker News: Ask HN
V
V2EX
B
Blog RSS Feed
The Last Watchdog
The Last Watchdog
博客园 - 司徒正美
Simon Willison's Weblog
Simon Willison's Weblog
V
Vulnerabilities – Threatpost
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
N
News and Events Feed by Topic
www.infosecurity-magazine.com
www.infosecurity-magazine.com
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
P
Proofpoint News Feed
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
AI
AI
C
Cisco Blogs
T
The Blog of Author Tim Ferriss

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant Common SOC 2 Failures (Real World) Stop Vibe-Checking Your AI App: A Practical Guide to Evals How to Use SonarQube and SonarScanner Locally to Level Up Your Code Quality Your Next To-Do App Is Dead — I Replaced Mine with an OpenClaw AI Sign a Nostr event in 60 lines of Python using coincurve — no nostr-sdk, no nbxplorer, no rust toolchain ITGC Audit Explained Like You’re in Big 4 Patch Tuesday abril 2026: Microsoft parcha 163 vulnerabilidades y un zero-day en SharePoint Stop scraping everything: a better way to track competitor price changes Listing on MCPize + the Official MCP Registry while routing payments OUTSIDE the marketplace — how I kept 100% of my x402 revenue Building an AI-Powered Risk Intelligence System Using Serverless Architecture Why We Ripped Function Overloading Out of Our AI Toolchain Testing AI-Generated Code: How to Actually Know If It Works SaaS Churn Is Killing Your Business. Here Is What to Do About It (Without a Support Team) The Speed of AI Is No Longer Linear - And Self-Improving Models Are Why How to Implement RBAC for MCP Tools: A Practical Guide for Engineering Teams From Standard Quote to Persuasive Proposal: AI Automation for Arborists I built a CLI that scaffolds complete multi-tenant SaaS apps Axios CVE-2025–62718: The Silent SSRF Bug That Could Be Hiding in Your Node.js App Right Now The dashboard that ended our friendship Data Pipelines Explained Simply (and How to Build Them with Python) The Hidden Cost of AI Systems Nobody Talks About. undefined vs undeclared, and how typeof behaves Switching from file-based jobs to NATS/Kafka in Rust without changing code io_uring Adventures: Rust Servers That Love Syscalls Why Agentic AI is Killing the Traditional Database The POUR principles of web accessibility for developers and designers Quantum Neural Network 3D — A Deep Dive into Interactive WebGL Visualization How To Install Caveman In Codex On macOS And Windows Automation Pipeline Reliability: Why Your Workflow Breaks When Nobody Is Watching I Built an 'Open World' AI Coding Agent — It Works From ANY Folder From Freelancing to Product: A Tech Service Company's SaaS Transformation China's AI Giants: Adding Tencent Hunyuan & ByteDance Doubao to AI University (74 Providers) On the Vibe Coders and Their Lies clerk: Auto-Summarize Your Claude Code Sessions AI Weekly — 2026/04/10–04/17 | The Model Lockdown Is Here, but the Toolchain Is the Real Battleground AI 週報 — 2026/04/10–2026/04/17 模型封鎖潮來了,但工具鏈才是真戰場 Maybe this is how Open-Source apps are born... 🚀 Fine-Tune LLMs with LoRA and QLoRA: 2026 Guide tRPC v11 + Next.js App Router: End-to-End Type Safety Without the Boilerplate ShadCN UI in 2026: Why I Stopped Installing Component Libraries and Started Owning My Components SaaS Billing in React Server Components: Stripe + Supabase Without a Single `useEffect` Join our DEV Weekend Challenge — $1,000 in Prizes Across TEN winners! Submissions Due April 20 at 6:59 AM UTC. Implementing FSRS Spaced Repetition in Flutter + Supabase — Adding Memory Science to an AI Learning App "I Texted My Localhost From the Train — Claude Code Fixed the Bug Before I Got Home" I Built a Sales Prep AI and It Went Deeper Than Expected Design to Code #2: One JSON, Eleven Outputs Solving the 100M-Row Problem: A Summary Table Pattern for High-Volume Push Notification Logs Flutter Web With Wasm: What Actually Changes For Developers I Built 50 Royalty-Free Soundtracks for My Side Project in a Weekend Using AI Music Generation The Vibe Coding Security Checklist: 7 Things to Check Before You Ship Stop Letting Googlebot Guess Fix Your React App's SEO Right Desconstruindo o Streaming do LinkedIn: Como Criar um Engine de Extração de Vídeo de Alta Performance com HLS e FFmpeg (EDA Part-1) EDA (Exploratory Data Analysis) Explained With Real Life — Why Looking at Your Data Is the Most Important Step in Machine Learning Brand Relationship Management at Scale: Our 4-Touch Outreach System for 200+ Brands Why String.fromEnvironment() Might Return an Empty String in Dart JGuardrails 1.0.0 — Hardening Java LLM Apps Against Jailbreaks, Toxicity, and Prompt Injection Plan and Schedule a Full Week of Threads Content From One Claude Conversation Coding Cat Oran Ep3, Five Tables Changed Everything Updated: BFF Pattern I'm done watching freelancers get buried by 200 proposals. So I'm building the alternative. This is my first post BFS Algorithm in Java Step by Step Tutorial with Examples Tracking LLM Pricing Monthly: An Open Dataset for 22 AI Models How We Measure Content ROI on a Comparison Site: Revenue Attribution Without Perfect Data Introducing Nova AI Ops: The AI-Native Operating System for SRE Teams I built a free desktop video downloader for Windows — Grabbit How Talkie OCR Helps Vision-Impaired & Dyslexic Users Read the World Around Them VRCFaceTracking安装和iPhone面捕配置教程,有bug Even CrowdStrike Can't See Your Agents The Automation Gold Rush: What n8n Workflows and Claude Are Opening Up for Developers Right Now
How to Avoid Losses in a Bear Market: A Crypto Trader's Survival Guide
Gunnar Thord · 2026-05-03 · via DEV Community

How to Avoid Losses in a Bear Market: A Crypto Trader's Survival Guide

Here's a number most traders don't want to hear: over the last 51 days of continuous market monitoring, 93% of the time the crypto market was classified as bearish. Not choppy. Not neutral. Bearish.

That data comes from 10,000+ market snapshots taken every five minutes by the Regime API, scoring 10 weighted signals across funding rates, crowd sentiment, on-chain flows, macro context, and price structure.

The traders who survived that stretch aren't the ones with the best entry signals. They're the ones who recognized the regime and stopped fighting it.

What a Bear Market Actually Means

A bear market isn't just "prices going down." It's a statistical regime where the market's behavior changes in measurable ways:

  • Rallies get sold. Every bounce attracts sellers, not buyers. What looks like a reversal becomes a lower high.
  • Support levels break. Key levels that held for weeks give way because there's no buying pressure underneath.
  • Funding goes negative. Leveraged traders are positioned short. The crowd expects lower prices, and in bear regimes, the crowd is usually right.
  • Macro headwinds persist. DXY strength, rising VIX, weak equity correlations — the external environment isn't supporting risk assets.
  • Volume dries up on bounces. Real buying volume only shows up on capitulation wicks, not on recovery candles.

In a bear regime, strategies that work in bull markets — breakout buying, dip buying, trend following on longs — become systematic losers. The market punishes the same behavior it rewarded three months ago.

Why Most Strategies Fail in Bear Markets

The core problem is simple: most trading strategies are designed for one regime and deployed in all of them.

A long-only momentum strategy that crushed it during a bull run will slowly bleed during a bear market. Not from one catastrophic loss, but from dozens of small ones. Each entry looks reasonable on the chart. The setup triggers, the pattern matches, the indicator fires. But the trade fails because the broader environment doesn't support it.

This is death by a thousand cuts. The strategy's edge disappears, but the signals keep firing, and the bot keeps entering.

The second failure mode is late recognition. By the time a trader manually identifies a bear market — usually after weeks of declining equity — they've already given back most of their bull market gains. Human pattern recognition is too slow for crypto, where regime transitions can happen in 48 hours.

The third failure mode is denial. "This is just a pullback." "It'll bounce from here." "The fundamentals haven't changed." These are stories traders tell themselves while the regime classifier is reading 8 out of 10 signals as bearish.

Five Steps to Protect Your Portfolio

1. Add a Regime Filter to Every Strategy

Before your strategy takes any entry, check the market regime. This is the single highest-impact change you can make:

# Check regime before entering a trade
REGIME=$(curl -s https://getregime.com/api/v1/market/regime | jq -r '.regime')

if [ "$REGIME" = "bear" ]; then
  echo "Bear regime — no new long entries"
  exit 0
fi

Enter fullscreen mode Exit fullscreen mode

A regime filter doesn't need to be complex. The simplest version: if the market is bearish, don't open new long positions. That single rule would have prevented the majority of losses during the 93% bear stretch in our data.

For Freqtrade bots, there's a dedicated endpoint:

curl https://getregime.com/api/v1/freqtrade/regime

Enter fullscreen mode Exit fullscreen mode

2. Reduce Position Size — or Go to Cash

Bear markets reward patience, not aggression. If you're going to trade at all during a bear regime:

  • Cut position size by 50-75%. If you normally risk 2% per trade, drop to 0.5%. The expected value of trades is lower, so your risk per trade should be too.
  • Move 50-80% to stablecoins. Cash is a position. During the 93% bear period in our data, sitting in USDT outperformed every long-only strategy.
  • Set a portfolio heat limit. No more than 10-15% of capital at risk during bear regimes, regardless of how good individual setups look.

3. Flip to Mean-Reversion (If You Trade at All)

In bear markets, trend-following dies and mean-reversion works. If you're going to trade:

  • Short overextended bounces instead of buying dips
  • Fade moves into resistance, don't buy breakouts
  • Use tighter take-profits — rallies in bear markets are short-lived

The regime classification tells you which playbook to use. Bull regime = trend-following. Bear regime = mean-reversion or cash. Chop regime = reduce size, widen stops, or sit out.

4. Monitor Regime Transitions, Not Price

Staring at price charts during a bear market leads to emotional trading. Instead, monitor the regime itself.

The Regime API tracks 10 weighted signals:

  • Funding rates and open interest — Are leveraged traders getting more bearish or is pressure releasing?
  • Crowd sentiment — Fear & Greed reaching extreme lows (potential exhaustion) or sustained fear?
  • On-chain flows — Stablecoin supply growing (dry powder) or shrinking?
  • Macro context — DXY weakening? VIX dropping? SPX recovering?
  • Price structure — Volume patterns shifting? Volatility compressing?

When these signals start flipping from bearish to neutral, the regime is weakening. That's your signal to prepare — not to trade, but to get ready. The regime transition from bear to chop to bull is where the next opportunity starts.

Pro tier users can set up webhook alerts that fire automatically on regime transitions:

curl -X POST -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://your-server.com/alert", "events": ["regime.transition"]}' \
  https://getregime.com/api/v1/webhooks

Enter fullscreen mode Exit fullscreen mode

5. Use the Bear Market to Build

The most productive thing you can do during a bear market is improve your system. The market isn't rewarding trading, so invest in infrastructure:

  • Backtest your strategy across different regimes using historical regime data
  • Build the regime filter you should have had before the bear started
  • Review your worst trades — how many happened during bear regimes?
  • Set up automated alerts so you're notified when the regime shifts

The traders who come out of bear markets strongest aren't the ones who traded through it. They're the ones who used the downtime to build better systems.

The Data Behind This Advice

This isn't theoretical. The Regime API has been classifying the market continuously since early March 2026:

  • 10,000+ market snapshots every 5 minutes
  • 460+ regime transitions captured and timestamped
  • 51 days of continuous classification
  • 93% bear regime in the most recent period

Every transition is documented. Every signal score is recorded. The track record page shows live classification accuracy against actual market data.

Bear Markets End

Bear regimes don't last forever. The same 10-signal classifier that kept you out of bad trades will tell you when conditions are shifting. When funding flips positive, sentiment reaches extreme fear (contrarian signal), stablecoin dry powder peaks, and macro headwinds ease — the regime transitions.

The goal isn't to predict the bottom. It's to have a system that tells you when the environment changes, so you can adjust your exposure accordingly.


The Regime API provides real-time crypto market regime detection for traders, funds, and bots. Add a regime filter to your strategy in under 10 minutes — start with the quickstart guide. Free tier available, no credit card required.


Try Regime Intelligence

Regime is a real-time crypto market regime detection API. One endpoint tells you if the market is bull, bear, or chop — so your bot only trades when conditions match your strategy.

Free API access → | See pricing → | API docs →