A single liquidation wiped out $1.2 billion in leveraged positions during Bitcoin’s flash crash to $25,000 in August 2023. The traders who survived? They all had one thing in common: properly placed stop losses.
According to Glassnode data, traders using disciplined stop-loss strategies preserve 73% more capital during bear markets compared to those who “ride it out.” Yet CoinGecko’s 2025 Trader Survey revealed that 68% of retail crypto traders either don’t use stop losses or place them incorrectly.
The difference between protecting your portfolio and watching it evaporate often comes down to a few percentage points—the exact placement of your exit strategy.
This comprehensive guide examines 11 proven stop loss strategies backed by on-chain data, institutional research, and real trading outcomes. You’ll learn when to use each method, how to calculate optimal placement, and the critical mistakes that turn protective stops into profit killers.
The noise is deafening in crypto markets. Only those who listen to the signal—and protect capital when the signal turns—survive to profit.
What Is a Stop Loss and Why It Matters in Crypto
A stop loss is an automated order that closes your position when the price reaches a predetermined level, limiting your downside risk. In traditional markets, it’s a safety net. In crypto’s 24/7 volatility, it’s essential survival equipment.
The Brutal Math of Crypto Drawdowns:
| Drawdown | Required Gain to Break Even |
|---|---|
| -10% | +11.1% |
| -25% | +33.3% |
| -50% | +100% |
| -75% | +300% |
| -90% | +900% |
This asymmetric recovery math explains why professional traders obsess over capital preservation. According to a Kaiko Research analysis of 50,000+ trading accounts, portfolios using stop losses recovered 4.2x faster from market downturns than those without.
Why Crypto Demands Different Stop Loss Approaches
Crypto markets exhibit unique characteristics that make traditional stop loss strategies inadequate:
- Extreme Volatility: Bitcoin’s average daily range in 2026 was 8.3% (per CoinGecko)—compare that to the S&P 500’s 0.7%.
- 24/7 Markets: Flash crashes happen at 3 AM. According to Binance data, 23% of major liquidation events occur between midnight and 6 AM UTC.
- Stop Hunting: According to Chainalysis, approximately $340 million in retail stop losses were “hunted” by whales in 2025—deliberate price manipulation to trigger stops before reversal.
- Thin Liquidity: Glassnode reports that order book depth for most altcoins drops 60-80% outside U.S. trading hours, creating slippage nightmares.
These factors don’t make stop losses useless—they make strategic stop losses essential.
For traders looking to combine multiple protective approaches, our guide on combining crypto indicators effectively demonstrates how to layer stop loss strategies with confirmation signals.
The Foundation: Understanding Stop Loss Types
Before diving into advanced strategies, you need to understand the mechanical differences between stop loss types. Each serves different market conditions and trading styles.
1. Hard Stop Loss (Market Order)
Mechanics: Triggers a market order when price hits your stop level.
Pros:
- Guaranteed execution
- Simple to implement
- Works on all exchanges
Cons:
- Slippage in volatile markets
- Can execute far below stop price
- Vulnerable to flash crashes
Data Point: According to a Kaiko analysis of 10,000 stop loss executions, hard stops experienced average slippage of 1.8% during normal volatility and 7.3% during flash crash events.
Best For: Liquid markets, lower leverage positions, long-term holds.
2. Stop Limit Order
Mechanics: Triggers a limit order when price hits your stop level. The limit order only executes at your specified price or better.
Pros:
- Controlled execution price
- No slippage beyond limit
- Better for illiquid pairs
Cons:
- May not fill during rapid moves
- Can leave you exposed if price gaps through
- Requires tighter monitoring
Data Point: Binance data shows stop-limit orders fail to execute in 31% of flash crash scenarios, leaving traders holding underwater positions.
Best For: Ranging markets, illiquid altcoins, partial position management.
3. Trailing Stop Loss
Mechanics: Automatically adjusts stop level as price moves in your favor, locking in profits while allowing positions to run.
Pros:
- Captures trend continuation
- Automatic profit protection
- Reduces emotional decision-making
Cons:
- Can trigger on normal retracements
- Requires optimal trail distance
- Less effective in choppy markets
Data Point: According to TradingView backtests across 500 BTC trades, trailing stops with 8-12% distance captured 68% of major trends while avoiding 73% of false exits.
Best For: Trending markets, swing trades, momentum strategies.
For traders building systematic approaches, our automated stop loss systems guide provides implementation frameworks for each type.
Strategy 1: ATR-Based Stop Loss (Volatility-Adjusted Protection)
The Average True Range (ATR) method adjusts your stop loss based on current market volatility—wider stops in volatile conditions, tighter in calm markets. This prevents getting stopped out by normal price action.
How to Calculate ATR-Based Stops
Formula: Stop Distance = ATR(14) × Multiplier
Typical Multipliers by Trading Style:
- Day Trading: 1.5-2.0× ATR
- Swing Trading: 2.5-3.0× ATR
- Position Trading: 3.5-5.0× ATR
Real Example: BTC/USDT Trade
Entry: $42,000 ATR(14): $1,680 Trading Style: Swing (2.5× multiplier) Stop Distance: $1,680 × 2.5 = $4,200 Stop Loss: $42,000 – $4,200 = $37,800
Performance Data
According to a comprehensive backtest by CryptoQuant analyzing 2,000 BTC trades from 2020-2025:
| Multiplier | Win Rate | Avg Winner | Avg Loser | Profit Factor |
|---|---|---|---|---|
| 1.5× | 42% | +8.2% | -3.1% | 1.11 |
| 2.5× | 56% | +11.7% | -5.2% | 1.26 |
| 3.5× | 61% | +14.3% | -7.1% | 1.23 |
| 5.0× | 67% | +16.8% | -9.8% | 1.15 |
Sweet Spot: The 2.5-3.0× multiplier range provided optimal balance between protection and staying in winning trades.
When ATR Stops Fail
Limitation: In rapid trending markets with expanding volatility, ATR can widen stops too much, allowing larger losses. During Bitcoin’s March 2023 crash, ATR expanded from $1,200 to $3,800 in 72 hours, pushing stops from -5% to -9% for traders who hadn’t locked in earlier levels.
Solution: Combine with absolute maximum loss rules (covered in Strategy 8).
Strategy 2: Support/Resistance-Based Stops
Technical levels where price has historically bounced or stalled provide logical stop loss placement. This aligns your exit with the point where your trade thesis breaks down.
Identifying Valid Support/Resistance Levels
Criteria for Strong Levels (per TradingView analysis of 10,000+ chart patterns):
- Multiple Touches: At least 3 tests increases validity by 67%
- Volume Confirmation: 40%+ above average volume at level
- Time Spacing: Tests separated by weeks/months (daily timeframe)
- Round Numbers: Psychological levels ($40K, $50K) hold 23% stronger
Placement Strategy
For Long Positions: Place stop 1-3% below support For Short Positions: Place stop 1-3% above resistance
Example: ETH Long Setup
Support Level: $2,200 (tested 4 times over 3 months) Entry: $2,250 (bounce from support) Stop: $2,150 (2.3% below support) Risk: 4.4% of position
Support Strength Data
According to Glassnode’s analysis of Bitcoin’s major support levels:
| Support Type | Hold Rate | Avg Bounce |
|---|---|---|
| Previous All-Time High | 73% | +18.3% |
| 200-Day MA | 68% | +12.7% |
| Major Fibonacci Level | 64% | +11.2% |
| Round Number ($10K, $20K) | 61% | +9.4% |
| Trend Line | 58% | +8.1% |
The Stop Hunt Problem
Critical Insight: Chainalysis data reveals that 34% of major support levels experience a “wick below” before bouncing—deliberate hunts for retail stop losses clustered just below support.
Solution:
- Place stops 2-3% below obvious support instead of 0.5-1%
- Use OCO (One-Cancels-Other) orders to pyramid back in if price returns above support within 4 hours
- Monitor whale wallet movements for accumulation signals before major support tests
Strategy 3: Percentage-Based Stops (Fixed Risk Management)
The simplest approach: risk a fixed percentage on every trade regardless of technical setup. While mechanical, it enforces discipline and prevents catastrophic losses.
Standard Risk Percentages by Account Size
Recommended Risk Per Trade:
- Accounts under $10K: 1-2%
- Accounts $10K-$100K: 0.5-1.5%
- Accounts over $100K: 0.5-1%
- Professional/Institutional: 0.25-0.5%
Position Sizing Formula
Position Size = (Account Size × Risk %) / (Entry Price – Stop Loss Price)
Example:
- Account: $50,000
- Risk Tolerance: 1% = $500
- Entry: $42,000
- Stop: $39,900 (5% below entry)
- Position Size: $500 / ($42,000 – $39,900) = $500 / $2,100 = 0.238 BTC
Performance Analysis
Binance’s analysis of 100,000+ retail accounts (2024-2025) revealed:
| Risk % Per Trade | 12-Month Survival Rate | Median Return |
|---|---|---|
| 5%+ | 23% | -47% |
| 3-5% | 41% | -18% |
| 2-3% | 58% | +4% |
| 1-2% | 71% | +23% |
| <1% | 83% | +31% |
Key Finding: Accounts risking under 1% per trade had 3.6× higher survival rates and achieved positive returns despite win rates below 50%.
The Drawdown Reality
Fixed percentage stops create predictable maximum drawdown scenarios:
10 Consecutive Losses:
- 5% per trade: -40.1% total drawdown
- 2% per trade: -18.3% total drawdown
- 1% per trade: -9.6% total drawdown
This math explains why professionals cap single-trade risk below 1%.
Strategy 4: Trailing Stop Loss (Momentum-Following Protection)
Trailing stops lock in profits automatically as price moves in your favor while allowing winners to run. According to TradingView’s analysis of 5,000 momentum trades, properly configured trailing stops captured 71% of major trend moves.
Types of Trailing Stops
4A. Fixed Percentage Trail
Mechanics: Stop trails at a fixed percentage below highest price (long) or above lowest price (short).
Example:
- Entry: $40,000
- Trail: 8%
- Price peaks at $52,000
- Stop now at: $47,840 (8% below $52,000)
Optimal Trail Distances (per Glassnode data on BTC 2020-2025):
| Market Condition | Optimal Trail | Win Rate | Profit Capture |
|---|---|---|---|
| Strong Trend | 6-8% | 62% | 73% |
| Moderate Trend | 10-12% | 58% | 81% |
| Choppy/Ranging | 15%+ | 43% | 89% |
4B. ATR-Based Trail
Formula: Trail Distance = Current ATR × Multiplier (typically 2.0-3.0×)
Advantage: Adapts to changing volatility. During Bitcoin’s consolidation phases (ATR ~$1,200), trail tightens to ~$2,400-$3,600. During volatile breakouts (ATR ~$3,000), trail widens to ~$6,000-$9,000.
Performance: CryptoQuant backtests show ATR-based trails reduced false exits by 34% compared to fixed percentage trails.
4C. Indicator-Based Trail
Common Triggers:
- Below/Above 21-EMA
- RSI drops below 60 (for longs)
- MACD crossover
- Parabolic SAR flip
Example Strategy: Trail stop to 1% below 21-EMA on daily chart.
Data: According to analysis from our RSI indicator guide, RSI-based trailing stops (exit when RSI crosses below 60) captured 68% of trend moves with 23% fewer false exits than fixed trails.
Trailing Stop Pitfalls
Problem #1: Premature Exits Too-tight trails get stopped out on healthy retracements. TradingView data shows 8-12% trails on BTC allow for normal -6% to -8% pullbacks in uptrends.
Problem #2: Giving Back Too Much Too-wide trails surrender hard-won gains. During Bitcoin’s April 2025 correction, positions with 15%+ trails gave back $6,000-$8,000 from peak.
Solution: Scale out approach (Strategy 9).
Strategy 5: Time-Based Stop Loss Adjustments
Market conditions change. Your stop loss strategy should too. Time-based adjustments account for holding period, volatility cycles, and event risk.
5A. Breakeven Stops After Initial Move
Rule: Once position moves [X]% in your favor, move stop to breakeven (entry price).
Standard Triggers:
- Day Trades: Move to BE after +2-3% gain
- Swing Trades: Move to BE after +5-8% gain
- Position Trades: Move to BE after +10-15% gain
Example:
- Entry: $40,000
- Target: +15%
- Rule: Move to BE at +5%
- Price hits $42,000 (+5%)
- Stop moved from $38,000 (-5% risk) to $40,000 (breakeven)
Impact: Binance analysis shows traders using breakeven stops reduced losing trades by 28% and improved risk-adjusted returns by 34%.
5B. Ladder Stops Based on Time Held
Concept: Tighten stops the longer you hold a position to protect unrealized gains and force reevaluation.
Sample Framework:
| Time Held | Stop Distance |
|---|---|
| Day 0-7 | ATR × 3.0 |
| Day 8-21 | ATR × 2.5 |
| Day 22-60 | ATR × 2.0 |
| Day 61+ | ATR × 1.5 or 21-EMA |
Rationale: According to Glassnode, Bitcoin trades held longer than 60 days have 73% lower volatility on average, justifying tighter protection.
5C. Event-Based Stop Tightening
High-Risk Events:
- FOMC meetings
- CPI releases
- Major exchange listings
- Network upgrades/hard forks
- Leverage unwind events
Strategy: Reduce stop distance by 30-50% or close positions entirely 24 hours before high-impact events.
Data: Kaiko’s analysis of 500+ high-volatility events showed that positions with pre-event stop tightening preserved 41% more capital during adverse price moves.
Our guide on how to filter false signals provides additional event-risk frameworks for protecting positions during market noise.
Strategy 6: Fibonacci Retracement-Based Stops
Fibonacci levels identify where price corrections typically exhaust before trend resumption. Placing stops below key retracement levels aligns protection with market structure.
Key Fibonacci Stop Levels
For Long Positions in Uptrends:
- Aggressive: Below 38.2% retracement
- Standard: Below 50% retracement
- Conservative: Below 61.8% retracement
For Short Positions in Downtrends:
- Aggressive: Above 38.2% retracement
- Standard: Above 50% retracement
- Conservative: Above 61.8% retracement
Real Example: ETH Bull Run
Move: $1,500 → $3,000 Entry on Pullback: $2,650 (near 38.2% fib) Fibonacci Levels:
- 38.2%: $2,427
- 50.0%: $2,250
- 61.8%: $2,073
Stop Placement: $2,180 (3% below 50% fib level)
Outcome: According to TradingView data, 67% of healthy uptrend corrections in BTC/ETH hold above the 50% retracement, making this a statistically favorable stop level.
Fibonacci Performance Data
Analysis from our Fibonacci retracement guide shows:
| Fib Level | Hold Rate (Uptrends) | Avg Bounce | Stop Out Rate |
|---|---|---|---|
| 23.6% | 43% | +6.2% | 57% |
| 38.2% | 61% | +11.7% | 39% |
| 50.0% | 67% | +14.3% | 33% |
| 61.8% | 74% | +18.9% | 26% |
| 78.6% | 82% | +12.1% | 18% |
Insight: The 61.8% level provides highest success rate but requires holding through deeper retracements. The 50% level offers best risk-reward balance.
Combining Fibonacci with Volume
Enhanced Strategy: Only place stops below Fibonacci levels that align with high-volume support zones.
Criteria:
- Fib level must have 2+ previous tests
- Volume at level 30%+ above average
- On-chain support (check Glassnode UTXO data)
This confluence increases hold rate to 79% according to CryptoQuant analysis.
Strategy 7: On-Chain Signal-Based Stops
Advanced traders use blockchain data to set dynamic stops based on smart money behavior. When whales accumulate, widen stops. When whales distribute, tighten or exit.
7A. Exchange Flow-Based Adjustments
Concept: Large exchange inflows often precede selling pressure. Use this as stop-tightening trigger.
Implementation:
- Monitor exchange netflow (Glassnode, CryptoQuant)
- Baseline: 7-day average inflow
- Alert: Inflow exceeds baseline by 200%+
- Action: Tighten stops by 30-40% or take partial profits
Example:
- Normal BTC exchange inflow: 2,000 BTC/day
- Spike detected: 6,500 BTC inflow
- Action: Reduce stop from -8% to -5%
Historical Accuracy: According to Glassnode, exchange inflow spikes preceded drawdowns within 72 hours in 71% of cases (2020-2025 data).
7B. MVRV-Based Stop Adjustment
MVRV Ratio = Market Value / Realized Value
This metric shows if holders are in profit (MVRV >1) or loss (MVRV <1).
Stop Strategy:
- MVRV > 3.5: High profit-taking risk → tighten stops to -5%
- MVRV 2.0-3.5: Moderate risk → standard stops -8%
- MVRV 1.0-2.0: Lower risk → wider stops -10%
- MVRV < 1.0: Capitulation zone → widest stops -12%
Data: Per our Bitcoin MVRV analysis guide, MVRV readings above 3.7 preceded corrections of -20% or more in 89% of historical cases.
7C. Whale Accumulation Signals
Strategy: Monitor large wallet addresses (1,000+ BTC). When whales accumulate during your trade, widen stops to avoid shakeouts.
Tools:
- Whale tracking platforms
- Glassnode whale ratio
- CryptoQuant exchange whale ratio
Rule: If whale accumulation increases 15%+ week-over-week, widen stops by 20-30% to weather volatility.
Case Study: During Bitcoin’s August 2025 dip to $38,000, whale addresses accumulated 47,000 BTC over 72 hours. Traders who widened stops to -12% (vs. standard -8%) avoided stop-outs and caught the subsequent rally to $49,000.
For comprehensive on-chain strategies, see our on-chain data interpretation guide.
Strategy 8: The Hard Floor Stop (Maximum Loss Rule)
No matter how bullish your thesis, always define the absolute maximum you’ll lose on any position. This overrides all other stop strategies.
Setting Your Hard Floor
Formula: Maximum Acceptable Loss = Account Size × Max Risk %
Conservative Levels:
- High-conviction trades: 5% account risk
- Medium-conviction: 3% account risk
- Low-conviction/speculation: 1% account risk
Why This Matters
Even with perfect technical analysis, black swan events happen:
- May 2021: BTC dropped 30% in 24 hours
- November 2022: FTX collapse triggered -25% cascade
- March 2023: Banking crisis flash crash -18%
Reality Check: According to Glassnode, Bitcoin has experienced 24 single-day drops exceeding -10% since 2020. Your stop strategy must account for these.
Implementation Example
Position:
- Account: $100,000
- Max acceptable loss: 3% ($3,000)
- Entry: $42,000 BTC
- Technical stop: $39,900 (5% below entry)
- Position size calculation: $3,000 / ($42,000 – $39,900) = 1.43 BTC
Hard Floor Stop: $40,900 (3% account risk limit)
If price gaps through your technical stop at $39,900 and continues falling, the hard floor at $40,900 caps your actual loss.
Mental Stop vs. Hard Stop
Mental Stops (no automatic order): Dangerous in crypto’s 24/7 markets.
Data: Kaiko’s study of 5,000 retail traders found that those relying on mental stops executed exits 3.2 hours later on average, resulting in 34% larger losses.
Recommendation: Always use hard stops for maximum loss levels. Mental stops only appropriate for profit-taking.
Strategy 9: Scaling Out Stops (Partial Position Management)
Professional traders rarely exit entire positions at once. Scaling out captures profits while maintaining exposure to further upside.
Standard Scaling Framework
3-Tier Exit Strategy:
- First Third: Exit at +1R (R = initial risk)
- Second Third: Exit at +2R or major resistance
- Final Third: Trail with 10-12% stop
Example Trade:
- Entry: $40,000
- Stop: $38,000 (5% risk, -$2,000 per BTC)
- Position: 1.5 BTC
Exit Plan:
- 0.5 BTC at $42,000 (+5% = +1R)
- 0.5 BTC at $44,000 (+10% = +2R)
- 0.5 BTC trails with 10% stop
Outcome if BTC reaches $50,000 then retraces to $45,000:
- First exit: +$1,000 profit
- Second exit: +$2,000 profit
- Final exit at $45,000: +$2,500 profit
- Total: +$5,500 (vs. +$7,500 if held all to peak, but +$0 if entire position stopped at $38,000 on a shakeout)
Performance Comparison
According to Binance’s analysis of 10,000 comparable trades:
| Strategy | Win Rate | Avg Win | Avg Loss | Profit Factor |
|---|---|---|---|---|
| All-In, All-Out | 52% | +$2,840 | -$980 | 1.51 |
| 3-Tier Scaling | 67% | +$1,920 | -$620 | 2.08 |
| 5-Tier Scaling | 71% | +$1,650 | -$510 | 2.31 |
Key Finding: Scaling improved win rates by 15-19 percentage points and profit factor by 38-53%.
Dynamic Scaling Based on Market Conditions
Trending Markets: Use wider spacing (1R, 2.5R, trail) Range-Bound: Use tighter spacing (0.5R, 1R, 1.5R) High Volatility: Scale faster (0.3R, 0.7R, 1R)
For traders managing altcoin portfolios, scaling becomes even more critical given higher volatility profiles.
Strategy 10: Volatility Regime-Based Stops
Crypto markets cycle through distinct volatility regimes. Your stop-loss approach should adapt accordingly.
Identifying Volatility Regimes
Low Volatility (VIX-equivalent <30):
- Bollinger Bands contracting
- ATR declining
- Price consolidation patterns
- Typically precedes breakouts
Normal Volatility (VIX 30-60):
- Steady ATR
- Normal intraday ranges
- Predictable support/resistance reactions
High Volatility (VIX >60):
- Expanding Bollinger Bands
- Rising ATR
- Frequent gap moves
- Leverage cascades
Stop Adjustments by Regime
| Regime | Stop Type | Typical Distance | Risk/Trade |
|---|---|---|---|
| Low Vol | Tight fixed % | 3-5% | 1-2% |
| Normal | ATR-based | 2.5× ATR | 1% |
| High Vol | Wide ATR or none | 4-5× ATR | 0.5% or cash |
Real Data: Bitcoin Volatility Analysis
According to Glassnode’s realized volatility data (2020-2025):
Low Vol Periods (30 total):
- Average duration: 18 days
- Followed by breakout: 87% of cases
- Average breakout move: +14.3%
High Vol Periods (43 total):
- Average duration: 12 days
- Preceded major trend changes: 64% of cases
- Optimal strategy: Reduce position sizes, widen stops
The Regime Shift Problem
Critical Insight: Most traders get stopped out when volatility regime shifts from low to high. Price makes a normal move in the new regime that would have been extreme in the old regime.
Solution: When ATR increases by 40%+ in 3 days, immediately widen existing stops by 30-50% or reduce position size.
Example:
- Holding BTC with -5% stop during low volatility
- ATR jumps from $1,200 to $2,100 (+75%) over 3 days
- Widen stop to -7.5% or reduce position by 40%
This prevented stop-outs during 71% of regime transitions according to CryptoQuant analysis.
Strategy 11: Correlation-Based Stop Management
When multiple crypto positions are highly correlated, traditional stop losses can all trigger simultaneously, causing catastrophic portfolio damage.
Understanding Crypto Correlations
30-Day Rolling Correlation (CoinGecko data, Q1 2026):
| Asset Pair | Correlation |
|---|---|
| BTC/ETH | 0.87 |
| ETH/Large-Cap Alts | 0.82 |
| BTC/Small-Cap Alts | 0.71 |
| Stablecoins/BTC | -0.03 |
| DeFi Tokens/ETH | 0.76 |
The Correlation Cascade Problem
Scenario: Portfolio holds BTC, ETH, SOL, AVAX—all 0.75+ correlation.
Market Event: BTC drops -8%, triggering your stop.
Cascade Effect: Within 2-4 hours:
- ETH drops -7.2%
- SOL drops -9.1%
- AVAX drops -8.8%
All positions stopped out at worst prices, converting temporary volatility into permanent losses.
Data: According to Kaiko, during the May 2025 correction, portfolios with 4+ correlated positions experienced average drawdowns of -23.4% vs. -11.7% for diversified portfolios.
Correlation-Aware Stop Strategies
Strategy 11A: Portfolio-Level Circuit Breaker
Instead of individual stops, trigger portfolio-wide reassessment at threshold.
Rule: If portfolio drawdown hits -10% intraday, halt all automated stops, reassess market conditions, then manually manage exits.
Prevents: Cascade liquidations at synchronized worst prices.
Strategy 11B: Staggered Stop Distances
Deliberately set different stop distances for correlated positions.
Example Portfolio:
- BTC: -8% stop
- ETH: -10% stop
- SOL: -12% stop
- AVAX: -14% stop
Rationale: Allows evaluation of which assets show relative strength during corrections. Strong performers deserve wider stops.
Strategy 11C: Reduce Position Sizing for Correlated Assets
Formula: Adjusted Position Size = Standard Size / (1 + Correlation)
Example:
- Standard position: 10% of portfolio
- Asset correlation to existing holdings: 0.80
- Adjusted size: 10% / (1 + 0.80) = 5.6%
This mathematical approach prevents over-concentration in correlated risk.
For traders building diversified strategies, our best crypto to buy guide provides correlation matrices for major assets.
Common Stop Loss Mistakes (And How to Avoid Them)
Mistake 1: Placing Stops at Obvious Levels
Problem: Everyone else places