exit-strategies

Name: exit-strategies
Author: agiprolabs

216installs53forks

How to install exit-strategies?

agiprolabs/claude-trading-skills/exit-strategies

$npx -y skills add agiprolabs/claude-trading-skills --skill exit-strategies

Installs into the current project.

Summary

Systematic exit rules, stop-loss methods, take-profit strategies, and trailing stop implementations for crypto trading

Files · 1

View on GitHub

SKILL.md

1	# Exit Strategies
2
3	Entries are easy, exits are everything. A mediocre entry with a disciplined exit will
4	outperform a perfect entry with no exit plan. This skill covers systematic, rule-based
5	exit methods for crypto and Solana token trading.
6
7	## Why Exits Matter
8
9	- Entries determine _if_ you participate. Exits determine _how much_ you keep.
10	- Most traders spend 90% of effort on entries and 10% on exits — invert this.
11	- Without defined exits you rely on emotion, which guarantees inconsistency.
12	- Every trade should have three exits defined before entry: stop loss, take profit,
13	and trailing stop.
14
15	## Exit Categories
16
17	### 1. Stop Loss — Risk Management Exits
18
19	Predefined price level where you close the position to cap downside.
20
21	\| Method \| Description \| Best For \|
22	\|--------\|-------------\|----------\|
23	\| Fixed percentage \| Exit at entry − X% \| Simple setups, beginners \|
24	\| ATR-based \| Entry − ATR(14) × multiplier \| Volatility-adaptive \|
25	\| Support level \| Below nearest swing low \| Technically defined risk \|
26	\| Maximum loss \| Absolute SOL/USD cap \| Account protection \|
27
28	ATR-based stop (recommended default):
29
30	```python
31	import pandas_ta as ta
32
33	atr = df.ta.atr(length=14)
34	stop_loss = entry_price - (atr.iloc[-1] * 2.0) # 2x ATR below entry
35	```
36
37	Multiplier guide:
38	- 1.5× — Tight. High win rate needed. Good for scalps.
39	- 2.0× — Standard. Balances noise filtering with risk.
40	- 3.0× — Wide. For swing trades in volatile conditions.
41
42	See `references/stop_loss_methods.md` for complete methodology.
43
44	### 2. Take Profit — Target Exits
45
46	Predefined levels where you lock in gains.
47
48	Fixed risk/reward targets:
49
50	```python
51	risk = entry_price - stop_loss_price
52	tp_2r = entry_price + (risk * 2) # 2:1 R:R
53	tp_3r = entry_price + (risk * 3) # 3:1 R:R
54	tp_5r = entry_price + (risk * 5) # 5:1 R:R
55	```
56
57	Scaled exit framework (recommended for meme/PumpFun tokens):
58
59	\| Tranche \| Size \| Target \| Action After \|
60	\|---------\|------\|--------\|--------------\|
61	\| 1 \| 25% \| 2× risk \| Move stop to breakeven \|
62	\| 2 \| 25% \| 3–5× risk \| Trail remainder \|
63	\| 3 \| 25% \| 5–10× risk \| Tighten trail \|
64	\| 4 \| 25% \| Trailing stop \| Moonbag — let it ride \|
65
66	Market cap milestone exits:
67
68	For PumpFun and meme tokens where R:R ratios are less meaningful:
69
70	```python
71	milestones = [
72	{"mcap": 50_000, "sell_pct": 0.25, "label": "Cover cost"},
73	{"mcap": 100_000, "sell_pct": 0.25, "label": "Lock profit"},
74	{"mcap": 500_000, "sell_pct": 0.25, "label": "Major profit"},
75	# Hold 25% as moonbag with trailing stop
76	]
77	```
78
79	See `references/take_profit_strategies.md` for full methodology including Fibonacci
80	extension targets and volume-based exits.
81
82	### 3. Trailing Stop — Trend-Following Exits
83
84	Dynamic stops that follow price upward but never move down.
85
86	Percentage trailing:
87
88	```python
89	def percentage_trailing_stop(
90	current_price: float,
91	highest_since_entry: float,
92	trail_pct: float = 0.10,
93	) -> tuple[float, bool]:
94	"""Return (stop_level, triggered)."""
95	highest = max(highest_since_entry, current_price)
96	stop = highest * (1 - trail_pct)
97	return stop, current_price <= stop
98	```
99
100	ATR trailing (Chandelier Exit):
101
102	```python
103	def chandelier_exit(
104	highs: list[float],
105	atr_value: float,
106	multiplier: float = 2.5,
107	lookback: int = 22,
108	) -> float:
109	"""Highest high over lookback minus ATR * multiplier."""
110	highest_high = max(highs[-lookback:])
111	return highest_high - (atr_value * multiplier)
112	```
113
114	EMA trailing:
115
116	```python
117	# Exit when close < EMA for M consecutive bars
118	ema = df.ta.ema(length=20)
119	below_ema = df["close"] < ema
120	consecutive_below = below_ema.rolling(3).sum() == 3 # 3 bars below
121	```
122
123	Typical EMA periods: 10 (scalp), 20 (day trade), 50 (swing).
124
125	See `references/trailing_stops.md` for Parabolic SAR, SuperTrend, and step trailing.
126
127	### 4. Time-Based Exits
128
129	Exit if the trade hasn't moved in your favor within a defined window.
130
131	```python
132	bars_since_entry = current_bar - entry_bar
133	if bars_since_entry > max_hold_bars and current_pnl <= 0:
134	exit_reason = "time_stop"
135	```
136
137	Guidelines:
138	- Scalp: 5–15 minutes
139	- Day trade: 4–8 hours
140	- Swing: 3–5 days
141	- PumpFun snipe: 2–10 minutes (token-specific)
142
143	Time stops prevent capital from sitting in dead trades.
144
145	### 5. Signal-Based Exits
146
147	Exit when the indicator that generated the entry signal reverses.
148
149	```python
150	# RSI reversal exit
151	rsi = df.ta.rsi(length=14)
152	if position == "long" and rsi.iloc[-1] > 70:
153	exit_reason = "rsi_overbought"
154
155	# MACD crossover exit
156	macd = df.ta.macd()
157	if macd["MACDs_12_26_9"].iloc[-1] < macd["MACDh_12_26_9"].iloc[-1]:
158	exit_reason = "macd_bearish_cross"
159	```
160
161	Signal exits work well when combined with trailing stops — the signal triggers
162	tightening the trail rather than an immediate full exit.
163
164	### 6. Liquidity-Based Exits
165
166	Exit when volume or liquidity dete

People who liked this also viewed

6 picks

Type

azure-costAzure cost management: query costs, forecast spending, optimize to reduce waste. WHEN: \"Azure costs\", \"Azure bill\", \"cost breakdown\", \"how much am I spending\", \"forecast spending\", \"optimizSkillsJul 2026275k1.3k
pricingWhen the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increaseSkillsJul 202638k41k
stripe-integrationMulti-harness agentic plugin marketplace for Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, and Gemini CLISkillsJul 202611k38k
startup-financial-modelingMulti-harness agentic plugin marketplace for Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, and Gemini CLISkillsJul 20269.5k38k
tushare-finance专为 Claude Code 设计的 Tushare Pro 金融数据技能包，支持 220+ 个接口，用自然语言获取 A 股行情、财务数据、宏观经济等金融数据。SkillsJul 20265.0k75
azure-pricingFetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure seSkillsJul 20264.5k37k

exit-strategies

216installs53forks

View on GitHub

How to install exit-strategies?

agiprolabs/claude-trading-skills/exit-strategies

$npx -y skills add agiprolabs/claude-trading-skills --skill exit-strategies

Installs into the current project.

Summary

Systematic exit rules, stop-loss methods, take-profit strategies, and trailing stop implementations for crypto trading

Files · 1

View on GitHub

SKILL.md

1	# Exit Strategies
2
3	Entries are easy, exits are everything. A mediocre entry with a disciplined exit will
4	outperform a perfect entry with no exit plan. This skill covers systematic, rule-based
5	exit methods for crypto and Solana token trading.
6
7	## Why Exits Matter
8
9	- Entries determine _if_ you participate. Exits determine _how much_ you keep.
10	- Most traders spend 90% of effort on entries and 10% on exits — invert this.
11	- Without defined exits you rely on emotion, which guarantees inconsistency.
12	- Every trade should have three exits defined before entry: stop loss, take profit,
13	and trailing stop.
14
15	## Exit Categories
16
17	### 1. Stop Loss — Risk Management Exits
18
19	Predefined price level where you close the position to cap downside.
20
21	\| Method \| Description \| Best For \|
22	\|--------\|-------------\|----------\|
23	\| Fixed percentage \| Exit at entry − X% \| Simple setups, beginners \|
24	\| ATR-based \| Entry − ATR(14) × multiplier \| Volatility-adaptive \|
25	\| Support level \| Below nearest swing low \| Technically defined risk \|
26	\| Maximum loss \| Absolute SOL/USD cap \| Account protection \|
27
28	ATR-based stop (recommended default):
29
30	```python
31	import pandas_ta as ta
32
33	atr = df.ta.atr(length=14)
34	stop_loss = entry_price - (atr.iloc[-1] * 2.0) # 2x ATR below entry
35	```
36
37	Multiplier guide:
38	- 1.5× — Tight. High win rate needed. Good for scalps.
39	- 2.0× — Standard. Balances noise filtering with risk.
40	- 3.0× — Wide. For swing trades in volatile conditions.
41
42	See `references/stop_loss_methods.md` for complete methodology.
43
44	### 2. Take Profit — Target Exits
45
46	Predefined levels where you lock in gains.
47
48	Fixed risk/reward targets:
49
50	```python
51	risk = entry_price - stop_loss_price
52	tp_2r = entry_price + (risk * 2) # 2:1 R:R
53	tp_3r = entry_price + (risk * 3) # 3:1 R:R
54	tp_5r = entry_price + (risk * 5) # 5:1 R:R
55	```
56
57	Scaled exit framework (recommended for meme/PumpFun tokens):
58
59	\| Tranche \| Size \| Target \| Action After \|
60	\|---------\|------\|--------\|--------------\|
61	\| 1 \| 25% \| 2× risk \| Move stop to breakeven \|
62	\| 2 \| 25% \| 3–5× risk \| Trail remainder \|
63	\| 3 \| 25% \| 5–10× risk \| Tighten trail \|
64	\| 4 \| 25% \| Trailing stop \| Moonbag — let it ride \|
65
66	Market cap milestone exits:
67
68	For PumpFun and meme tokens where R:R ratios are less meaningful:
69
70	```python
71	milestones = [
72	{"mcap": 50_000, "sell_pct": 0.25, "label": "Cover cost"},
73	{"mcap": 100_000, "sell_pct": 0.25, "label": "Lock profit"},
74	{"mcap": 500_000, "sell_pct": 0.25, "label": "Major profit"},
75	# Hold 25% as moonbag with trailing stop
76	]
77	```
78
79	See `references/take_profit_strategies.md` for full methodology including Fibonacci
80	extension targets and volume-based exits.
81
82	### 3. Trailing Stop — Trend-Following Exits
83
84	Dynamic stops that follow price upward but never move down.
85
86	Percentage trailing:
87
88	```python
89	def percentage_trailing_stop(
90	current_price: float,
91	highest_since_entry: float,
92	trail_pct: float = 0.10,
93	) -> tuple[float, bool]:
94	"""Return (stop_level, triggered)."""
95	highest = max(highest_since_entry, current_price)
96	stop = highest * (1 - trail_pct)
97	return stop, current_price <= stop
98	```
99
100	ATR trailing (Chandelier Exit):
101
102	```python
103	def chandelier_exit(
104	highs: list[float],
105	atr_value: float,
106	multiplier: float = 2.5,
107	lookback: int = 22,
108	) -> float:
109	"""Highest high over lookback minus ATR * multiplier."""
110	highest_high = max(highs[-lookback:])
111	return highest_high - (atr_value * multiplier)
112	```
113
114	EMA trailing:
115
116	```python
117	# Exit when close < EMA for M consecutive bars
118	ema = df.ta.ema(length=20)
119	below_ema = df["close"] < ema
120	consecutive_below = below_ema.rolling(3).sum() == 3 # 3 bars below
121	```
122
123	Typical EMA periods: 10 (scalp), 20 (day trade), 50 (swing).
124
125	See `references/trailing_stops.md` for Parabolic SAR, SuperTrend, and step trailing.
126
127	### 4. Time-Based Exits
128
129	Exit if the trade hasn't moved in your favor within a defined window.
130
131	```python
132	bars_since_entry = current_bar - entry_bar
133	if bars_since_entry > max_hold_bars and current_pnl <= 0:
134	exit_reason = "time_stop"
135	```
136
137	Guidelines:
138	- Scalp: 5–15 minutes
139	- Day trade: 4–8 hours
140	- Swing: 3–5 days
141	- PumpFun snipe: 2–10 minutes (token-specific)
142
143	Time stops prevent capital from sitting in dead trades.
144
145	### 5. Signal-Based Exits
146
147	Exit when the indicator that generated the entry signal reverses.
148
149	```python
150	# RSI reversal exit
151	rsi = df.ta.rsi(length=14)
152	if position == "long" and rsi.iloc[-1] > 70:
153	exit_reason = "rsi_overbought"
154
155	# MACD crossover exit
156	macd = df.ta.macd()
157	if macd["MACDs_12_26_9"].iloc[-1] < macd["MACDh_12_26_9"].iloc[-1]:
158	exit_reason = "macd_bearish_cross"
159	```
160
161	Signal exits work well when combined with trailing stops — the signal triggers
162	tightening the trail rather than an immediate full exit.
163
164	### 6. Liquidity-Based Exits
165
166	Exit when volume or liquidity dete

People who liked this also viewed

6 picks

Type