etf-premium

Name: etf-premium
Author: himself65

1.3kinstalls351forks

How to install etf-premium?

himself65/finance-skills/etf-premium

$npx -y skills add himself65/finance-skills --skill etf-premium

Installs into the current project.

Summary

Calculate ETF premium/discount vs NAV via Yahoo Finance, and decompose single-day surges into NAV-driven vs structural components (gamma squeeze, dealer hedging, blocked AP arbitrage). Use whenever the user asks about an ETF's premium or discount, NAV comparison, why an ETF diver

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SKILL.md

1	# ETF Premium/Discount Analysis Skill
2
3	Calculates the premium or discount of an ETF's market price relative to its Net Asset Value (NAV) using data from Yahoo Finance via [yfinance](https://github.com/ranaroussi/yfinance).
4
5	Why this matters: An ETF's market price can diverge from the value of its underlying holdings (NAV). When you buy at a premium, you're overpaying relative to the assets; at a discount, you're getting a bargain. This divergence is typically small for liquid US equity ETFs but can be significant for bond ETFs, international ETFs, leveraged/inverse products, and crypto ETFs — especially during periods of market stress.
6
7	Important: For research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.
8
9	---
10
11	## Step 1: Ensure Dependencies Are Available
12
13	Current environment status:
14
15	```
16	!`python3 -c "import yfinance, pandas, numpy; print(f'yfinance={yfinance.__version__} pandas={pandas.__version__} numpy={numpy.__version__}')" 2>/dev/null \|\| echo "DEPS_MISSING"`
17	```
18
19	If `DEPS_MISSING`, install required packages:
20
21	```python
22	import subprocess, sys
23	subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance", "pandas", "numpy"])
24	```
25
26	If already installed, skip and proceed.
27
28	---
29
30	## Step 2: Route to the Correct Sub-Skill
31
32	Classify the user's request and jump to the matching section. If the user asks a general question about an ETF's premium or discount without specifying a particular analysis type, default to Sub-Skill A (Single ETF Snapshot).
33
34	\| User Request \| Route To \| Examples \|
35	\|---\|---\|---\|
36	\| Single ETF premium/discount \| Sub-Skill A: Single ETF Snapshot \| "is SPY at a premium?", "AGG premium to NAV", "BITO premium" \|
37	\| Compare multiple ETFs \| Sub-Skill B: Multi-ETF Comparison \| "compare bond ETF discounts", "which has bigger premium IBIT or BITO", "rank these ETFs by premium" \|
38	\| Screener / find extreme premiums \| Sub-Skill C: Premium Screener \| "which ETFs have biggest discount", "find ETFs trading below NAV", "premium screener" \|
39	\| Deep analysis with context \| Sub-Skill D: Premium Deep Dive \| "why is HYG at a discount", "is ARKK premium normal", "ETF premium analysis with context" \|
40	\| Sudden premium surge / gamma squeeze \| Sub-Skill E: Premium Surge Decomposition \| "why did KWEB jump 13% today", "is this ETF rally driven by gamma", "decompose today's ETF move", "dealer GEX for SOXL", "how long until the premium converges" \|
41
42	### Defaults
43
44	\| Parameter \| Default \|
45	\|---\|---\|
46	\| Data source \| yfinance `navPrice` field \|
47	\| Price field \| `regularMarketPrice` (falls back to `previousClose`) \|
48	\| Screener universe \| Common ETF list by category (see Sub-Skill C) \|
49
50	---
51
52	## Sub-Skill A: Single ETF Snapshot
53
54	Goal: Show the current premium/discount for one ETF with context about what's normal, plus a peer comparison to show how it stacks up against similar ETFs.
55
56	### A1: Fetch and compute
57
58	```python
59	import yfinance as yf
60
61	# Peer groups by category — used to automatically compare the target ETF against its closest peers
62	CATEGORY_PEERS = {
63	"Digital Assets": ["IBIT", "BITO", "FBTC", "ETHA", "ARKB", "GBTC"],
64	"Intermediate Core Bond": ["AGG", "BND", "SCHZ"],
65	"High Yield Bond": ["HYG", "JNK", "USHY"],
66	"Long Government": ["TLT", "VGLT", "SPTL"],
67	"Emerging Markets Bond": ["EMB", "VWOB", "PCY"],
68	"Large Growth": ["QQQ", "VUG", "IWF", "SCHG"],
69	"Large Blend": ["SPY", "VOO", "IVV", "VTI"],
70	"Commodities Focused": ["GLD", "IAU", "SLV", "DBC"],
71	"China Region": ["KWEB", "FXI", "MCHI"],
72	"Trading--Leveraged Equity": ["TQQQ", "UPRO", "SOXL", "JNUG"],
73	"Trading--Inverse Equity": ["SQQQ", "SPXU", "SOXS", "JDST"],
74	"Derivative Income": ["JEPI", "JEPQ", "QYLD"],
75	"Large Value": ["SCHD", "VYM", "DVY", "HDV"],
76	}
77
78	def etf_premium_snapshot(ticker_symbol):
79	ticker = yf.Ticker(ticker_symbol)
80	info = ticker.info
81
82	# Verify this is an ETF
83	quote_type = info.get("quoteType", "")
84	if quote_type != "

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etf-premium

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View on GitHub

How to install etf-premium?

himself65/finance-skills/etf-premium

$npx -y skills add himself65/finance-skills --skill etf-premium

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# ETF Premium/Discount Analysis Skill
2
3	Calculates the premium or discount of an ETF's market price relative to its Net Asset Value (NAV) using data from Yahoo Finance via [yfinance](https://github.com/ranaroussi/yfinance).
4
5	Why this matters: An ETF's market price can diverge from the value of its underlying holdings (NAV). When you buy at a premium, you're overpaying relative to the assets; at a discount, you're getting a bargain. This divergence is typically small for liquid US equity ETFs but can be significant for bond ETFs, international ETFs, leveraged/inverse products, and crypto ETFs — especially during periods of market stress.
6
7	Important: For research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.
8
9	---
10
11	## Step 1: Ensure Dependencies Are Available
12
13	Current environment status:
14
15	```
16	!`python3 -c "import yfinance, pandas, numpy; print(f'yfinance={yfinance.__version__} pandas={pandas.__version__} numpy={numpy.__version__}')" 2>/dev/null \|\| echo "DEPS_MISSING"`
17	```
18
19	If `DEPS_MISSING`, install required packages:
20
21	```python
22	import subprocess, sys
23	subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance", "pandas", "numpy"])
24	```
25
26	If already installed, skip and proceed.
27
28	---
29
30	## Step 2: Route to the Correct Sub-Skill
31
32	Classify the user's request and jump to the matching section. If the user asks a general question about an ETF's premium or discount without specifying a particular analysis type, default to Sub-Skill A (Single ETF Snapshot).
33
34	\| User Request \| Route To \| Examples \|
35	\|---\|---\|---\|
36	\| Single ETF premium/discount \| Sub-Skill A: Single ETF Snapshot \| "is SPY at a premium?", "AGG premium to NAV", "BITO premium" \|
37	\| Compare multiple ETFs \| Sub-Skill B: Multi-ETF Comparison \| "compare bond ETF discounts", "which has bigger premium IBIT or BITO", "rank these ETFs by premium" \|
38	\| Screener / find extreme premiums \| Sub-Skill C: Premium Screener \| "which ETFs have biggest discount", "find ETFs trading below NAV", "premium screener" \|
39	\| Deep analysis with context \| Sub-Skill D: Premium Deep Dive \| "why is HYG at a discount", "is ARKK premium normal", "ETF premium analysis with context" \|
40	\| Sudden premium surge / gamma squeeze \| Sub-Skill E: Premium Surge Decomposition \| "why did KWEB jump 13% today", "is this ETF rally driven by gamma", "decompose today's ETF move", "dealer GEX for SOXL", "how long until the premium converges" \|
41
42	### Defaults
43
44	\| Parameter \| Default \|
45	\|---\|---\|
46	\| Data source \| yfinance `navPrice` field \|
47	\| Price field \| `regularMarketPrice` (falls back to `previousClose`) \|
48	\| Screener universe \| Common ETF list by category (see Sub-Skill C) \|
49
50	---
51
52	## Sub-Skill A: Single ETF Snapshot
53
54	Goal: Show the current premium/discount for one ETF with context about what's normal, plus a peer comparison to show how it stacks up against similar ETFs.
55
56	### A1: Fetch and compute
57
58	```python
59	import yfinance as yf
60
61	# Peer groups by category — used to automatically compare the target ETF against its closest peers
62	CATEGORY_PEERS = {
63	"Digital Assets": ["IBIT", "BITO", "FBTC", "ETHA", "ARKB", "GBTC"],
64	"Intermediate Core Bond": ["AGG", "BND", "SCHZ"],
65	"High Yield Bond": ["HYG", "JNK", "USHY"],
66	"Long Government": ["TLT", "VGLT", "SPTL"],
67	"Emerging Markets Bond": ["EMB", "VWOB", "PCY"],
68	"Large Growth": ["QQQ", "VUG", "IWF", "SCHG"],
69	"Large Blend": ["SPY", "VOO", "IVV", "VTI"],
70	"Commodities Focused": ["GLD", "IAU", "SLV", "DBC"],
71	"China Region": ["KWEB", "FXI", "MCHI"],
72	"Trading--Leveraged Equity": ["TQQQ", "UPRO", "SOXL", "JNUG"],
73	"Trading--Inverse Equity": ["SQQQ", "SPXU", "SOXS", "JDST"],
74	"Derivative Income": ["JEPI", "JEPQ", "QYLD"],
75	"Large Value": ["SCHD", "VYM", "DVY", "HDV"],
76	}
77
78	def etf_premium_snapshot(ticker_symbol):
79	ticker = yf.Ticker(ticker_symbol)
80	info = ticker.info
81
82	# Verify this is an ETF
83	quote_type = info.get("quoteType", "")
84	if quote_type != "

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