vectorbt-expert

Name: vectorbt-expert
Author: marketcalls

177stars45forks

How to install vectorbt-expert?

marketcalls/vectorbt-backtesting-skills/vectorbt-expert

$npx -y skills add marketcalls/vectorbt-backtesting-skills --skill vectorbt-expert

Installs into the current project.

Summary

VectorBT backtesting expert. Use when user asks to backtest strategies, create entry/exit signals, analyze portfolio performance, optimize parameters, fetch historical data, use VectorBT/vectorbt, compare strategies, position sizing, equity curves, drawdown charts, or trade analy

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SKILL.md

1	# VectorBT Backtesting Expert Skill
2
3	## Environment
4
5	- Python with vectorbt, pandas, numpy, plotly
6	- Data sources: OpenAlgo (Indian markets), DuckDB (direct database), yfinance (US/Global), CCXT (Crypto), custom providers
7	- DuckDB support: supports both custom DuckDB and OpenAlgo Historify format
8	- API keys loaded from single root `.env` via `python-dotenv` + `find_dotenv()` — never hardcode keys
9	- Technical indicators: OpenAlgo ta (DEFAULT - `from openalgo import ta`, 100+ indicators covering trend/momentum/volatility/volume/oscillators/statistical/hybrid). Use TA-Lib only if the user explicitly asks for TA-Lib/talib. NEVER use VectorBT built-in indicators either way.
10	- Specialty indicators (no TA-Lib equivalent, always `openalgo.ta`): Supertrend, Donchian, Ichimoku, HMA, KAMA, ALMA, ZLEMA, VWMA
11	- Signal cleaning: `openalgo.ta` for exrem, crossover, crossunder, flip (always, regardless of indicator library)
12	- Fee model: Indian market standard (STT + statutory charges + Rs 20/order)
13	- Benchmark: NIFTY 50 via OpenAlgo (`NSE_INDEX`) by default
14	- Charts: Plotly with `template="plotly_dark"`
15	- Environment variables loaded from single `.env` at project root via `find_dotenv()` (walks up from script dir)
16	- Scripts go in `backtesting/{strategy_name}/` directories (created on-demand, not pre-created)
17	- Never use icons/emojis in code or logger output
18
19	## Critical Rules
20
21	1. Default to OpenAlgo ta (`from openalgo import ta`) for ALL technical indicators (EMA, SMA, RSI, MACD, BBANDS, ATR, ADX, STDDEV, MOM, and 90+ more). Only use TA-Lib if the user explicitly requests "talib"/"TA-Lib" in their prompt. NEVER use `vbt.MA.run()`, `vbt.RSI.run()`, or any VectorBT built-in indicator with either library.
22	2. Always use OpenAlgo ta for indicators not in TA-Lib at all: Supertrend, Donchian, Ichimoku, HMA, KAMA, ALMA, ZLEMA, VWMA - these have no TA-Lib equivalent, so they're openalgo.ta even in a TA-Lib-opt-in script.
23	3. Use OpenAlgo ta for signal utilities: `ta.exrem()`, `ta.crossover()`, `ta.crossunder()`, `ta.flip()`. If `openalgo.ta` is not importable (standalone DuckDB), use inline `exrem()` fallback. See [duckdb-data](rules/duckdb-data.md).
24	4. Always clean signals with `ta.exrem()` after generating raw buy/sell signals. Always `.fillna(False)` before exrem.
25	5. Market-specific fees: India ([indian-market-costs](rules/indian-market-costs.md)), US ([us-market-costs](rules/us-market-costs.md)), Crypto ([crypto-market-costs](rules/crypto-market-costs.md)). Auto-select based on user's market.
26	6. Default benchmarks: India=NIFTY via OpenAlgo, US=S&P 500 (`^GSPC`), Crypto=Bitcoin (`BTC-USD`). See [data-fetching](rules/data-fetching.md) Market Selection Guide.
27	7. Always produce a Strategy vs Benchmark comparison table after every backtest.
28	8. Always explain the backtest report in plain language so even normal traders understand risk and strength.
29	9. Plotly candlestick charts must use `xaxis type="category"` to avoid weekend gaps.
30	10. Whole shares: Always set `min_size=1, size_granularity=1` for equities.
31	11. DuckDB data loading: When user provides a DuckDB path, load data directly using `duckdb.connect()` with `read_only=True`. Auto-detect format: OpenAlgo Historify (table `market_data`, epoch timestamps) vs custom (table `ohlcv`, date+time columns). See [duckdb-data](rules/duckdb-data.md).
32
33	## Modular Rule Files
34
35	Detailed reference for each topic is in `rules/`:
36
37	\| Rule File \| Topic \|
38	\|-----------\|-------\|
39	\| [data-fetching](rules/data-fetching.md) \| OpenAlgo (India), yfinance (US), CCXT (Crypto), custom providers, .env setup \|
40	\| [simulation-modes](rules/simulation-modes.md) \| from_signals, from_orders, from_holding, direction types \|
41	\| [position-sizing](rules/position-sizing.md) \| Amount/Value/Percent/TargetPercent sizing \|
42	\| [indicators-signals](rules/indicators-signals.md) \| OpenAlgo ta indicator reference (default), TA-Lib opt-in, signal generation \|
43	\| [openalgo-ta-helpers](rules/openalgo-ta-helpers.md) \| Complete OpenAlgo ta catalog (100+ indicators): exrem, crossover, Supertrend, Donchian, Ichimoku, MAs \|
44	\| [stop-loss-take-profit](rules/stop-loss-take-profit.md) \| Fixed SL, TP, trailing stop \|
45	\| [parameter-optimization](rules/parameter-optimization.md) \| Broadcasting and loop-based optimization \|
46	\| [performance-analysis](rules/performance-analysis.md) \| Stats, metrics, benchmark comparison, CAGR \|
47	\| [plotting](rules/plotting.md) \| Candlestick (category x-axis), VectorBT plots, custom Plotly \|
48	\| [indian-market-costs](rules/indian-ma

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vectorbt-expert

177stars45forks

View on GitHub

How to install vectorbt-expert?

marketcalls/vectorbt-backtesting-skills/vectorbt-expert

$npx -y skills add marketcalls/vectorbt-backtesting-skills --skill vectorbt-expert

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# VectorBT Backtesting Expert Skill
2
3	## Environment
4
5	- Python with vectorbt, pandas, numpy, plotly
6	- Data sources: OpenAlgo (Indian markets), DuckDB (direct database), yfinance (US/Global), CCXT (Crypto), custom providers
7	- DuckDB support: supports both custom DuckDB and OpenAlgo Historify format
8	- API keys loaded from single root `.env` via `python-dotenv` + `find_dotenv()` — never hardcode keys
9	- Technical indicators: OpenAlgo ta (DEFAULT - `from openalgo import ta`, 100+ indicators covering trend/momentum/volatility/volume/oscillators/statistical/hybrid). Use TA-Lib only if the user explicitly asks for TA-Lib/talib. NEVER use VectorBT built-in indicators either way.
10	- Specialty indicators (no TA-Lib equivalent, always `openalgo.ta`): Supertrend, Donchian, Ichimoku, HMA, KAMA, ALMA, ZLEMA, VWMA
11	- Signal cleaning: `openalgo.ta` for exrem, crossover, crossunder, flip (always, regardless of indicator library)
12	- Fee model: Indian market standard (STT + statutory charges + Rs 20/order)
13	- Benchmark: NIFTY 50 via OpenAlgo (`NSE_INDEX`) by default
14	- Charts: Plotly with `template="plotly_dark"`
15	- Environment variables loaded from single `.env` at project root via `find_dotenv()` (walks up from script dir)
16	- Scripts go in `backtesting/{strategy_name}/` directories (created on-demand, not pre-created)
17	- Never use icons/emojis in code or logger output
18
19	## Critical Rules
20
21	1. Default to OpenAlgo ta (`from openalgo import ta`) for ALL technical indicators (EMA, SMA, RSI, MACD, BBANDS, ATR, ADX, STDDEV, MOM, and 90+ more). Only use TA-Lib if the user explicitly requests "talib"/"TA-Lib" in their prompt. NEVER use `vbt.MA.run()`, `vbt.RSI.run()`, or any VectorBT built-in indicator with either library.
22	2. Always use OpenAlgo ta for indicators not in TA-Lib at all: Supertrend, Donchian, Ichimoku, HMA, KAMA, ALMA, ZLEMA, VWMA - these have no TA-Lib equivalent, so they're openalgo.ta even in a TA-Lib-opt-in script.
23	3. Use OpenAlgo ta for signal utilities: `ta.exrem()`, `ta.crossover()`, `ta.crossunder()`, `ta.flip()`. If `openalgo.ta` is not importable (standalone DuckDB), use inline `exrem()` fallback. See [duckdb-data](rules/duckdb-data.md).
24	4. Always clean signals with `ta.exrem()` after generating raw buy/sell signals. Always `.fillna(False)` before exrem.
25	5. Market-specific fees: India ([indian-market-costs](rules/indian-market-costs.md)), US ([us-market-costs](rules/us-market-costs.md)), Crypto ([crypto-market-costs](rules/crypto-market-costs.md)). Auto-select based on user's market.
26	6. Default benchmarks: India=NIFTY via OpenAlgo, US=S&P 500 (`^GSPC`), Crypto=Bitcoin (`BTC-USD`). See [data-fetching](rules/data-fetching.md) Market Selection Guide.
27	7. Always produce a Strategy vs Benchmark comparison table after every backtest.
28	8. Always explain the backtest report in plain language so even normal traders understand risk and strength.
29	9. Plotly candlestick charts must use `xaxis type="category"` to avoid weekend gaps.
30	10. Whole shares: Always set `min_size=1, size_granularity=1` for equities.
31	11. DuckDB data loading: When user provides a DuckDB path, load data directly using `duckdb.connect()` with `read_only=True`. Auto-detect format: OpenAlgo Historify (table `market_data`, epoch timestamps) vs custom (table `ohlcv`, date+time columns). See [duckdb-data](rules/duckdb-data.md).
32
33	## Modular Rule Files
34
35	Detailed reference for each topic is in `rules/`:
36
37	\| Rule File \| Topic \|
38	\|-----------\|-------\|
39	\| [data-fetching](rules/data-fetching.md) \| OpenAlgo (India), yfinance (US), CCXT (Crypto), custom providers, .env setup \|
40	\| [simulation-modes](rules/simulation-modes.md) \| from_signals, from_orders, from_holding, direction types \|
41	\| [position-sizing](rules/position-sizing.md) \| Amount/Value/Percent/TargetPercent sizing \|
42	\| [indicators-signals](rules/indicators-signals.md) \| OpenAlgo ta indicator reference (default), TA-Lib opt-in, signal generation \|
43	\| [openalgo-ta-helpers](rules/openalgo-ta-helpers.md) \| Complete OpenAlgo ta catalog (100+ indicators): exrem, crossover, Supertrend, Donchian, Ichimoku, MAs \|
44	\| [stop-loss-take-profit](rules/stop-loss-take-profit.md) \| Fixed SL, TP, trailing stop \|
45	\| [parameter-optimization](rules/parameter-optimization.md) \| Broadcasting and loop-based optimization \|
46	\| [performance-analysis](rules/performance-analysis.md) \| Stats, metrics, benchmark comparison, CAGR \|
47	\| [plotting](rules/plotting.md) \| Candlestick (category x-axis), VectorBT plots, custom Plotly \|
48	\| [indian-market-costs](rules/indian-ma

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