mcpbeat

Backtest

marketcalls/backtest

Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
183
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills --skill backtest

The instruction itself

5 sections, as written by the author

Create a complete VectorBT backtest script for the user.

Arguments

Parse $ARGUMENTS as: strategy symbol exchange interval

  • $0 = strategy name (e.g., ema-crossover, rsi, donchian, supertrend, macd, sda2, momentum)
  • $1 = symbol (e.g., SBIN, RELIANCE, NIFTY). Default: SBIN
  • $2 = exchange (e.g., NSE, NFO). Default: NSE
  • $3 = interval (e.g., D, 1h, 5m). Default: D

If no arguments, ask the user which strategy they want.

Instructions

  • Read the vectorbt-expert skill rules for reference patterns
  • Create backtesting/{strategy_name}/ directory if it doesn't exist (on-demand)
  • Create a .py file in backtesting/{strategy_name}/ named {symbol}_{strategy}_backtest.py
  • Use the matching template from rules/assets/{strategy}/backtest.py as the starting point
  • The script must:
  • Load .env from the project root using find_dotenv() (walks up from script dir automatically)
  • Fetch data via client.history() from OpenAlgo
  • If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True) instead of OpenAlgo API. Auto-detect format: Historify (market_data table, epoch timestamps) vs custom (ohlcv table, date+time). See vectorbt-expert rules/duckdb-data.md.
  • If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback.
  • Use OpenAlgo ta for ALL indicators by default (EMA, SMA, RSI, MACD, BBands, ATR, ADX, STDDEV, MOM, and 90+ more) - from openalgo import ta
  • Only use TA-Lib if the user explicitly says "talib"/"TA-Lib" in their request; specialty indicators (Supertrend, Donchian, Ichimoku, HMA, KAMA, ALMA, ZLEMA, VWMA) always come from OpenAlgo ta regardless, since TA-Lib has no equivalent
  • Use ta.exrem() to clean duplicate signals (always .fillna(False) before exrem)
  • Run vbt.Portfolio.from_signals() with min_size=1, size_granularity=1
  • Indian delivery fees: fees=0.00111, fixed_fees=20 for delivery equity
  • Fetch NIFTY benchmark via OpenAlgo (symbol="NIFTY", exchange="NSE_INDEX")
  • Print full pf.stats()
  • Print Strategy vs Benchmark comparison table (Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor)
  • Explain the backtest report in plain language for normal traders
  • Generate the OpenStatz interactive dashboard tearsheet via ostz.dashboard(...) if openstatz is available - a self-contained offline HTML file, no server needed (always use OpenStatz, never QuantStats; never the legacy ostz.reports.html static report). Set strategy_returns.name (e.g. "EMA 20/50 Crossover - SBIN") and benchmark.name before calling dashboard() - that name, not the title= argument, is what the tearsheet shows as the strategy header/column/legend (see the openstatz-tearsheet rule)
  • Plot equity curve + drawdown using Plotly (template="plotly_dark")
  • Export trades to CSV
  • Never use icons/emojis in code or logger output
  • For futures symbols (NIFTY, BANKNIFTY), use lot-size-aware sizing:
  • NIFTY: min_size=65, size_granularity=65 (effective 31 Dec 2025)
  • BANKNIFTY: min_size=30, size_granularity=30
  • Use fees=0.00018, fixed_fees=20 for F&O futures

Available Strategies

| Strategy | Keyword | Template |

|----------|---------|----------|

| EMA Crossover | ema-crossover | assets/ema_crossover/backtest.py |

| RSI | rsi | assets/rsi/backtest.py |

| Donchian Channel | donchian | assets/donchian/backtest.py |

| Supertrend | supertrend | assets/supertrend/backtest.py |

| MACD Breakout | macd | assets/macd/backtest.py |

| SDA2 | sda2 | assets/sda2/backtest.py |

| Momentum | momentum | assets/momentum/backtest.py |

| Dual Momentum | dual-momentum | assets/dual_momentum/backtest.py |

| Buy & Hold | buy-hold | assets/buy_hold/backtest.py |

| RSI Accumulation | rsi-accumulation | assets/rsi_accumulation/backtest.py |

Benchmark Rules

  • Default: NIFTY 50 via OpenAlgo (symbol="NIFTY", exchange="NSE_INDEX")
  • If user specifies a different benchmark, use that instead
  • For yfinance: use ^NSEI for India, ^GSPC (S&P 500) for US markets
  • Always compare: Total Return, Sharpe, Sortino, Max Drawdown

Example Usage

/backtest ema-crossover RELIANCE NSE D

/backtest rsi SBIN

/backtest supertrend NIFTY NFO 5m

How to use it

Copy the folder

Take marketcalls/backtest from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.