Futures backtesting has pitfalls that equity backtesting doesn't: contract rolls distort returns, near/far spreads behave differently near expiry, and basis convergence is non-linear. alphabench's Quant agent handles all of this through specialised futures tools that account for expiry calendars, roll adjustments, and multi-contract positions.
1. Continuous contract momentum strategy
The simplest futures backtest is trend-following on a continuous (back-adjusted) contract:
"Backtest a momentum strategy on NIFTY futures. Go long when 20-day EMA crosses above 50-day EMA, exit when it crosses below. Test the last 3 years using continuous (back-adjusted) contracts."
The Quant agent calls backtest_futures with back-adjusted price series so the roll
gap doesn't create false signals. You'll get:
- Equity curve with each roll point marked
- Per-trade P&L including financing cost estimates
- Sharpe, CAGR, max drawdown
- Roll cost impact (how much the back-adjustment affected returns)
Common single-contract futures setups:
- Index futures (NIFTY, BANKNIFTY) for trend following or mean-reversion
- Single-stock futures for large-caps (RELIANCE
NSE:RELIANCE, HDFCBANK 
NSE:HDFCBANK, INFY 
NSE:INFY, TCS 
NSE:TCS) - Commodity futures for cross-asset portfolios (NSE-listed only)
2. Calendar spread (near vs far contract)
Calendar spreads profit from the spread between near and far expiry contracts narrowing or widening. This is distinct from a directional futures position. You're trading the shape of the futures curve, not the underlying price.
"Backtest a long calendar spread on BANKNIFTY futures: buy the near-month contract, sell the next-month contract. Enter when the spread is below its 30-day average, exit when it reverts to average. Test the last 2 years."
The Quant agent calls backtest_futures_calendar which:
- Tracks both legs independently through each expiry
- Handles near-leg expiry roll automatically (rolls the short leg on rollover day)
- Computes net P&L as spread convergence/divergence, not raw price move
- Returns per-trade spread entry, exit, and realised move
3. Cash-and-carry basis trade
A basis trade exploits the difference between the futures price and the spot price (the "basis"). As expiry approaches, the basis converges to zero. A classic carry trade is: buy spot, sell futures, collect the spread as it converges.
"Backtest a cash-and-carry basis trade on RELIANCE: when futures trade at more than 0.5% premium to spot, short the futures and notionally hold spot. Exit at 0.1% premium or on expiry. Test the last 18 months."
The Quant agent calls backtest_futures_basis. The tool:
- Computes the basis (futures - spot) at each bar
- Simulates entry when basis crosses your threshold
- Accounts for the convergence path (non-linear near expiry)
- Estimates financing cost on the spot leg
4. Hedged equity + futures
A common institutional strategy: hold a diversified equity portfolio and hedge the systematic risk with index futures. The futures leg creates a beta-neutral (or partially neutral) book.
"Backtest a hedged equity strategy: hold Nifty 50 INDICES:NIFTY 50 stocks, short NIFTY futures to hedge 70% of portfolio beta. Rebalance the hedge monthly. Test the last 3 years."
The Quant agent calls backtest_futures_hedged:
- Computes portfolio beta vs NIFTY at each rebalance point
- Sizes the futures short to achieve the target hedge ratio
- Separates alpha (stock selection) from market return in the equity curve
- Returns Sharpe for the hedged vs unhedged portfolio side-by-side
5. Intraday futures on 1m / 5m bars
For intraday futures strategies, the platform constructs 1-minute or 5-minute OHLC bars from tick data:
"Backtest an intraday momentum strategy on NIFTY futures: go long when 5-minute bar closes above the 15-period VWAP with volume > 1.5x average, exit at 15:15 or when RSI exceeds 70. Test June 2024 to June 2025."
The Quant agent calls backtest_futures_intraday:
- Runs on intraday OHLC bars (1m or 5m) not daily close data
- Supports VWAP, intraday EMAs, opening range, volume filters
- EOD flat: all positions close at 15:25 automatically
- Returns time-of-day P&L heatmap so you can see which sessions the strategy works
6. Reading futures backtest results
All futures backtests return:
| Field | What it tells you |
|---|---|
| Equity curve | Cumulative P&L with roll events marked |
| Per-trade table | Entry/exit date, price, quantity, P&L, roll-adjusted basis |
| Roll cost summary | Total drag from contract rolls across the test period |
| Sharpe / CAGR / Max DD | Standard metrics on roll-adjusted returns |
| Financing cost estimate | Implicit cost of holding the futures position overnight |
For calendar and basis trades, there's an additional spread P&L breakdown showing what each leg contributed.
7. Validate before deploying
Futures strategies benefit from the same validation workflow as equity strategies:
"Run a walk-forward test on the NIFTY calendar spread strategy with 6 folds and a 70/30 split."
See Walk-Forward and Monte Carlo Validation for the full workflow. The stitched out-of-sample equity curve is especially important for calendar spreads where the in-sample period can have unusual carry regimes.