Cash-futures arbitrage in India: how traders profit from price discrepancies

The no-arbitrage pricing principle

In a frictionless market, the theoretical price of a stock futures contract is determined by the spot price plus the cost of holding the stock until expiry. This is called the cost of carry model:

F = S × e^((r - q) × t)

Where:

• F = theoretical futures price
• S = current spot price of the stock
• r = risk-free interest rate (annualised, typically 10-year G-Sec yield)
• q = expected dividend yield over the futures contract period
• t = time to expiry in years

A simpler approximation for short tenors:

F ≈ S × (1 + (r - q) × t)

When the actual futures price diverges from this theoretical price, an arbitrage opportunity exists. The market typically corrects these discrepancies quickly — that is exactly what arbitrageurs do.

Long stock + short futures arbitrage

The most common and accessible form of cash-futures arbitrage in India.

When to set up

When the futures price trades at a meaningful premiumto the spot price — i.e., the futures price is higher than the theoretical fair value. This is sometimes called "contango" in commodity markets. The annualised premium percentage is the rough return you lock in.

Worked example

Suppose Reliance Industries trades at Rs 2,500 in the cash market, and the 1-month futures trades at Rs 2,520. The Rs 20 spread on Rs 2,500 spot is 0.8%, which annualised (×12) is approximately 9.6% per annum.

The arbitrage setup:

• Step 1: Buy 250 shares (1 lot) of Reliance in cash market at Rs 2,500 = Rs 6,25,000 capital
• Step 2: Sell 1 lot of Reliance futures at Rs 2,520 = locked spread of Rs 20 × 250 = Rs 5,000 gross
• Step 3: Hold both positions until expiry
• At expiry: Futures auto-converges to spot price (cash settlement for indices, physical for stocks). Net P&L = Rs 5,000 minus transaction costs.

The Rs 5,000 on Rs 6,25,000 capital is 0.8% in 30 days, which is approximately 9-10% annualised gross. After brokerage, STT, exchange transaction charges, GST, and other costs, the net annualised return historically ran around 5-7% — competitive with debt MF returns but with the advantage of being effectively risk-free if held to expiry.

Why this works: convergence at expiry

The reason this strategy is "risk-free" (in theory) is that at futures expiry, the futures price mustequal the underlying stock price — the contract settles at the spot price. So whatever spread you locked in at trade initiation is captured at expiry, regardless of where the stock price ends up.

Whether Reliance is at Rs 2,300 or Rs 2,800 at expiry, your spread (Rs 20 in our example) is preserved:

• If Reliance closes at Rs 2,800: cash leg gain Rs 75,000 (Rs 300 × 250) + futures leg loss Rs 70,000 (Rs 280 × 250) = Net Rs 5,000
• If Reliance closes at Rs 2,300: cash leg loss Rs 50,000 (Rs 200 × 250) + futures leg gain Rs 55,000 (Rs 220 × 250) = Net Rs 5,000

The Rs 5,000 spread stays constant because the spread itself locks in at trade time.

Capital required and economics for retail

The capital requirement breaks down as:

• Cash leg: Full notional of the futures lot. For a Rs 6 lakh stock futures lot, you need Rs 6 lakh in cash to buy the equivalent number of shares.
• Futures margin: 15-25% of notional, depending on the stock's volatility and SPAN+exposure margin. For Rs 6 lakh notional, expect Rs 90,000-1.5 lakh margin requirement.
• Total capital: Rs 7-7.5 lakh per arbitrage position on a single stock.

The brokerage and tax cost stack:

• Cash leg buy: brokerage + STT 0.1% (sale side later)
• Futures sell: brokerage + STT 0.0125% on premium
• Cash leg sell at expiry: brokerage + STT 0.1%
• Futures expiry: STT 0.125% on settlement value (stock futures)
• Exchange transaction charges, GST, SEBI turnover, stamp duty

For retail-scale arbitrage on liquid F&O stocks, total cost typically eats 0.20-0.40% of notional per round trip. On a 0.8% spread, that leaves 0.40-0.60% net per month, which annualised is 5-7%. This is competitive with conservative debt fund returns but with the operational complexity of running futures positions.

Reverse arbitrage: short stock + long futures

When futures trade at a discountto spot (relatively rare in liquid Indian F&O), the reverse trade exists in theory: short the stock in cash, long the futures, capture the negative spread as it converges.

However, this is rarely practical for Indian retail because:

• Short selling restrictions: Indian cash markets allow short selling only for intraday (must be squared off same day) or via securities lending and borrowing (SLB), which is operationally complex and has limited stock coverage.
• SLB liquidity: Securities lending market in India is shallow for most stocks; fees can erode the negative spread.
• Holding period: Cash short positions cannot be carried to expiry (opposite of arbitrage need).

Reverse arbitrage is primarily an institutional play in India, executed through SLB by entities with the operational infrastructure.

Calendar arbitrage: near vs far month

Beyond cash-futures spread, traders also exploit price differences between near-month and far-month futures of the same stock. If the spread between near-month (May 2026) and far-month (June 2026) is wider than theoretical, you can sell the expensive month and buy the cheap month.

Calendar arbitrage typically has tighter spreads (0.3-0.6% per month) but lower capital requirement (only futures margins, no cash leg). Net annualised returns historically ran 4-5% on calendar arbitrage in liquid Indian futures.

Risks in cash-futures arbitrage

• Margin call risk: Futures margin can increase during high volatility events. If you fail to meet margin, the broker squares off your position at unfavourable prices, breaking the arbitrage.
• Dividend risk: If a stock declares an unexpected special dividend, the spread economics change because dividends are received by the cash leg holder but futures price typically adjusts downward.
• Liquidity risk: Less liquid F&O stocks have wider bid-ask spreads, which eat into your locked spread.
• Operational risk: Mismatched lot sizes (cash leg shares not matching futures lot), incorrect margin calculation, expiry-day execution errors.
• Tax complexity: Cash leg gains/losses and futures gains/losses are computed separately. Cash leg may be capital gains; futures is typically business income for active arbitrageurs.

Why retail often struggles

• Capital scale: Most retail accounts cannot afford the Rs 6-12 lakh per position to make brokerage costs negligible.
• Speed disadvantage: Algorithmic desks at institutions and prop firms close arbitrage opportunities in milliseconds. Retail click-traders rarely catch the best spreads.
• Cost stack: Retail brokerage, even at discount levels, eats more of the spread than institutional rates.
• Margin calls: Retail accounts get margin-called more aggressively, leading to forced exits at the worst times.
• Better alternatives: 6-7% post-cost annualised return is achievable with debt mutual funds (Liquid, Money Market, Short Duration) without operational complexity.

Retail arbitrageurs who do succeed typically focus on a small set of highly liquid stocks (Reliance, HDFC Bank, Infosys, TCS, ICICI Bank), use dedicated arbitrage trading platforms, and maintain comfortable margin buffers to ride out volatility.

Detailed cost stack analysis: every fee broken down

The seemingly attractive 0.8% spread on a Reliance cash-futures arbitrage gets eroded materially by the cost stack in Indian markets. Walking through each component clarifies why retail-scale arbitrage often produces returns competitive with conservative debt funds rather than dramatically better.

Securities Transaction Tax (STT):STT applies on multiple legs of an arbitrage trade. On the cash leg, STT is 0.1% on the sale value (charged only on the sell side, not buy). On the futures sell side at trade initiation, STT is 0.0125% of the premium (i.e., on the futures price). On expiry of stock futures with physical settlement, STT is 0.125% on the settlement value — meaningfully higher than the at-trade STT. For Nifty/Bank Nifty index futures with cash settlement, the expiry STT is 0.0125% (same as the at-trade rate). Stock futures physical settlement is the largest STT item in the stack.

Exchange transaction charges: NSE charges 0.00325% on stock futures turnover and 0.0035% on equity cash turnover. BSE charges vary by segment and exchange-fee schedule. These are small as a percentage but add up across a round-trip arbitrage with two cash transactions and two futures transactions plus expiry settlement.

GST on brokerage:The 18% Goods and Services Tax applies to brokerage as well as exchange transaction charges. For a discount broker charging Rs 20 per executed order, GST adds Rs 3.60 per order — small absolutely but multiplicative across all legs of an arbitrage.

SEBI turnover fee: SEBI charges 0.0001% on the turnover (notional value) of all secondary market transactions across cash and derivatives. This is among the smallest items in the stack but applies on every leg.

Stamp duty (state-wise):Stamp duty on equity transactions is set centrally as 0.015% on cash market buy and 0.002% on stock futures buy (charged only on the buyer side). The duty is collected by the exchange and remitted to the state of the buyer's registered address.

Worked example: Rs 5,000 spread becoming Rs 3,500 net:Take the Reliance arbitrage example with Rs 6,25,000 cash leg notional, Rs 6,30,000 futures notional, and a Rs 5,000 gross spread. Approximate cost stack: cash buy stamp duty (0.015% on 6.25 lakh) Rs 94, cash sell STT (0.1% on 6.25 lakh approx at expiry) Rs 625, futures sell STT (0.0125% on 6.30 lakh) Rs 79, futures expiry STT (0.125% on 6.30 lakh stock futures physical) Rs 788, exchange + GST + SEBI fees Rs 50-100 across all legs, brokerage at Rs 20 per order on 4-5 orders Rs 100 (with GST Rs 118). Aggregate costs reach approximately Rs 1,500-1,800 per round trip on a Rs 5,000 spread, leaving a net of approximately Rs 3,200-3,500. Net annualised return on Rs 7 lakh capital becomes 5.4-6.0% — competitive with Liquid funds but far below the gross 9.6% headline.

Calendar arbitrage in detail

Calendar arbitrage trades the spread between two expiries of the same underlying instrument. Unlike cash-futures arbitrage, no spot-market leg is involved — only futures positions on both sides.

Near month vs far month spreads: In the Indian futures market, near-month contracts (current expiry, e.g., May 2026) typically trade at a slightly different premium-to-spot than far-month contracts (June, July). The near-far spread reflects the additional time-value of the longer-dated contract, dividend expectations between the two expiries, and supply-demand. When the spread widens beyond theoretical fair value (computed from interest cost differences across the two expiry windows minus expected dividend), the arbitrage opportunity exists: sell the expensive month, buy the cheap month, hold through near-month expiry, and roll the remaining position.

Capital required:Only futures margins are needed for both legs. For a Rs 6 lakh notional Nifty calendar pair, margin requirement is approximately Rs 90,000-1.5 lakh per leg, but the exchange typically allows margin offsets between calendar spreads since the directional exposure is partially hedged. Net margin can drop to Rs 60,000-1 lakh for a recognised calendar spread — a fraction of the cash-futures arbitrage capital. This makes calendar arbitrage capital-efficient relative to cash-futures arbitrage.

Worked example with Nifty May vs June futures: Suppose Nifty spot is at 25,500. May Nifty futures trade at 25,560 (Rs 60 premium, near-month). June Nifty futures trade at 25,640 (Rs 80 premium over May, Rs 140 over spot). The May-June spread of Rs 80 versus a theoretical fair-spread of Rs 50 (computed from interest cost over the additional month) presents a Rs 30 arbitrage. Selling June and buying May for Rs 30 net spread on a 25-lot Nifty position (1 lot = 25 shares) means Rs 30 × 25 = Rs 750 per lot pair gross, before transaction costs. Net annualised return on the Rs 1 lakh required margin capital historically worked out to 4-5%.

Index arbitrage between Nifty futures and basket of underlying stocks

Index arbitrage is conceptually similar to cash-futures arbitrage but applied at the index level — trading Nifty futures against a basket of 50 underlying stocks weighted to replicate the Nifty composition.

Institutional strategy: When Nifty futures trade at a meaningful premium to the theoretical fair value (computed from the spot index and the basket cost-of-carry), institutional desks buy the underlying basket (all 50 Nifty stocks in correct weights) and sell Nifty futures. At expiry, the futures cash-settle against the closing Nifty value, and the basket leg can be sold or held. The strategy is theoretically lower-risk than single-stock arbitrage because diversification dampens single-name shocks (special dividends, corporate actions).

Why retail typically cannot do it:Replicating the Nifty 50 in correct proportion requires simultaneous execution across 50 securities — operationally infeasible for a click-trader. Each weighting change in the index (which happens periodically as Nifty rebalances) requires basket adjustment. Slippage in executing the basket against the moving index is the principal cost. Institutions deploy algo execution across all 50 names within milliseconds; retail cannot match that. As an alternative, retail traders sometimes use Nifty BeES or Nifty index funds versus Nifty futures, but the ETF-versus-futures spread is typically narrow and arbitraged away by institutional desks.

Putable spread arbitrage and dividend arbitrage

Beyond calendar and index arbitrage, traders also exploit corporate-action-driven discrepancies. These opportunities are episodic but historically meaningful.

Corporate action arbitrage opportunities:When a stock declares a dividend, bonus, stock split, or rights issue, the futures price typically adjusts based on the exchange's announcement of contract specification changes. If the actual price reaction differs from the theoretical adjustment, arbitrage opportunity arises. For example, when a stock declares a special dividend after the futures contract is open, the futures price typically falls by the dividend amount on the ex-date. If the futures price falls by less or more than the dividend, an arbitrage can be set up.

Special dividend handling:Special dividends (one-time large payouts, such as those historically declared by some PSUs and select private-sector companies) create a particularly clear arbitrage window. The futures contract may not fully discount the special dividend due to uncertainty around the record date, leading to futures trading at apparent "discount" to spot. Sophisticated arbitrageurs analyse the announcement, model the dividend cash flow timing, and set up positions to capture the residual mispricing. Tax treatment is nuanced because the cash-leg holder receives the dividend (taxable as Income from Other Sources at slab) while the futures-leg holder books a corresponding adjustment loss.

ITC arbitrage example: real-world historical

As an illustrative historical example, ITC futures during certain quarters historically traded at a meaningful discount to the spot price — sometimes Rs 2-4 below spot on cash-month contracts. The driver was dividend uncertainty: ITC was historically a high-dividend payer with quarterly and special dividends, and the market sometimes mispriced the dividend expectation in the futures price.

For an arbitrageur observing this at trade initiation, the apparent inverted spread could be exploited only by short-sell-cash-and-long-futures — which retail investors typically cannot do effectively due to short-selling constraints. Institutional desks with SLB infrastructure and prop-trading capability did execute these trades. The historical episode illustrates how single-name arbitrage opportunities arise from corporate-action complexity rather than continuous market inefficiency. The ITC reference here is illustrative and educational; specific spread observations were tied to specific trading sessions historically and do not constitute a current observation or projection.

Algorithmic arbitrage and the institutional edge

The biggest structural shift in Indian arbitrage markets over the last decade has been the migration from manual click-arbitrage to fully algorithmic execution.

Why algos win the milliseconds game:Cash-futures arbitrage spreads in highly liquid stocks (Reliance, HDFC Bank, Infosys, TCS) typically last for milliseconds in the active trading day. Institutional algorithms running at co-located NSE servers detect the spread, route the cash and futures orders simultaneously, and capture the spread within a window measured in tens of milliseconds. By the time a manual trader sees the spread on their terminal and clicks, the spread is gone. The institutional edge is structural — latency, infrastructure, and capital scale.

What retail traders can still capture:Two windows remain meaningfully open for retail arbitrageurs. First, longer time-horizon spreads — if you are willing to enter on day 1 of a new contract and hold for 25-28 days to expiry, you capture a different opportunity profile than the millisecond market-microstructure spreads that algos chase. Algos chase the volatile transient spreads; retail can capture the steadier carry spread that sometimes persists due to overall market premium structure. Second, smaller positions in less-tracked F&O stocks — while the top-10 liquid names are tightly arbitraged, the long tail of mid-liquidity F&O names sometimes shows wider spreads where retail-scale orders can execute without competing against algorithms. The trade-off: less liquid names also have wider bid-ask spreads and more dividend / corporate-action risk.

Frequently asked questions

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