Key takeaways
- Costs are a major driver of whether any Indian options rule produced a net edge.
- Brokerage, STT, exchange fees, SEBI fees, GST, and stamp duty must be modelled separately.
- Slippage scales with strike liquidity, timeframe, and order size — flat assumptions hide risk.
- A study that survives doubled slippage is more credible than one with a single optimistic assumption.
Why cost modelling decides everything
In Indian options, costs are not a rounding error. They are often the single largest determinant of whether a historical rule was net-profitable. A 0.4% gross edge per observation can become a 0.1% loss per observation after realistic Indian charges and one-tick slippage. The same rule, with different cost assumptions, can look 'good' or 'bad'.
The Indian cost stack
An honest options study models, separately: brokerage (flat or percentage, depending on broker model), STT (charged differently on sold premium and on exercised settlement value), exchange transaction charges (segment-specific), SEBI turnover fees, GST on chargeable items, and stamp duty (state-dependent in principle, harmonised by the centre).
STT deserves special attention. The rate and base differ between options sold and options exercised; using a single 'STT %' on turnover is the most common shortcut and a frequent source of inflated results.
Slippage
Slippage is the difference between the price the rule assumes and the price the market actually fills. In Indian options, it is structural: bid-ask spreads on far-OTM weekly strikes can be wide relative to premium, and lot sizes mean even moderate notional positions can move the displayed price.
A defensible slippage model scales with three things: strike liquidity at the decision moment, timeframe of the rule (intraday is more sensitive than swing), and order size as a fraction of typical traded volume at that strike.
Liquidity filters
A backtest can spuriously trade strikes that nobody actually traded historically. A liquidity filter — minimum open interest, minimum traded volume, maximum bid-ask spread — removes those phantom observations and produces a more realistic universe. Without a filter, headline metrics include trades that could not have been executed in practice.
What conservative modelling looks like
A conservative Indian options study assumes the realistic worst-side fill (not the mid), scales slippage with liquidity, applies full Indian charges, includes a liquidity filter on strikes, and reports the result twice — once under the base assumption and once with slippage doubled. If the result survives the doubled assumption, it is more credible.
Common mistakes
- Modelling only brokerage and ignoring STT, GST, exchange, and SEBI charges.
- Using flat slippage on all strikes regardless of liquidity.
- Assuming mid-quote fills on illiquid weekly options.
- Ignoring lot-size revisions across the data window.
- Trading strikes in simulation that had no real traded volume historically.
How this appears in OptionScience reports
Every OptionScience report lists brokerage, slippage, taxes, and liquidity filter assumptions in the Assumptions section, and the Performance dashboard reproduces them per study.
Practical educational example
Checklist
- Are brokerage, STT, GST, exchange, and SEBI charges modelled separately?
- Is slippage scaled by strike liquidity and timeframe?
- Is there a liquidity filter on the strike universe?
- Is the rule still net-profitable when slippage is doubled?