Arthalab vs StockMock: Simulation Depth or Live Automation?

StockMock is best known as a backtesting and simulation tool for options strategies. Arthalab backtests and then deploys the same strategy to run live. The question is whether you want to study strategies or to run them.

The core difference

	Arthalab	StockMock
Leads with	Automation — backtest, paper, deploy live	Backtesting and simulation depth
Ends at	A strategy running in your broker account	A tested strategy and a report
Needs a broker	For live trading, yes	Not for testing
Needs a static IP	For live trading, yes	Not for testing
Markets	NIFTY and SENSEX index options	Indian index options

The second row is the dividing line. A backtesting tool's output is knowledge. An automation platform's output is a position in your account. Both are legitimate; they are not substitutes.

When a testing tool is all you need

This is a genuine case and it is worth naming, because automation carries a setup cost that is only worth paying if you intend to use it.

You trade manually and want to know whether an approach has historically worked.
You are learning and want to see how parameters change outcomes.
You are researching rather than deploying.
Your strategy requires judgement and therefore cannot be automated anyway.

If all four describe you, the broker connection, the static IP and the daily routine are overhead for something you will not use.

When testing alone leaves a gap

The gap appears at the point where a tested strategy has to become a traded one.

A backtest proves the idea worked historically. It cannot prove the logic executes correctly on live prices.
Paper trading catches logic errors a backtest structurally cannot, because it runs forward in real time.
Live at minimum size reveals your execution cost, which no simulation can tell you.
Running it daily is the actual objective, and that is what automation is for.

Backtesting, compared honestly

Both backtest options strategies on Indian indices. What matters when comparing any two tools is the same regardless of which they are.

Data granularity — can intraday stop losses be evaluated at all?
Cost modelling — gross, per trade, or per leg?
Whether lot-size revisions follow the historical date
How cheap it is to re-run at different parameters
Whether the report shows drawdown duration and trade count, not just profit

The backtesting evaluation guide covers what each answer tells you. The fourth item matters most, because the plateau test is the best defence against curve fitting and needs several runs.

What Arthalab's backtesting includes

For transparency: 10 credits a day, resetting at midnight IST. One per normal backtest; a bucket backtest uses one per active strategy inside it. Failed runs are refunded and unused credits do not carry over.

Backtests use the lot size applicable to each historical date, so a report spanning a revision stays internally consistent.

The limitation

The honest constraint is the daily cap. Ten runs supports genuine iteration including plateau testing, but a workflow sweeping dozens of combinations in an afternoon will hit it.

Using both

There is no conflict. A testing tool for research, an automation platform for what you decided to run.

They touch your broker account differently — a testing tool mostly does not touch it at all — so running both is straightforward. The only configuration to avoid is two platforms placing orders into the same account without knowledge of each other.

How to decide

Ask what happens after a good backtest

If the answer is that you place the trade manually, a testing tool is sufficient.

Count how often you place the same structure

Three times a week is a strong signal it should run itself.

Ask what currently costs you money

Missing entries because you were busy is an automation problem. Choosing badly is a research problem.

Trial the one matching that answer

Arthalab's 3-day trial includes backtesting and paper trading at full access.

The short version

A testing tool's output is knowledge; an automation platform's output is a position
If you trade manually or discretionarily, testing alone is sufficient
A backtest cannot prove the logic executes correctly on live prices — paper trading can
Compare backtesting on data granularity, cost modelling and re-run cost
Running both is normal; two systems placing orders into one account is not

Frequently asked questions

Partly. Both backtest options strategies on Indian indices. StockMock leads with testing and simulation; Arthalab continues through paper trading to running the strategy live.

Only if you intend to run strategies automatically. If you trade manually or your approach needs judgement, a testing tool is sufficient and the automation setup is overhead.

No. A backtest replays history and assumes perfect fills. Paper trading runs forward on live prices through the same engine as live trading, which catches a different class of problem.

10 credits a day, resetting at midnight IST, with failed runs refunded. A bucket backtest uses one credit per active strategy inside it.

Compare on data granularity, how costs are modelled, whether lot-size revisions follow the historical date, and how cheap it is to re-run. Those decide quality more than the interface does.

Yes. Research on one, automation on the other. They do not conflict, since a testing tool generally does not touch your broker account.

No. Backtesting and paper trading need no broker, no static IP and no capital. Only live trading does.

Some people do, using one for research and the other for live execution. The thing to watch is that assumptions about fills and data granularity differ, so compare the shape of results rather than the exact numbers.

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