FastBT is a new simulation engine written for one contract: predict what a live deployment actually does — in seconds, on Indian, US and crypto markets, for any strategy the Strategy Builder can express. The highlights are on this page; every claim opens into its full evidence — measured runs, published audits, validation against real executed fills. Since 25 August 2026, every backtest on Tradetron — web or AI chat — runs on FastBT.
New pricing ₹20 per 6 months tested → ₹20 flat per backtest — full 6+ year history, walk-forward includedBacktests stuck in queues for days. History that started in 2020. No MCX, no crypto. Keywords that worked live but not in backtest. A trader on X summed it up:
“If I am using Tradetron, I should use the BhagwanBharose Platform.”
— @khanzubare, X (Twitter), June 2024. Fair, at the time.
FastBT wasn’t a patch on that engine. It is a replacement — built and instrumented so every one of those complaints now has a measurable answer.
That replacement is now complete: on 25 August 2026 the previous engine was retired and FastBT became the only backtest engine on Tradetron — for every user, on every plan. Before flipping, we replayed 306 real user jobs on the new fleet and checked every outcome — not one would have been lost. In that same sample, one in five previous-engine runs had quietly delivered nothing at all: no fills, no report. FastBT’s contract is fail-closed — every run either delivers, or tells you so and refunds. [9]
Shipped, not roadmapped
A backtest engine earns trust the way a broker does — by being corrected in public and fixing it. These landed in the last fortnight. Each one was reported by someone, measured, fixed, and verified against raw exchange data before it shipped.
Same strategies, same windows, same data — old engine vs FastBT, timed on production hardware. The grey bar is the old engine; the indigo sliver is FastBT, on the same linear scale. The sliver is the point. And beyond hand-picked jobs: before the one-engine cutover we replayed 306 real user backtests on the production fleet — the median job ran 3.7× faster and the slowest tenth 42× faster, same template, same window, same fills [9].
| Backtest window | Old engine | FastBT | Same job, side by side | |
|---|---|---|---|---|
| 18 days · 1-min | 35 min | 4.3 s | 486× faster | |
| 6 months · 5-min | 3 h 21 m | 31 s | 393× faster | |
| 2 months · 1-min | 3 h 35 m | 43 s | 299× faster | |
| 3.7 years · hourly | 10 h 48 m | 5 m 29 s | 118× faster |
Paired runs of identical jobs on the production backtest fleet, August 2026 — cold-cache, contended-box conditions, i.e. understated [2].
Six segments on minute-level data — and if the Strategy Builder can express it, FastBT can test it: the same conditions, keywords, legs and exits your live deployment runs.
Any backtester can agree with itself. FastBT’s data is audited exhaustively, its fills are scored against real executed trades from live deployments, and its reports are built to stop you fooling yourself. Each card opens the full evidence.
Every run produces an interactive report — 60+ metrics across 20+ sections: verdict & grade, equity and drawdown, Monte-Carlo ranges, VIX-regime splits, leg and exit attribution, trades superimposed on the real chart, a live cost lab, and every raw fill. Each metric has a plain-English tooltip written for traders, not quants. Open a live sample report ↗
Two real samples, both generated by the production engine: a single 6.5-year run ↗ · a 12-variant sweep with walk-forward ↗ — the sweep one carries a variant navigator, so you can step through all twelve inside the same report. More on that below.
Change one number and a strategy’s result changes. So test the number, not your hunch about it. A parameter sweep re-runs the whole backtest once per value and lays the results out as a grid. Walk-forward then splits the history, so the strategy is judged on data it was never tuned on. A sweep without walk-forward is just a machine for finding the luckiest number — which is why walk-forward is free here, and why the winner is chosen by it.
Up to 4 parameters, up to 10 values each, up to 16 combinations in one run. Each cell is a full backtest — real charges, your slippage, the same fail-closed refusals — never an interpolation. Click any cell to open that variant’s own complete report.
Choose an out-of-sample share (up to 90%; 30% is the usual pick) and the window splits in two: tune on the early part, verify on the rest. Every variant gets a plain verdict — holds up, degrades, fails out-of-sample — from how much of its in-sample daily average actually survived.
Not the best in-sample number — the best in-sample number that also holds up. If nothing holds up, the grid says so and labels the pick least-bad, not deployable instead of crowning it. Variants that looked strong in-sample and collapsed after are flagged ⚠, not quietly ranked.
Here is a real one, and it is not flattering. Twelve entry/exit-time combinations of a NIFTY intraday short straddle over 18 months, 30% of the window held back. In-sample they look like a menu of winners — +6.5% to +21.8%, every one profitable. Out of sample, ten of the twelve lose money and the other two merely degrade. The best in-sample variant, +21.8%, comes back at −3.3% on data it was not tuned on. Nothing holds up, so the report crowns nothing and says in writing: treat the whole grid as overfit. Twelve ways to be wrong, found for ₹240 instead of in a live account. Open the sample sweep report ↗
A sweep costs 1 credit per variant — a 6-variant sweep is ₹120, and the number is on screen before you run it. Walk-forward adds nothing, on a sweep or on a single backtest.
Tradetron ships an MCP server — the open standard that lets AI assistants use real tools. Connect Claude (or any MCP-capable AI) to your account once, describe a strategy in plain English, and get a real editable template and the full backtest report URL back in the chat, seconds later. No other algo platform — Indian or global — offers this.
See it working: One idea, thirteen versions ↗ · How to connect your AI ↗
Compiled August 2026 from each platform’s public documentation, pricing pages and user forums. If we got a cell wrong, tell us and we’ll fix it.
| Capability | FastBT (Tradetron) | Platform A | Platform B | Platform C | Platform D | Platform E | Platform F |
|---|---|---|---|---|---|---|---|
| NSE index options, minute-level | ✓2020→, audited bar-by-bar | ✓7.5 yrs, 1-min | ~ weakno true option-leg BT | ✓7 yrs on top plan | ✗ EOD only | ✓ | ✓ |
| Stock options & cash equity | ✓F&O stocks + 1,700+ cash symbols | ~~50 stock options, no cash | ✓ equity | ~ | ~ 51 stocks | ~ 7 stocks | ✓ |
| MCX commodities backtest | ✓futures + options, evening session | ✗ | ~ indicators only | ✗their own FAQ | ✗ | ✗ | ✗ |
| Crypto backtest (BTC/ETH) | ✓options + perps, 24/7 | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| US options backtest (SPX/SPY/QQQ) | ✓0DTE + weeklies, validated vs live US fills | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Multi-year positional backtests | ✓4 yrs in ~30 s | ✓ | ~~3 months on 5-min candles | ✓ | ~ EOD | ✓ | ✓metered by the minute |
| Custom Python in backtest | ✓same code as live deploy | ✗ no-code only | ✗ | ✗ | ✗ | ✗ | ✓₹5,310+/mo tiers |
| Parameter sweep / optimiser | ✓16 variants, up to 4 axes | ✗portfolio combiner only | ✗ | ✗ | ✗ | ~ Greeks tests | ✗ |
| Walk-forward / out-of-sample | ✓ freeverdict on every run | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Monte-Carlo robustness in report | ✓ | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Margin modelling in report | ✓peak/avg margin, return on margin | ✗ | ✗ | ✗ | ~ Greeks/payoff | ✗ | ✗ |
| Historical lot sizes per trade date | ✓from exchange circulars | ? | ✗ | ? | ✗ | ? | ? |
| Validated against real live fills | ✓21,011-fill ground-truth program | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Create + backtest from inside an AI (MCP) | ✓report URL delivered in the chat | ✗ | ✗ | ✗ | ✗ | ✗ | ✗ |
| Backtest → one-click paper deploy | ✓same template, same engine keywords | ✓ | ✓ | ✓ | ✗ | ✗via bridge software | ✓ |
| Backtest pricing | ₹20 flatany period · WF included | ₹1/run · ₹1.5k/mo25 free/week | freebroker clients only | ₹1.3k–5.4k/mo | ₹1k/mo + demat | ₹1.1k/30d | ₹1.2k–23.6k/mo |
Sources: each platform’s public documentation, pricing pages, and public user forums as of August 2026. Platform names withheld — the cells stand on their own. Cells marked “?” were not documented publicly.
A backtest is the only way to confront an idea with thousands of days it didn’t get to choose. And the engine you test on matters as much as testing at all: repainting, fabricated ticks or silent data holes don’t reduce your risk — they manufacture false confidence. That is why FastBT’s integrity layer exists.
Compare: unlimited plans elsewhere run ₹1,499–₹5,417/month whether you test or not; code-first platforms meter by the minute; one platform requires opening a demat account just to backtest. ₹20 to interrogate an idea against six years of audited data is the cheapest insurance in trading.
Open the 6.5-year NIFTY weekly put-ladder sample ↗ — the full diligence file including the new trades-on-chart view — with the section-by-section walkthrough above as your guide.
One idea, thirteen versions ↗ — a real, unedited journey of a put-ladder strategy going from a one-line idea to a backtested, deployable template in a single Claude session, every version backtested along the way.
Connect Claude or any MCP-capable assistant ↗ to your Tradetron account — then describe a strategy in plain English and get the backtest report URL back in the chat.
Describe a strategy in the builder — or in plain English to your AI — and have a full diligence report in your hands before your chai gets cold.