The Algo Desk is where a trading idea becomes something you can read, test, run, and trust — not a black box, and not a spreadsheet that breaks when you look away. A strategy here is a recipe of rules; the desk compiles it, seals it with a fingerprint, and runs it on live data as a paper book. Let's start with what one of those recipes actually looks like.
A strategy you can read top to bottom
Here is a real strategy — the built-in Portfolio Auto-Pilot — trimmed to its shape. No code, no jargon: just the decisions it makes, every day, on real data.
ALGO Portfolio Auto-Pilot ────────────────────────────────────────────── REGIME halt new buys in a CRISIS · max 25% per sector UNIVERSE liquid Indian equities · market cap ≥ ₹1000 Cr · avg. traded value ≥ ₹5 Cr ENTRY a confirmed uptrend (Weinstein Stage 2) + a fresh breakout + earnings improving, near a 52-week high, and NOT overextended ADD pyramid a winner that's up ≥ 8% and still trending TRIM cut the overheated (weekly RSI > 70) · enforce a 10% single-stock cap EXIT close on a trend breakdown, or when the ATR stop is hit EXECUTION stop −10% · single-stock cap 10% · build slowly (1.5% at a time)
Everything a strategy does is one of a small set of verbs — ENTRY, HOLD, ADD, TRIM, EXIT — each a condition written in a shared vocabulary of real market signals (Weinstein stage, relative strength, breakouts, volume, ATR volatility). Because it's written this way, the desk can do four things a black box can't: compile it, back-test it on history, run it live on paper, and seal it with a fingerprint so any later edit is detectable. That's what "deterministic" means here — the same data always produces the same actions, and you can see exactly why.
Strategies come in classes
A single strategy is an instance; behind it stands a class — a family that defines what kind of strategy it is, what fields you can tune, and how those settings compile into runnable rules. The desk ships six classes today, each a different way to be in the market:
Portfolio Rebalance
Screen a liquid universe daily, hold a diversified book of momentum names, manage exits under a regime overlay. The everyday work-horse.
Momentum Breakout
Concentrated, built from zero. Enters only on a confirmed breakout, a blue-sky high, or a strong Stage-2 leader. Aggressive by design.
Inverse H&S · RS Ladder
A pattern specialist: enter on a confirmed inverse head-and-shoulders breakout in a relative-strength leader, equal-weighted.
RS-Leader Rotation
Start from the current book, then continuously rotate capital toward the strongest Stage-2 relative-strength leaders.
Regime Router
A meta-strategy: each day it routes the book to whichever validated child strategy fits the current market regime.
Regime Factor-Tilt
One engine, two sleeves — tilt to small-caps when the market is calm and rising, defensive quality when it isn't.
Adding a new class is a development task, not a user one — but once a class exists, anyone can spin up a strategy from it, tune its fields in a structured builder or edit its rules directly, and the desk compiles the result into the same kind of runnable, sealed recipe as a built-in.
The strategies currently running
Every strategy runs as a paper book — real market data, real rules, real trades, but no real capital at stake — so a dozen ideas can run forward, side by side, and prove themselves (or not) before a rupee is ever committed. Here is the desk today:
| Strategy | Class | Seeded from | Status |
|---|---|---|---|
| Portfolio Auto-Pilot | Portfolio Rebalance | the current real book | running |
| Breakout & Blue-Sky Momentum | Momentum Breakout | ₹1 Cr paper cash | running |
| Inverse H&S RS-Ladder | Inverse H&S | from zero | running |
| Regime Router | Regime Factor-Tilt | the current real book | running |
| Small-Cap Auto-Pilot | Portfolio Rebalance | small-cap universe | running |
| Large-Cap Momentum | Portfolio Rebalance | large-cap universe | running |
| Reset & Concentrate 30 | Portfolio Rebalance | the current real book | draft |
Notice the "seeded from" column — it's one of the most important differences between strategies, and it's worth dwelling on with the two we'll now open up.
Portfolio Auto-Pilot vs. Breakout & Blue-Sky Momentum
Both are momentum strategies. Both share the same non-negotiable risk skeleton — a regime overlay, a 25%-per-sector cap, hard single-stock caps, ATR-based stops. But in temperament they are near-opposites, and the rules make it obvious. First, where they begin:
Seeds from the current real book — it picks up your actual portfolio and keeps flying it. A steady auto-pilot for a whole book.
Seeds from zero — ₹1 crore of paper cash and an empty book, filled only by fresh breakouts. A hunter that builds its own book.
That single choice cascades through everything else. Here are the two entry rules, side by side — the heart of each strategy's character:
ENTRY # diversified, fundamentals-gated early-to-mid Stage 2 uptrend AND a fresh breakout or rising volume AND earnings & cash-flow improving AND near a 52-week high AND NOT overextended
ENTRY # pure price & momentum a confirmed breakout with volume OR a blue-sky 52-week high OR a Stage-2 relative-strength leader # (no fundamentals required) AND NOT overextended
Auto-Pilot insists on improving fundamentals before it buys — it wants a real business behind the chart. Breakout doesn't care about the balance sheet at all; it's pure price and momentum, trading confirmed strength wherever it appears. And how they size a position is the mirror image of that:
| Portfolio Auto-Pilot | Breakout & Blue-Sky | |
|---|---|---|
| Book size | up to 50 names | up to 30 names |
| First buy | 1.5% of the book — a toe in | 5% of the book — a real stake |
| Pyramid up to | 2.5% cost basis | 8% cost basis |
| Single-stock cap | 10% | 8% |
| Buys per day | 2 buys · 5 adds | 4 buys · 3 adds |
| Entry gate | price + fundamentals | price / momentum only |
| Trims | looser (40% above trend) | tighter (30% above trend) |
| Temperament | diversified, patient | concentrated, aggressive |
Auto-Pilot spreads across up to fifty names and builds each one slowly, a toe at a time — a diversified caretaker. Breakout runs a tighter book of thirty, takes a real stake on the first buy, and lets its winners grow to twice Auto-Pilot's per-name weight — a concentrated hunter. Neither is "better": they are different bets, and the desk runs both so the market can settle the argument.
Live, on paper — the early scoreboard
Both books were seeded on 14 August 2026 and have run every trading day since. It is far too early to read anything into a few weeks of returns — but the behaviour already shows each strategy being itself:
Barely traded — a caretaker keeping a full, diversified book steady.
Deployed ₹1 Cr of cash into 27 fresh breakouts, trading actively to build the book.
Three weeks is noise, not signal — these numbers prove the machinery works, not that one strategy beats another. The point of running them as paper books is exactly this: let them compound forward across real markets and regimes, on the record, until the evidence is actually worth something.
From a written rule to a running book
Whichever strategy you're looking at, the path from rules to results is the same — and it's what makes the whole desk trustworthy:
Two properties do the heavy lifting. First, the sealed recipe: every strategy — and every later edit — is stamped with a fingerprint, so what ran last Tuesday is provably the exact rules you can read today. Second, the paper book: because nothing risks real capital, the desk can run many strategies forward at once and let evidence, not opinion, decide which deserve attention.
The desk in the bigger picture
The clean, point-in-time market data every strategy reads — prices, Weinstein stages, relative strength, accumulation, fundamentals — for Indian and US equities. Covered in its own article.
The interactive terminal where a human reads the same signals a strategy trades on — stage analysis, relative strength, institutional accumulation. Covered separately.
An optional layer that lets a strategy improve itself — an AI proposing changes to its own rules, behind a deterministic guardrail. It builds directly on the sealed recipes described here. Read the agentic-layer article →
Rules you can read, results you can trust
The whole point of the Algo Desk is to take the mystery out of a systematic strategy. You can read exactly what it does. You can watch it run on real data without risking a rupee. You can compare a patient caretaker against an aggressive hunter and let the market referee. And whatever a strategy did, the sealed recipe proves precisely which rules it followed.
Dhakua Research builds research infrastructure. Nothing here is a recommendation, a tip, or a promise of returns — it is a description of how strategies are engineered, tested, and run in the open.