Table of Contents
This interview features Isar Chaudry, a hedge fund manager with a KPMG-audited track record who runs a lean seven-person team and grades trade ideas from AAA to B before they ever hit the market. He breaks down why he moved beyond retail tactics and prop-firm roulette to a professional, research-led process—complete with dedicated risk, research, analysis, and execution roles—so every position is a documented “case study,” not a hunch.
In this piece, you’ll learn how Chaudry designs “boring but bankable” returns (think 2–3% a month) by prioritizing risk management over strategy-hopping, sizing with ATR and daily/weekly ranges, and knowing when to sit in cash. You’ll see his framework for building an investor-ready track record, how to diversify across multiple strategies and portfolios, the signals that elevate an idea to “AAA,” and the practical path from retail trader to managing outside capital—without blowing up your edge or your emotions.
Chaudry Isar Playbook & Strategy: How He Actually Trades
North Star & Risk Objective
Before anything else, Chaudry Isar designs the account around steady compounding, not lottery wins. The aim is a professional equity curve that an investor would actually fund—controlled drawdowns, clean documentation, and repeatable actions.
- Target a monthly return band of 2–3% with a hard max drawdown of 6–8% from peak; pause new risk if drawdown hits 5%.
- Risk per trade: 0.25–0.50% of equity baseline; expand to 0.75–1.00% only on top-graded setups (see grading).
- Daily loss limit: stop trading after −1.5R or −1.2% (whichever comes first).
- Weekly loss limit: stop trading for the week at −3R; switch to review mode only.
- If volatility spikes (e.g., true range > 1.5× its 20-day median), cut all position sizes by 30–50% until range normalizes.
Team of One (Even if You’re Solo)
He runs with distinct roles—research, risk, execution—even if the same person wears each hat. This separation keeps decision-making clean and prevents “winging it.”
- Block your day: Research (pre-London or pre-NY), Execution (session), Post-mortem (end of day).
- Keep three notebooks (digital is fine): Idea Log, Trade Log, Risk Log. Update each in real time.
- Never let “execution” overrule “risk”: if risk says pass, it’s a pass—no exceptions.
- Use checklists for each role to prevent spur-of-the-moment mistakes.
The Idea Grading System (AAA → B)
Not every idea deserves the same size or attention. He grades trade ideas from AAA (institutional quality) down to B (speculative), and the grade dictates size and leash.
- AAA: Multi-timeframe confluence (HTF trend + level + catalyst), clean risk box, ample liquidity. Size up to 1.5× baseline risk; allow add-ons only if MAE < 0.5R.
- AA: Two strong confluences, clear stop. Size = baseline risk.
- A: One confluence, decent structure. Size = 0.75× baseline; partial targets only.
- B: Exploratory/learning. Size ≤ 0.25× baseline; no add-ons; journal heavily or skip.
- Auto-downgrade any idea if news risk is binary (e.g., minutes before a major release).
Market Selection & Instruments
He sticks to liquid markets where slippage won’t kill the thesis. Liquidity plus clarity beats chasing every shiny chart.
- Trade a core universe (e.g., 6–10 FX majors/indices/commodities) with known behavior; avoid random tickers.
- Require minimum average daily range and tight spreads; skip instruments with erratic gaps.
- If your last 20 trades show >20% slippage vs planned exit, remove that instrument for a month.
Setup Architecture (Top-Down → Trigger)
The process cascades from higher-timeframe bias to lower-timeframe execution. Do the slow thinking first, so the fast decisions are simple.
- HTF map: start weekly/daily to mark trend, key levels, value areas, and supply/demand zones.
- Identify “where I’m paid”: locations with asymmetric payoff (prior week high/low, HTF mean reversion, AVWAP anchors).
- Define the trigger timeframe (M5–H1): you only pull the trigger at pre-defined locations, never mid-air.
- If HTF bias is unclear, reduce the size by 50% or pass.
Entry Triggers That Don’t Drift
Entries are rule-based, so the log reads like a lab notebook, not a diary. No “felt right” trades.
- Break-and-retest of a pre-marked level with delta/volume confirmation or a failed breakout back inside range.
- Pullback to anchored VWAP from the session/impulse start with a rejection wick and lower-timeframe structure shift.
- For trend trades: buy higher-low/sell lower-high only after a clean market structure break (HH/LL) on the execution timeframe.
- If the spread widens > 1.5× normal at entry, cancel the order.
Stop Placement & Position Sizing
Stops are placed where the trade thesis is objectively invalidated, sized by volatility so one loss doesn’t dent the week.
- Compute ATR(14) on the execution timeframe; stop distance = technical invalidation level, but never < 1.0× ATR.
- If technical invalidation > 2.5× ATR, pass (reward will rarely justify it).
- Position size = (Account × Risk%) ÷ Stop distance (in price terms). Round down to the nearest lot/contracts to avoid over-exposure.
- Move to breakeven only after the first partial at +1.0R or when the price closes beyond the last swing in your favor.
Trade Management & Scaling
Managing winners is where consistency is made. He pre-defines add-ons, partials, and exits so emotions don’t take the wheel.
- Pre-plan add-ons for AAA ideas only after a higher-low/lower-high forms beyond entry and MAE < 0.5R.
- Standard partials: 30–50% off at +1.0R, trail remainder behind structure or a 20-EMA/ATR stop.
- Time stop: if price hasn’t moved >0.5R in your favor within two average session ranges, scratch.
- News guard: close or halve exposure 5–10 minutes before tier-1 releases unless the trade is already >1.5R in profit.
Portfolio Construction & Correlation
He thinks in baskets, not single heroes. Correlation and exposure caps keep the book durable.
- Max simultaneous risk on correlated assets (e.g., DXY vs majors): 1.5× baseline risk total.
- Limit strategy concentration: no more than 40% of weekly risk from one setup type (e.g., only break-and-retests).
- Net exposure guardrails: cap total long-USD or short-equity beta at 2× baseline risk.
- If three trades in the same theme lose back-to-back, freeze that theme for 5 sessions and review.
Daily & Weekly Routine
A boring routine is a profitable routine. He runs the same play every day, so the outcomes are comparable and improvable.
- Pre-market (30–60 min): update HTF levels, mark session ranges, write a one-page plan with “if/then” statements.
- During session: execute only planned triggers; log screenshots at entry/exit; speak the checklist out loud.
- Post-session: tag trades (setup, theme, grade), compute R-multiple stats, and write two improvement bullets.
- Weekly: grade each strategy’s win rate, average R, drawdown contribution; re-weight the playbook for next week.
Documentation & Track Record
Every position is a case study. Keeping investor-grade records forces discipline and makes capital scalable.
- Maintain an auditable trade ledger: date/time, instrument, grade, thesis, screenshots, MAE/MFE, exit reason, and R.
- Export monthly stats: win rate, expectancy, average hold time, heat map of errors; compare vs prior 3 months.
- Screenshot “best five” and “worst five” trades each month with notes on what to repeat/avoid.
- If a rule saves you from a loss, record it as an “averted drawdown” and keep score—it reinforces good behavior.
Psychology & Error Budget
He treats psychology as a rules problem: define failure modes, restrict them, and measure them.
- Set an error budget: max 2 rule breaks per week; exceeding it triggers a one-day trading lockout and process review.
- Use a pre-trade breath + checklist (30 seconds) to slow down; no market orders without a spoken checklist.
- If you revenge-trade or widen a stop, tag the trade “rule-break,” size the next session at 50%, and write a correction plan.
- Keep sleep, caffeine, and screen-time baselines; if two are off, trade half size or stand down.
Capital Scaling & Pauses
Scaling is earned by rule adherence, not excitement. He steps up only when the data proves the system can handle it.
- Increase risk per trade by 0.10–0.15% only after three consecutive profitable months with drawdown < 5% and error rate < 5%.
- If equity drops 4% from peak, cut size by 50% until a fresh equity high is made.
- No new strategies are added mid-drawdown; fix the current book first.
- Quarterly: retire the lowest-expectancy setup and incubate one improved variant at half size.
Playbook for Events & News
Event risk is managed with simple switches. Either you’re paid to take it, or you’re flat.
- Have a calendar of tier-1 events on your desk; mark “no-trade windows” 5–10 minutes around releases.
- Only hold through a release if spread/volatility historically stays tradable and your trade is >1.5R in profit.
- For overnight holds, use alerts at key levels and a disaster-stop with brokers that honor them; otherwise, reduce size or exit.
Quality Control & Kaizen
The edge stays sharp with constant small improvements. He iterates weekly, so the system compounds, too.
- Each week, choose one micro-upgrade (e.g., tighten level marking rules, refine add-on criteria) and A/B test it for 20 trades.
- Remove rules that add complexity without improving expectancy; simplicity wins under stress.
- Keep a “Hall of Fame” for best setups with full play-by-play; rehearse them before the session so execution is automatic.
Size Risk First: Volatility-Adjusted Positions That Survive Bad Days
Isar Chaudry starts every trade by deciding how much he can lose, not how much he wants to make. He scales position size to the instrument’s current volatility, so one stop-out is just a scratch on the equity curve. If range expands, size contracts; if range compresses, size gently increases—never the other way around. This way, a spike in ATR or a jumpy session doesn’t hijack the account.
He also caps daily and weekly damage, so a bad stretch can’t spiral. Risk per trade stays small by default, with size bumps reserved only for top-graded setups that meet strict criteria. Stops live where the thesis breaks, not where the P&L feels comfortable, and they’re wide enough to avoid noise but tight enough to keep R multiples meaningful. The result is simple: adapt to volatility, protect capital first, and let winners do the heavy lifting.
Trade the Mechanics, Not Predictions: Rules That Remove Guesswork
Isar Chaudry treats forecasting like a distraction and execution like the job. He builds simple mechanical triggers—level, structure shift, confirmation—and lets the rules fire or not. If the checklist isn’t green across the board, he doesn’t “feel it out”; he passes and keeps the book clean.
The play is prewritten: where to enter, where to be wrong, where to scale, and when to stand down. He measures outcomes in R, not opinions, and only upgrades rules that improve expectancy over dozens of trades. A break-and-retest with volume shift gets taken; a drift through the level with widening spreads is canceled on the spot. By forcing decisions through the mechanics, Isar Chaudry removes debate, trades faster, and saves his mental capital for review—not mid-candle guesses.
Diversify Smart: Underlying, Strategy, and Duration Working Together
Isar Chaudry spreads risk across what actually differs—underlying, strategy type, and holding time—so one theme can’t sink the ship. He avoids “fake diversification,” like being long USD across three pairs or running the same breakout logic on five correlated indices. Correlation gets capped at the book level, not trade by trade, and he tracks theme exposure like long-dollar, long-energy, or long-momentum. When the same factor drives multiple positions, he sizes the basket, not each ticket.
He also staggers duration so intraday mean-reversion doesn’t collide with swing trend-following. Each strategy gets its own risk budget and rules for adds, partials, and time stops, and weights are rebalanced monthly by expectancy and drawdown contribution. If two losses hit in the same theme, he reduces size; three in a row, and the theme goes on a cooldown. Hedging is optional, but overlapping bets are not—if exposures rhyme, he cuts to the cleanest expression. That way, diversification isn’t a slogan; it’s a portfolio rule that keeps compounding intact.
Define Your Risk Box: Entries, Stops, and Adds by Design
Isar Chaudry starts with a “risk box”—a pre-marked price zone where the thesis makes sense and beyond which it’s dead. Entries only trigger inside that box after a clear structure shift (break-and-retest, failed breakout, or AVWAP rejection), never mid-chop. Stops sit outside the box at objective invalidation—typically beyond the prior swing or 1–1.5× ATR—so a normal wiggle can’t knock you out. If spread or slippage widens beyond 1.5× normal at the moment of entry, the order is canceled and the setup is re-queued.
Adds are earned, not guessed. Isar Chaudry only scales when price makes a higher low/lower high beyond the initial level and maximum adverse excursion stays under 0.5R. First partial lands around +1R, then the remainder trails behind the structure or a volatility stop; no partial, no trail. If price fails to travel at least 0.5R within two session ranges, the trade is scratched—because a good idea that refuses to move is usually a trap.
Process Discipline Daily: Plan, Execute, Review, Then Scale
Isar Chaudry treats every session like a flight plan—written before takeoff, flown by checklist. He writes a one-page premarket plan with specific “if/then” triggers, executes only what’s pre-approved, and logs each decision with screenshots and R multiples. If a rule is broken, he tags it and automatically cuts size for the next session instead of pretending it didn’t happen. The result is a rhythm that keeps emotions in the passenger seat while the process drives.
Scaling is earned by data, not vibes, and Isar Chaudry won’t raise risk until the book proves it can handle more. He runs weekly expectancy reports, grades setups by win rate and average R, and promotes only the highest-quality plays; weak setups get benched or reworked. Size increases are incremental and contingent on low error rates and shallow drawdowns, while any equity dip triggers an immediate size cut. The loop is simple: plan it, trade it, review it—then scale what works and scrap what doesn’t.
In the end, Isar Chaudry’s edge isn’t a magic entry—it’s a professional operating system. He builds investor-grade returns by sizing to volatility, grading ideas (AAA to B), and only paying up when multiple confluences align. He caps correlation across portfolios, accepts “boring” 2–3% months as the target, and is perfectly happy to sit in cash for weeks if the market isn’t paying. The risk box comes first, entries and adds are earned, and stops sit where the thesis is objectively dead, not where the P&L feels comfortable.
He runs the process like a fund even when a trader is solo: distinct roles for research, risk, and execution; a prewritten plan; strict daily/weekly loss limits; and auditable journaling that promotes only what works. Top-down context sets the bias, the trigger is mechanical, and management follows clear rules for partials, time stops, and news risk. He leans toward trend over reversal, blends technicals with fundamental case studies, and measures everything in R so decisions outlive opinions. Do that long enough—document, refine, and protect downside—and you don’t just trade well; you build a track record people can trust.
