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This interview features Sovit Manjani, CMT—a systematic equities and derivatives trader who rebuilt his approach after the 2008 bear market and now runs rule-based models with tight risk controls. Recorded while the host was in Bangkok and Sovit was in India, the conversation matters because it unpacks how a real trader moved from discretionary errors to coded, testable processes, and why mindset practices like Vipassana meditation sit alongside checklists and stop-losses in his day-to-day routine.
In this piece, you’ll learn how Sovit Manjani designs strategies that combine trend, momentum, relative strength, and retracement logic; why “doable” drawdowns beat theoretical CAGR; and how to validate ideas with simple manual reviews or full backtests before risking a dollar. You’ll also see his playbook for versioning systems in live “shadow” mode, cutting losses early, and using meditation and physical training to keep discipline during inevitable losing streaks—clear, transferable lessons any retail trader can apply immediately.
Sovit Manjani Playbook & Strategy: How He Actually Trades
Core Idea: Build “Doable” Systems
Sovit Manjani focuses on strategies you can actually stick with through drawdowns. That means simple signals, tight risk rules, and realistic expectations instead of chasing the highest backtested CAGR. The goal is longevity and consistency, not perfection.
- Keep strategy logic to three or fewer core signals (trend, momentum, relative strength).
- Favor rules you can execute daily with minimal discretion.
- Target a drawdown you can emotionally tolerate first; let returns follow from discipline.
- If a rule causes repeated hesitation in live trading, simplify or drop it.
Market Universe & When He Trades
He works a liquid list where slippage is small and fills are reliable. Think leading stocks and index derivatives, with occasional rotation into stronger groups when market regimes change. This keeps execution clean and lets the edge come from the rules, not lucky fills.
- Build a liquid watchlist (e.g., top-volume stocks, index futures/options).
- Refresh the list weekly using volume, trend, and relative strength scans.
- Avoid illiquid names and exotic structures that complicate exits.
- Stand aside during obvious event risk if your rules don’t explicitly handle it.
Signal Stack: Trend, Momentum, Relative Strength
Sovit’s edge comes from combining simple, widely tested signals. A higher-timeframe trend filter, a momentum kick, and a relative strength overlay keep him trading with the tape, not against it. This stack cuts noise and avoids “false positives.”
- Trade long only when price is above the 100–200 day trend filter; short (or flat) when below.
- Require momentum confirmation (e.g., close above a short moving average or recent swing high).
- Rank candidates by relative strength versus the benchmark; prefer top decile names.
- Skip trades that meet one signal but fail the other two.
Entries: Buy Strength, Add on Clean Pullbacks
He enters on strength but keeps entries repeatable and calm. Breakouts are fine, but the bread-and-butter entry is a shallow pullback that holds structure and re-accelerates—easy to see, easy to execute.
- Set entry at the prior day’s high after a brief pullback in an uptrend.
- Only take the trade if the pullback stays above the trend filter or last higher low.
- If using breakouts, require a narrow-range setup day first to reduce whipsaws.
- One retry max: if the first entry fails and re-triggers, take it once, then stop.
Risk: Small, Fixed, and Volatility-Aware
He risks small so he can survive long enough for the edge to show up. Volatility tools (like ATR) size stops to the instrument, so loud names don’t blow him out, and quiet names don’t dead-stop him for noise.
- Risk 0.25%–0.75% of equity per trade; never more than 1.0%.
- Place initial stop ~2x ATR(14) below entry (longs) or above (shorts).
- Cap portfolio heat at ~3% total open risk across all positions.
- If implied or realized volatility doubles from entry, cut size by half on new adds.
Position Sizing & Adds
Sizing is systematic and tied to volatility and conviction from the signal stack. Ads are pre-planned; no “feel” ads. He scales in when the trade proves itself and scales out when risk swells.
- Size each position so the distance to stop equals your fixed percent risk.
- Allow up to two adds only after price advances 1R and structure remains intact.
- Never add if the position has pulled back to breakeven after reaching 1R.
- Reduce size into earnings or macro events unless explicitly modeled.
Exits: Rules for Losers and Winners
Exits are where many systems leak. Sovit’s approach keeps losers small and lets winners breathe with structure-based trailing. That balance preserves R-multiple math without micromanaging.
- Hard stop always lives on the broker; no mental stops.
- If price closes back through your trend filter, exit at the next open.
- Trail winners under higher swing lows or a short moving average (e.g., 20-day).
- Bank partial profits at +2R only if volatility expands and the risk of mean reversion rises.
Portfolio Construction & Correlation Control
He avoids loading up on names that move together. It keeps drawdowns smoother and the edge cleaner. Correlation sneaks up—so he checks it before entries, not after.
- Limit to one or two names per highly correlated group/sector.
- Avoid taking five “different” tickers that are all essentially the index.
- If three open positions share >0.8 correlation to the benchmark, drop the weakest.
- Balance exposures across trend phases; don’t crowd the same pattern.
Validation: From Idea to Live via “Shadow Mode”
Nothing goes live until it survives a simple validation path. Sovit sanity-checks ideas with quick historical reviews, then runs them in “shadow mode” (paper/live signals, no capital) before committing cash.
- Write the rule in one paragraph; if you can’t, it’s too complex.
- Manually review ~50 past signals to spot obvious failure modes.
- Run shadow trades for 4–8 weeks; track hits, misses, slippage, and emotion.
- Only go live if execution was straightforward and drawdowns felt “doable.”
Daily Routine & Trade Hygiene
Mindset enables the rules. Sovit keeps a repeatable routine so decisions feel boring—in a good way. That steadiness is what gets you through the cold streaks without breaking the system.
- Pre-market: update watchlist, mark levels, set alerts; no social feeds.
- During session: execute pre-written plans only; log entries/exits immediately.
- Post-market: tag outcomes (signal quality, execution grade, emotion notes).
- Use brief mindfulness drills before placing orders to reduce impulsive overrides.
Handling Drawdowns Without Breaking the System
Drawdowns happen; he plans for them. When equity dips, the goal is to shrink risk and keep taking qualified signals so the next cluster of winners can repair the dent.
- Pre-define a “slowdown line” (e.g., −8% peak-to-trough): cut per-trade risk by 50%.
- Freeze new strategy experiments until equity recovers above the slowdown line.
- Keep taking A-setups from your primary system; don’t widen stops or chase.
- Schedule a formal post-mortem at 12% to evaluate if regime filters need adjustment.
Regime Filters & Going Flat
Sometimes the best trade is cash. Sovit uses simple market filters to reduce exposure when conditions are hostile, protecting capital and confidence.
- Require the index to be above its long-term trend for net-long portfolios.
- If the index slips below and volatility spikes, scale down to half normal exposure.
- Go flat if both trend and breadth are broken and your systems keep triggering stops.
- Re-risk gradually as the filter flips back; don’t jump from zero to full size in a day.
Versioning & Continuous Improvement
He treats strategies like software: versioned, logged, and improved in small steps. Tiny upgrades compound; big rewrites often break.
- Change one rule at a time and tag it as a new version (v1.1, v1.2, etc.).
- Track metrics by version: win rate, average R, time-in-trade, heat, MAE/MFE.
- Roll back quickly if a new version underperforms for a full cycle of trades.
- Archive “retired” rules with a short note on why they were removed.
Options & Derivatives Overlay (When Used)
For names with liquid options, he’ll sometimes express the same directional view with defined risk. The intent is the same: keep losers small, avoid ruin, and let structure guide exits.
- Use debit spreads instead of naked calls to define risk and reduce decay bite.
- Align option duration with the expected move window (often 30–60 days).
- Exit the spread on a technical exit or at 50–75% of the max value, whichever comes first.
- Avoid selling undefined risk into earnings or high-volatility events unless explicitly modeled.
Size Risk First: Keep Losses Small, Let R-Multiples Compound
Sovit Manjani starts every trade by deciding how much he’s willing to lose—never the other way around. He fixes a small percent of equity at risk per idea, so a cold streak dents confidence but doesn’t kill the account. That one decision forces clean stops, saner position sizes, and fewer “hope” moments when price wiggles against you. When Sovit says “doable,” he means risk small enough that you can keep taking qualified signals without flinching.
He also ties risk to volatility, so loud names don’t knock him out, and quiet names don’t waste time. Stops sit where the structure actually breaks, and the position size is calculated backward from that distance, not guessed. Portfolio heat stays capped; if multiple positions stack up, he trims size before the market trims him. The magic isn’t big winners—it’s many small, controlled losses that let the occasional 2R–4R run show up in the equity curve.
Trade the Trend Stack: Momentum, Relative Strength, Simple Rules
Sovit Manjani trades with a simple stack: confirm the bigger trend, demand a momentum kick, then choose the strongest names versus the market. He starts with a higher-timeframe trend filter so he’s not fighting the tape, then waits for price to show fresh strength—like reclaiming a short moving average or taking out a recent swing. Only after trend and momentum align does Sovit sort by relative strength to prioritize leaders, not laggards pretending to wake up.
This three-part check keeps decisions clean and repeatable. It cuts false positives from lone signals, reduces overtrading, and funnels attention to setups that have multiple winds at their back. Sovit Manjani likes that it’s easy to execute day after day: no crystal ball, just a quick “trend, momentum, RS” pass before risking a dollar. When the stack isn’t aligned, he passes—because the missed trade he can always replace, but a broken rule starts a costly habit.
Volatility-Based Position Sizing and Adds You’ll Actually Stick With
Sovit Manjani sizes every trade-off volatility so the stop lives beyond normal noise, not in it. He calculates position size from the distance to an ATR- or structure-based stop, keeping per-trade risk small and consistent. When volatility expands, size shrinks automatically; when volatility contracts, size can step up without changing the risk percentage. This keeps execution calm because Sovit knows the math is protecting him, not wishful thinking.
Adds are earned, not assumed. Sovit Manjani only scales when the trade proves itself—typically after price advances one risk unit and structure holds. If a winner coughs back to breakeven after a first add, he stops adding and often trims to the original size. The effect is a staircase of justified exposure in good trends and self-limiting damage when conditions turn choppy. It’s simple, mechanical, and—most importantly—doable when emotions try to hijack the plan.
Diversify By Underlying, Strategy, and Duration To Smooth Drawdowns
Sovit Manjani spreads exposure so one market mood can’t wreck the whole month. He mixes indices with leading single names, and when options are liquid, he’ll overlay defined-risk structures so not every bet is a naked directional punt. He also diversifies entry logic—primary trend-following alongside a small, rules-based pullback module—so he isn’t relying on a single trigger to pay the bills. The aim is simple: different edges, different pathways to P&L, fewer perfectly correlated headaches.
Duration is part of the edge, too. Sovit staggers holding periods—some swings intended for days to weeks, a few positions managed for multi-week trend legs—so exits don’t all fire during the same volatility burst. He watches correlation, limiting clones from the same sector or factor and dropping the weakest when the basket starts walking like the index. When conditions get hostile, he dials back gross exposure and shifts weight to the more “durable” sleeve, keeping the equity curve steadier without abandoning the plan.
Mechanics Over Prediction: Pre-Plan Entries, Exits, and Slowdowns
Sovit Manjani treats every trade like a checklist, not a forecast. He decides the entry trigger, the stop location, and the first take-profit before he lifts a finger, so there’s nothing to “figure out” when the candles start moving. If price hits the entry without the full checklist, he skips it; if the stop hits, he’s out instantly—no debate, no story, no “just this once.” The point isn’t to predict the next bar; it’s to execute the next rule flawlessly.
He also pre-plans the slowdown switch for when equity draws down, because that’s when traders make their worst decisions. Sovit Manjani halves risk after a predefined loss threshold, pauses all experiments, and only takes A-setups until the account recovers. Journal notes are mandatory, capturing whether he followed the plan, not whether the market behaved. By removing guesswork and scripting responses ahead of time, he keeps the process boring—and the results far more consistent.
In the end, Sovit Manjani’s edge isn’t a magic indicator—it’s a durable operating system forged by hard lessons. He was humbled by the 2008 bear market, rebuilt with a rule-based mindset, and deepened his craft through the CMT curriculum by 2013. From there, he kept the logic simple: trade with trend, require a momentum kick, and prioritize leaders. The point is to make execution boring and repeatable so the math can work—small, fixed risk per trade, stops where structure truly breaks, and position sizes calibrated to volatility rather than hope.
Equally important is how Sovit manages the human side. He treats drawdowns as a design constraint, not an afterthought, aiming for “doable” pain rather than theoretical perfection. When a system version hits turbulence, he doesn’t panic-pivot; he runs the new version in parallel, lets the old one exit its drawdown, and only then transitions. Meditation and physical training aren’t accessories in his playbook—they’re the braces that keep discipline intact when markets turn noisy. The result is a pragmatic framework any trader can adopt: codify your rules, size through volatility, version your improvements, and protect your mindset so you can keep showing up long enough for the edge to show.
