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This interview features Rajan Dhall—a 15-year trading veteran, strategy designer, and founder of DND Capital—sitting down with host Riz on the Words of Wisdom trading podcast. Rajan’s path runs from STA technical analysis and newsroom squawk desks to running live rooms where traders can see his entries, stops, and targets in real time. He’s written for major finance outlets and coached traders on matching personality to approach, but what stands out is his radical simplicity: naked charts, one trade a day, and an ethos where psychology and risk management matter as much as the system.
In this piece, you’ll learn Rajan’s “33/33/33” lens (strategy, risk, psychology), why he abandoned indicator-heavy charts, and how he now uses simple cues—like a 21-day moving average—for bias rather than signals. You’ll also see how he builds consistency through routine, accountability, and strict risk limits, plus his take on sentiment and money flow, so you can focus where volatility actually pays. If you’re a trader chasing a clean, durable process, this is a beginner-friendly blueprint you can apply today.
Rajan Dhall Playbook & Strategy: How He Actually Trades
Core Philosophy: Simple Charts, Three Equal Pillars
Rajan strips the chart back to price and focuses on doing a few things exceptionally well. He frames performance as a balance of three equal parts—strategy, risk management, and psychology—while avoiding indicator clutter and information overload.
- Trade naked or near-naked charts; if you add anything, it must improve clarity, not add noise.
- Treat strategy/risk/psychology as 33% / 33% / 33%—no pillar compensates for a missing one.
- Before adding inputs, ask: “Does this make my decision faster or my risk tighter?” If not, remove it.
- When in doubt, prioritize a clean price structure over lagging indicators.
Market Bias: One Clean Filter to Define Trend
He prefers trending conditions and uses a single moving-average lens to define bias—simple, binary, and consistent. The point is not to predict but to align with the path of least resistance.
- Use a 21-period moving average on your main timeframe to set bias:
- Above = long-only mindset; Below = short-only mindset.
- If price chops around the 21MA (three or more flips in 20–30 bars), stand down until structure cleans up.
- Weekly trend contradicts daily bias? De-risk or pass—only take trades when higher and the trading timeframe agrees.
Setup & Entry: Structure First, Then a Trigger
Rajan forms a view from structure and context, then waits for a simple, repeatable trigger. He’s not trying to catch every move—just the clean ones where structure, bias, and execution line up.
- Baseline conditions (all must be true):
- Price aligned with 21MA bias.
- Fresh higher-high/ higher-low (for longs) or lower-high/ lower-low (for shorts) on your execution timeframe.
- No major data release within the next 15–30 minutes.
- Entry triggers (pick one):
- Pullback to prior value area/mini-range followed by rejection wick and close back in trend direction.
- Break-and-retest of a clear level with failed push against your bias (wick through, close back inside).
- If the candle that triggers your entry exceeds your max stop distance, skip—don’t force R: R to fit after the fact.
Risk Management: Pre-Defined and Non-Negotiable
His edge survives because risk is fixed, small, and planned. The goal is a consistent R multiple, not a perfect hit rate.
- Risk per trade: 0.25%–0.5% account risk until you’ve logged 100+ trades with positive expectancy.
- Stop placement: beyond the prior swing that invalidates the structure (longs: below swing low; shorts: above swing high). Aim for ~2:1 reward-to-risk on base setups.
- If price moves +1R, move stop to breakeven only after a structure break in your favor; otherwise, let the initial stop stand.
- If you widen a stop, you must reduce the size to keep initial risk constant—never “hope-add.”
Trade Management: Measured, Rules-Driven, Calm
He doesn’t babysit every tick; he manages by structure and planned targets so psychology doesn’t hijack decisions. The idea is fewer, higher-quality decisions executed the same way each time.
- Targets:
- Base case: +2R; stretch to +3R only if trend remains intact (higher-timeframe momentum and clean pullbacks).
- Scale-out rule: optional 50% at +1R only if volatility expands abruptly; otherwise hold for full +2R.
- Time stop: if price hasn’t reached +0.5R within 8–12 bars on the execution timeframe, consider exit—your read is likely early or wrong.
- One change at a time: if you adjust stop logic this week, do not change targets until next week’s review.
Psychology & Process: Build the Trader, Not Just the Trade
Rajan emphasizes that psychology and risk discipline carry as much weight as the setup itself. He profiles personality and risk tolerance so the method fits the human, not the other way around.
- Complete a personality + risk profile; don’t day-trade if you’re naturally methodical and patient (swing may fit better).
- Pre-commit: write the entry, stop, size, and two exit conditions before placing the order.
- Rate each executed trade 1–5 on discipline (followed plan?) and state the emotion at entry/exit in your journal.
- If you break a rule, tag and size down next session by half until two clean sessions reset confidence.
Event Risk & “Info Diet”: Trade Around the Calendar
He accounts for structure heading into key releases and avoids drowning in data that doesn’t move his edge. Keep the calendar tight and the plan tighter.
- No new positions within 15–30 minutes before tier-1 releases (CPI, NFP, FOMC, central bank decisions).
- If already in a trade pre-event: halve size or move stop to reduced-risk (e.g., 0.2R exposure) unless your tested plan says otherwise.
- Post-event, wait for two closes that re-confirm your 21MA bias before re-engaging.
Routine & Review: Make Consistency Inevitable
The routine makes the method. Rajan stresses repetition, journaling, and accountability so improvement compounds whether a trade wins or loses.
- Daily prep (20–30 min): mark higher-timeframe bias, two key levels, the day’s event risk, and a single “A-setup” you’ll allow.
- After session (10 min): screenshot chart with entries/exits, annotate rules followed/violated, and log R results.
- Weekly review: compute win rate, average R, and expectancy; keep/change exactly one rule based on data—never overhaul the system after a small sample.
Execution Framework: From Scan to Done
This is how the whole thing flows in practice—fast to run, easy to repeat, and hard to mess up if you stick to it.
- Scan: pick 3–5 symbols with clean alignment to the 21MA on daily + execution timeframe.
- Plan: define structure, event windows, entry trigger, stop, size, target(s).
- Execute: place a single limit/stop order; no chasing.
- Manage: follow the pre-set rules; no discretionary tweaks mid-trade unless explicitly part of the plan.
- Record: journal and tag each trade for future iteration—edge is built in the review, not the result.
Size Every Trade by Volatility; Cap Daily Risk Like a Pro
Rajan Dhall keeps it simple: position size expands and contracts with volatility, not with gut feel. When the range widens, he dials down size so the same stop distance risks the same slice of equity. When the range tightens, he can step up in size while keeping risk constant. That way, a wild market doesn’t hijack his P&L, and a quiet tape doesn’t waste opportunity. Rajan Dhall’s point is that consistency in risk per trade beats any fancy forecast.
He also hard-caps total risk for the session, so one bad morning can’t ruin the week. If he hits that daily limit, he’s done—no revenge trades, no “one more try.” The cap protects psychology as much as capital, keeping execution steady for the next setup. Over time, this combo—volatility-based sizing plus a non-negotiable daily stop—turns uneven markets into a smoother equity curve.
Diversify Across Underlying, Strategy, and Timeframe to Smooth Equity Curves
Rajan Dhall spreads risk on purpose: not just across markets, but across how he trades them and over what horizons. He’ll pair a trending FX play with a mean-reversion equity index scalp and a swing in a strong commodity theme, so one bad patch doesn’t dominate returns. The goal isn’t more trades—it’s different return drivers that don’t all fail the same way. Rajan Dhall keeps correlation in mind, rotating to instruments that move on separate catalysts when possible.
He also diversifies execution rules and holding periods while keeping risk logic constant. A daily-bias trend setup can coexist with a tighter intraday pattern and a slower swing framework, each with its own triggers and time stops. This mix reduces the “all or nothing” feel of a single method in a single market. When one lane stalls, another can carry the portfolio, and the equity curve stays steadier without sacrificing edge.
Trade Mechanics Over Predictions: Predefine Setup, Trigger, Stop, and Target
Rajan Dhall doesn’t try to outguess the market—he out-processes it. He decides the setup before the session, names the exact trigger that gets him in, and knows precisely where the trade is wrong. That means no mid-candle improvisation, no moving stops because “it might bounce,” and no target creep when price inches close. Rajan Dhall’s edge lives in repeatable mechanics, not forecasts, so every click is either your plan or a pass.
He writes the four parts on the chart: setup context, entry trigger, stop location, and target path. If the price doesn’t meet the trigger, he doesn’t trade; if it does and the stop is too wide, he sizes down or skips. Targets are set by structure first, R-multiple second, so reward isn’t a wish—it’s mapped. By treating execution like a checklist, he keeps emotions boxed out and lets statistics—not guesses—do the heavy lifting.
Use Defined-Risk Structures; Avoid Open-Ended Loss From Undefined Risk
Rajan Dhall is blunt about it: if a position can blow past your max loss without a plan to stop it, it doesn’t belong in your playbook. He builds trades around structures where the worst-case is known up front—clear invalidation levels, hard stops, and size that respects the distance to that line. No averaging down, no “it can’t go lower,” no naked exposure to gap risk you can’t absorb. Rajan Dhall would rather miss a home run than take a swing that can bankrupt the account.
He keeps risk defined in practice by using the prior swing as a structural stop and calculating size backwards from that distance. If volatility stretches the stop beyond his max per-trade risk, he cuts size or skips—simple as that. He treats undefined-risk behaviors as rule breaks: adding to losers, removing stops, or trading into binary events without a contingency plan. This way, every trade is a measured bet with a capped downside, not an open invitation to disaster.
Process First: Routine, Journaling, and Weekly Review Drive Consistency
Rajan Dhall treats consistency as a process, not a mood. He starts each session with a brief plan: bias, two levels, and the one setup he’s allowed to take. That constraint keeps him from chasing anything outside the lane. If the plan’s trigger never prints, he logs a zero-trade day and calls that a win.
After the close, Rajan Dhall journals screenshots, entry logic, emotions at click, and whether he obeyed rules. He scores each trade on discipline, not P&L, so wins that break rules don’t get celebrated. Weekly, he computes win rate, average R, and expectancy, then changes exactly one rule at most. That “one tweak only” policy prevents system-hopping while still evolving the edge. Over months, the repetition builds a personal playbook that survives bad days because the process never changes.
Rajan Dhall’s core message lands with refreshing clarity: strip the chart back to price, define a single bias filter, and let rules—not opinions—drive execution. He leans on a simple trend lens (think one clean moving average to decide long-only or short-only), then waits for structure to confirm before acting. Position size flexes with volatility, so every trade risks a consistent slice of equity, and a hard daily loss cap keeps both capital and mindset intact. The result is an approach that survives different market moods because it’s built on mechanics, not forecasts.
He treats risk as non-negotiable and process as the real edge. Stops sit beyond invalidation, targets are mapped by structure and R-multiples, and undefined-risk behavior—adding to losers, pulling stops, trading into binary events without a plan—simply doesn’t cut. Beyond a single setup, he smooths the equity curve by diversifying across instruments, strategies, and timeframes while keeping risk logic constant. And he closes the loop with routine and review: pre-session plans, disciplined journaling, and one small, data-driven tweak at a time. Do that the Rajan Dhall way and you won’t need to predict; you’ll just need to execute.
