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On this Words of Rizdom podcast quick-hit, RTD Krishna Sharma sits down with host and returning guest Pat to talk straight about trading: why most beginners stumble, how mindset beats fancy indicators, and what actually keeps you consistent. Krishna’s known in the Viper community for cutting through hype and putting discipline first, and here he breaks down the real-world lessons from teaching, trading prop challenges, and growing personal accounts—stuff that matters whether you’re on demo or live.
Read on to learn the core takeaways: why you should think in percentages (not dollars), how fixed risk (often 0.5%–1%) stabilizes your equity curve, the pros and cons of prop firms vs. building a personal account, and the buyer–seller/liquidity lens Krishna uses to keep setups simple and repeatable. You’ll walk away with a beginner-friendly playbook you can apply today—mindset first, risk defined, and strategy executed with boring consistency.
Patrick Frain Playbook & Strategy: How He Actually Trades
The Core Framework Patrick Runs
Think of this as Patrick’s operating system—what he trades, when he’s active, and what he waits for before pressing the button. Knowing the lanes he stays in will help you cut noise and build a routine you can actually stick to.
- Trade the most liquid products first (e.g., majors/US indices) and only add a second market once the first is consistently profitable.
- Focus on two sessions: London open and New York open; be flat into major news unless the setup is already risk-free.
- Build a small menu of A-setups (2–3 patterns max) and ignore everything else.
- Accept that “no trade” is a position; if conditions are off (range chop, holiday liquidity), stand down.
Setups He Actually Takes (And Why)
Patrick filters for context first (trend, liquidity, time of day), then looks for a precise trigger. This section translates that into rules you can copy and test.
- Context: identify higher-timeframe bias (daily/4H swing points, prior day high/low, weekly open) before any lower-timeframe trigger.
- Liquidity map: mark equal highs/lows, session highs/lows, and obvious stop pools; prefer entries that run into/away from these levels.
- Triggers:
- Reversal: stop-run through a key level → swift reclaim → break of the reclaim candle; enter on the first pullback.
- Continuation: pullback to prior breakout level or VWAP/AVWAP with rejection wick and absorption on the tape.
- If the trigger candle’s range > 1.5× your average entry bar, pass—volatility is too jumpy for tight risk.
Risk: Fixed, Boring, Relentless
Patrick’s edge compounds because he keeps risk fixed and survivability high. These are the guardrails that keep hot streaks from turning into setbacks.
- Risk a fixed 0.5%–1.0% per trade; never scale risk because you “feel” confident.
- Hard stop goes in immediately; no “mental stops.”
- One add-on only, and only if the initial risk is covered (move stop to breakeven after +1R).
- Daily loss cap = 2R; hit it and you’re done—no exceptions.
- Weekly drawdown circuit-breaker: pause if down 5R on the week and switch to replay/backtest.
Trade Management & Exits
Entries are easy; exits are where P&L is made. Patrick uses mechanical targets so emotions don’t negotiate with the market mid-trade.
- Pre-define two targets: T1 at 1R to pay yourself, T2 at structure (next liquidity pool, ADR band, or prior day high/low).
- Trail only behind structure (swing low/high or VWAP reclaim), not behind arbitrary fixed ticks once 1R is booked.
- If price stalls for two full candles at your level with decreasing momentum, punch out—protect time in trade.
- News exception: if a high-impact release is due in <10 minutes and your trade isn’t at least +1R, flatten.
Prop Firms vs. Personal Accounts (How He Navigates Both)
Patrick is pragmatic about rules, drawdowns, and payout stability. Use these rules to avoid typical pitfalls and build durability.
- Treat prop evaluation like a different product: lower risk (0.25%–0.5%), strict max daily loss, stop trading after a strong morning.
- Scale payouts in tranches (e.g., 30%, 30%, 40%) to de-risk the account and move capital to a personal account.
- Keep the same playbook between prop and personal—only sizing and session filters change.
- Never chase objectives; if you’re behind on the target, keep the risk the same and extend the evaluation via consistency, not impulse.
Pre-Market Routine That Sets Up The Day
Consistency starts before the bell. Patrick front-loads decisions so execution is near-automatic during the session.
- 30–45 minutes pre-session: mark higher-timeframe levels, session liquidity, overnight high/low, and expected range (ADR/ATR).
- Write a one-liner for bias: “Bullish above X while Y holds; fade into Z if sweep + reclaim.”
- Define the two A-setups you will take today and the exact invalidations; if it’s not on the card, it’s not getting traded.
- Visualize the first trade: entry, stop, partials, and the point where you’ll stand down.
Psychology: The Circle, Monk Mode, and Noise Control
Patrick emphasizes protecting focus and the environment. The point is to keep your decision-making clean when the market is loud.
- Curate your circle: interact with traders who publish plans before the open and outcomes after—no hindsight heroes.
- Monk mode windows: 60–90 minutes of zero notifications around entries/exits; review social or chat only after flat.
- Use a reset ritual after losses: two minutes of breathwork + walk + rewrite of next trade criteria; never revenge trade.
- Track “emotional R”: note when you deviate from the plan and assign a negative R; aim to keep emotional R ≥ 0 weekly.
Data, Journaling, and Iteration
Patrick keeps stats so the playbook evolves with evidence, not vibes. Here’s how to capture the right data without turning it into a second job.
- Journal only what changes decisions: setup type, time, location vs. liquidity, R multiple, and reason for exit.
- Weekly audit: sort trades by setup and session; cut the lowest-performing combo for the next week.
- Maintain a “kill list” of contexts you do not trade (e.g., mid-range chop, post-news drift, inside-day afternoons).
- Build a 20-trade sample before tweaking rules; one good or bad day doesn’t justify rewriting the playbook.
A-Setup Checklist (Copy This)
When it’s go-time, Patrick runs a quick checklist to avoid forcing trades. Use this to standardize execution.
- Bias aligns across daily → 15m; price is at or near a mapped liquidity level.
- Time filter passes (London/NY open) and no red-flag news in the next 10 minutes.
- Trigger appears (stop-run + reclaim or VWAP retest with rejection) and risk fits within 0.5%–1.0%.
- Trade plan written: entry, stop, T1 at 1R, T2 at structure, add-on rules, and invalidation.
- If three boxes fail, skip and wait—opportunity cost beats actual loss.
Example Parameters (So You Can Test)
Concrete numbers help you prototype quickly. Start here and iterate with your own stats.
- Stop size cap: 0.35× ADR for indices; 0.20× ADR for FX majors.
- Target bands: T1 = 1R; T2 = opposing liquidity pool or 0.8× ADR, whichever comes first.
- Max open risk: one position at a time; no stacking unless the first position is risk-free.
- Weekly target: +3R with a hard stop at 5R; once the target is hit, size down or switch to sim for the rest of the week.
Krishna Sharma Playbook & Strategy: How He Actually Trades
What Krishna Prioritizes (The Operating Principles)
This is the backbone of how Krishna approaches the market—what gets his attention and what he ignores. Use these principles to keep your day clean, focused, and executable under pressure.
- Trade liquid majors and US indices first; only diversify once your stats are stable.
- Think in percentages, not dollars; judge every decision by risk taken vs. R returned.
- Keep a compact menu of A-setups (2–3 patterns) and pass on everything else.
- If the environment is thin (holidays, pre-news chop), stand down—cash is a position.
Markets, Sessions, and When He Strikes
Krishna filters opportunities by time and volatility, so he meets the market when it’s most likely to pay. This section sets your schedule so you aren’t forcing trades in dead zones.
- Primary activity windows: London open and New York open; avoid mid-session chop unless price is at a key level.
- Be flat into high-impact events unless already risk-free; let the market re-price and then reassess.
- Track ADR/ATR to know what “normal” movement looks like and size stops inside those bounds.
- No trades in the last hour of the session unless it’s a clean retest into closing flow.
The Setups Krishna Actually Takes
Context first, trigger second. Krishna wants prices at meaningful levels with a clear sign that one side is trapped. These rules give you a repeatable way to find that.
- Context checklist: prior day high/low, weekly open, session extremes, obvious liquidity pools (equal highs/lows).
- Reversal template: stop-run through a mapped level → swift reclaim → break of reclaim bar high/low → pullback entry.
- Continuation template: retest of breakout level or VWAP/AVWAP with rejection wick + lower-timeframe absorption.
- Skip if the trigger candle > 1.5× your average entry bar or if the spread widens beyond normal.
Risk & Sizing (Boring On Purpose)
Survival is the edge. Krishna fixes risk per trade so a bad hour doesn’t become a bad month.
- Fixed risk: 0.5%–1.0% per trade; never increase risk because you “feel” it.
- Hard stops only; place immediately and don’t move them further from the entry.
- Daily circuit breaker: −2R, done for the day. Weekly breaker: −5R, switch to review/sim.
- One add-on max, only after locking +1R and moving stop to breakeven.
Entry, Management, and Exits
Krishna pre-plans exits so emotions don’t negotiate mid-trade. Here’s how he turns good entries into booked R.
- Pre-set targets: T1 at +1R to pay yourself; T2 at next liquidity pool, ADR band, or prior day extreme.
- Trail behind structure (last swing or VWAP reclaim) after T1 prints; no arbitrary tick trails.
- If momentum dies (two full candles of stall at level), flatten and recycle the idea later.
- If a major release is due in <10 minutes and trade < +1R, exit and re-evaluate after the print.
News & Event Playbook
Event risk can make or break your week. Krishna treats news as a separate regime with clear boundaries.
- Pre-news: map the two most likely path dependencies (breakout vs. fade) with invalidations.
- No fresh risk within 10 minutes of high-impact news; exceptions only if already risk-free.
- Post-news: wait for first impulse, then structure; trade the retest, not the spike.
- If the first minute’s range exceeds ADR×0.25, reduce the size by half for the next attempt.
Prop Evaluations vs. Personal Account
The setup stays the same; only the constraints change. Krishna adapts sizing and session filters to respect prop rules while building personal equity.
- Prop mode: 0.25%–0.5% risk, one trade per session unless +1R early; stop on any rule breach risk.
- Payout strategy: withdraw in tranches and seed a personal account; keep strategies identical to avoid cognitive load.
- Don’t chase targets; if behind, keep risk unchanged and extend the evaluation with consistent days.
- Maintain identical journaling across both accounts so stats remain comparable.
Daily Routine & Prep
Your preparation determines your restraint. Krishna compresses decisions before the bell, so execution is almost automatic.
- 45 minutes pre-session: mark HTF levels, session highs/lows, and expected range; write the bias line for the day.
- Define today’s two A-setups with precise invalidations; if it’s not on the card, it’s not getting traded.
- Visualize the entry, stop, and partial plan; decide in advance when to stand down.
- Post-session: tag trades by setup and session; log deviations as “emotional R”.
Psychology & Environment Control
Focus is a force multiplier. Krishna engineers his environment so he trades the plan, not the P&L.
- Silent windows: 60–90 minutes around entries/exits with all notifications off.
- Reset protocol after a loss: two minutes breathwork → short walk → rewrite next-trade criteria; no instant re-entries.
- Curate inputs: only follow traders who publish plans pre-market and results post-market.
- Track emotional R weekly; goal is to keep it ≥ 0 by eliminating off-plan clicks.
Data, Journaling, and Iteration
Iterate with evidence. Krishna keeps the data inputs light but decision-changing.
- Log only what affects decisions: setup, location vs. liquidity, time, R multiple, and exit reason.
- Weekly review: rank setups by R/attempt and win rate by session; bench the bottom combo next week.
- Build 20-trade samples before altering rules; avoid reacting to one-off outcomes.
- Maintain a “do-not-trade” list (mid-range chop, inside-day afternoons, thin holidays) and update it monthly.
A-Setup Checklist (Quick Yes/No)
When the alert hits, run this checklist in seconds. If it doesn’t pass, you wait.
- Bias aligns from daily → 15m; price at a mapped liquidity level.
- Time filter passes (London/NY open) with no imminent red-flag news.
- Trigger prints (stop-run + reclaim or VWAP retest + rejection) and stop fits inside 0.5%–1.0% risk.
- Plan written: entry, stop, T1=1R, T2=structure, add-on rule, invalidation.
- Three or more “no’s” = skip; opportunity cost beats actual loss.
Starter Parameters You Can Test
Numbers make it real. Use these as a baseline and refine with your own stats.
- Stop cap: 0.20× ADR for FX majors; 0.35× ADR for US indices.
- Targets: T1 at +1R; T2 at next liquidity pool or 0.8× ADR (whichever comes first).
- Position concurrency: one open trade; add only after the first is risk-free.
- Weekly framework: aim +3R, hard stop −5R; after hitting target, reduce size or move to sim.
Size Risk First: Fix Percent, Let R-Multiples Drive Every Decision
Patrick Frain hammers home that consistency starts with defined risk per trade, not with finding a “perfect” setup. He fixes a small percentage—think half to one percent—so every position is sized backward from the stop, never forward from hope. Krishna Sharma echoes the same rule, reminding traders that dollars distract while percentages clarify, especially during drawdowns. Both traders treat R as the scoreboard: plan for 1R at the first partial, let structure determine the rest, and refuse to widen stops after entry.
This approach frees your mind to execute instead of negotiate. Patrick Frain cuts the trade when invalidated because the risk was prepaid; no “give it a little room” excuses. Krishna Sharma keeps the daily loss cap at a hard multiple of R, shutting the platform when it’s hit, so a tough morning doesn’t become a ruined week. Together they prove that when risk is fixed, the only variable left is performance—and that’s exactly how you build a curve that climbs.
Trade the Mechanics, Not Predictions: Let Levels, Liquidity, and Timing Lead
Patrick Frain keeps forecasts out of it and lets the tape do the talking. He lines up prior day highs/lows, weekly opens, and session extremes, then waits for the price to interact with those areas before acting. If liquidity is thin or price is mid-range, he does nothing—because no level, no trade. When the market raids a stop pool and immediately reclaims, Patrick triggers off the reclaim candle, not a hunch.
Krishna Sharma runs the same play by prioritizing structure and time of day over opinions. He wants clean interaction at VWAP/AVWAP or a fresh breakout retest, ideally during London or New York opens when volume confirms intent. If momentum stalls for a couple of candles at a key level, Krishna exits, proving mechanics also dictate when to quit. Together, Patrick Frain and Krishna Sharma show that focusing on levels, liquidity, and timing beats calling tops and bottoms—execution first, predictions never.
Volatility Controls Allocation: Use ATR/ADR Bands To Set Stops And Targets
Patrick Frain sizes positions by what the market is actually doing today, not what he wishes it would do. He caps stop distances as a fraction of ADR, so a hot, wide-ranging session naturally shrinks his size while a calmer day allows a touch more. Patrick also anchors first targets to 1R and stretches second targets toward opposing liquidity or a percentage of ADR, making exits scale with conditions instead of ego. If the trigger candle is too large relative to recent volatility, he simply passes—no setup is worth breaking the risk math.
Krishna Sharma applies a similar volatility governor using ATR on the instrument’s primary timeframe. He rejects fixed-tick stops, preferring ATR-based buffers that keep noise from knocking him out while still respecting the 0.5%–1.0% risk cap. Krishna will downshift after a volatility spike—cutting size or waiting for a retest—because post-news ranges can fake momentum and punish late entries. Together, Patrick Frain and Krishna Sharma prove the point: let ATR/ADR dictate stops and targets, and your allocation will adapt automatically to the market you actually have.
Diversify Smartly: Underlying, Strategy, and Duration—Not Ten Correlated Setups
Patrick Frain warns that adding more charts isn’t diversification if they move together, so he spreads risk across uncorrelated underlyings first. He then layers diversity by strategy—running both mean-reversion fades and breakout continuations—so one playbook isn’t carrying the whole week. Patrick also staggers holding periods, mixing quick session trades with occasional multi-hour swings, which smooths equity without bloating exposure. When a combo overlaps too much, he cuts one and keeps the cleaner edge.
Krishna Sharma follows the same logic but makes it rule-based: no more than one position per theme, and avoid doubling up on instruments tied to the same macro impulse. He prefers a “2×3×2” grid—two underlyings, three setups, two typical durations—so performance is driven by independent levers, not luck. Krishna audits correlation after every week; if P&L rises and falls together across trades, he trims until the curve breathes again. Both Patrick Frain and Krishna Sharma prove that smart diversification is designed on purpose—by underlying, by strategy, and by time—so a single market mood can’t wreck your month.
Process Before P&L: Pre-Market Plan, Post-Market Review, Ruthless Discipline
Patrick Frain starts every session with a written bias, mapped levels, and two A-setups preselected—no plan, no trade. He measures success in executed process, not dollars, logging whether entries matched the trigger and if stops/targets were honored. When the day hits −2R, Patrick shuts it down and switches to review, protecting the weekly curve from one bad stretch. He treats discipline like a position: you either hold it or you’re out of the market.
Krishna Sharma runs the same play with a tight loop—plan, execute, debrief—so small improvements compound. He tags each trade by setup, session, and location versus liquidity, then benches the lowest-performing combo for the next week. Krishna scores “emotional R” to quantify off-plan clicks and aims to keep that number at or above zero. Together, Patrick Frain and Krishna Sharma show that when process quality is the KPI, the P&L follows as a lagging metric—not the other way around.
In the end, the message from Patrick Frain and Krishna Sharma is surprisingly simple: win by taking care of the downside first and letting the upside take care of itself. Fix risk as a small percent, think in R, and let volatility set your stop and objectives so you’re trading the market you actually have—not the one you hope for. Trade the mechanics—levels, liquidity, and time-of-day—rather than predictions, and diversify on purpose by underlying, strategy, and holding period so one market mood can’t nuke your week.
Wrap that in process and you’ve got something durable. Come in with a written bias and two A-setups, execute only when your checklist is true, and cap the day when you hit your max loss so discipline doesn’t leak. Journal the few things that change decisions, bench the lowest-performing combo each week, and track “emotional R” to keep off-plan clicks from taxing your edge. Do that consistently, and—as both Patrick Frain and Krishna Sharma show—the curve follows.
