Table of Contents
This interview brings together trader Riz and macro-focused trader–researcher Joe for a no-fluff conversation on what it really takes to win in the markets. Filmed for the “Words of Rizdom” podcast, the session dives into how these two think, work, and balance real-life responsibilities while trading—why they matter, in short, is that they combine lived execution with thoughtful analysis. You’ll hear candid talk about the lonely grind, the value of a strong network, and how consistency outside the charts (gym, routines, family) often mirrors consistency on them.
Read on to learn the actionable bits: how Riz blends technical execution with growing fundamental awareness, how Joe frames inflation/CPI and bond-market signals for FX, and how both approach risk, scaling, and prop-firm psychology without getting wrecked. You’ll get a beginner-friendly map for building discipline, filtering distractions, and spotting when to push vs. when to protect—so you can craft a trader strategy that actually fits your life, not just your watchlist.
Riz Sardar Playbook & Strategy: How He Actually Trades
Core Philosophy & Market Focus
Before charts, Riz is big on building a professional framework and removing emotional noise. He blends technical execution with a growing macro process, aiming to behave like an asset manager, not a gambler.
- Trade like a professional: define process, tools, and risk rules before touching the buy/sell buttons.
- Keep a mechanical bias: if a rule isn’t testable or repeatable, it doesn’t go in the plan.
- Start with markets you actually understand; list knowledge gaps (equities, bonds, macro basics) and close them methodically.
- Review price reaction to primary macro events directly (e.g., central bank statements) before trusting commentary.
Set Up Criteria: When He Allows Himself to Trade
Riz favors clear, high-quality conditions over constant action. The goal is to filter for asymmetric opportunities that fit his plan and timeframe.
- Only trade a setup if the market structure aligns on two adjacent timeframes (e.g., H1 with M15).
- Require a catalyst: session liquidity (London/NY overlap), range break, or scheduled data that can drive expansion.
- Price must be at a predefined area: prior day high/low, weekly level, or a mapped supply/demand zone—no “mid-range” chasing.
- If spread/volatility pushes stop distance beyond pre-set risk, skip; the pass is part of the edge.
Execution Rules: From Trigger to Fill
Execution is simple on purpose so it can be repeated under stress. Entries are planned; clicks are just the final confirmation.
- Pre-define entry, stop, and first target before the order; no clicking without coordinates.
- Use limit orders at levels when liquidity is strong; switch to market orders only on momentum breaks you planned.
- First scale-out at 1R to reduce variance, then trail to structure (last swing or session VWAP/prevailing pivot).
- Never widen a stop; cancel, re-plan, or accept the loss.
Risk & Position Sizing: Survive First, Compound Second
He treats risk as a fixed business expense. Sizing flexes with volatility, but account drawdown and per-trade loss are capped.
- Risk per trade: 0.25%–0.75% account risk; hard daily loss cap: 1%–1.5%, then shut down.
- Volatility filter: if ATR pushes a logical stop >0.75% risk, either reduce size or stand down.
- Max concurrent risk: 1.5% across correlated positions; new trades require offsetting exposure.
- Equity curve rule: after any 3R sequence, trade half-size until two clean winners print.
Trade Management: Scaling, Targets, and “Do Nothing”
Winners are managed by rules, not vibes. Scaling locks progress without killing potential.
- At +1R, bank 30% and move stop to breakeven only if structure confirms; otherwise, keep original stop until +1.2R.
- Trail beneath/above swing structure on the execution timeframe; widen only if the higher timeframe trend is intact.
- Time stop: if price goes nowhere for one full session after entry, reduce exposure by half.
- News proximity rule: 15 minutes before tier-1 data, close partials, and park stops at logical structure.
Macro Filter He Uses More Each Year
Riz is increasingly blending fundamentals with his technicals. He looks at how bonds, rates, and equities narrate FX moves, then checks if price action agrees.
- Map the macro driver first (policy path, growth/inflation impulse), then pick instruments that express it cleanly.
- Read primary sources for rate/FX context (central bank statements, minutes, presser Q&A), then compare to market reaction.
- No macro = no trade on higher-timeframe swings; day trades can be technical-only but must avoid fighting the dominant macro impulse.
- If macro and technicals diverge, size down or wait for alignment.
Session Playbook: Routine That Makes Entries Obvious
Consistency comes from ritual. The same checklist every day reduces decision fatigue and errors.
- Pre-London: mark yesterday’s high/low, Asia range, and news times; write a one-line bias for each pair.
- Pre-NY: reassess with futures, DXY, and yields; update levels and kill any idea that lost context.
- Mid-day: journal morning executions with screenshots; set alerts at untouched levels for the close.
- End-day: export stats (R, win rate, MAE/MFE); tag each trade by setup and session for weekly review.
Psychology: Mechanical Over Motivational
The emotional edge is built outside the trade via rules, reps, and environment—not hype.
- Trade the plan you wrote when calm; if you edit it mid-session, you’re not trading—you’re improvising.
- One distraction rule: during execution windows, phone on airplane mode and notifications off.
- Loss acceptance protocol: after a full-rule loser, take a 10-minute reset and re-read the checklist before any new order.
- Weekly “no-trade” hour: review missed setups and FOMO screenshots to desensitize the trigger.
Networking & Environment: Only Exchange Real Value
Riz is selective with who he lets into his circle—he filters for mutual value and growth, not clout. This keeps his information diet clean and focused.
- Meet fewer people, more intentionally: attend events with an agenda and questions tied to your current edge.
- Share something concrete (research, levels, a tool) before asking for time or feedback.
- If a conversation doesn’t improve your process, politely exit; time is edge.
- Build a small mastermind with complementary strengths (macro, execution, journaling) and consistent cadences.
Professionalization: From Retail to Asset Manager
Beyond content, Riz frames himself as a manager of outside capital, with expectations and structure to match. Your rules should reflect that same accountability.
- Write a one-page “Fund Mandate” for your own account: instruments, max leverage, risk limits, drawdown rules, and reporting cadence.
- Produce a Monthly Letter (even if nobody reads it): P&L, volatility, best/worst trades, and process improvements.
- Keep a compliance mindset: no revenge trading, no off-plan bets, no sizing beyond mandate—ever.
- Track capacity: if average slippage worsens or spreads balloon at your size, scale back until fills normalize.
Joe Olashugba Playbook & Strategy: How He Actually Trades
Core Philosophy: Macro First, Price Always Confirms
Joe approaches markets like a macro analyst who must still trade clean levels. He builds a top-down narrative from policy, growth, and inflation, then demands that price action agree before committing risk.
- Start each week with a one-page narrative: policy stance, growth trend, inflation direction, and key risks.
- Convert the narrative into 2–3 base cases and 1 alternative; define what data would switch you between them.
- No narrative = no swing risk; day trades can be technical, but may not fade the dominant macro impulse.
Building the Macro Narrative: From Regime to Trade Idea
A narrative isn’t a hot take; it’s a structured map of the current regime. Joe distills policy probabilities, bond-market signals, and global equity tone into a coherent view that guides instrument selection.
- Track rate curves (e.g., 2s10s, 5s30s) daily; note steepening/flattening and link to growth/credit expectations.
- Translate CPI/PPI surprises into path-of-policy adjustments using simple rules (e.g., hotter CPI → higher terminal odds).
- Maintain a “drivers board” per asset: FX = rate differentials & terms of trade; equities = earnings & liquidity; commodities = supply/demand shocks.
Instruments & Timeframes: Expressing the View Cleanly
Joe prefers FX, rates, and equity indices to express macro views with fewer idiosyncratic landmines. He aligns a swing timeframe with a tactical execution window so entries are timely but thesis-driven.
- Choose the cleanest proxy: policy divergence → FX pairs; duration views → bonds/futures; global risk pulse → indices.
- Swing map on 4H/D1; execute on M15–H1 to control risk per structure.
- Avoid “noisy” pairs/instruments when multiple non-macro forces dominate (illiquidity, one-off flows).
Pre-Trade Checklist: Gatekeeping Before Risk
Joe’s checklist filters out low-quality ideas so only aligned, high-asymmetry trades pass. If the boxes don’t tick, the trade doesn’t exist.
- Thesis written in one sentence; catalyst identified (data, policy, flows, session).
- Levels marked: prior day/week high-low, session range, HTF supply/demand, VWAP/AVWAP.
- Risk defined: stop location from structure; R multiple to first target ≥ 1.5R; max news proximity rule applied.
Set up Criteria: When He’s Allowed to Click
Good trades share structure, catalyst, and location. Joe only acts when all three align with his macro stance or a clear technical impulse.
- Structure: trend or range with clear swing points on the execution TF.
- Catalyst: scheduled data, session open, range break, or cross-asset impulse (yields/DXY) in his favor.
- Location: bid/offer at mapped levels; no mid-range chasing; spread/ATR must permit planned risk.
Execution Triggers: Simple, Repeatable, Testable
Execution is designed for repeatability under stress. Triggers are pre-defined; the button click is just the last step.
- Limit at the level when liquidity is abundant; market order only on pre-planned momentum breaks.
- First scale at +1R to cut variance; stop stays until structure justifies BE.
- Never widen stops; if invalidated, flatten and wait for the next location.
Risk & Sizing: Variance Control Over Ego
Joe treats risk as a business expense that must be budgeted by volatility and correlation. Survive first; then compound.
- Risk per trade: 0.25%–0.75%; hard daily loss cap 1%–1.5%—platform closed after hit.
- Volatility gate: if ATR makes the logical stop exceed plan, cut size, or skip.
- Correlation cap: max 1.5% total across positively correlated expressions of the same macro bet.
Managing Winners: Targets, Trailing, and Time
Big winners come from staying with the move when structure holds. Joe uses objective rules to lock progress without strangling potential.
- Partial at +1R (≈25%–35%); next target at prior HTF swing or measured move.
- Trail under/over last confirmed swing; only widen on HTF trend continuation.
- Time stop: if price stalls a full session post-entry, reduce by half and reassess.
Data & Calendar Discipline: Let the Tape Prove It
Events move regimes; preparation prevents surprises. Joe plans entries around data rather than reacting in panic.
- Map tier-1 releases (CPI, NFP, central bank) weekly; tag trades “pre-data,” “post-data,” or “avoid.”
- Fifteen minutes pre-tier-1: reduce exposure to core risk; re-risk only if reaction confirms thesis.
- After data, wait for the 5–15 minute repricing; enter only if structure resets in your favor.
Bond Market Compass: Yields Lead, FX Follows
Rates often telegraph the trade. Joe watches curve moves to choose direction and instrument before looking for the level.
- If curves steepen bullishly (cuts expected), favor growth FX and indices; if bear-steepen (inflation risk), favor USD and defensives.
- Use futures or bond ETFs to express pure duration views when FX transmission is messy.
- Confirm with DXY or rate-differential charts before pressing size.
FX Expression: Pick the Pair That Carries the Story
Not all pairs carry the same macro load. Joe chooses the one where the narrative is most concentrated and slippage is manageable.
- Policy divergence → trade the clearest differential (e.g., hawkish vs. dovish CB) rather than forcing your favorite pair.
- Terms-of-trade shocks → prefer commodity FX aligned with the move; avoid crosses with offsetting drivers.
- Liquidity check: during your execution window, confirm spreads/vol are compatible with your stop distance.
Journaling & Metrics: Turn Trades Into Systems
Progress is measured, not felt. Joe tags every trade, so reviews reveal what to do more of—and what to cut.
- Tag by setup, catalyst, session, and direction; record R, MAE, MFE, and hold time.
- Weekly: top/bottom five by R and expectancy; kill or fix the bottom bucket.
- Maintain a “rule drift” log—any deviation becomes a written change or a banned behavior.
Daily Routine: Repeatable Edge Comes From Habit
Edge compounds when the routine is stable. Joe keeps a tight loop from prep to review so he’s fresh when opportunity shows up.
- Pre-London: narrative update, levels, alerts; write a one-line bias per instrument.
- Pre-NY: cross-asset check (yields, DXY, indices); invalidate ideas that lost context.
- End-day: screenshot entries/exits; summarize what confirmed or killed the thesis in three lines
Size Risk First: Fixed-R, daily loss caps, survive variance
Joe Olashugba starts by treating risk like rent—paid before anything else—and that means fixed-R sizing on every ticket. He keeps the loss per trade constant so a bad streak can’t spiral, and he respects a hard daily loss cap that closes the platform if hit. Riz Sardar echoes the same discipline: he picks size from structure and volatility, not confidence, and refuses to widen stops once the trade is live. Together, they make the point that consistency in risk is how you build a curve that doesn’t implode.
Joe ties his fixed-R to the current ATR, so stops are logical and size flexes only within the plan, while Riz uses session context to decide whether to take half-size or sit out entirely. Both agree that a -3R sequence is a signal to cut size and slow down, not to press for a comeback. Their mantra is simple: control variance, live to compound, and let the edge show up over many reps. If you lead with risk, the rest of your trader identity—setups, targets, even psychology—gets a lot easier to execute.
Let Volatility Dictate Size, Targets, And When Not To Trade
Joe Olashugba treats volatility as the steering wheel, not a side mirror. When ATR expands, he narrows his menu to cleaner instruments and cuts position size so the same structural stop doesn’t balloon risk. If ranges compress, he stops forcing multi-R home runs and takes quicker partials, accepting that smaller moves are the day’s reality. Riz Sardar adds a session filter—London vs. New York conditions—to decide whether today is a half-size, full-size, or no-trade day. Both of them agree that the spread and average excursion must physically fit inside the plan; if the math doesn’t work, the trade doesn’t exist.
Riz uses volatility to time exits too: when rotations are fast, he locks earlier profits and trails tighter; when tape is smooth, he lets winners breathe to the higher-timeframe target. Joe anchors targets to recent range statistics, so “reasonable” isn’t a vibe; it’s a number. They both downshift after news shocks, letting the first repricing settle before risking capital in a chaotic tape. The shared idea is simple—size, targets, and pass/participate decisions all flow from volatility, and ignoring that is how good setups become bad trades. Vol is the market telling you how loud to talk; Joe Olashugba and Riz Sardar only speak at the volume the room supports.
Diversify By Underlying, Strategy, And Timeframe To Smooth Equity Curve
Joe Olashugba frames diversification as correlation control, not collection—fewer, cleaner bets across different engines of return. He’ll pair an FX macro swing with a tactical index future day trade so one expresses policy while the other harvests intraday structure. Riz Sardar echoes that play, splitting exposure between trend-continuation setups and mean-reversion fades, so the equity curve doesn’t depend on a single market mood. Both traders stress that if two positions move for the same reason, they count as one; size the “theme,” not the tickers.
Riz keeps a rotation between sessions and timeframes—London momentum, New York pullbacks, and higher-timeframe levels—so opportunity isn’t confined to one window. Joe mixes underlying types (rates, indices, major FX) and staggers holding periods, letting swings work while scalps chip variance down. When volatility bunches, they prune overlapping trades and keep the highest-quality expression of the view, often cutting the rest to half-risk. The net effect is a smoother path: diversified edges, sized by correlation, with Joe Olashugba and Riz Sardar constantly curating which trades actually earn their spot.
Trade Mechanics Over Predictions: Rules, Checklists, And Session-Based Execution
Joe Olashugba treats predictions as entertainment and mechanics as the job. He pre-writes a one-sentence thesis, maps levels, defines entry/stop/targets, and won’t click until every box is ticked. The checklist lives on-screen during execution, so the decision is binary: either the rules are met or there is no trade. Riz Sardar runs a similar flow but binds it to sessions—London for discovery, New York for confirmation—so time-of-day guides that trigger are valid.
Both traders separate “thinking time” from “doing time.” During the session, Joe only executes pre-approved plays: limit at level, or momentum break he scripted beforehand—no ad-libbing. Riz adds a reset rule after any full-stop loss: close the chart for ten minutes, re-read the checklist, and only return if the setup still qualifies. The result is boring by design, which is the point—mechanics reduce noise, protect focus, and let Joe Olashugba and Riz Sardar compound by repeating the same high-quality behaviors day after day.
Choose Defined Or Undefined Risk Intentionally, Then Manage Exits Relentlessly
Joe Olashugba treats risk type as a conscious design choice, not an afterthought. When the catalyst is binary or news-driven, he prefers defined risk—tight structural stops, smaller position, and pre-committed partials at +1R and +2R. If the backdrop is trending and liquidity is healthy, he’ll allow undefined risk only in the sense of trailing structure, never widening stops once set. His view is simple: pick the risk framework that fits the tape, and the rest of the plan becomes easier to execute.
Riz Sardar mirrors that intent with a focus on exits that pay the bills. He front-loads the plan with exact levels for scale-outs and uses time stops when momentum dies, so “hope” never becomes a strategy. For defined risk, Riz wants the first profit-taking event close enough to de-risk variance; for looser, trend-follow setups, he trails behind swings and respects higher-timeframe context. Both Joe Olashugba and Riz Sardar hammer the same rule: your risk type sets the rules of engagement—choose it deliberately, then manage the exit like it’s 80% of the outcome.
In the end, Joe Olashugba and Riz Sardar are aligned on one big truth: edge is a process, not a hunch. They start with risk—fixed-R sizing, hard daily loss caps, and correlation limits—so variance never gets to drive the bus. Volatility sets the pace for everything else: size, target distance, and whether today deserves action at all. When the tape expands, they cut size and let structure breathe; when it compresses, they bank quicker and avoid forcing multi-R fantasies in a one-R market.
Their execution is deliberately boring. Both traders gate every idea with checklists, pre-mapped levels, and clear catalysts, then run session-based routines that turn entries into a simple yes/no. Mechanics beat predictions every day of the week. Joe leans macro-first—policy path, curves, and cross-asset tone must rhyme with price—while Riz keeps the technicals razor-clean and uses sessions to decide when to press or pass. Together, they diversify intelligently (by underlying, strategy, and timeframe), prune overlapping bets, and manage exits like professionals: partials at logical milestones, structural trails, and time stops when momentum dies.
The throughline is a discipline you can measure. Journal tags, MAE/MFE, and weekly reviews tell them what to do more of—and what to delete. After a rough sequence, they cut size and slow down; after clean execution, they scale with intention, not ego. If you take one playbook from these two, make it this: size risk first, let volatility set your voice, trade your rules (not your hopes), and choose your risk type on purpose. Do that consistently, and the curve tends to take care of itself.
