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In this interview, Alyse Amores sits down to break down how she grew from a 2017 beginner into a fund manager and consistently profitable trader by simplifying around price, volume, and liquidity. She matters because she pairs real-world capital management with a straight-talk approach to risk: journal relentlessly, focus on high-volume areas, and let simple tools like supply/demand and wick analysis do the heavy lifting. You’ll also hear why she’s shifting from FX to futures as a U.S. trader, and how working with outside capital sharpened her expectations and discipline.
In this piece, you’ll learn Alyse Amores’s practical playbook: cap risk per day, split it across multiple positions with different stops and targets, and enter only when price action validates the setup. We’ll unpack her journaling framework that kills recency bias, the psychology traps she watches (loss aversion, anchoring, overconfidence, gambler’s fallacy), and the mindset shift from chasing monthly goals to trusting process and compounding. Expect clear examples of how to read liquidity, when not to take a trade, and how to balance simplicity with flexibility so your strategy survives changing market conditions.
Alyse Amores Playbook & Strategy: How She Actually Trades
Risk Framework: Cap the Day, Not Every Trade
Alyse runs risks from the top down. Instead of fixed risk per trade, she sets one daily risk allowance and allocates it dynamically based on opportunity quality. That shift keeps her in the game after an early loss and forces discipline across the entire session.
- Set a hard daily risk limit (e.g., 2% of equity) and never exceed it—no exceptions.
- If your first trade loses >50% of your daily risk, reduce the size for the next trades by at least half.
- Pause after any back-to-back losses; re-validate conditions before deploying remaining daily risk.
- Predefine “stop-for-the-day” triggers (max daily loss hit, 3 trade attempts, or market regime shift).
Position Architecture: Multiple Tickets, Staggered Risk
She often expresses one idea with multiple positions: some with tighter stops to validate, others with wider stops to give the trade room. This structure lets her scale out logically and pursue deeper targets without abandoning risk control.
- Split daily risk across 2–4 tickets for the same idea (e.g., 0.50% + 0.50% + 0.25% + 0.25%).
- Use at least one “validation” ticket with a tight stop near the structure to confirm the read.
- Assign differentiated targets: smaller TF for near targets, higher TF for swing extensions.
- Add only on pullbacks aligned with the original thesis; never add to losers.
Read the Tape: Price, Volume, Liquidity
Her toolkit is deliberately simple: price action, traded volume, and liquidity. She watches wicks and absorption around supply/demand to spot where orders actually changed hands and where they’re likely stacked.
- Mark high-volume nodes and prior absorption wicks; expect chop and re-tests there.
- Avoid entries directly into heavy liquidity pools; wait for a sweep or clear rejection first.
- Track who’s trapped: failed breakouts with long wicks often fuel the move the other way.
- Keep indicators minimal; if used, favor volume-derived tools that corroborate structure.
Set up Validation: Only When Price Is “Ready”
Experience taught her to wait for the market to confirm timing—she doesn’t try to knife-catch every turn. If validation is missing, she skips the trade entirely and protects mental capital.
- Define “ready” for each setup (e.g., break + retest + absorption wick + delta slowdown).
- If invalidation is unclear, you don’t have a trade—stand down.
- Enter at the first valid pullback after confirmation, not the initial impulse.
- Require asymmetric R: R at entry (≥2R net of partials and costs).
Markets & Access: Futures over FX (for U.S. Constraints)
As a U.S. trader, broker choice and product access matter. She’s shifting from primarily FX/CFDs toward futures because the instruments map well to her indices/commodities focus and offer reliable venues.
- If you’re U.S.-based, evaluate regulated futures for indices/commodities you already trade.
- Prioritize brokers with long track records and robust infrastructure as your size grows.
- Align product selection with your read (index/fuel for liquidity and tight spreads).
- Keep rules portable so the same setup works across FX and futures.
External Capital: Expectations Drive Risk
Managing other people’s money sharpened her appreciation for realistic return targets and a consistent process. Smaller, steadier goals translate to tighter risk and better durability across regimes.
- Set annual targets that a pro allocator would accept (e.g., single-digit to low-teens) and size risk accordingly.
- Write a mandate: max daily loss, monthly max drawdown, and “no-trade” days.
- Measure hit rate and payoff per setup; redeploy risk to the fattest edge, cut the rest.
- Communicate that the monthly P&L will vary—process continuity beats calendar targets.
Trade Management: Targets, Partials, and Flexibility
She moved from big single positions with partials to multi-ticket structures that naturally scale risk off while leaving runners. That change improved flexibility and outcome distribution across timeframes.
- Pre-tag targets: T1 = structure close, T2 = session range, T3 = HTF level.
- If T1 hits, trail validation ticket to breakeven; leave swing ticket untouched.
- Reduce size into adverse volatility spikes; widen stops only if the structure still holds.
- Never let green turn red—ratchet a portion to lock ≥1R once T1 is banked.
Journal to Learn, Not to Vent
Her evolution came from adding and subtracting elements deliberately. Journaling turns vague “feelings” into testable adjustments and keeps the playbook tight.
- Log every trade with setup tag, context snapshot, entry/exit rationale, and rule adherence.
- Add a “keep/remove/tweak” line item weekly; kill anything that isn’t pulling its weight.
- Track per-setup expectancy monthly; stop trading any tag with a negative 3-month expectancy.
- Screenshot the moment of validation and the first invalidation tell for pattern memory.
Psychology: Process over Outcome
She focuses on cause over effect—process over P&L—so the risk plan survives losing days. That philosophy reduces emotional whipsaws and prevents revenge trading.
- Define success for the day as “followed rules,” not “made money.”
- If you break a rule, stop for the session and rewrite the trigger you missed.
- Use pre-trade breathing and a 60-second checklist to slow impulses.
- Review only statistics you can control (entries taken by plan, R deployed, slippage), not outcome noise.
Your Pre-Trade Checklist (Run It Aloud)
Turning the playbook into a spoken checklist hard-wires discipline. Read it before each order so the market can’t rush you.
- Is the daily risk limit set and current drawdown < threshold?
- Is this a tagged setup with a defined validation signal and clear invalidation?
- Do I have 2–4 tickets planned with distinct stops/targets and total risk ≤ daily cap?
- Am I trading away from/after liquidity, not directly into it?
- Do broker/product constraints support clean execution for this idea today?
Cap Daily Risk, Split Across Tickets, Survive Cold Starts
Alyse Amores is all about controlling risk from the top down. Instead of risking the same amount on each trade, she caps her total daily risk and then splits that across multiple positions. This method helps her manage the ups and downs of a trading day without blowing her account on a single loss. By focusing on the overall daily risk, rather than on each trade, Alyse ensures that even a string of losses doesn’t take her out of the game. It’s a disciplined approach that focuses on the long-term game rather than short-term wins.
In practice, Alyse uses this strategy by defining a hard daily risk limit—say 2% of her equity—and then breaking it down into smaller pieces across several trades. If she takes a hit early in the day, she’ll lower her position size for subsequent trades, making sure she doesn’t exceed her daily cap. This allows her to stay in the market, avoid emotional overtrading, and protect her capital, even if things aren’t going her way. It’s a rule-driven approach that helps her stay consistent, no matter how volatile the market gets.
Trade Liquidity, Not Hopes: Wait For Sweep, Rejection, Validation
Alyse Amores emphasizes the importance of understanding market liquidity rather than trading based on hope. She doesn’t jump in blindly when she sees a potential setup; instead, she waits for clear signals that show where the market’s real liquidity lies. By focusing on liquidity, she can identify when a move is supported by actual market participants, reducing the likelihood of being caught in a false breakout or choppy price action. Alyse looks for signs of liquidity sweeps or rejection near key levels, as these show where big players are either entering or being stopped out, giving her more confidence in the trade.
Alyse’s approach revolves around waiting for validation before entering any trade. She doesn’t chase the market; instead, she looks for rejections at significant price points or areas with high liquidity. This method of waiting for price action to confirm her analysis ensures that she only trades when the odds are stacked in her favor, reducing unnecessary risk. It’s a more methodical, patient approach, focusing on real-time market moves rather than predictions or assumptions. By prioritizing liquidity over guesswork, Alyse trades with the flow of the market, increasing the probability of successful trades.
Diversify By Timeframe, Underlying, and Strategy To Smooth Equity
Alyse Amores takes a broad approach to diversification, not just in the assets she trades, but in the strategies and timeframes she uses. By spreading her risk across different timeframes and trading methods, she smooths out her equity curve and reduces the impact of any single trade or market condition. For example, she may take a swing trade on a higher timeframe while simultaneously trading intraday setups on lower timeframes. This allows her to capture opportunities in different market environments, whether they’re trending or consolidating, while keeping her risk evenly distributed.
Her strategy also involves diversifying by underlying assets, such as trading both indices and commodities. By not relying on just one market or instrument, Alyse reduces the correlation between her trades, allowing for more consistent overall returns. This multi-strategy approach helps her avoid the trap of relying too heavily on any single trade or market condition, making her trading system more resilient in the face of shifting market dynamics. Whether it’s through different timeframes, diverse instruments, or varying strategies, Alyse ensures that her trading style remains adaptable and flexible, improving her ability to weather market fluctuations.
Mechanics Over Prediction: Predefine Setups, Invalidation, Targets, and Exits
Alyse Amores firmly believes that trading is more about following a mechanical process than trying to predict the market’s next move. She doesn’t rely on gut feelings or instinct when entering trades; instead, she meticulously defines her setups in advance. This includes clearly identifying the conditions that must be met for a trade to be valid, as well as setting predefined levels for invalidation, targets, and exits. By focusing on the mechanics of her strategy, Alyse reduces emotional decision-making and ensures that every trade has a well-thought-out plan before she pulls the trigger.
For Alyse, this approach ensures consistency and discipline in her trading. She treats every trade as a business decision with clearly defined risk and reward ratios, leaving no room for ambiguity. The key is to never enter a trade without knowing exactly where the trade can go wrong (invalidation) and what success looks like (targets and exits). This method minimizes surprises and allows Alyse to stay grounded, no matter what the market throws her way. By sticking to a strict set of rules, she keeps her trading process structured, reducing the chances of being swept up by market noise or emotional impulses.
Journal Ruthlessly, Kill Weak Rules, Double Down On Proven Edges
Alyse Amores treats her journal like a trading lab, not a diary. Every trade gets a tag for setup, context, entry trigger, invalidation, and exit logic, plus a quick post-mortem on rule adherence. She saves screenshots at the moment of validation and the moment of breakdown to train pattern memory. Over time, those tagged notes reveal which ideas actually carry positive expectancy and which ones only feel good in the moment.
From there, Alyse Amores prunes hard. She maintains a weekly “kill list” of rules and setups that underperform and removes them without hesitation, while cloning and stress-testing the winners with small, controlled tweaks. Her goal is to compound process, not just capital—tighten what works, delete what doesn’t, and scale size only after repeatable results show up in the stats. The journal becomes a living playbook, turning guesswork into clear decisions she can trust under pressure.
Alyse Amores closes the loop with a playbook that’s built to last: cap risk at the day level, express one idea with multiple tickets, and let price, volume, and liquidity do the talking. She waits for the market to prove it—retests, absorption, and clean invalidation—before committing size, then manages the position with pre-tagged targets and flexible scaling so winners can breathe while losses stay small. As her capital and responsibilities grew, she favored products and brokers that support clean execution and stable access, leaning into futures when that alignment made the most sense.
Her edge isn’t prediction; it’s mechanics and iteration. Alyse journals like a quant, tagging setups, documenting validation and breakdown moments, and pruning anything that doesn’t carry its weight. She diversifies by timeframe, underlying, and strategy to smooth the equity curve, sets realistic return expectations, and defines hard “stop-for-the-day” triggers to protect decision quality. The lesson is simple and transferable: when your rules allocate risk, your validation gates time entries, and your journal evolves the system, you don’t need to outguess the market—you just need to execute.
