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Richard Olsen sits down to unpack how he thinks about markets—from his early work making retail FX possible to what he’s building now around crypto, AI-driven forecasting, and ultra-low-cost execution. If you’ve heard the name around high-frequency trading, event-time research, or the early days of retail forex, this is Richard Olsen, and he’s as candid as ever about what actually helps a trader survive. You’ll hear why he believes the next leg of market innovation merges stablecoins with FX, and why tools that adapt to volatility beat old-school indicators.
In this piece, you’ll learn Richard Olsen’s core trader strategy principles: set realistic return targets, build a clear risk framework, and obsess over total cost (fees plus spread) because small frictions compound faster than hypothetical gains. You’ll also get his take on “intrinsic time” for timing entries in fast/slow regimes, how prefabricated AI building blocks can let non-coders construct robust systems, and a contrarian lesson on capital—raise it only after your track record shows you don’t need it. Read on if you want practical, no-fluff rules you can apply this week, whether you trade crypto, FX, or both.
Richard Olsen Playbook & Strategy: How He Actually Trades
Core Philosophy: Trade Events, Not the Clock
Markets don’t move in neat, evenly spaced candles—so Richard treats “time” as the distance between meaningful price events. This perspective keeps you active when markets are alive and patient when they’re dull. The goal is to sample price only when something real happens and size risk to the market’s actual pace.
- Define a “directional-change” threshold for each instrument (e.g., 0.20–0.60% FX majors, 0.50–2.00% liquid crypto).
- Only log a new “bar” when the price moves by the threshold; ignore everything in between.
- Trade after an event: act on reversals rather than predicting them.
- Increase position size as the event rate rises; cut it when events slow down.
- If the event rate (count of threshold hits per hour) drops below your baseline, stand down.
Instruments & Venues: Liquidity First, Friction Last
Richard builds around ultra-liquid markets and low all-in costs. The more liquid the product and the cheaper the execution, the more edge survives. That’s why top FX pairs and top-cap crypto with solid stablecoin rails tend to be the core.
- Focus list: EURUSD, USDJPY, GBPUSD + top 10 crypto by market cap and depth.
- Set hard fee/spread limits: if all-in round-trip cost > 0.03% (FX) or > 0.10% (crypto), skip.
- Prefer marketable limits during peak-liquidity windows; avoid chasing outside core sessions.
- Route to venues with reliable fills, deep books, and stable APIs; diversify routing to cut slippage risk.
- Keep custody risk separate from trading logic; use segregated, risk-scoped accounts.
Setups: Directional-Change & Overshoot Logic
The backbone is simple: let price move enough to matter, then trade the response. After a directional change, markets tend to “overshoot” before flipping again—this becomes a programmable edge.
- Calibrate DC threshold per symbol; re-check weekly with recent realized volatility.
- Entry template: after a DC up, buy the first pullback that holds above the DC pivot; after a DC down, sell the first bounce that fails below the pivot.
- Target = a fraction of the median overshoot observed for that threshold (e.g., 60–80%).
- Time-out rule: if the target isn’t reached within N intrinsic events (e.g., 6–10), exit flat.
- Forbidden zone: no entries if two consecutive DC events print inside an ultra-low range—wait for range expansion.
Entries & Exits: Rules You Can Code—or Click
Execution is just the setup expressed in precise do-this, do n’t-do-that steps. You’ll keep winners uncomplicated and cut losers before they metastasize.
- Long entry: confirm DC up; place buy stop a tick above the micro pullback high; cancel if a fresh DC down prints first.
- Short entry: confirm DC down; place sell stop a tick below the micro bounce low; cancel if a fresh DC up prints first.
- Initial stop: beyond the DC pivot minus/plus a volatility buffer (e.g., 0.25× recent median overshoot).
- Profit exit: take 70% at the target; trail the remainder behind subsequent DC pivots.
- One-and-done rule per side: if stopped, wait for a new DC in your favor before retrying.
Risk & Money Management: Edges Survive on Sizing
Richard treats costs and variance as first-class citizens. Your system’s edge is tiny compared to market noise, so risk has to be precise and repeatable.
- Per-trade risk = 0.25–0.50% of equity; hard cap daily VaR at 2.0%—stop trading if hit.
- Volatility scaling: position size ∝ 1/median overshoot for your threshold; bigger overshoot ⇒ smaller size.
- Portfolio guardrails: max 3 correlated positions; cap aggregate margin at 30% of equity.
- Daily loss stop and “cooling off”: two consecutive full-stop losses ⇒ minimum 2 hours or 20 intrinsic events flat.
- Equity curve protection: if monthly drawdown > 8%, cut size by 50% until equity makes a new monthly high.
Cost & Execution: Treat Friction Like a Competitor
Every basis point of spread, fee, and slippage compounds against you. Richard’s approach bakes cost into the strategy design rather than hoping to overcome it later.
- Track all-in cost per round trip; if the average cost > 30% of the average target, the setup is untradable.
- Route smart: prefer venues with tighter top-of-book and lower reject rates; measure “quote-to-fill” slippage weekly.
- Batch exits in volatile bursts to avoid walking the book; use IOC/marketable limits over pure markets where possible.
- Avoid trading during scheduled maintenance windows and known thin-liquidity periods.
- Maintain a live “cost dashboard”: spread, fee tier, slip, reject %, partial fill %.
Data & AI: Modular Blocks, Not Magic
Richard favors small, composable building blocks you can understand and test. Think “LEGO bricks” of signals rather than an opaque monolith that’s tough to debug when it breaks.
- Features: event-rate, DC direction, overshoot size, microstructure imbalance; avoid overfitting with dozens of inputs.
- Labels: event-time outcomes over N events ahead (not minutes); keep horizons consistent with your threshold.
- Validation: walk-forward on rolling weeks of event-time data; zero look-ahead; retrain only on closed segments.
- Latency budgets: if decision time > 150 ms for FX or > 300 ms for crypto, simplify features or pre-compute.
- Kill-switch: turn model weights to neutral if live hit rate drops > 2σ below backtest baseline over 200 trades.
Regime Detection: Let Volatility Drive the Bus
Instead of guessing macro narratives, let the tape tell you whether to press or protect. Event-rate and spread/volatility ratios are your regime sensors.
- Compute event-rate z-score intraday; > +1.0 ⇒ allow add-ons, < −1.0 ⇒ reduce size by half.
- If the spread/ATR ratio widens beyond a set limit, disallow new entries (costs too high for available move).
- In expansions, allow pyramids of up to 2 add-ons, each half the prior size; in contractions, single-shot entries only.
- Switch thresholds: increase DC threshold one notch in high-vol regimes; decrease it a notch in low-vol.
Journaling & Metrics: Proof Beats Opinion
Richard’s ethos is intensely empirical—track what matters and remove what doesn’t. Your journal isn’t a diary; it’s a scoreboard for capital allocation.
- Record per trade: threshold, event-rate, entry type (reversal/continuation), target/stop distance, cost, venue, slip.
- Weekly metrics: net expectancy (after costs), cost/target ratio, overshoot capture %, time-to-target in events.
- Prune rules that underperform three review cycles in a row; redirect risk to the rules with superior net expectancy.
- Keep a “what changed?” log any time regime metrics shift beyond bands; adjust size only after review.
Capital & Scaling: Earn the Right to Add Size
The play is to become economically anti-fragile—able to trade smaller during turbulence and scale prudently when conditions are favorable. Growth follows discipline.
- Scale after a 200-trade sample shows positive net expectancy and > 1.0 net Sharpe at your all-in costs.
- Add size in 20–25% increments; never double overnight.
- Withdraw a slice of profits monthly to de-risk operations and maintain psychological clarity.
- Seek outside capital only after your curve proves you don’t need it; terms are best when your data speaks for you.
Mastering Risk Sizing: How to Protect Capital and Maximize Growth
In his approach to risk management, Richard Olsen emphasizes the importance of sizing risk properly to ensure longevity and consistency in the markets. Instead of throwing large positions at every opportunity, Olsen recommends a more measured approach, focusing on capital protection first. He advocates for a risk size that is a direct reflection of the volatility in the asset being traded. For example, in more volatile markets, position sizes should be smaller, while in quieter markets, traders can afford to increase their exposure—but always with a well-defined stop loss to protect against adverse moves.
Olsen’s strategy revolves around the idea that risk should be controlled and never assumed. He advises traders to calculate risk on each trade based on recent volatility and adjust their positions accordingly. The goal isn’t to chase the highest returns but to preserve capital, allowing you to survive the inevitable losing streaks. By sizing trades in this way, traders ensure they can stay in the game long enough to capitalize on the setups that really matter.
Volatility-Based Allocation: Tailoring Position Sizes to Market Conditions
Richard Olsen takes a nuanced approach to volatility-based allocation, adjusting his position sizes based on the volatility of the market he’s trading. He believes that adapting to the market’s inherent volatility is key to managing risk while maximizing potential returns. For example, during periods of high volatility, Olsen recommends reducing position sizes to protect against larger, unpredictable price swings. Conversely, in calmer market conditions, traders can increase their size, capitalizing on more predictable movements. The idea is to always align your trade size with the level of risk that the market is presenting at that moment.
Olsen’s strategy focuses on flexibility and responsiveness to market conditions rather than rigid rules. He encourages traders to observe and react, ensuring that their risk exposure is always in line with the volatility they’re experiencing. By doing so, traders can navigate through high-risk periods without overexposing themselves and take full advantage of quieter times. This volatility-based allocation method ensures that your strategy is adaptable, allowing for better risk control and improved consistency in performance.
Diversification Strategies: Spreading Risk Across Assets and Timeframes
Richard Olsen’s approach to diversification goes beyond simply holding multiple assets—he emphasizes diversification by strategy, timeframes, and underlying assets. Rather than relying on a single asset class or approach, Olsen advocates for spreading risk across different market conditions. He believes that by using multiple trading strategies (for example, short-term momentum or long-term trend-following) and combining them with a diverse set of assets, traders can smooth out returns and reduce the risk of large drawdowns. This diversified approach also helps minimize the impact of any one strategy or asset class underperforming during specific market conditions.
Olsen stresses that timing is just as important as the instruments traded. Diversifying by timeframes means taking advantage of different trading windows—whether that’s shorter-term intraday trades or longer-term position holding. This allows for constant market exposure without being overly reliant on one timeframe. According to Olsen, the key to successful diversification is balancing these different approaches in a way that doesn’t overcomplicate your process, but instead creates a well-rounded, adaptable strategy capable of thriving in various market conditions.
Mechanics Over Prediction: Building Consistency Through Repeatable Rules
Richard Olsen firmly believes in prioritizing mechanics over prediction when it comes to trading. He advocates for a strategy built around clear, repeatable rules that focus on what the market is doing in real-time, rather than trying to predict what it will do next. In Olsen’s view, predictions are often unreliable and can lead to unnecessary risk-taking. By focusing on mechanical systems—rules-based entries, exits, and risk management—traders can develop a consistent approach that works regardless of market conditions. This shift towards mechanical trading allows for objectivity and discipline, reducing emotional decision-making that often derails retail traders.
Olsen’s framework encourages traders to build and follow a structured process. Rather than relying on intuition or trying to forecast future price movements, he suggests using indicators and price action that are derived from historical data. His approach emphasizes systematic execution, ensuring that every trade has a defined entry, exit, and risk plan. By adhering to these mechanical strategies, traders can create a more reliable and repeatable process that minimizes guesswork and increases the likelihood of consistent performance over time.
Defined vs. Undefined Risk: Navigating Uncertainty with Clear Boundaries
Richard Olsen’s trading philosophy emphasizes the importance of understanding the difference between defined and undefined risk. According to Olsen, defined risk is when you know exactly what you stand to lose on a trade, such as setting a stop loss or position size that limits exposure. This gives traders the ability to plan their trades with confidence, knowing the worst-case scenario before entering. In contrast, undefined risk occurs when there’s uncertainty about the potential loss, often resulting from volatile markets or improper risk management. Olsen stresses that undefined risk should be avoided at all costs, as it can quickly erode capital and undermine a trader’s long-term success.
Olsen encourages traders to embrace strategies that have clearly defined parameters for every trade. By keeping risk defined and within manageable bounds, traders can avoid the catastrophic losses that stem from unpredictable market behavior. He suggests using technical tools like stop orders or volatility-based position sizing to keep risk in check and create a clear risk/reward profile before committing to any trade. This approach allows for better emotional control, as traders are not left second-guessing their exposure. By focusing on defined risk, Olsen’s strategy helps traders minimize surprises and maintain consistency in their trading performance.
Richard Olsen’s trading philosophy revolves around practical risk management and systematic decision-making, which serve as the foundation for long-term success in the markets. By emphasizing volatility-based allocation, he teaches traders to adjust their risk exposure based on market conditions, ensuring they’re never overexposed during volatile periods. His focus on diversification across strategies, assets, and timeframes further helps traders reduce risk and smooth returns, providing a robust framework for navigating any market environment.
Olsen also advocates for a mechanical, rule-based approach to trading, where the goal is to build repeatable systems that take the guesswork out of decision-making. By following clear and consistent rules, traders can avoid emotional pitfalls and unpredictable market swings. He encourages traders to define their risk boundaries clearly, using tools like stop losses and position sizing to manage risk effectively. This commitment to defined risk over undefined exposure is a key lesson that ensures traders maintain control over their trades, no matter the market conditions. Ultimately, Richard Olsen’s strategy boils down to protecting capital, managing volatility, and sticking to disciplined processes—principles that all traders can apply to improve their performance and longevity in the market.
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