Nick Radge on the Algo Advantage Podcast

Last week, Nick joined Simon M on the Algo Advantage podcast to chat about all aspects of his diverse trading arsenal, including robustness, portfolio structuring, Tactical Asset Allocation, dual momentum, and how to build a trading business. It’s a fantastic discussion and well worth a listen. Click here to listen now.​

Strategies Built to Last & Give You a Life Back (& The Wonder of Compounding)!

Write up from Simon of Algo Advantage
Traders, I’ll keep it on point in this article. The key factors of Nick’s portfolio & the design principles that make for robust all-weather strategies.

I think Nick Radge’s edge is actually an architecture: robust, simple, momentum-driven systems stitched together into a portfolio that survives, adapts, and compounds. Across nearly four decades, he’s traded through crashes, chop, and melt-ups; shifted from futures to equities for business reasons; and kept his build-process stubbornly logic-first and comfortingly boring—by design.

Strategy Breakdown
Nick trades nine strategies. All long-only. Australian and US equities and ETFs. Multiple styles, but the dominant driver is quantitative momentum—both absolute (trend-following breakouts) and relative (rank-and-rotate the strongest). That stack gives him serially correlated equity exposures, but with diversified return streams across universes, parameters, and rebalance tempos.

Tactical Asset Allocation (TAA)
Nick runs tactical rather than static all-weather: a small, vanilla roster of ETFs in two buckets—growth (equity indices) and defensive (gold, rates/bonds, select commodities; a small, liquid crypto sleeve in some mandates)—with monthly rebalancing and rules that only hold assets while they’re trending up. If nothing’s trending, revert to cash. Rebalancing keeps single-line exposures from ballooning; the tactile approach cuts drawdowns versus classic “set-and-forget” allocations. Australian and US sleeves are built slightly differently (e.g., one static/binary roster vs. one bucketed “pick-the-strongest” scheme), which adds another sliver of diversification. He’s targeting single digit worst case draw-downs and returns to date have been very impressive. Follow him on twitter where he frequently posts his stats and research.

Key Tenets of the TAA Approach

• Diversify exposures. Split growth/defensive; diversify across AUS/US ETFs; diversify styles.
• Be open to riding whatever trends are present. Positions exist only while momentum is positive; otherwise sit in cash.
• Allocate wisely to defensive, not just offensive assets. Gold and rates matter—especially when equities wobble.
• Let profits run, cut losers short. The edge comes from positive skew, not hit-rate vanity. Catch the big winners.
• Keep it simple and robust. Big, liquid, vanilla ETFs; low parameter count; monthly cadence.

What is TAA?
TAA is an ‘all weather’ dynamic approach that tilts a portfolio toward (or away from) broad asset classes – (such as equities, bonds, commodities, cash) – based on objective momentum in the asset. The broad idea is that you want exposure to ‘defensives’ (assets which should fare better when equities crash), as well as to ‘offensives’ (equities), but never be exposed to anything that isn’t performing (revert to cash). This allows us to ride non-correlated trends in whichever assets are moving. With the rise of liquid ETF’s, the implementation of a TAA portfolio became easier. Select a diverse set of assets, use simple and robust measures of momentum, set desired weights / exposures to different classes, and review on a regular schedule (typically monthly). The goal is to gain equity-like returns with drastically lower volatility.

Nick uses circa 6 large, plain ETFs—some defensive (gold, commodities, interest-rate/bond, some BTC), some offensive (broad equities, global or country specific). Set max weights per line, rebalance monthly, and only hold lines that are rising on simple momentum rules. If nothing qualifies, the portfolio stays in cash. Repeat with certain modifications in different geographies for added diversification.

Dual-Momentum Style Strategies in Equities
Key Principles

• Align with the broader market. Use a regime filter (e.g., index > long MA or breadth up) so you buy stocks when the tide lifts all boats.
• Treat stocks as correlated assets. Diversify at the return-stream level: strategy-type, timeframe, rebalance period, universe, parameters, and market regimes. Let exposures wax and wane over different internal cycles.
• Keep it simple and robust. Prefer few, round-number parameters.
• Follow trend-following math. Hunt outliers, keep the right-tail, cut the left-tail fast. Expect ~45–50% win rates with winners many times larger than losers.
• “Profits are easier over longer periods.” Longer lookbacks tolerate noise, keep you in the outliers & set you up for the larger (easier) returns. More lifestyle, better bang-for-your-buck business model.

Nick runs a couple of relative-momentum models (rank the universe, own the leaders) and a couple of absolute trend models (breakouts/strength filters). Geography matters: the US—heavily institutionalized—leans toward relative momentum; Australia (and similar markets like Canada) is friendlier to absolute trend. Blend both. In crisis, expect correlations to rush toward 1—so TAA is the safety net. Also, match style to strata: some models prefer mega caps, others mine lesser-covered names for outliers.

Australia vs. the United States (Know Your Habitat)
The more institutionalized the market (think: analyst coverage depth, indexing, efficiency), the less friendly it tends to be for absolute trend according to Nick’s research. In the US, Nick runs relative momentum exclusively; in Australia (and similar markets), absolute trend still shines. He also tilts away from the cap-weighted, analyst-swarmed top layer to avoid index-hugging.

Other Strategies
There’s a small allocation to shorter-term mean reversion—useful, but not a headline driver in Nick’s book. The real horsepower is the slow, simple, scalable momentum stack.

Robustness is the Engine; Compounding is the Outcome
If you don’t deeply believe in your strategies, you won’t sit through the equity-curve pullbacks that fuel future growth. Confidence built on logic—rather than hope—prevents Holy-Grail chasing, burnout, and the death of compounding. Treat trading like a business: set objectives, align expectations with reality, and build for your account size and lifestyle.

Portfolio-Level Thinking & Qualitative Factors
There’s always an art to the science. Design for where you’re going (e.g., managing external capital with larger balances, higher diversification, more automation). Qualitative calls still matter around the quant core: stage of life (wealth creation vs preservation), risk tolerance, time available, and interests (perhaps crypto floats your boat). Think of sequencing risk and the impact it could have on your trading if you are nearing retirement. Basically, in a short sequence of events (any shorter-term time frame), the “averages” are unlikely to play out. You could see a severe down tilt right when you want to retire. Suddenly, “the long term” isn’t as important as wealth preservation. This is exactly where great traders generally end up if they’ve had a successful career right? Sequence-of-returns risk is real; lower-vol sleeves (like the “all-weather” TAA) live inside Nick’s retirement account to keep drawdowns single-digit and income withdrawal smoother.

Trading Is a Business (Plan It Like One)
Thinking about these qualitative factors, and other aspects of Nick’s wisdom, reminds me how important it is to actually have a business plan for trading. Actually write one out if you haven’t already. How many strategies will you start with? At what expected vol? How many strategies would you like to be running in 3–5 years? Targeted return? With how much capital? Preferences for data, software, order management? Not to mention the budget/roadmap to get there. That vision keeps you from tapping out right before the outlier shows.

Here’s the personal lens that shaped my build: my north star was to trade external money. That conscious choice—because it’s the most scalable way to compound my efforts—influenced everything downstream. I designed portfolios and software for larger balances, which let me run leaner and broader: more efficient execution, deeper diversification, greater portfolio horsepower. It also fit my temperament: do the job properly, to the best of my ability, and engineer out as many avoidable mistakes as possible. Invest in software to automate and execute a broad range of strategies. Get mentorship from experience experts. Know it would take a few years.

This flows into a favourite theme: the qualitative side of quantitative trading. Your plan isn’t just code and back tests; it’s policy around real-life variables. Decide your preferred strategies, and define when they should be retired. Consider your macro outlook without overfitting to it. Factor in your age and distance to retirement (risk tolerance isn’t static). Be honest about labour: how much work you want to do, how many hours you’ll actually spend at screens, and what you enjoy. These non-numeric constraints shape durable systems that fit you. It’s important.
Get the plan done. Have a vision for how you’ll grow into it. Accept that it requires investment—of time, money, and discipline. Then deploy with confidence.

So How to Spend More Time Fishing?
Keep things robust. Nick doesn’t want to frantically swap models; he wants durable engines that run for years with minimal tinkering. He’s outlasted multiple crises, outperformed plenty of flashier names, and done it without wearing a tie (hard to reconcile with fishing and golf). That’s success by several metrics in my book.

How to make things robust

• Know why your strategy makes money. If you can’t articulate the edge, you won’t trust it when it bleeds. Trend/momentum’s edge is simple: small losses, large wins; no prediction required.
• Use minimal, round-number parameters. Complexity creates scaffolding and stress points. Favor 100/200-day style lengths; keep pairs coherent (e.g., regime and stock filters of similar order).
• Favor longer-term. Markets are noisy. Longer windows are more efficient, harvesting bigger outliers.
• Back ideas with research, logic, and common sense. Over fitting is difficult if the model is built on principle rather than data mining. Build individual models with the portfolio in mind.
• Secret sauce: Optimize only to find the most volatile parameter, then monitor that one most closely and review annually with minimal changes.

Stress-testing the living daylights out of it

• Say no to single-market systems. Prove ideas across multiple markets/universes.
• Skip trades in testing. Drop best and worst fills; see if the equity curve survives without the lucky shots.
• Model frictions realistically. Slippage happens; opens/closings are noisy. Randomize closing or opening prices by a few percent and re-test for variance resilience.
• Use regime filters. A simple index > 200-day (or breadth) filter materially improves risk-adjusted returns. Diversify regime filters for the secret sauce.

In summary: Radge’s core philosophical tenets

• The trend is your friend—because of skew. You don’t need to “be right a lot;” you need to win big when you are and lose small when you aren’t. Markets aren’t normally distributed; momentum and trend-following exploit the real-world right tail.
• Trends can’t not happen. For trends not to exist, every asset would have to be perfectly priced and humans perfectly rational. That’s not our universe. So build to capture trends when they appear and to survive when they don’t.

Wrap Up
The pro vs amateur divide, per Nick: pros ride the drawdowns and are present for the next outlier. They profit from human bias—fear, greed, crowding—by refusing to trust their own emotions and by outsourcing discretion to rules they can defend under pressure. Write the plan. Build the engines. Diversify the return streams. Rebuke complexity. Then let compounding do its weird, beautiful work.

Hope that helps!
Simon