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StatOasis · by Ali Casey

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Research, build, test, combine, deploy: the loop that turns trader confidence into conviction.

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Illustrative: a clean backtest is a hypothesis, not proof.
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The loop most traders skip three steps of.

Five stages, running as a loop - every live strategy feeds the next round of research. The red shortcut is the one most traders take instead.

Most traders follow this path and call it done.
1

Research

Start from a behavioral hypothesis, not a prediction.

2

Build

Turn the hypothesis into rules, not a curve fit.

3

Robustness test

Out-of-sample, walk-forward, across regimes the optimizer never saw.

4

Portfolio construction

Combine strategies that fail at different times.

5

Live deployment

Size it, monitor it, plan the drawdown before it comes.

Most traders follow this path and call it done.

  1. 1

    Research

    Start from a behavioral hypothesis, not a prediction.

  2. 2

    Build

    Turn the hypothesis into rules, not a curve fit.

    ↷ Most traders follow this path and call it done.

  3. 3

    Robustness test

    Out-of-sample, walk-forward, across regimes the optimizer never saw.

  4. 4

    Portfolio construction

    Combine strategies that fail at different times.

  5. 5

    Live deployment

    Size it, monitor it, plan the drawdown before it comes.

back to research

Can you survive a decade of real markets?

A decade of markets. Five decisions. About eight minutes. See how your instincts hold up against the regimes that broke real strategies, then see the trading personality your choices reveal.

Start: Survive the Decade

I'm Ali Casey.

I build systematic trading strategies and teach the workflow behind them. Not a content creator. A system builder who happens to teach.

More about me →
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Algo trader since 2014

Here is how I can help you.

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Overfit - the newsletter

Skip the hype. Trust the data. One practical, evidence-driven takeaway per issue: strategy testing, portfolio construction, market structure, and the mechanics behind systematic trading - every claim with the backtest behind it. Publishing since 2024, formerly The AlgoTrader.

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Algo Trading Masterclass

The complete build-a-system workflow, taught end to end: finding an edge, testing it honestly, assembling strategies into a portfolio, and putting it live - the same process behind every study I publish. Currently open as a waitlist.

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Community

Where builders share strategies, code, and feedback. Get plugins, correlation book, indicators and more. Free to join today.

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Digital Products

Everything you can download and use the same day: books, strategy packs, and tools - starting with 36 Ways to Buy the Dip, backtested mean-reversion entries for systematic dip-buying, every variant tested, every result shown. Listed on the products page with everything else StatOasis makes.

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AlgoChef

The validation layer I built for the step most traders skip: pressure-testing a strategy before it risks real money. Launched 2026.

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Latest from StatOasis YouTube channel

I Fixed the Rainbow Moving Average. It Got Noisier

I Fixed the Rainbow Moving Average. It Got Noisier

Oct 5, 2026

70,000 Monte Carlo Sims Said Yes. Walk-Forward Matrix Said No.

70,000 Monte Carlo Sims Said Yes. Walk-Forward Matrix Said No.

Sep 14, 2026

Almost Everyone Draws The NR4 Pattern Wrong

Almost Everyone Draws The NR4 Pattern Wrong

Aug 31, 2026

Latest from StatOasis X channel

StatOasis card. Up or down, gaps drift up . Direction & side. +0.194% Down-gap · 5-day; +0.206% Up-gap · 5-day. Every top-ranked variant is long and the median short variant loses, but neither side beats random entries.

SPY opening gaps, 1993 to 2026: down-gaps drift +0.194% over 5 days, up-gaps +0.206%. Direction is noise. What actually predicts the drift is gap SIZE: smallest +0.19%, largest +0.734%. Full study (3 size lenses, long vs short): https://statoasis.com/overfit/research/sp500-opening-gaps

Oct 9, 2026 · 59 impressions
StatOasis card. Direction is noise, size is the signal. One figure fills the card as the standout: plus 0.73 percent, the average 5-day drift after the biggest SPY opening gaps above 2 percent, the top of a climb from just plus 0.19 percent after the smallest. Bigger gap, bigger drift.

I measured every SPY opening gap since 1993. 8,397 of them. The thing everyone watches — up-gap or down-gap — turned out to be the part that doesn't matter. Here's what actually does. 🧵

Oct 8, 2026 · 59 impressions · 1 reaction
StatOasis card. None of them beat buy-and-hold. A single figure 0 fills the card as the standout, over the line 0 of 934 reliable z-score variants beat holding the E-mini. Holding returned 274,175 dollars and would have taken the account to minus 5,737 dollars on the way.

I tested the z-score "buy the dip" strategy 2,400 ways — on S&P 500 futures and SPY, 33 years. The famous 74% win rate is real. It's also a trap. 🧵

Oct 7, 2026 · 74 impressions · 3 reactions

Latest from LinkedIn

StatOasis card. Volatility clustering. ATR x lens. Big days beget big days.

Here is what this big-range-day study cannot tell you. It's frictionless: no commission, no slippage. The forward drifts (down days +0.305% over 5 days, low closes +0.351%) are gross. The volatility-clustering signal doesn't care about costs, but any return you'd try to harvest from it does. It's an event study, not a system. Events overlap, and the most extreme buckets are thin. The 3+ ATR days are only 40 events from 1993 to 2026, the 2.5-3x ATR bucket only 49, flagged rather than dropped, and their exact numbers will move on new data. If you try to harvest those drifts without a cost model, you are reading gross numbers as net. What survives: next-day range rises with today's ATR x size, and the effect decays over weeks not hours. Long ranks above short (median CAR/MaxDD +0.010 to +0.020 long, negative short), but even long sits below a random-entry control's 0.025. No edge over luck. Turning any of it into a strategy is separate work. Full caveats: https://statoasis.com/overfit/research/sp500-big-range-days

Oct 9, 2026
StatOasis card. A big day is relative. Points lie. ATR x is the tell. 2.7 x The spread in next-day range.

2,736 backtested variants. 8,397 events. Three size lenses that flatly disagree. The design: Every SPY session since 1993 flagged as a big range day, measured for forward return AND next-day volatility at 0-20 day horizons. Then the same days bucketed three ways: raw points, price %, and ATR x, plus direction (up/down) and close location (low/mid/high). Then a flat-only backtest across 942 long and 942 short reliable variants, $35,000 each, frictionless. Points says big days are a 2020s phenomenon: 549 of 635 six-point days landed after 2019. Price % peaks in the 2000s. ATR x spreads evenly across every decade. If you pick the points ruler, you will think the 2020s invented volatility. Only one of those can be the honest yardstick, and it's the one that normalises each day against its own era. The trading sweep is a ranking of sides, not a finished system. Full methodology and the era-distortion table: https://statoasis.com/overfit/research/sp500-big-range-days

Oct 8, 2026
StatOasis card. Volatility clustering. ATR x lens. Big days beget big days.

I expected the volatility spike to fade by the next session. It didn't. The intuition is that a big range day is a one-off, a shock that resolves overnight. The data says the elevated volatility is sticky. For the biggest days (1.5+ ATRs), the next-day range runs 1.297x the average, and it's still 1.202x five days later and 1.128x a full month out. Calm days do the mirror image: they start at 0.855x and drift back toward normal. The shock doesn't reset. Not a flicker. It decays, slowly, over weeks. If you size a position off yesterday's range, you are already late by a week of elevated risk. That changes how you'd size and stop around one of these days. The risk environment you just entered is the one you're living in for a while, not a one-session spike. Full decay curve and horizon table: https://statoasis.com/overfit/research/sp500-big-range-days

Oct 7, 2026

What you won't find here.

No trade calls. No daily predictions. No PnL screenshots. This is for traders who want to understand how to build trading systems, how they behave in different market regimes, when they break, and why. If that's not you, there are plenty of other places, and no hard feelings.

What traders say.

rodolfo berrocal's photo

rodolfo berrocal

Hello, my name is Rodolfo Berrocal, I'm from Lima, Peru. I just stopped by to thank you for all the great work you do. I'm doing my best to understand your videos since I don't speak English very well, but I'm still learning a lot from you. I'm just getting started in the world of algorithmic trading, and it's going well for me. Thank you again, and blessings.

Tommy's photo

Tommy

Dear Ali, your attention to detail - and people - was always bar none. No question, you are our Financial Guru, while also a loving/caring figure so you deserve our utmost respect! Thank you for all your shared experience and everyday hard work for our not-only-financial wellfare! :)

Chad's photo

Chad

I’ve been in the program since Feb, have found a way to create and find a lot of pretty good algos, but magic sauce happens when we combine the uncorrelated “pretty goods”. Happy to report since Feb, up 28pct and am now in maintenance mode working on the process instead of reflexively reacting to every draw down that I think is the end of the world. Biggest learnings. Test for worst case portfolio drawdown, size accordingly. Trade top strategies within that portfolio, cycle out worst performers every few months. Seems to be a winning recipe and am so excited to think about the next chapter in this journey I’ve been on for many many moons 😃

Read more →

StatOasis is calm, evidence-based algorithmic-trading education, founded by Ali Casey. Ali builds systematic trading strategies and teaches the workflow behind them: research, build, test, combine, deploy. He writes the Overfit newsletter, published since 2024, and runs the Algo Trading Masterclass.

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