The Persuit of HAPPYNESS
Pursuing Trading as a Career: Systems Over Speculation
Personal Essay • June 2026 | Shane • Systematic trader & tool builder, Texas
When people hear I'm deeply involved in trading — building custom scanners, backtesters, automated alerts, and live dashboards — some assume it's a sophisticated form of gambling. I get why. The public image of trading is frenetic screens, dopamine hits from green candles, and stories of overnight riches or spectacular blowups.
But that’s not what I’m doing. This is the pursuit of a career — a real one — built on data, repeatable processes, risk management, and the slow accumulation of edge through deliberate engineering and iteration. It’s closer to software development or quantitative research than rolling dice.
The distinction matters. Gambling has negative or zero expected value by design. A professional trading career, approached correctly, is about creating positive expectancy through rigorous testing and strict adherence to rules — then scaling that process responsibly.
The Numbers We're Up Against
The statistics on retail trading success are brutal and consistent across markets. Studies from Taiwan, Brazil, and U.S. broker data show that 70–97% of active retail traders lose money over meaningful timeframes. Only a small fraction — often cited between 1–13% — achieve consistent profitability.
| Statistic | Figure |
|---|---|
| Consistently profitable over 5+ years | ~1% |
| Quit within the first month | 40%+ |
| Lose money after transaction costs | 70–95% |
Sources include peer‑reviewed analyses of complete market datasets (Taiwan Stock Exchange), futures trader studies in Brazil, FINRA retail trading data, and broker disclosures. The pattern is clear: most people who try active trading lose.
Why I'm Building Systems, Not Just Taking Trades
Given those odds, why pursue this at all? Because the small percentage who succeed long‑term share common traits: they treat it like a business, they have a verifiable edge, they manage risk obsessively, and they remove as much emotion and discretion as possible.
That’s why my focus has been on infrastructure first. I’ve spent significant time building and refining custom tools rather than staring at charts all day:
- Custom backtesting frameworks — realistic slippage, costs, regime awareness.
- Scanners & Playbooks — automated detection of high‑probability setups.
- Live Dashboards & Alerts — real‑time monitoring and execution discipline.
- Reporting & tracking automation — surfacing what works and what doesn’t.
This isn’t about removing all human judgment. It’s about making the hard decisions in advance — during calm analysis — not in the heat of a fast‑moving market.
Core Principles Driving the Pursuit
01. Positive Expectancy First
No trade is worth taking unless the historical edge — after realistic costs — is positive.
02. Risk Management Is Non‑Negotiable
Position sizing, max drawdowns, correlation awareness — these come before any entry.
03. Process Over Outcome
A good process can have losing weeks. A bad process can have winning streaks that end in disaster.
04. Continuous Iteration
Markets evolve. Strategies degrade. The work is never “done.”
Where These Skills Lead: Professional Roles & Compensation
The same capabilities I’m building — backtesting engines, scanners, risk systems, dashboards — are exactly what top quant firms, hedge funds, and fintech companies hire for.
| Role | Junior / Early Career Total Comp (US) | Key Transferable Skills |
|---|---|---|
| Algorithmic Trading / Quant Developer HFT, Prop Firms, Hedge Funds |
$130k–$220k+ Base often $110k–$160k + bonus |
Python systems, backtesting frameworks, data pipelines, automated execution |
| Junior Quantitative Trader Prop Trading, Market Making |
$150k–$250k+ Highly bonus‑driven |
Systematic strategy development, risk engines, real‑time systems |
| Junior Quant / Market Analyst Banks, Asset Managers, Fintech |
$90k–$140k base + bonus |
Data analysis, scanner logic, reporting automation |
Notes: These are mid‑2026 ranges. Top prop firms often exceed the high end. Compensation is usually heavily bonus‑weighted.
Current Opportunities (June 2026)
OpenQuant.co — Dedicated quant job board
Hudson River Trading — Algo dev & systems roles
The Real Challenges (Beyond the Charts)
This pursuit happens alongside managing chronic health conditions, navigating SSDI benefits, and balancing energy carefully. Those constraints reinforce the need for systems: I can’t afford burnout or emotionally driven decisions.
The tools I’m building aren’t just for performance — they’re for sustainability. Automation reduces screen time. Playbooks reduce decision fatigue. Metrics reduce second‑guessing.
What Progress Actually Looks Like
- Improving expectancy and robustness across backtests
- Higher adherence to risk and process rules
- Cleaner, faster decision‑making
- Reduced emotional reactivity
- Better documentation and review processes
This Is a Marathon, Not a Sprint
I’m under no illusion that this is easy. The data says most people fail. But I’m not treating this like a lottery ticket — I’m engineering a career.
The pursuit continues. One backtest, one refined rule, one disciplined day at a time.
Follow the journey at wst.dfwsas.com — playbooks, tool updates, and honest performance notes.
Shared for educational and transparency purposes only.
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