A personal record of navigating markets, risk, and life — not a fund, not a business, not financial advice.
I am a private, accredited investor with decades of trading experience and a process that combines proprietary algorithmic models with discretionary decisions.
In 2025, I competed in the United States Investing Championship, a real-money trading competition organized by Financial-Competitions.com. I placed 8th in the $1 Million+ Enhanced Growth category with a return of +43.2%.
As an inherently private and introspective individual, I value personal achievement and discretion more than public recognition.
A personal record of how I think about uncertainty, discipline, risk, and recovery — not an attempt to build a public persona.
High risk, long-term capital growth — accepting deep drawdowns as part of the process.
Like a balloon pushed deep underwater, I tend to come back. I have recovered from levels where many would give up — in markets and in life.
Some of my best trades came when I felt most afraid. Being scared is acceptable; acting with discipline despite fear is part of my edge.
My life outside markets has shaped the way I think inside them.
I was partly raised by my grandmother, who gave me the warmth and stability I was missing elsewhere — and shaped much of who I am today.
I tend to be the trusted one in difficult times. That role has also taught me when to protect myself and how much to share.
Living with a progressive medical condition, I have spent thousands of hours in research papers — not just for investing, but to understand my own health.
That same analytical, relentless approach defines how I invest: unwilling to give up easily.
Deep drawdowns and difficult periods are part of the reality, not exceptions to it.
Research, structure, and judgment matter most when fear is highest.
I am drawn to the idea of returning stronger after hardship, in markets and in life.
The foundation of the portfolio is a proprietary private algorithm that acts as the stabilizing core of the overall structure.
The Core Algo is the base layer — designed for structure and stability, while the broader portfolio can include additional positions around it.
It trades Nasdaq 100 stocks exclusively. Historical testing spans the Nasdaq 100 back to 1993 and the S&P 500 back to 1957 — stress-tested across the 1987 crash, dot-com collapse, 2008 crisis, COVID-19, and multiple stagflation and recessionary periods.
Fees stay low due to modest trading frequency, and slippage tends to balance out over time. I target a long-term net CAGR of roughly 30–50% per year.
Results exclude slippage and fees — a theoretical tool, not a guarantee. The algo was tested on survivorship-bias-free data, validated on 5–10 year windows first, then applied to the full sample and cross-checked across indexes.
Backtests show exponential growth over decades, but live results differ. A six-month live run in 2025 revealed that overriding signals degraded performance; the key lesson was to let the system run without interference.
Real live-trading results including fees and slippage, updated daily. The full portfolio is broader than this chart — it also includes discretionary positions beyond the algorithm.
Last updated 13th April 2026
This is my own project and I only manage my own funds.
I am not looking for investors and I am not licensed or registered to manage money for others or to provide professional financial advice.
Investing and trading involve substantial risk.
You can lose some or all of your capital. Past performance is not a reliable indicator of future results. Anything you read here is at your own risk — please consult a qualified, regulated professional before making any financial decisions.
I value my privacy deeply. I may not always respond — please understand that discretion matters more to me than presence.
I sometimes write under pseudonyms — both in finance and in areas related to degenerative diseases — hoping to make life a little easier for others.
I respond when there is clear mutual value in the exchange.