SHARPE RATIO
DAILY R · √2520.53
Annualized √252
01 · $1,000,000 QUANT CHALLENGE
THE $1,000,000 QUANT ODYSSEY
Can a 100% systematic Python options engine turn a $20k base into $1,000,000 USD?
Zero Discretionary Trading. I research, backtest, and engineer. The algorithm executes with mathematical discipline during market hours — zero manual clicks, zero emotional overrides.
CURRENT RISK UNIT: 1R = $200 USD (1.0% Base) • Stage 1: Scaling Alpha
START
100.00
NAV · $20,000
CURRENT
100.33
NAV
TARGET
5,000.00
NAV · $1,000,000
PROGRESS
0.01%
100.00 → 5,000.00 NAV
CUMULATIVE RESULT +0.66 R Sum of all 36 closed trades.
The Builder's Log • Solo Engineering
I am a software engineer and algorithmic options trader. This challenge is not a corporate marketing demo or a paper-trading simulation — it is a public, real-money execution experiment on my personal Interactive Brokers account.
I built this autonomous Python engine to test a single hypothesis: can pure mathematical discipline, rigorous risk parity, and zero discretionary screen-time take a $20k base to $1,000,000 USD? The code executes live. The fills, commissions, and drawdowns are real. Every tick is public.
Kris • Lead Quant Developer Interactive Brokers Live Account
02 · SCORECARD
Live snapshot
PROFIT FACTOR
ABOVE 1.001.07
GAINS / |LOSSES|
WIN RATE
CLOSED TRADES44.4%
R > 0
MAX DRAWDOWN
CUMULATIVE R-2.75 R
PEAK TO TROUGH
TOTAL CLOSED TRADES
CLOSED ONLY36
JOURNAL
DAYS LIVE
UNIQUE SESSIONS19
sessions
03 · EQUITY CURVE
NAV index
BASELINE 100.00 · SESSION CLOSE
04 · MANIFESTO
Will the model reach the $1M target?
One vote per email address. The tally is public.
0.0% YES
0 votes
0.0% NO
SYSTEM ARCHITECTURE & GOVERNANCE
The Division of Responsibilities: Engineer in the Pits vs Algorithm on the Track
LIVE MARKET HOURS (100% AUTONOMOUS)
The machine executes the math in real time.
- Zero manual order entry
- Hard time-stops & limit exits
- M2 Anti-chase & RVOL filters
- 100% code-driven risk parity
OFF-MARKET QUANT R&D (HUMAN ENGINEER)
I research the data, eliminate bugs, and optimize the model off-market.
- Walk-forward backtesting
- CI/CD test suites
- Data lake curation
- Universe & liquidity profiling
CORE RISK GOVERNANCE
Capital-protection rules that do not bend.
- Strictly capped 1R risk
- Freeroll ratchet ladder
- Performance-gated capital tranches
- Daily loss circuit-breaker
- Zero screen-time mandate
TRANCHE SCALING & GIPS NAV ISOLATION
I do not wait years for the base to grow only from micro-gains. After a phase proves its statistical edge — like Gate T0 cleared at N ≥ 30 — I may allocate the next capital tranche myself, expanding the base to $30,000 or $40,000 USD. Cash added later stays strictly outside the NAV calculation.
A deposit does not raise the rate of return or the NAV index. The path from 100.00 to 5,000.00, and the result in R, measure market results only.
05 · TRADE CARDS
Sanitized execution archive
Latest 10 of 36 closed trades. Earlier results are in the cumulative total, not in this list.
The full PNG card and broker receipt unlock after you verify an email code.
- SPY LONG CALL -0.72 R -$144 USD @ 1R=$200
2026-10-30 · 335m
- QQQ LONG CALL -0.60 R -$120 USD @ 1R=$200
2026-10-30 · 76m
- SPY LONG CALL -0.70 R -$140 USD @ 1R=$200
2026-10-29 · 344m
- SPY LONG CALL -0.14 R -$28 USD @ 1R=$200
2026-10-29 · 89m
- SPY LONG CALL -0.42 R -$84 USD @ 1R=$200
2026-10-28 · 334m
- PLTR LONG PUT 0.00 R $0 USD @ 1R=$100
2026-10-27 · 173m
- SPY LONG CALL +0.80 R +$80 USD @ 1R=$100
2026-10-27 · 343m
- NVDA LONG PUT -0.34 R -$34 USD @ 1R=$100
2026-10-26 · 333m
- SPY LONG CALL +0.40 R +$40 USD @ 1R=$100
2026-10-26 · 344m
- SPY LONG PUT -0.56 R -$56 USD @ 1R=$100
2026-10-23 · 344m