Investment monitoring & simulation /Production

A dual-horizon advisor that argues with itself before it recommends anything, then paper-trades its own advice.

nightly report · book B

ticker	signal	grade	size
AAA	BUY	B+	3.1%
BBB	WATCH	C	—
CCC	HOLD	A-	5.4%

01 Built a dual-horizon multi-agent investment advisor — DeepSeek-graded long-term (fundamentals/DCF) and short-term (momentum) signals, a bull/bear researcher debate, deterministic position sizing off real IBKR NAV, and an options overlay, delivered nightly per user via Telegram
02 Fixed a position-sizing defect in an automated trading system that recommended stock purchases up to 1.7x the account's available cash, by implementing cash-aware sizing caps across equity and options order sizing.
03 Redesigned an LLM-based short-term trading signal grader to incorporate current holdings and prior-day signal history, fixing a HOLD recommendation state that was unreachable by design and measured at only 4.3% of signals versus 84.3% WATCH across 140 signal-days.
04 Added a paper-trading simulation layer — deterministic entry scoring (A-F grade, no LLM) on every trade, a Δ-vs-Hold dashboard across multiple simulated books, and a lessons-learned loop that feeds post-mortems back into future recommendations

Interface recreated with invented data — no production screenshot is published. Private system; walkthrough and code review available on request.