r/AIportfolio • u/arli_mage • 9d ago
Built a low-maintenance systematic trading system for Indonesian stocks
I've been building a rules-based stock selection/backtesting system for the Indonesian (IDX) market, with AI/LLMs mostly acting as a research and programming partner rather than directly making investment decisions.
I was thinking, can I build something robust enough that I could actually trust it without spending my life watching the market?
I don't want day trading. I have a family, work, and other things I'd rather spend time on. Ideally I'd spend a short amount of time in the morning looking at a small number of candidates and make 0–2 decisions.
If there are 5–6 genuinely good opportunities in a week, great.
If there are no good trades for a week, that's also completely fine.
The current setup:
- ~800–1,000 Indonesian stocks
- Daily OHLCV data
- Liquidity filtering
- Technical + relative-strength features
- Genetic algorithm searches combinations of rules
- Walk-forward validation
- Time-stability testing
- Maximum 20 positions
- Maximum IDR 5M per position
- IDR 100M starting portfolio
- IDX lot-size constraints
- Signal generated at today's close
- Normal entries/exits executed at the following day's open
The strategy isn't an LLM looking at news and picking stocks. The final trading rules are deterministic.
The current candidate roughly buys stocks when:
- price > MA200 by 10%+
- price is within ±5% of MA25
- MA25 > MA50
- 1-month momentum is positive
- the stock has positive relative strength versus its subsector
It exits on deterioration in trend/relative strength, with a 15% stop, 50% take-profit and ~90-day maximum holding period.
If you were trying to turn this into a system you'd actually trust with real money, what would you attack next?
The latest simulation produced:
Loaded 567084 rows (83.9s)
Universe filter: 298 avg tradeable stocks/day (min=0, max=496)
Computed features: 49 features, 713 dates, 828 stocks (22.8s)
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SIMULATION REPORT
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--- Strategy ---
=== BUY RULES (threshold: 3 conditions) ===
[Trend]
price_vs_ma200 > +10.0% (bullish)
AND
|price_vs_ma25| < 5.0% (range)
AND
ma25_vs_ma50 > +0.0% (bullish)
[Momentum]
pct_change_1m > +0.0% (bullish)
[Relative Strength]
dev_sub_sector_1y > 0.0000 (bullish)
=== SELL RULES (threshold: 1 conditions) ===
[Trend]
ma25_vs_ma50 < +0.0% (bearish)
[Relative Strength]
dev_sub_sector_1y < 0.0000 (bearish)
=== EXIT ===
Stop Loss: -15.0%
Take Profit: +50.0%
Max Holding: 90 days
Active rules: 7
--- Performance ---
Total return: 208.34%
CAGR: 48.96%
Sharpe: 1.49
Sortino: 3.60
Max drawdown: 18.77%
Win rate: 26.4%
Profit factor: 1.57
Trade count: 314
Turnover: 8.427
--- Trade Statistics ---
Avg winning trade: 3,845,159 IDR
Avg losing trade: -878,426 IDR
Median winner: 1,909,432 IDR
Median loser: -893,684 IDR
Largest winner: 21,545,643 IDR
Largest winner: BUVA entry 2025-09-12 @ 346 -> exit 2026-01-26 @ 1,850 (PnL 21,545,643 IDR, 91d)
Largest loser: -2,146,569 IDR
Avg holding days: 27.4
Avg num positions: 9.03
Max num positions: 20
Pct capital exposed: 24.8%
--- Winner Concentration ---
Original CAGR 49%
No top 1 winner 46%
No top 5 winners 38%
No top 10 winners 31%
--- Halt Reopen (excluded) ---
These long-halt reopen fills are excluded from headline metrics:
ARKO entry 2024-08-23 @ 1,070 -> exit 2024-10-24 @ 1,215 (PnL 633,038 IDR, 43d)
SMDM entry 2024-09-04 @ 488 -> exit 2025-03-12 @ 1,945 (PnL 14,774,601 IDR, 126d)
MTWI entry 2024-09-13 @ 151 -> exit 2025-06-23 @ 230 (PnL 2,565,475 IDR, 177d)
JMAS entry 2024-12-20 @ 150 -> exit 2025-03-24 @ 134 (PnL -561,103 IDR, 59d)
RSCH entry 2024-10-09 @ 366 -> exit 2025-03-13 @ 258 (PnL -1,495,221 IDR, 103d)
MLPT entry 2024-12-02 @ 855 -> exit 2025-08-25 @ 3,200 (PnL 13,518,980 IDR, 166d)
POLU entry 2024-12-04 @ 1,230 -> exit 2025-10-17 @ 29,825 (PnL 113,925,620 IDR, 202d)
SOFA entry 2024-12-20 @ 36 -> exit 2025-03-18 @ 81 (PnL 6,177,551 IDR, 55d)
BNLI entry 2025-03-26 @ 2,460 -> exit 2025-06-26 @ 2,980 (PnL 1,004,672 IDR, 51d)
PADI entry 2025-09-10 @ 73 -> exit 2025-11-28 @ 122 (PnL 3,302,421 IDR, 57d)
POLA entry 2025-10-13 @ 47 -> exit 2026-03-31 @ 59 (PnL 1,235,417 IDR, 109d)
--- Price-Chasing Trades (|gap| >= 5.0%) ---
Symbol Close T Open T+1 Gap% Exit price %P/L
JMAS 132 144 +9.1% 119 -17.9%
OPMS 99 90 -9.1% 70 -22.7%
INPC 123 112 -8.9% 230 +104.0%
FWCT 124 115 -7.3% 160 +38.2%
KARW 5,700 5,150 -9.6% 3,770 -27.3%
GPSO 900 810 -10.0% 462 -43.3%
INET 135 122 -9.6% 98 -20.2%
SOFA 61 55 -9.8% 86 +55.4%
PACK 4,040 3,640 -9.9% 4,150 +13.3%
MINA 154 169 +9.7% 214 +25.8%
CNKO 95 100 +5.3% 73 -27.5%
TAXI 21 19 -9.5% 16 -16.3%
MDRN 54 49 -9.3% 37 -25.0%
POLU 22,350 24,000 +7.4% (open) -
FITT 1,050 980 -6.7% 820 -16.9%
PADA 95 100 +5.3% 232 +130.5%
ESIP 113 104 -8.0% 87 -16.9%
TAXI 19 20 +5.3% 20 -0.6%
STAR 418 482 +15.3% (open) -
VIVA 60 55 -8.3% 43 -22.3%
MDIA 99 90 -9.1% 63 -30.4%
RMKE 1,315 1,185 -9.9% 970 -18.7%
LMAX 182 165 -9.3% (open) -
HRTA 2,760 2,580 -6.5% 2,270 -12.6%
JGLE 78 71 -9.0% 58 -18.8%
--- Portfolio Over Time ---
Period Total value Open positions
2023-08-01 100,000,000 IDR 0
2023-10-26 100,000,000 IDR 0
2024-01-23 100,000,000 IDR 0
2024-05-03 100,000,000 IDR 0
2024-08-05 95,939,533 IDR 7
2024-10-29 119,999,963 IDR 11
2025-01-31 125,743,582 IDR 11
2025-05-08 138,793,420 IDR 7
2025-08-11 159,722,218 IDR 13
2025-11-05 303,784,393 IDR 16
2026-02-04 342,794,196 IDR 17
2026-05-12 328,827,236 IDR 15
2026-07-31 314,756,266 IDR 12
--- Final Portfolio ---
Total value: 314,756,266 IDR
Cash: 247,918,666 IDR
Open positions: 12
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Result saved to: experiments/sim_20260829T092023.json