ARES Flow A @import url(‘https://fonts.googleapis.com/css2?family=IBM+Plex+Sans+Thai:wght@400;500;600;700&display=swap’);#aresFlowA{ –blue:#00CFFF; –blue2:#47E9FF; –ink:#111; –muted:#555; –burgundy:#800020; –radius:10px; –shadow:0 6px 16px rgba(0,0,0,.08); background:#e9ebed; font-family:”IBM Plex Sans Thai”,sans-serif; color:var(–ink); line-height:1.55; font-size:20px; padding:32px 0 60px; text-align:center; } #aresFlowA .wrap{max-width:980px;margin:24px auto}/* cards */ #aresFlowA .cardA{ background:#fafafa;border:1px solid #e5e5e5;border-radius:var(–radius); padding:22px 26px;text-align:center;box-shadow:var(–shadow); opacity:0;transform:translateY(14px); animation:aresA_in .7s cubic-bezier(.22,.61,.36,1) forwards; font-size:20px;font-weight:500; } #aresFlowA .cardA:nth-of-type(1){animation-delay:.05s} #aresFlowA .cardA:nth-of-type(2){animation-delay:.16s} #aresFlowA .cardA:nth-of-type(3){animation-delay:.27s} #aresFlowA .cardA:nth-of-type(4){animation-delay:.38s} #aresFlowA .cardA:nth-of-type(5){animation-delay:.49s} #aresFlowA .cardA:nth-of-type(6){animation-delay:.60s} #aresFlowA .cardA strong{font-weight:600;font-size:22px}/* arrows */ #aresFlowA .arrowA{ height:22px;display:flex;align-items:center;justify-content:center;margin:12px 0 16px; animation:aresA_bounce 1.5s ease-in-out infinite .12s; } #aresFlowA .arrowA:before{ content:””;width:11px;height:11px; border-right:2.8px solid var(–blue); border-bottom:2.8px solid var(–blue); transform:rotate(45deg); filter:drop-shadow(0 0 5px rgba(0,207,255,.4)); }/* blue band */ #aresFlowA .bandA{ background:linear-gradient(0deg,var(–blue2),var(–blue)); color:#111;border:none;font-weight:700;border-radius:var(–radius); font-size:21px;position:relative;overflow:hidden; box-shadow:0 0 10px rgba(0,207,255,.25); } #aresFlowA .bandA:after{ content:””;position:absolute;inset:0; background:linear-gradient(90deg,transparent,rgba(255,255,255,.4),transparent); transform:translateX(-120%); animation:aresA_shimmer 2.5s ease-in-out infinite 1.2s; pointer-events:none; }/* final */ #aresFlowA .finalA{ background:var(–burgundy);color:#fff;border:none;font-weight:700;border-radius:var(–radius); font-size:22px; box-shadow:0 10px 22px rgba(128,0,32,.25); animation:aresA_in .7s cubic-bezier(.22,.61,.36,1) forwards .65s, aresA_pulse 3s ease-in-out infinite 1.5s; }#aresFlowA .hintA{display:block;color:var(–muted);font-size:17px;margin-top:8px} #aresFlowA .cardA:hover{transform:translateY(-1px);transition:transform .25s ease}/* CTA text link */ #aresFlowA .cta-wrap{margin-top:42px;text-align:center;} #aresFlowA .cta-link{ color:var(–burgundy); font-size:22px; font-weight:600; text-decoration:underline; transition:color .25s ease; opacity:0; animation:aresA_in .7s ease .8s forwards; } #aresFlowA .cta-link:hover{color:#a0273f;}/* keyframes */ @keyframes aresA_in{to{opacity:1;transform:translateY(0)}} @keyframes aresA_bounce{0%,100%{transform:translateY(0)}50%{transform:translateY(5px)}} @keyframes aresA_shimmer{0%{transform:translateX(-120%)}60%,100%{transform:translateX(120%)}} @keyframes aresA_pulse{0%,100%{box-shadow:0 8px 18px rgba(128,0,32,.25)}50%{box-shadow:0 12px 26px rgba(128,0,32,.40)}}/* responsive */ @media (max-width:768px){ #aresFlowA .wrap{max-width:90%;margin:20px auto} #aresFlowA .cardA{padding:18px;font-size:18px;line-height:1.6} #aresFlowA .bandA{font-size:19px} #aresFlowA .finalA{font-size:20px} #aresFlowA .hintA{font-size:15px} #aresFlowA .cta-link{font-size:20px} } @media (max-width:480px){ #aresFlowA{font-size:17px;line-height:1.6;padding:28px 0 50px;} #aresFlowA .cardA{padding:14px 16px;font-size:16px;line-height:1.5} #aresFlowA .cardA strong{font-size:18px;} #aresFlowA .bandA{font-size:17px} #aresFlowA .finalA{font-size:18px;padding:16px} #aresFlowA .hintA{font-size:14px} #aresFlowA .cta-link{font-size:18px} #aresFlowA .arrowA{margin:10px 0 14px;} #aresFlowA .wrap{margin:20px auto} }@media (prefers-reduced-motion:reduce){ #aresFlowA .cardA,#aresFlowA .arrowA,#aresFlowA .bandA:after,#aresFlowA .finalA,#aresFlowA .cta-link{animation:none} #aresFlowA .cardA,#aresFlowA .cta-link{opacity:1;transform:none} }

หุ้นจากตลาดสหรัฐฯ ≈ 5,000 หุ้น

คัดกรองบริษัทที่มีขนาดใหญ่ (Liquidity เพียงพอ) ≈ 2,000 – 3,000 หุ้น

Expert System ใช้ข้อมูลงบการเงิน นำมาคำนวณตามกฎเกณฑ์
(Rule-Based Filtering by FM)

Quality Stock Universe (250 หุ้น)

ARES : AI/ML Expected Return Rankings จัดอันดับผลตอบแทนคาดหวังด้วยโมเดล AI/ML

Fund Manager’s Top 10 : Strong Fundamentals, High Potential Returns

ดูข้อมูลเพิ่มเติมเกี่ยวกับนวัตกรรม AI/ML (ARES)