feat: add scoped alpha sync and local self-correlation
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@@ -0,0 +1,191 @@
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import { useEffect, useState } from "react";
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import {
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Banner,
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Button,
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Descriptions,
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Empty,
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Spin,
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Table,
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Tag,
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Toast,
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} from "@douyinfe/semi-ui-19";
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import { api, correlationLabels, formatNumber, formatTime, post } from "../api";
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import type { CorrelationResult } from "../types";
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export function SelfCorrelationPanel({
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id,
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version,
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timezone,
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onTask,
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}: {
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id: string;
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version: string;
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timezone?: string;
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onTask: () => void;
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}) {
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const [result, setResult] = useState<CorrelationResult | null>(null);
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const [loading, setLoading] = useState(true);
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const [busy, setBusy] = useState(false);
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const [error, setError] = useState("");
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useEffect(() => {
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const controller = new AbortController();
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setLoading(true);
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api<{ result: CorrelationResult | null }>(
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`/alphas/${id}/self-correlation`,
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{ signal: controller.signal },
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)
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.then((value) => {
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if (!controller.signal.aborted) {
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setResult(value.result);
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setError("");
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}
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})
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.catch((e) => {
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if (!controller.signal.aborted) setError(e.message);
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})
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.finally(() => {
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if (!controller.signal.aborted) setLoading(false);
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});
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return () => controller.abort();
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}, [id, version]);
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async function check() {
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setBusy(true);
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try {
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await post("/sync-jobs", { kind: "self_correlation", alpha_ids: [id] });
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onTask();
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} catch (e) {
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Toast.error((e as Error).message);
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} finally {
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setBusy(false);
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}
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}
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return (
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<div className="correlation-panel">
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<div className="section-toolbar">
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<h3>本地自相关</h3>
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<Button onClick={() => void check()} loading={busy}>
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{result ? "重新检测自相关" : "检测自相关"}
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</Button>
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</div>
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<p className="muted">
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与本地已同步的同地区已提交 Alpha 比较,排除自身。使用 PnL
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缓存,缺失时自动获取;建议先全量同步已提交 Alpha。
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</p>
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<p className="muted">
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近四年 PnL 日变化的 Pearson 相关系数,至少 30 个共同样本;本地告警线为
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0.7,检测结果与平台检查分别记录。
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</p>
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{error && <Banner type="danger" description={error} />}
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{loading && !result ? (
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<Spin />
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) : !result ? (
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<Empty description="尚未检测自相关" />
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) : (
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<>
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{result.stale && (
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<Banner
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type="warning"
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description="PnL 或比较样本已更新,以下为上次结果,请重新检测。"
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/>
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)}
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<div className="inline-actions">
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<Tag
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color={
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result.stale
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? "grey"
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: result.status === "high"
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? "orange"
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: result.status === "low"
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? "green"
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: "grey"
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}
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>
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{correlationLabels[result.status]}
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</Tag>
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<span className="muted">
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计算于 {formatTime(result.calculated_at, timezone)}
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</span>
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</div>
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<Descriptions
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data={[
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{
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key: "最大相关系数",
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value: formatNumber(result.max_correlation, 4),
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},
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{
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key: "有效比较",
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value: `${result.compared_count} / ${result.candidate_count}`,
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},
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{ key: "跳过样本", value: result.skipped_count },
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{
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key: "比较窗口",
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value: result.window_from
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? `${result.window_from} 至 ${result.window_to}`
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: "未提供",
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},
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{
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key: "目标 PnL 更新",
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value: result.target_pnl_fetched_at
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? formatTime(result.target_pnl_fetched_at, timezone)
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: "未提供",
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},
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]}
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/>
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{result.reason && <p>{result.reason}</p>}
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{result.status === "partial" && (
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<p>已有样本低于阈值,但部分基准无法比较,不能据此判断全部样本。</p>
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)}
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{result.matches.length > 0 && (
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<>
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<h3>相关系数最高的 Alpha(最多 10 条)</h3>
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<Table
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dataSource={result.matches}
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rowKey="alpha_id"
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size="small"
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pagination={false}
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columns={[
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{
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title: "Alpha",
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dataIndex: "alpha_id",
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render: (value) => (
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<a
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href={`https://platform.worldquantbrain.com/alpha/${encodeURIComponent(value)}`}
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target="_blank"
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rel="noreferrer"
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>
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{value}
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</a>
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),
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},
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{
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title: "相关系数",
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dataIndex: "correlation",
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render: (value) => formatNumber(value, 4),
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},
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{ title: "共同样本", dataIndex: "sample_count" },
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{
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title: "PnL 更新",
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dataIndex: "pnl_fetched_at",
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render: (value) => formatTime(value, timezone),
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},
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]}
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/>
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</>
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)}
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{result.skipped.length > 0 && (
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<details>
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<summary>
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跳过原因({result.skipped_count} 条,最多展示 100 条)
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</summary>
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{result.skipped.map((item) => (
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<p key={item.alpha_id}>
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<code>{item.alpha_id}</code>:{item.reason}
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</p>
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))}
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</details>
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)}
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</>
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)}
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</div>
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);
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}
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