Free ETF Price API
Quotes, OHLCV & Python免费 ETF 行情 API
报价、K 线与 Python 接入

TL;DR概览

Free ETF price API data: quotes versus OHLCV免费 ETF 行情 API：报价与历史 K 线数据

An ETF quote API commonly returns the latest trade or close, change, currency, volume, and a timestamp. An ETF OHLCV API returns open, high, low, close, and volume by interval. Treat “real time” as a claim to verify: free plans may be delayed or limited to specific venues.

ETF 报价 API 通常返回最新成交价或收盘价、涨跌、币种、成交量和时间戳；ETF K 线数据 API 按周期返回开高低收与成交量。不要默认“实时”一定无延迟，免费层可能只提供延迟行情或有限市场。

Decide which market observation the application needs. A last trade can be old, a midpoint depends on a valid bid and ask, an official close follows venue rules, and a bar aggregates transactions under a stated session and interval. Premarket, regular, and after-hours data should not be merged without explicit session labels and comparable volume definitions.

应用必须先明确需要哪一种市场观测。最新成交可能已经陈旧，中间价依赖有效买卖报价，官方收盘遵循交易所规则，K 线则在明确时段与周期内汇总成交。盘前、常规盘和盘后数据不能在缺少时段标签与可比成交量口径时直接混合。

ETF market price, NAV, and iNAV are different valuesETF 市价、NAV 与 iNAV 是不同的数据

An ETF trades on an exchange, so its latest trade, bid, ask, and historical OHLCV come from the listing market. Net asset value (NAV) is a fund accounting value calculated from portfolio assets and liabilities, commonly published after the market close. An intraday indicative value—often labeled iNAV or IOPV—is an estimate calculated during the session under a stated methodology. It is neither the official closing NAV nor a guaranteed executable price.

ETF 在交易所挂牌，因此最新成交、买卖价和历史 OHLCV 来自上市市场。基金资产净值（NAV）则是根据组合资产与负债计算的会计数值，通常在收盘后公布。盘中参考净值常写作 iNAV 或 IOPV，是按照特定方法在交易时段内估算的参考值，既不是官方日终 NAV，也不是保证可以成交的价格。

Worked example: calculate premium or discount with aligned timestamps实例：在时间口径一致时计算 ETF 溢折价

If an ETF closes at $50.40 and the official NAV for the same valuation date is $50.00, the closing premium is (50.40 / 50.00 - 1) × 100 = 0.80%. Label it as a closing premium and retain both source timestamps. If the market is currently trading at $50.60 but the only NAV available is yesterday's $50.00, calculating 1.20% does not produce a real-time premium: it compares a current market observation with a stale accounting value.

假设某 ETF 收盘价为 50.40 美元，同一估值日的官方 NAV 为 50.00 美元，则收盘溢价为 (50.40 / 50.00 - 1) × 100 = 0.80%。结果应明确标注为收盘溢价，并保存两项数据的来源时间。如果当前市价为 50.60 美元，但能取得的 NAV 仍是昨日 50.00 美元，计算出的 1.20% 并不是实时溢价，因为它比较了当前市价与已经陈旧的会计净值。

Why market price can diverge from NAVETF 市价为什么会偏离 NAV

Premiums and discounts can widen when underlying assets are closed, illiquid, difficult to value, or trading in another timezone; when FX moves after a local market closes; during volatility, halts, or market stress; and when the ETF's spread or depth deteriorates. The creation and redemption mechanism can support alignment, but it does not guarantee that every displayed trade equals contemporaneous NAV.

当底层资产已经休市、流动性不足、难以估值或处于其他时区时，汇率在当地市场收盘后继续波动时，以及发生剧烈波动、停牌、市场压力或 ETF 自身价差扩大、深度下降时，溢折价都可能扩大。申购赎回机制有助于价格与净值靠拢，但并不保证每一笔成交都等于同一时点的 NAV。

Combine sources instead of expecting one endpoint to do everything组合不同来源，不要要求一个接口解决所有问题

How to compare a free ETF market data API如何比较免费 ETF 行情数据 API

ETF price API for Python: a safe integration pathPython 获取 ETF 行情：安全接入步骤

Map the provider response into the fields below before displaying a quote. This validator treats the source timestamp—not HTTP arrival speed—as the freshness clock and returns a midpoint only for a non-crossed, sufficiently recent market.

展示报价前，先把供应商响应映射为下面使用的字段。校验器以数据源时间戳而不是 HTTP 到达速度判断时效；只有买卖价没有倒挂且报价足够新时，才返回中间价。

from datetime import datetime, timezone
from decimal import Decimal, InvalidOperation


def parse_time(value: str) -> datetime:
    parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
    if parsed.tzinfo is None:
        raise ValueError("source timestamp must include a timezone")
    return parsed


def validate_etf_quote(quote: dict, max_age_seconds: int = 60) -> dict:
    required = {
        "instrument_id", "symbol", "exchange", "currency",
        "session", "market_status", "source_timestamp", "bid", "ask"
    }
    missing = required - quote.keys()
    if missing:
        raise ValueError(f"missing quote fields: {sorted(missing)}")
    try:
        bid = Decimal(str(quote["bid"]))
        ask = Decimal(str(quote["ask"]))
        last = None if quote.get("last") is None else Decimal(str(quote["last"]))
    except InvalidOperation as exc:
        raise ValueError("quote contains a non-numeric price") from exc
    if bid <= 0 or ask <= 0 or (last is not None and last <= 0):
        raise ValueError("prices must be positive")
    if bid > ask:
        raise ValueError("crossed market: bid is above ask")

    source_time = parse_time(quote["source_timestamp"])
    now = datetime.now(timezone.utc)
    age_seconds = (now - source_time.astimezone(timezone.utc)).total_seconds()
    if age_seconds < 0:
        raise ValueError("source timestamp is in the future")
    is_live_session = quote["market_status"] == "open"
    is_stale = is_live_session and age_seconds > max_age_seconds
    return {
        "instrument_id": quote["instrument_id"],
        "midpoint": (bid + ask) / Decimal("2"),
        "last_trade": last,
        "spread": ask - bid,
        "source_time": source_time,
        "age_seconds": age_seconds,
        "is_stale": is_stale,
        "session": quote["session"],
    }

Use QVeris to discover ETF quote API capabilities用 QVeris 发现 ETF 报价 API 能力

• Open the QVeris provider details for quote and historical-price capabilities.
• Inspect identifiers, venue, session, quote or bar type, timestamps, condition codes, adjustment policy, response schema, and stated limitations before calling.
• Require the exact listing, currency, data type, interval, session, freshness tolerance, and raw-versus-adjusted choice in the tool request.
• Use the QVeris documentation to connect the selected capability while preserving source evidence and safe failure states.

• 在 QVeris 服务商详情中查找报价与历史行情能力。
• 调用前检查标识、市场、时段、报价或 K 线类型、时间戳、条件代码、复权规则、响应结构和公开限制。
• 在工具请求中明确上市、币种、数据类型、周期、时段、时效容忍度和原始或复权选择。
• 参考 QVeris 文档接入选定能力，并保留来源证据与安全失败状态。

Free ETF price API FAQ免费 ETF 行情 API 常见问题

Authoritative references and next steps权威参考与后续步骤