Molson Coors Beverage Company (TAP)
概览 · 期权链 · 波动率 · 预期涨跌幅历史记录 · 财报
Cboe delayed options data · 截至 00:38 UTC · 基于完整期权链衍生的数据 (212 合约, 6 到期日) · IV自身历史百分位在记录满60天后显示 (4 迄今为止)
预期涨跌幅 — Oct 16, 2026 (43 天)
方法论 →从期权价格中读取：平值跨式期权的成本即为市场在此日期前预计的双向波动幅度。这是对波动空间的估算，而非对方向的预测。
期权隐含波动幅度约为 ±8.3% (区间 37.16–43.91) 由 Oct 16, 2026. ATM 跨式组合: 3.38 @ 行权价 40 · ATM IV: 29.6%.
概率分布
模型与假设 →该曲线显示以当前隐含波动率为输入的对数正态模型对本到期日结果区间的估计，阴影部分为预期波动区间。
| 级别 | vs 价格 | P(上涨)Model-estimated chance the stock finishes above a level at expiration, derived from current IV under a lognormal model with stated assumptions — an estimate, not a prediction. | P(下跌) |
|---|---|---|---|
| 36.49 | -10% | 83.8% | 16.2% |
| 38.51 | -5% | 67.5% | 32.5% |
| 40.54 | +0% | 48.0% | 52.0% |
| 42.57 | +5% | 29.7% | 70.3% |
| 44.59 | +10% | 16.2% | 83.8% |
模型估算的标的在到期时收于各价位上方/下方的概率——基于既定假设的估算，非预测。
概率探索工具
拖动滑块至任意价位，查看模型估算的股票在所选到期日收于该价位上方或下方的概率。
期限: Oct 16, 2026 · 对数正态模型，零漂移——仅为估算，非预测。 假设条件
到期日
打开期权链 →| 到期时间 | DTEDays to expiration, in calendar days. | 隐含涨跌幅 | ATM IV | 未平仓量 |
|---|---|---|---|---|
| Sep 18, 2026 | 15 | ±4.9% | 28.4% | 4,216 |
| Oct 16, 2026 | 43 | ±8.3% | 29.6% | 5,746 |
| Nov 20, 2026 | 78 | ±12.3% | 32.9% | 249 |
| Jan 15, 2027 | 134 | ±15.0% | 30.9% | 11.4K |
各行权价未平仓量 — Oct 16
期权头寸集中分布的位置。青色柱为 call，红色柱为 put；虚线为当前价格。
未平仓量最集中的头寸（所有到期日 ≤ 60天）： 45 C · 1,85042.5 C · 1,29940 P · 1,28047.5 C · 1,14537.5 P · 1,005
关于 Molson Coors Beverage Company
Molson Coors Beverage Company is a global entity engaged in the production, marketing, and sale of a diverse range of beer and other malt-based beverages. Its extensive operations span the Americas, Europe, the Middle East, Africa, and the Asia Pacific region. The company's product lineup also features flavored malt beverages, craft beers, and convenient ready-to-drink selections. Founded in 1774, the firm, headquartered in Golden, Colorado, was previously known as Molson Coors Brewing Company before officially adopting its current name, Molson Coors Beverage Company, in January 2020.
必需消费品 · Beverages - Alcoholic · NYSE · 公司简介：Financial Modeling Prep