风险价值（VaR）计算器

分类： Uncategorized
- August 31, 2026
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Estimate potential losses in your portfolio with different confidence levels and time horizons

$
%
Standard deviation of annual returns
Probability that losses will not exceed the VaR value
Calculation Method:

VaR Results

Value-at-Risk (VaR) $0.00 Based on 95% confidence
Maximum Loss Percentage 0.00%
预期亏损（CVaR） $0.00 Average loss when VaR is exceeded

VaR Distribution

VaR by Confidence Level

VaR Comparison

时间跨度 95% VaR 99% VaR 99.9% VaR

Advanced Settings

压力测试

2008 Financial Crisis

Simulates portfolio losses based on 2008 market conditions

Potential Loss: $0.00

2020 COVID Crash

Models the rapid market decline seen in March 2020

Potential Loss: $0.00

2% Interest Rate Spike

Simulates impact of a sudden 2% rise in interest rates

Potential Loss: $0.00

About Value-at-Risk (VaR)

Value-at-Risk (VaR) is a statistical technique used to measure and quantify the level of financial risk within a portfolio over a specific time frame. It estimates how much a portfolio might lose in value over a defined period, with a given confidence level, under normal market conditions.

Parametric VaR

This approach assumes returns follow a normal distribution and uses volatility to estimate potential losses. It's simple and fast but may underestimate risks during extreme market conditions.

Historical VaR

Uses actual historical returns to estimate VaR. This approach doesn't assume a specific distribution but is limited by the historical data available and may not capture future risks.

Monte Carlo VaR

Generates thousands of random simulations based on statistical properties of returns. Offers flexibility in modeling different market conditions but is computationally intensive.

Conditional VaR (CVaR)

Also known as Expected Shortfall, CVaR measures the average loss exceeding the VaR threshold. It provides more insight into tail risk and is considered a more coherent risk measure than VaR.

Tips for Using VaR Effectively

  • VaR is not a maximum loss estimate; it can be exceeded with the probability specified (e.g., 5% for a 95% confidence VaR).
  • Consider using multiple confidence levels and time horizons to better understand your risk profile.
  • Supplement VaR with stress testing to assess potential losses during extreme market events.
  • Remember that all VaR models have limitations and should be part of a broader risk management strategy.
  • Regularly recalibrate your VaR model as market conditions and portfolio composition change.

本工具计算什么

在指定信心水平下，投资组合预期不会超出的亏损金额。

公式
VaR = 组合价值 × z 值 × 波幅 × √时间。95% 信心水平 z = 1.645，99% 为 2.326
计算示例
1,000,000 港元组合、日波幅 1.2%，一日 95% VaR = 1,000,000 × 1.645 × 0.012 ≈ 19,740 港元。
何时使用
为既定时间内的常态下行风险订出具体数字。
常见错误
VaR 完全不描述超出门槛后的亏损。95% VaR 对最差的 5% 日子只字不提，而真正的损失正在其中。