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V-Lab

Volatility News Impact Curve User Guide

Visualize how return shocks affect next-day volatility

Contents

  • Tool Overview

  • Essential Concepts

  • How to Use

  • Data Interpretation

  • Practical Applications

  • Understanding Data

  • Troubleshooting

  • Tips & Best Practices

Tool Overview

The News Impact Curve is an interactive tool that visualizes the relationship between return shocks and subsequent volatility. Use it to understand model behavior, test scenarios, and compare how different models respond to market moves.

Shock Explorer

Use the interactive slider to simulate market shocks from -5% to +5% and see the immediate impact on volatility.

Asymmetry Visualization

See the leverage effect in action: how the curve tilts to show larger volatility increases for negative shocks.

Model Statistics

View key metrics including persistence, long-run volatility, and half-life of shocks.

Forecast Sparkline

Watch volatility evolve over time after the selected shock, converging to long-run levels.

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Essential Concepts

These terms are essential for understanding the News Impact Curve:

News Impact Curve (NIC)

A graphical representation showing how different return shocks (positive and negative) affect the next day's conditional volatility. The curve plots shock magnitude on the x-axis against the resulting volatility level on the y-axis.

Why it matters: The NIC reveals the model's response function: how quickly and asymmetrically the model reacts to market moves. This helps you understand what volatility to expect after different market scenarios.

Return Shock

The size of a hypothetical return on a given day, typically ranging from -5% to +5%. A -3% shock represents a 3% daily decline; a +2% shock represents a 2% daily gain.

Why it matters: By testing different shock sizes, you can see how volatility responds to various market scenarios, from minor fluctuations to significant market moves.

Asymmetric Response (Leverage Effect)

The empirical observation that negative returns increase volatility more than positive returns of the same magnitude. In GARCH models, this is captured by the gamma parameter in GJR-GARCH or the asymmetry term in EGARCH.

Why it matters: Markets exhibit this pattern: bad news spikes volatility more than good news calms it. Models that capture asymmetry (like GJR-GARCH) produce more accurate forecasts during downturns.

Persistence

A measure of how long volatility shocks last. Calculated as alpha + beta in GARCH models. Values near 1 (e.g., 0.95) mean shocks decay slowly over many days; lower values mean faster decay.

Why it matters: High persistence means a volatility spike today will still affect forecasts weeks later. Low persistence means volatility quickly returns to normal after shocks.

Long-Run Volatility

The unconditional volatility level that the model predicts in the absence of new shocks. This is the level volatility tends toward over time, also called the unconditional standard deviation.

Why it matters: Compare current volatility to long-run volatility to understand if conditions are stressed (above long-run) or calm (below long-run). Forecasts ultimately converge to this level.

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Tool Layout

The News Impact Curve tool has three main components:

  • NIC Chart

    The main visualization showing the U-shaped (or asymmetric) curve. The x-axis shows shock magnitude; the y-axis shows resulting volatility. You can click anywhere on the curve to set the shock slider to that value.

  • Shock Slider

    An interactive slider ranging from -5% to +5%. Drag to select a specific shock and see the corresponding point on the curve highlighted. The slider background is color-coded: green indicates lower resulting volatility, while orange and red indicate progressively higher volatility outcomes.

  • Statistics Panel

    Displays model metrics (persistence, long-run volatility, half-life) and a sparkline showing forecast evolution.

  • Metrics Box

    Located below the chart, shows four key values: Current Vol (today's volatility), At -5% Shock (volatility after a 5% decline), At +5% Shock (volatility after a 5% gain), and Asymmetry (the ratio of volatility response to negative vs positive shocks, where values above 1 indicate negative shocks have greater impact).

Using the Shock Explorer

The shock slider is color-coded to help you navigate different scenarios:

  • Negative Shocks (Red Zone)

    Left side of the slider. Simulates market declines from -1% to -5%. For asymmetric models, these produce larger volatility increases.

  • Zero Shock (Neutral)

    Center position. Shows baseline volatility if tomorrow's return is zero, the natural decay toward long-run levels.

  • Positive Shocks (Green Zone)

    Right side of the slider. Simulates market gains from +1% to +5%. Typically produces smaller volatility increases than equivalent negative shocks.

Reading the Curve Shape

The shape of the NIC reveals important model characteristics:

  • Symmetric U-Shape (Standard GARCH)

    The curve is symmetric around zero. Positive and negative shocks of equal magnitude produce identical volatility increases. The model treats good and bad news equally.

  • Tilted Curve (GJR-GARCH, EGARCH)

    The left side rises higher than the right. Negative shocks produce larger volatility increases. This captures the leverage effect observed in equity markets.

  • Curve Steepness

    Steeper curves mean the model is more reactive to shocks. A steep curve indicates volatility changes dramatically with return size; a flatter curve indicates more gradual response.

Understanding Model Statistics

The statistics panel shows three key metrics:

  • Persistence

    How quickly shocks decay. Values near 1 (e.g., 0.95) mean high persistence: a shock today still affects forecasts weeks later. Values below 0.9 indicate faster mean reversion.

  • Long-Run Volatility

    The model's estimate of where volatility settles in the long term. Compare current volatility to this level to assess whether conditions are stressed or calm.

  • Half-Life

    Number of days for a volatility shock to decay by 50%. A half-life of 14 days means a spike will be half as elevated two weeks later.

Reading the Sparkline

The sparkline in the statistics panel shows how volatility evolves after the selected shock:

  • Forecast Curve

    Shows the path of volatility from today through one year, starting at the post-shock level and gradually converging toward long-run volatility.

  • Long-Run Reference

    The dashed horizontal line marks the long-run volatility level. Watch how and when the forecast curve approaches this line.

  • Key Values

    Below the sparkline you will see Half-Life (days for shock to decay 50%) and 1y Convergence (percentage of the way back to long-run after one year).

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Different GARCH models produce different NIC shapes. Understanding these differences helps you choose the right model for your analysis.

Comparing Model Types

Each volatility model produces a characteristic NIC shape:

  • Standard GARCH

    Produces a symmetric U-shaped curve. The same shock magnitude produces the same volatility regardless of sign. Simple but may underestimate volatility during selloffs.

  • GJR-GARCH

    Produces an asymmetric curve tilted toward negative shocks. Captures the leverage effect through the gamma parameter. V-Lab's default model for most assets.

  • EGARCH

    Models log-volatility, producing a different curve shape. Always yields positive volatility forecasts and captures asymmetry through an additive term rather than an indicator function.

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Risk Management

Use the NIC to understand portfolio exposure to market shocks. See how much volatility increases after various downside scenarios to calibrate risk limits.

Scenario Analysis

Test 'what-if' scenarios by selecting specific shocks. What happens to volatility if the market drops 3%? Use the sparkline to see how long elevated volatility persists.

Model Selection

Compare NIC shapes across different models. If you expect asymmetric behavior but see a symmetric curve, consider switching to GJR-GARCH or EGARCH.

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The News Impact Curve is computed from the estimated GARCH model parameters for the selected asset.

How the Curve is Calculated

For each point on the curve, the tool computes next-day variance using the model's variance equation with the current variance (sigma squared) and a range of hypothetical returns. The square root converts variance to volatility (annualized).

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Common Questions
Why is my curve symmetric when I expected asymmetry?

You're likely using standard GARCH rather than GJR-GARCH or EGARCH. Standard GARCH doesn't capture the leverage effect. Switch to an asymmetric model in the model selector.

Why does the GJR-GARCH curve look nearly symmetric?

Some assets have small gamma coefficients, meaning limited asymmetry in practice. This can occur with assets that don't exhibit strong leverage effects, such as commodities or currencies.

What does it mean if persistence is above 0.99?

Very high persistence (>0.99) indicates shocks decay extremely slowly and volatility is nearly integrated. This is common for equity indices. It means short-term forecasts are most reliable while long-term forecasts quickly converge to long-run levels.

Technical Questions
Why does the sparkline converge to a different level than current volatility?

The sparkline shows how volatility evolves from current levels given the selected shock. It converges to the long-run volatility, which may be above or below current levels depending on whether volatility is currently stressed or calm.

How does the NIC work for liquidity (ILLIQ) models?

For liquidity models, the NIC shows how return shocks affect next-day illiquidity rather than volatility. The interpretation is similar: negative shocks typically increase illiquidity as trading becomes more costly during selloffs.

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Get the most out of the News Impact Curve tool with these recommendations.

Recommended Workflow
  • 1. Observe the Curve Shape

    Is it symmetric or tilted? This tells you whether the model captures the leverage effect.

  • 2. Test Relevant Scenarios

    Move the slider to shocks that matter for your analysis, perhaps a -3% decline matching recent market stress.

  • 3. Check Model Statistics

    Review persistence and long-run volatility to understand how shocks decay and where volatility settles.

  • 4. Use the Sparkline

    Watch how volatility evolves after your selected shock. How many days until it normalizes?

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