---
title: VIX Forecasting
url: https://www.ml-quant.com/papers/ssrn/5106657/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5106657
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5106657
featured: 2025-02-05
citations: unknown
topic: Derivatives & Volatility
---


# VIX Forecasting

An ARIMA-GARCH model is developed to forecast changes in the VIX, achieving a direction prediction accuracy of 56.01% but struggles to replicate extreme VIX spikes.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5106657
- Identifier: SSRN 5106657
- Released: 2025-01-22
- First featured: Quant Letter No. 84 (2025-02-05): https://www.ml-quant.com/issues/2025-02-05/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Derivatives & Volatility

## Related

- [SP 500 Volatility Forecasting](https://www.ml-quant.com/papers/ssrn/4903194/): The research investigates four techniques to enhance the precision of volatility forecasts for the SP 500, including the GARCH model, an LSTM network, a hybrid LSTM-GARCH model, and an advanced hybrid model incorporating the VIX index.
- [VIX options in the SABR model](https://www.ml-quant.com/papers/arxiv/2501.06398/): The pricing of VIX options in the SABR model is examined, revealing infinite VIX futures and call prices, and suggesting a capped volatility process as a solution.
- [Option Pricing with Time-Varying Volatility Risk Aversion](https://www.ml-quant.com/papers/arxiv/2204.06943/): The paper presents a pricing kernel with fluctuating volatility risk aversion to account for changes in the pricing kernel's shape, showing reduced pricing errors in an empirical application to the S&P 500 index, the CBOE VIX, and option prices.
- [Short-Time Behavior of the At-the-Money Implied Volatility for the Jump-Diffusion Stochastic Volatility Bachelier Model](https://www.ml-quant.com/papers/arxiv/2503.22282/): The research uses advanced calculus techniques to analyze short-time behavior of stock price volatility, supported by numerical examples.
- [Deep Hedging with Options Using the Implied Volatility Surface](https://www.ml-quant.com/papers/arxiv/2504.06208/): A new deep hedging framework for index option portfolios, which includes surface-informed decisions and transaction costs, has been proposed and outperforms traditional methods in both simulated and historical data from 1996 to 2020.
- [Unified GARCH-Recurrent Neural Network in Financial Volatility Forecasting](https://www.ml-quant.com/papers/arxiv/2504.09380/): The paper proposes a new GARCH-GRU model for financial volatility forecasting, showing better computational efficiency and forecasting accuracy than other models.