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Multi-Source Information Fusion for Market Volatility: An Interpretable Statistical and Machine Learning Framework for the VIX Index

Version 1.0

Fiszeder, Piotr; Pietrzyk, Radosław, 2026, "Multi-Source Information Fusion for Market Volatility: An Interpretable Statistical and Machine Learning Framework for the VIX Index", https://doi.org/10.18150/LF0FUW, RepOD, V1

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Description

The data start on February 3, 2015, and end on March 31, 2025.

It includes VIX daily, VIX weekly, VIX monthly and exogenous variables which are categorized grouped into twelve categories: 

(1) S&P 500 specific factors: Trading volume, Market capitalization, SVI for “VIX”, SVI for “S&P 500”, CBOE SKEW Index; 

(2) technical analysis indicators for the S&P 500: MACD(12,26), RSI(14), EMA(9), OBV, ATR(14), ROC(10);

(3) global stock indices: S&P 500, DJIA, Nasdaq 100, Russell 2000, Euro STOXX 50, FTSE 100, Nikkei 225, Hang Seng, Shanghai SE Comp., MSCI World Index;

(4) major stocks: Apple, Microsoft, NVIDIA, Alphabet, Amazon;

(5) fiat currencies and Bitcoin: EUR/USD, USD/JPY, GBP/USD, USD/AUD, USD/CHF,

USD/CAD, USD/CNY, US Dollar Index, BTC/USD;

(6) US government bonds: 1-month T-bill rate, 3-month T-bill rate, 6-month T-bill rate, 1-year bond yield, 2-year bond yield, 10-year bond yield, 30-year bond yield; 

(7) interest rate spreads and yields: Term spread US10Y-US3M, US10Y minus effective FFR, 10Y breakeven inflation, Moody's Aaa corporate bond minus FFR, Moody's Baa corporate bond minus FFR; 

(8) commodities: WTI crude oil, Henry Hub natural gas, Gold spot, Silver, Copper, Bloomberg Commodity Index, CRB Index;

(9) implied volatility indices: DJIA VI, Nasdaq 100 VI, Russell 2000 VI, 

EURO STOXX 50 VI, CBOE Crude Oil ETF VI, CBOE Gold ETF VI;

(10) realized variances and variance risk premiums: RV S&P 500, RV DJIA,

RV Nasdaq 100, RV Russell 2000, VRP DJIA, VRP Nasdaq 100, VRP Russell 2000;

(11) US macroeconomic variables: Effective FFR, M2 money supply, US initial jobless claims, Business Conditions Index;

(12) policy and market uncertainty indices: Economic Policy Uncertainty Index, 

Geopolitical Risk Index, Risk Aversion Index, Uncertainty Index, St. Louis Fed Financial Stress Index, Chicago Fed's National Financial Conditions Index, AII Sentiment Survey.


The data comes from various sources, which are detailed in the paper in Table 2. 

For the variables in the first and third groups, we apply logarithms and first differences of logarithms. For the financial series in the second group, two measures are calculated: logarithmic returns and the Parkinson estimator of variance. We use the following symbols to denote these transformations: ln, s_ln, delta, r, and v for logarithm, signed logarithm, first difference of logarithms, logarithmic return, and variance, respectively. 

Subject
Social Sciences
Keyword

Volatility forecasting, Implied volatility, Realized volatility, Economic indicators, Explainable AI, Foundation models, Deep learning

Related Publication

Dudek, G., Pietrzyk, R., Pełka, P., Kasprzyk, M., Fiszeder, P., 2026. Multi-Source Information Fusion for Market Volatility: An Interpretable Statistical and Machine Learning Framework for the VIX Index :

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Readme.txt
Plain Text - 3.0 KB - Apr 27, 2026 - 0 Downloads
MD5: 2ee67ebdae33865d20af0d1e0b786625
License: CC0 Creative Commons Zero 1.0
Description of data
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VIX_repository_data.tab
Tabular Data - Original format: MS Excel (XLSX) - 7.7 MB - Apr 27, 2026 - 0 Downloads
License: CC BY - Creative Commons Attribution 4.0
160 Variables, 2555 Observations - UNF:6:x5vIDekO/0f711y3/bg1Zw==
Financial data
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