Speculative Volatility Index: Separating Sentiment from Fundamentals

A volatility index is a measure of expected future volatility derived from market data. For example, the VIX reflects expected volatility in the S&P 500 based on option prices. Reference [1] constructed a novel volatility index, called the Speculative Volatility Index (SVI). It was motivated by the idea that the equity risk premium contains speculative and non-speculative components: the speculative premium being closely linked to market sentiment, while the non-speculative premium reflects fundamental risk exposure.

The author used 24 return series representing key segments of the Japanese equity market and applied principal component analysis (PCA) to construct the SVI. The first principal component (PC1) captures the dominant variation in speculative signals and serves as a proxy for speculative intensity in the market. The second component (PC2) represents asymmetric or directional variations in speculative behavior. The SVI was then utilized to develop long/short trading strategies, producing superior risk-adjusted returns.

The authors pointed out,

This study contributes to the expanding body of empirical asset pricing literature by presenting new evidence on the predictive power of PCA-based speculative volatility index (SVI) derived from a broad array of derivatives-based sentiment and speculative-based indices returns. Our findings indicate that speculative factors, when distilled through low-dimensional latent factors, exhibit substantial predictive power for in-sample and out-of-sample contexts.

The first principal component of the SVI emerges as a consistent and statistically significant predictor of future returns across nearly all specifications… The second principal component demonstrates more selective predictive power. Its influence is strongest in innovation-intensive and growth-oriented segments of the market…

The out-of-sample forecasting performance of the SVI-based model is particularly noteworthy. Across a broad range of market and sector indices, our model consistently outperforms naive historical mean benchmarks in terms of both root mean squared error (RMSE) and out-of-sample 𝑅².

In short, the paper proposed a novel Speculative Volatility Index and demonstrated its effectiveness through the performance of an SVI-based long/short strategy.

This approach is noteworthy because it separates sentiment-driven effects from fundamental components embedded in the risk premium. It also offers a framework for building volatility indices in markets where sentiment plays a dominant role, such as the cryptocurrency market.

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References

[1] Abdalaziz Saed, Speculative Volatility and Return Predictability: Evidence from the Japanese Equity Market,  Journal of Management Science Research Review, Volume 4 Issue 3, 2025

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