# An instantaneous market volatility estimation

## TL;DR

This paper introduces an invariant linking market volatility with trading volume, spread, and order book volume, providing a new method for instantaneous volatility estimation that outperforms traditional models like GARCH(1,1).

## Contribution

The paper discovers a new market invariant and develops an instantaneous volatility estimator based on it, validated across various markets and asset classes.

## Key findings

- Invariant holds across different markets and assets.
- Instantaneous volatility outperforms GARCH(1,1) in reproducing realized volatility.
- Method suitable for short-term volatility prediction and trading applications.

## Abstract

Working on different aspects of algorithmic trading we empirically discovered a new market invariant. It links together the volatility of the instrument with its traded volume, the average spread and the volume in the order book. The invariant has been tested on different markets and different asset classes. In all cases we did not find significant violation of the invariant. The formula for the invariant was used for the volatility estimation, which we called the instantaneous volatility. Quantitative comparison showed that it reproduces realised volatility better than one-day-ahead GARCH(1,1) prediction. Because of the short-term prediction nature, the instantaneous volatility could be used by algo developers, volatility traders and other market professionals.