This article focuses on the calculation of annual volatility of stock returns and related knowledge.

The annual volatility of stock returns refers to the magnitude of change in stock prices over a year. It is an important indicator of stock price volatility and an important reference for investors in risk assessment and asset allocation.

The concept of annual stock return volatility was proposed by American scholar Louis Bachelier in 1900. With the development of statistics and finance, more and more people began to pay attention to the volatility of stock returns, and the annual volatility of stock returns has gradually become an important indicator in the financial market.

Features and Characteristics

There are various methods for calculating the annual volatility of stock returns, and the common ones are the historical volatility method, the implied volatility method and the volatility forecasting model. Among them, the historical volatility method is a commonly used method, which estimates future volatility by calculating the standard deviation of stock returns over a past period of time. The level of annual volatility of stock returns can reflect the degree of risk in stock prices, and in general, the higher the volatility, the greater the risk of the stock.

The annualized volatility of stock returns is widely used in financial markets for risk management, asset allocation and investment decisions. For example, investors can choose an investment portfolio that suits their risk appetite based on the size of the annual volatility of stock returns.

Currently, research on annual stock return volatility focuses on volatility prediction models and risk management. With the development of artificial intelligence and big data technology, more and more researchers have begun to use methods such as machine learning and deep learning to predict the annual volatility of stock returns.

Outlook and Development

In the future, as the financial market continues to change and develop, the calculation methods and application areas of annual stock return volatility will continue to expand and improve. At the same time, how to better predict the annual volatility of stock returns and reduce investment risk will also become an important direction for future research.