Predicting Market Volatility: Tools, Techniques and Software

Market Volatility Analytical Platform
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Predicting Market Volatility: Tools, Techniques and Software

What is Market Volatility?

An essential component of risk management and portfolio construction is forecasting market volatility. In order to make wise investment decisions, it aids investors in understanding potential price fluctuations. Market volatility is about the ups and downs in the price of assets like stocks. If there’s high volatility, it means prices are moving up and down a lot. If there’s low volatility, prices are more stable.

Why is Predicting Market Volatility Important?

Predicting market volatility is important for two main reasons. First, it helps with risk management. This means figuring out what risks you might face and deciding what to do about them. Second, it’s useful when you’re putting together a collection of investments, also known as a portfolio.

How Do We Measure it?

There are a few different ways to measure market volatility:

  1. Historical Volatility: This method looks at how much asset prices have moved in the past. The idea is that what happened in the past can give us clues about what might happen in the future. For instance, Markowitz’s Modern Portfolio Theory is built on this assumption.
  2. Implied Volatility: This is a prediction of future volatility that’s calculated from the price of an option. An option is a contract that gives you the right to buy or sell an asset at a certain price.
  3. Volatility Index (VIX): This is a measure of expected future volatility. It’s often called the ‘fear gauge’ because it can show how worried investors are about the future.

What Tools Can We Use to Predict Market Volatility?

There are several tools we can use to predict market volatility:

  1. GARCH Models: These models use information about past changes in prices to predict future volatility.
  2. Machine Learning Techniques: These are computer programs that learn from data. They can be used to predict market volatility. On purpose, let’s see the performance of the most undervalued and overvalued stocks from our Configurator of Investment Strategies.


Market volatility can be better understood by using tools like Historical Volatility, Implied Volatility, the Volatility Index (VIX), GARCH models, and machine learning techniques.

While none of these tools can predict future volatility with absolute certainty, they offer guidance. Historical Volatility and the VIX give us a glimpse into the past and present, while Implied Volatility and GARCH models help us look into the future. Machine learning techniques offer a new frontier in volatility prediction, harnessing the power of data and computational algorithms. Understanding and predicting market volatility are key skills for anyone involved in investing or trading.

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