5 posts tagged with "volatility"

In our previous blog, we emphasized the importance of implied volatility for option traders and demonstrated how to retrieve it—across any strike scale and expiry—using a flexible API that:

• Supports a range of expiry definitions (tenor-based, listed, or custom date/time).
• Offers multiple strike scales (strike, moneyness, log-moneyness, delta call/put, or FX-style).

Transitioning from implied volatility to actual pricing requires the same versatile API—offering possibility to calculate these with different premium conventions (especially in FX or digital assets). In this post, we explore how to streamline pricing by:

• Allowing configurable premium conventions (for example, paying the premium in a chosen currency), and
• Defining preset payoffs that let users retrieve implied volatility, pricing, and risk metrics for multiple structures (European vanilla, digitals, risk reversals, strangles, ...) in one request.

Today, our focus is on European vanilla options as a straightforward example. The same method applies to more complex payoffs, which we’ll cover in future blogs.

In this post, we discuss how implied volatility (IV) is compared across different strikes, maturities. We’ll show how moneyness, log-moneyness, and delta quoting conventions help you visualize and interpret the “volatility smile.” Finally, we’ll highlight how an adaptable API—like Qytrees—streamlines retrieving and analyzing these data points.

In this blog, we discuss the relationship between realized volatility (RV) and implied volatility (IV), focusing on BTC as a case study. The goal is to introduce a simple option trading strategy that takes advantage of potential mispricing between RV and IV. We'll then compare the performance of this strategy against an alternative approach that doesn't incorporate RV information, highlighting the value of using RV in volatility-based trading strategies.

Disclaimer:​

This analysis is for educational purposes only and is not financial advice. The strategies discussed, particularly those involving shorting options, carry significant risks, especially in volatile markets like cryptocurrencies. This blog does not cover the impact of margin, which can increase risk for traders.

Leverage trading is a popular strategy among traders seeking amplified returns, especially in the volatile crypto markets. However, with high rewards come significant risks. Liquidations are common in futures trading, often resulting in substantial losses. For instance, on August 5, 2024, a significant market decline led to the liquidation of nearly 300,000 crypto traders from their leveraged positions or collateral trades, according to data from Coinglass. Reference

Disclaimer:​

This article is purely instructional and is not financial advice. Long options trading comes with strategic advantages and risks, including the potential loss of the entire premium paid. While long options avoid the liquidation risks associated with futures, if the option expires out of the money, the premium is lost. Additionally, shorting options carries significant risks and is not discussed in this article.

Realized volatility is a statistical measure that quantifies the degree of variation in the price of a financial asset over a specific period. This metric provides insights into the past behavior of asset prices and can be valuable for derivative traders.

This chart shows Bitcoin's (BTC) realized volatility over the past year. The x-axis represents time, while the y-axis shows the annualized realized volatility percentage. Higher realized volatility zones indicate periods of increased market activity and price changes.

What is Realized Volatility?​

Realized volatility is calculated based on historical price data and is mathematically defined as the standard deviation of past returns. It measures the historical price fluctuations of an asset, providing an indication of its actual volatility. Typically expressed as an annualized percentage, realized volatility offers a standardized method for comparing the volatility of different assets over various time periods.

There are multiple methods to calculate realized volatility. These parameters can be chosen by the user to adjust according to their needs.