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How to Calculate Annualized Standard Deviation

A stock trader will generally have access to daily, weekly, monthly, or quarterly price data for a stock or a stock portfolio. Using this data he can calculate corresponding returns from the stock (daily, weekly, monthly, quarterly returns). He can use this data to calculate the standard deviation of the stock returns. The standard deviation

Volatility Risk in Bonds with Embedded Options

Bonds with embedded options such as call options and put options also have volatility risk. This happens because any factor that affects the value of the embedded option will also impact the value of the bond. We earlier learned that interest rates affect embedded options. When interest rates rise, the price of the embedded call

Video Lecture for GARCH

GARCH, Generallized AutoRegressive Conditional Heteroskedasticity, is one of the popular methods of estimating volatility in finance. GARCH estimates volatility similar to EWMA, however, it adds more information to the series related to mean reversion. Also some people use both EWMA and GARCH, EWMA has been widely superceded by GARCH. There are three main steps in

Calculate Historical Volatility Using EWMA

Volatility is the most commonly used measure of risk. Volatility in this sense can either be historical volatility (one observed from past data), or it could implied volatility (observed from market prices of financial instruments.) The historical volatility can be calculated in three ways, namely: Simple volatility, Exponentially Weighted Moving Average (EWMA) GARCH One of

How Interest Rates and Volatility Affect Option Prices?

Both interest rates and underlying stock’s volatility have an influence on the option prices. Impact of Interest Rates When interest rates increase, the call option prices increase while the put option prices decrease. Let’s look at the logic behind this. Let’s say you are interested in buying a stock which sells at $10 per share.

Using GARCH (1,1) Approach to Estimate Volatility

This video provides an introduction to the GARCH approach to estimating volatility, i.e., Generalized AutoRegressive Conditional Heteroskedasticity. GARCH is a preferred method for finance professionals as it provides a more real-life estimate while predicting parameters such as volatility, prices and returns. GARCH(1,1) estimates volatility in a similar way to EWMA (i.e., by conditioning on new

Volatility: Moving Average Approaches

Within stochastic volatility, moving average is the simplest approach. It simply calculates volatility as the unweighted standard deviation of a window of X trading days. This video demonstrates three “flavors:” population variance (volatility = SQRT[variance]), sample, and simple. This video is developed by David from Bionic Turtle.