The most comprehensive educational resources for finance

## Understanding Hypothesis Testing and p-value

Behavioral scientists, market researchers, astrophysicists, drug testers all seek to better understand the target group. Often it is next to impossible to assess the entire population. Inferential statistical testing is instead done on a sample that exhibits most if not all characteristics of the population. This is done using hypotheses testing. Hypothesis (plural form being

## Properties of Uniform Distribution

Definition The most basic form of continuous probability distribution function is called the uniform distribution. It is a rectangular distribution with constant probability and implies the fact that each range of values that has the same length on the distributions support has equal probability of occurrence.  This belongs to the category of maximum entropy probability

## Calculate and Interpret Covariance and Correlations

Covariance defined In probability theory and statistics, covariance measures the comovement between two variables i.e. the amount by which the two random variables show movement or change together. If the two variables are dependent then the covariance can be measured using the following formula: For two independent variables the joint densities are separated and the

## FAQs on Quantitative Finance

Getting agreement between finance theory and finance practice is important like never before. In the last decade the derivatives business has grown to a staggering size, such that the outstanding notional of all contracts is now many multiples of the underlying world economy. No longer are derivatives for helping people control and manage their financial

## Hot Jobs: Five Careers in Quantitative Analysis

Quantitative analysis is the process of analyzing financial data with the goal being to form risk models and financial strategies based on mathematical formulas. These types of jobs require a high degree of skill and strong mathematical skills. For some positions, you will need a PhD in economics or finance. However, even though these positions

## Arithmetic Vs. Geometric Stock Returns

This video provides clarity about the confusion over the stock returns. The expected return of a stock is ambiguous because, if we assume returns are normal, then price levels are lognormal. In which case, the mean does not equal the median future stock price. Consider these two questions: 1. What is the average return per

## How to Scale Autocorrelated Returns?

We know that the square root rule can be used to scale volatility with time. This rule assumes that the returns are independent and identically distributed. However, this assumption is not very realistic. This video illustrates a scaling factor that adjusts the square root rule for for autocorrelation. This video is developed by David from

## Why Use Lognormal Returns in Finance (Stock Prices)?

The logarithm of a number is the exponent by which another fixed value, the base, has to be raised to produce that number. For example, the logarithm of 100 to base 10 is 2, because 100 is 10 to the power 2: 1000 = 10 × 10  = 103. More generally, if x = by, then y

## What is the Square Root Rule?

Volatility and VaR can be scaled using the square root of time rule. According to this rule, if the fluctuations in a stochastic process are independent of each other, then the volatility will increase by square root of time. It provides exact volatilities if the volatilities are based on lognormal returns. In case of simple

## What is Volatility?

The simple answer is the standard deviation of periodic returns. This video takes some sample data for closing prices of a stock and demonstrates how volatility is calculated in Excel. In finance, such as for price series, usually log returns are used, where log is the natural logarithm.