SPDR S&P 500 ETF Trust x Component CorrelationsSPY
Historical price and seasonality data
Seasonality
This multi-factor forecast for Paypal Holdings (PYPL) is based on a weighted average of five factor-dervied forecasts.
Backtest PYPL
Correlation Interval
|
Value
|
Multi-Factor
|
5.7
|
Volatility
|
6.1
|
Momentum
|
4.8
|
Value
|
6.5
|
Quality
|
5.8
|
Size
|
5.4
|
Correlation Interval
|
Last Value
|
Previous Month
|
Previous Year
|
20-day
|
.83787
|
.83787
|
.83787
|
40-day
|
.83787
|
.83787
|
.83787
|
60-day
|
.83787
|
.83787
|
.83787
|
80-day
|
.83787
|
.83787
|
.83787
|
100-day
|
.83787
|
.83787
|
.83787
|
120-day
|
.83787
|
.83787
|
.83787
|
140-day
|
.83787
|
.83787
|
.83787
|
160-day
|
.83787
|
.83787
|
.83787
|
180-day
|
.83787
|
.83787
|
.83787
|
Apple, Inc. engages in the design, manufacture, and sale of smartphones, personal computers, tablets, wearables and accessories, and other variety of related services. It operates through the following geographical segments: Americas, Europe, Greater China, Japan, and Rest of Asia Pacific. The Americas segment includes North and South America. The Europe segment consists of European countries, as well as India, the Middle East, and Africa. The Greater China segment comprises of China, Hong Kong, and Taiwan. The Rest of Asia Pacific segment includes Australia and Asian countries. Its products and services include iPhone, Mac, iPad, AirPods, Apple TV, Apple Watch, Beats products, Apple Care, iCloud, digital content stores, streaming, and licensing services.
What does this SPY heat map mean?
Apple Inc has tended to perform the worst during the month of October, during which the stock has historically returned an average of 5.35%.
Why do correlations matter?
Apple Inc has tended to perform the worst during the month of June, during which the stock has historically returned an average of -11.23%.
What components are included in the calculation?
Historically, the timeframe spanning between November 6 and ending February 5 has represented the most favorable three-month holding period for the stock of Apple Inc. The average return during this period as totaled 8.67% over the last 40 years.
The
Pearson correlation coefficient is a measure of linear correlation between two sets of data. It is used to determine the strength and direction of a relationship between two variables.
In the example of this
heat map analysis of SPY, the coefficient is measuring the strength of the relationship between average changes in the value of index components over distinct time periods.
A coefficient value of -1 represents a maximally inverse relationship between the variables, whereas a value of 1 represents a maximally positive relationship. A value of 0 indicates no relationship between the variables.
For example, a 20-day average correlation value of 1 would indicate that the index components have been moving together in concert over the past 20 days. A value of -1 would indicate the components have been moving in opposite directions.
The Pearson correlation coefficient is a measure of linear correlation between two variables, and does not take into account other types of relationships or correlations. As a result, it should only be used when there is a linear relationship between the variables.