ETRACS Monthly Pay 2xLeveraged Preferred Stock ETN
What is PFFL?
The ETRACS Monthly Pay 2xLeveraged Preferred Stock ETN (NYSE: PFFL) is an exchange-traded note linked to the performance of the Solactive Preferred Stock ETF Index, less investor fees. The Solactive Preferred Stock ETF Index, is intended to track the price movements of an equally weighted portfolio containing two U.S. preferred stock ETFs. Each of the ETFs seeks to track the performance of separate indices, which measure the performance of a select group of preferred stock securities.
ETFs related toPFFL
ETFs correlated to PFFL include PGX, PSK, PFF
What is ETF correlation?
Correlation is a measure of the strength of the relationship between two ETFs. It quantifies the degree to which prices of the two ETFs typically move together.
Here, correlation is measured over the past year with the Pearson correlation coefficient (Pearon’s r), which ranges from -1 to 1.
Using ETF correlations in portfolio and strategy construction
ETF correlations can help you create investing strategies and portfolios. Use them to:
- •Build a diversified portfolio from uncorrelated or inversely correlated ETFs with the aim of minimizing portfolio risk.
- •Compare correlated or related ETFs to find one with a lower expense ratio or higher trading volume.
- •Create an investing strategy that hedges an ETF with an uncorrelated or inversely correlated ETF.
We show information directly obtained from our data provider, Xignite. Data shown here is provided by Xignite, an unaffiliated third party. Composer believes the information shown here is reliable, but has not been verified and there is no guarantee that the information is accurate.
We show information based on calculations performed by Composer using data from our provider. Information provided here is based on calculations performed by Composer using data sourced from Xignite, an unaffiliated third party. Composer believes this information is reliable, but has not verified the data and there is no guarantee that the calculations are accurate.