iPath US Financial Indicators Patterns

STPP -- USA Etf  

USD 29.90  0.20  0.66%

Use fundamental data analysis to validate all available financial indicators of iPath US Treasury to find out if markets are presently mispricing the organization. We found seven available indicators for iPath US Treasury which can be compared to its rivals. Please utilize iPath US Treasury One Year Return to make a decision on weather iPath US Treasury Steepener ETN is priced some-what accurately. Use iPath US to protect against small markets fluctuations. The etf experiences moderate downward daily trend and can be a good diversifier. Check odds of iPath US to be traded at $29.3 in 30 days

iPath US Company Summary

iPath US competes with ProShares Inflation, Verizon Communications, Merck, HP, and CISCO SYS. iPath US Treasury Steepener ETN is USA based ETF administrated by null. The ETF is issued and managed by Barclays Capital, and composed of 0 constituents. The fund currently manages 4 M in total asset with null percent management fee and under null percent of total fund expense. USA Stock Exchange invests mostly in Developed Markets around North America and is publically traded since August 9, 2010.

iPath US Five Year Return vs Three Year Return

iPath US Treasury Steepener ETN is presently regarded as number one ETF in five year return as compared to similar ETFs. It is presently regarded as number one ETF in three year return as compared to similar ETFs .

iPath US Market Fundamentals

 Quote29.90
 Change(%) 0.66%
 Change0.20 
 Open30.1
 Low29.73
 High30.2525
 Volume3550.000
 ExchangeNGM

Distress Rating

iPath US Financial Distress Probability
52% 
Chance of Financial Distress
iPath US Treasury Steepener ETN has more than 52 (%) percent chance of experiencing financial distress in the next 2 years of operations. More Info

Compare iPath US

Compare iPath US To Peers

July 18, 2018 Opportunity Range

Also please take a look at World Market Map. Please also try Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.