Unknown Indicator
equity instruments polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for price as well as the accuracy indicators are determined from the period prices.
A single variable polynomial regression model attempts to put a curve through the equity instruments historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm
Other Indicators
All Technical Analysis
Investing Ideas
You can quickly originate your optimal portfoio using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your investment opportunity, you can then find an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility.Thematic Opportunities
Explore Investment Opportunities
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Money Managers module to screen money managers from public funds and ETFs managed around the world.
Other Complementary Tools
Companies Directory Evaluate performance of over 100,000 Stocks, Funds, and ETFs against different fundamentals | |
USA ETFs Find actively traded Exchange Traded Funds (ETF) in USA | |
Aroon Oscillator Analyze current equity momentum using Aroon Oscillator and other momentum ratios | |
Portfolio File Import Quickly import all of your third-party portfolios from your local drive in csv format | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm |