Unknown Indicator

Generate Optimal Portfolios

The classical approach to portfolio optimization is known as Modern Portfolio Theory (MPT). It involves categorizing the investment universe based on risk (standard deviation) and return, and then choosing the mix of investments that achieves the desired risk-versus-return tradeoff. Portfolio optimization can also be thought of as a risk-management strategy as every type of equity has a distinct return and risk characteristics as well as different systemic risks, which describes how they respond to the market at large. Macroaxis enables investors to optimize portfolios that have a mix of equities (such as stocks, funds, or ETFs) and cryptocurrencies (such as Bitcoin, Ethereum or Monero)
Fix your portfolio
By capturing your risk tolerance and investment horizon Macroaxis technology of instant portfolio optimization will compute exactly how much risk is acceptable for your desired return expectations
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.

Other Complementary Tools

Sign In To Macroaxis
Sign in to explore Macroaxis' wealth optimization platform and fintech modules
My Watchlist Analysis
Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like
Idea Optimizer
Use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio
Stock Screener
Find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook.
Portfolio Suggestion
Get suggestions outside of your existing asset allocation including your own model portfolios
Equity Valuation
Check real value of public entities based on technical and fundamental data