Hidehiko Tajima - Corporate Insider

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 Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.

Other Complementary Tools

USA ETFs
Find actively traded Exchange Traded Funds (ETF) in USA
Stock Tickers
Use high-impact, comprehensive, and customizable stock tickers that can be easily integrated to any websites
AI Investment Finder
Use AI to screen and filter profitable investment opportunities
Idea Analyzer
Analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas
Portfolio Holdings
Check your current holdings and cash postion to detemine if your portfolio needs rebalancing
ETFs
Find actively traded Exchange Traded Funds (ETF) from around the world
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm