Tieshen Chen - 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 Sync Your Broker module to sync your existing holdings, watchlists, positions or portfolios from thousands of online brokerage services, banks, investment account aggregators and robo-advisors..

Other Complementary Tools

Fundamental Analysis
View fundamental data based on most recent published financial statements
Bonds Directory
Find actively traded corporate debentures issued by US companies
Insider Screener
Find insiders across different sectors to evaluate their impact on performance
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm
AI Portfolio Architect
Use AI to generate optimal portfolios and find profitable investment opportunities
Equity Valuation
Check real value of public entities based on technical and fundamental data