Expected risks and annualized rewards are the result of:

  • The assumed ergodic behavior of the statistical processes on Wall Street
  • Historical exchange data with the maximum draw down as expected intermediary risk   
  • No assumed probability distribution functions of rewards that may give misleading information about confidence intervals and risks
  • Automated sequential investment decisions validated over 20-plus years during preset holding periods
  • Automated selection of long positions with matched short positions
  • Automated portfolio allocations and timing by optimizing risk/reward ratios
  • The risk/reward ratio as an alternative to the Markowitz variance or the inverse of the Sharpe ratio

Ergodic behavior:

  • Implies the strong simplification that a time average can be replaced by an ensemble average at each moment of time
  • Lets regression being replaced by a search algorithm in combination with a time invariant ranking system for all ensembles
  • Allows for dynamic systems that are not weakly or strongly mixing
  • Requires no probability distribution functions 
  • Allows for algorithms that vary linearly rather than in a quadratic manner with portfolio sizes, so that overfitting and suboptimal behavior of regression are avoided
  • Makes these algorithms much more efficient, so that they become accessible to a consumer laptop
  • Allows for finding local optima
  • Allows for simple back testing these optima with the following benchmarks:
    • Cap-weighted S&P500
    • Price-weighted DJIA
    • Equally-weighted Monkey Index
    • Equally- and price-weighted portfolios calculated from self-configured game plans
    so that beta (relative risk) en alpha (relative annualized reward) can be calculated for different benchmarks with different asset allocations.

Experience teaches us that DigiFundManager is able to screen, rank, weight, and time time series of optimal portfolios from a watch list of preselected stocks producing expected annualized rewards of 5% - 40% and where certain preselections hold the promise of a balanced risk/reward ratio of 0.5 - 1.5. 

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