How Portfolio Armor Works!

In a fairly to overvalued market do you want to get the best hedging cost numbers and reduce risk at the same time? Look no further.

We’ve partnered with Portfolio Armor, to enable investors to generate competitive returns while strictly limiting risk, via concentrated, hedged portfolios.

Portfolio Armor: How It Works

  1. Each trading day, Portfolio Armor runs 2 tests to weed out bad investments on each of the 4,000+ stocks and exchange traded products with options traded on them in the U.S.
  2. Next, it estimates potential returns over the next 6 months for each of the securities that pass both tests, using an analysis of historical returns as well as option market sentiment. Essentially, it starts with the assumption that security returns will begin to revert to their historic means. Then it tests that assumption against option market sentiment for each security.
  3. Then, it finds the optimal hedge for each security in its ranking, and calculates its hedging cost.
  4. It then subtracts hedging cost from each security’s potential return, and ranks each name by potential return, net of hedging cost.
  5. Finally, Portfolio Armor fine-tunes portfolio construction to minimize cash levels and minimize hedging cost while maximizing potential return.

Hedging Cost: Making Sure It Works

Portfolio Armor conducted 25,412 comparisons of its calculated potential returns to actual returns over an 11-year time period, determining that its security selection method generated alpha. It then tested the hedged portfolio method from 1/2/2003 to 4/30/2014, a time period which included two bull markets as well as one of the worst bear markets in generations, the one resulting from the global financial crisis of 2008-2009. It found that, at certain thresholds, such as 21% (i.e., for investors willing to risk declines of no more than 21% over each six month period), its method generated better returns, net of trading and hedging costs, than the leading S&P 500 index tracking ETF over the time period, with smaller drawdowns.

Want to learn more? Check it out here