An overview about how to define focus and stock market investment risk in high-net worth individual investing using using computer algorithms in 2017.

by Bret Rosenthal | @bretrosenthal

This is the age of the machines.

Computer algorithms dominate the investing landscape. Ninety (90) percent of all trades executed now are directed by computer algorithms. Developing an investment portfolio driven by fundamental analysis (the preferred and most successful way for decades) has never been more difficult.

The reason for such trouble can be described in one word: volatility. Computer algorithms are designed to take advantage of human emotion and execute at speeds far beyond human capability.

Can you fundamentally invest in a company with a 5-year time horizon and succeed? Of course.

But the volatility you must endure during that 5-year stretch has increased exponentially.

And the typical human brain can’t deal with the swings.

Computer Algorithms: Strategy Focus

Our goal is to employ our proprietary Index (S&P500 (SPY), NASD100 (QQQ) & Russell Small Cap (IWM)) and Group ETF algorithms, designed over the last 5-years and vigorously tested over the last 10-years, to aid the human brain by dramatically reducing volatility.

Our computer algorithms are individually calibrated to capture major moves higher in the markets while limiting exposure during major declines.

The computer algorithms’ core function: Assessing the optimal time for capital to be invested where the potential for immediate and sustainable profitability is greatest. This potential is otherwise known as “the best risk vs. reward scenario.”

Investing Risk

Whenever capital is deployed risk is taken. In a strategy where Stop Loss rules are followed one can safely say the risks are always going to be relatively equal.

The key then is to determine when reward possibilities are at their highest and expose capital only at those optimal times. This process will result in an equity curve that stair-steps higher at a 45-degree angle. This means our capital will be growing at a steady clip while dramatically reducing the drawdowns. This creates an experience much more suited to the human brain than the wild volatility of this algorithm driven world.

Algorithmic Investing Platform

Optimized algorithmic portfolio management remains our primary objective. The algorithm can be used in many different ways. We have four specific strategies (from most conservative to most aggressive) that we offer investors through our affiliation with Interactive Brokers:

  1. Compass Rose I: Long-only the S&P Index using the ETF SPY
  2. Compass Rose II: Long/Short the S&P Index using the ETFs SSO and SPY
  3. Compass Rose III: Multi-Asset Long/Short using the ETFs SPY, QQQ, IWM, SSO, QLD, UWM
  4. Compass Rose IV: Multi-Asset Long/Short (using the ETFs SPY, QQQ, IWM, SSO, QLD, UWM) including individual stocks

Over the last five years we have created an algorithmic platform and an investing process (we call it, Compass Rose). In 2017 we are deploying this investment strategy across all of our portfolios. The performance summary shows strong results for the back-tested period 2006 – 2016.

At its core the Compass Rose investing algorithm platform is a strategy to buy weakness and sell into strength.

We want to be market makers not market takers. 


NOTE: Algorithms are not guarantees of success. They are not magic but instead mathematical calculations based on statistics and probability.

As with any situation involving probabilities time is required for the edge to be revealed.

However, applied correctly, a quality algorithmic platform can effectively counteract the biggest hurdle to investment success: emotion. Algorithms make it possible to better handle the Fear/Greed response that so often derails solid investment decision-making.

The Rosenthal Capital Management blog explores how algorithmic trading strategies help individual investors get better returns.

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