In Part 2 I showed a weakness of one of the most frequently recommended passive investment allocation strategies, simply between stocks and bonds. I showed one potential remedy to the problem, but there are additional components to consider.
In this note, I focus on one of the most important steps to investment management improvement, which, should not be left out in investment advice. Money management systems can make a huge difference to portfolio returns.
The Tradestops software, outlined below, is just one money management system that could be considered. It is important to appreciate that any approach has benefits and disadvantage, no system comes with any guarantees, and it is impossible for any system to cover all possible future outcomes. So no matter how much research has been conducted risks will always remain, as well as benefits and disadvantages.
The head of research at Tradestops is a PHD in mathematical systems and has been working on money management systems for portfolios more than a decade. As a money management system it makes no comment on the timing or selection of security purchases or sales.
The sole focus is to discover whether an investor, or analyst could improve his long term returns simply by using different money management rules for the very same trades or recommendations that are made over any given time period.
I have introduced Tradestops because I believe that overall these rules are beneficial when applied in the right way. I will introduce the rules shown below and then discuss the potential benefits and disadvantages.
The rules are as follows:
1. The first rule is to estimate an effective sell discipline for any purchase or recommendation. Tradestops testing suggests that the optimal approach within a portfolio is to calculate an adaptive trailing stop calculated for each security. This trailing stop is linked to the volatility of the security, and adapts because over time the long term volatility changes.
2. The second rule is to calculate the weighting for each purchase so that every position in the portfolio carries a very similar risk. Higher volatility securities therefore have a smaller sized position. In this way, the gain or loss from any position should be similar regardless of the likely volatility of that security. Tradestops calculates an adaptive “Volatility Quotient” (VQ) for each stock, to use in the calculation of position size. No security can be bought unless it is in a confirmed uptrend, which is based on the recent high exceeding the prior daily low by more than the VQ.
3. Lastly, once a stock has been sold according to the rules above, what is an effective re-entry rule for that security? Tradestops, uses a buy signal that is around half the distance from the recent high to the current trailing stop.
The difference that each of these rules made in the one specific circumstance is shown below in the difference between the performance lines in the chart.
Advantages and Disadvantages:
The first major point that should be made is that the tradestops software approach should only be applied as a portfolio approach to risk management, and focused on portfolios with at least 20 positions. For portfolios of smaller sizes and certainly for individual securities it is unlikely to be optimal. Tradestops is also focused on long term results with consistent application of the trading rules. It should not be regarded as a short term trading system for less than a year’s duration, and the rules need to be applied consistently.
The benefit of the system is that it is a universal system and so can be applied to any portfolio approach, but there are still many questions about what portfolio selections can be made. On the one hand it can be applied to many different approaches, but choice of securities included is left wide open so it lacks some definition, which the investor needs to consider carefully.
That being said I believe that the results over increasingly longer periods suggest significant advantages from its application. The chart below and video, describe simulations of investment strategies that seek to improve upon traditional investment management.
The 5 charts shown below, from the bottom up, are:
1. The S&P 500.
2. A successful Newsletter writer’s results.
Then the following adjustments are made to the newsletter writer’s results.
3. The blue line introduces a trailing stop.
4. The green line adds in the equal risk position sizing.
5. The purple line introduces, in addition, the re-entry rule.
Past returns are no guarantee of future returns, and all these back tests are provided for educational and illustrative purposes only, because I believe this illustrates a very useful approach. Any investor should do their own further research and seek advice before implementing any similar approach. No method, software, or advisory services guarantee any return or could ever be regarded as risk free or in any way perfect as a risk management system. No returns should ever be guaranteed, and all methodologies carry risks as well as benefits. The information and charts are provided to illustrate how they can help construction of portfolios, and be a useful guide for decision making and for testing methodologies and illustrating how portfolio construction could change the dynamic of risk management. Analysis provided by any investment services, whether Tradestops or Stansberry Research has it’s limitations and may result in the loss of capital.
The purpose of providing the information contained in this note is as an illustration only to help investors understand some aspects of the investment process. The statistics mentioned are accurate to my best knowledge but only a snapshot at the time of writing and should also be regarded as illustrative only.
How does a money management system like this alter RVAR, the metric for excellent Investment Management discussed in Part 1? In the following ways:
1. Each step taken in the direction of additional Money Management techniques above shows how simulated returns can improve, even as volatility declines, consequently, RVAR can improve.
2. The trailing stops can lower risk.
3. Equal risk per position, weights any portfolio to lower risk assets. The chart above suggests that despite the lower portfolio risk this creates, it actually increases returns! This can significantly improve RVAR.
4. Tight stops on re-entry can lower risk and so increase RVAR.
Overall, there is the possibility of improvement in RVAR just by implementing these Tradestops money management techniques or similar ones.
Additional conclusion also follow from the above, building on the conclusions from Part 2.
1. In both Part 2 and Part 3, not only has it been shown how returns can improve, but also volatility can potentially be reduced at the same time! Together, therefore, there is an improvement in RVAR, by using both of these techniques together.
2. Importantly, these findings contradict the widespread belief that higher long term returns only come from taking higher risk. What is shown here is that by focusing on RVAR, long term returns can improve even as the volatility of those returns declines.
3. Investors who chase returns and in addition embrace a higher risk level in service to the hope of higher long returns may well be using two very bad equations for their long term investment returns!
4. In Part 1 I showed the increased risk of large losses in the long term by chasing returns. This is remedied by switching to the metric of RVAR
5. In Part 2 and Part 3, I have shown that long term returns can be improved by using strategies that carry less risk than traditional strategies. RVAR can steer the investor not only to the increased likelihood of higher long term returns, but also to increasing the likelihood of receiving those higher returns with lower risk.