Everything in financial services is evolving. Innovation in new tools and tech-driven approaches are challenging conventional thinking in asset management and offering new resources to traditional investment methodologies and processes. Especially as active managers as a group keep getting broad-brushed with a poor relative performance stigma, these established tech trends can potentially arm them with new battle plans to more consistently beat their benchmarks.
One area that seems to be increasingly making itself known is a new generation of sophisticated tools and models to analyze price trends. Adding well tested, intelligent trend analytics into the investment decision process has been proposed as a complement to asset managers traditional research and fundamentally driven strategies. By adding another layer of intelligence and a dynamic market perspective, advanced analytics can enhance the investment process offering the potential for generating more alpha and risk management protections. Since such tools and innovative approaches tend to go where fundamentals do not tread, they may be able to capture important market dynamics around fundamentally sound investments. Importantly, this may reveal a strong rip current lurking dangerously underneath seemingly calm waters providing investment managers with the means to be able to look at the forest for context, not just at the tall strong trees.
That is why we went to new Institute member Rocco Pelligrinelli, CEO of Trendrating – a Swiss company providing advanced analytic solutions for active investment managers. We invited him to share his first-hand industry knowledge of these tools and his firm’s experience in enabling trend-capture in a simple, systematic and transparent way to add value consistently over time. This area may well be creating a new frontier for active management.
Hortz: You oppose what you call “simplistic rationales” used by many to argue against active managers relative performance in the active-passive debate. What do you think are the deeper issues and reasons to explore?
Pellegrinelli: The facts point to a consistent underperformance of mutual funds versus benchmarks as discussed in this article on a recent SPIVA (S&P Indices Versus Active) Scorecard report and the poor returns of value investing as highlighted in this article on a recent study by Fama and French, “Is Value Investing Dead”. However, the latter study also points out that the research data makes it hard to elicit clear conclusions on value investing because the data is so noisy and been too volatile month by month.
This leads us to the realization that stock price action today is impacted by stronger forces that have emerged: faster deployment of “big” money, more institutional money being allocated to equities (as bond yields are at historic lows), the impact of social media sentiment and the 24×7 global news cycle. Markets have been steadily becoming more complex.
If all these developments weakened the correlation between old-school fundamentals and price trends, then what counts is getting the trend right, irrespective of the reasons behind why it’s happening, which typically is discovered after the price move. It is interesting to see that in the competitive hedge fund industry the winners are the players using systematic models to capture trends and the discretionary traders are way behind in terms of performance.
For any large universe of securities, performance dispersion exists and it’s huge. Yet many fund managers don’t have the necessary tools and analytics to profit from it. We see that Trend investing is the future in an increasingly faster pace world, driven more and more by technology processing massive amounts of data.
Hortz: What kind of opportunities does this newer perspective offer to help with active manager performance?
Pellegrinelli: Investors already rate, rank and measure fundamental and quantitative data. But they often lack a way to objectively assess the true direction and quality of medium-term price trends, despite the fact that trends are the key factor that impact investment performance for any style or philosophy.
Price trends are happening in all markets regardless of the type of market cycle at the time. Equity markets display an incredible dispersion of performance, which we seek to expose for our clients in our platform. We developed tools to capture a large part of the top trending performers and avoid a large portion of the bottom trending performers of the stocks asset managers are following. We can then measure the overall “Portfolio Rating” and any changes are pushed out to the manager via alerts. By raising the portfolio rating you improve the probability to generate superior returns. This allows active managers to outperform passive benchmarks that are simply relying on a mathematical combination of both winners and losers.
Active management can beat passive products, with the adoption of intelligent analytics and next-generation technology required to complement and strengthen their investment decision process.
Hortz: So you feel that concerted attention to the dynamics of stock price action should be an equal partner to stock fundamentals or be an overlay of some sort?
Pellegrinelli: We spent many years developing something quite complicated to gauge the magnitude of price trends and exposing the end result in a very simple and actionable manner – a “trend rating”.
For active managers who are fundamentally driven, they would still conduct their research as usual to identify potential securities to hold in the portfolio. Once selected, those stocks or ETFs can be quickly uploaded into a trend ratings and analytics program, such as ours, providing a variety of ways to enhance their decision-making process by employing this additional source of intelligence. Such data and analytics can help active managers determine if and to what degree fundamentals are disconnected from the price of the stock, as well as, help avoid “Value Traps”.
Furthermore, clients can use the filtering and ranking modules to identify new investment ideas, to overweight/underweight their existing holdings or as an enhanced sell discipline once they are alerted to downgrades in their portfolio. We also see a growing list of clients who use this tool to create systematic portfolios that are rebalanced by our engine. To sum it up, trend analysis easily fits with any investment style.
Hortz: How did you go about building your financial technology solution and analytic engine to accurately capture price trends?
Pellegrinelli: Our research and development team have 30 years of experience in researching and building models. I personally started creating my own models back in the 80’s when the IBM PC only had floppy discs and there was no internet. I had to manually insert the closing prices from a hard copy of the Wall Street Journal into technical analysis software each day. I knew someday there had to be a better way!
Trendrating is the result of strong passion and a dream – to develop the best trend capture model for medium to long-term equity investors, not for traders. We tested 357 technical indicators across 25 years of daily data for 18,000 listed stocks on a global scale. After many years of robust testing, we identified a small number of indicators that were more accurate than the others and we combined them into a master model.
We ended up with a pattern recognition model which contains a self-adjusting algorithm. When the majority of indicators are positive there is a high probability of a bull trend. When most are negative then a bear phase follows a high percentage of the time.
Hortz: How is your solution different from other price trend or momentum models being employed today?
Pellegrinelli: The rationale of technical analysis is sound. No questions, no biases, no human behavior traps. It’s objective, pragmatic, and cynical. But the problem is deciding what indicator to follow during different types of markets. The risk is either reacting too late or trying to make sense of a string of erratic signals. We found that the solution was a combination of multiple factors which were tested on 25 years of data that encompassed a number of different market cycles. Finally, we had to properly weigh them, and each day they self-adjust (based on volatility) to filter out price noise and reduce the whipsaw effect.
Classic momentum factor investing is another alternative. This is also good for discipline, but most models follow a predominant indicator and require the confirmation of a few months of performance. As a result, these models miss a good chunk of a price run up and risk being late in identifying key trend reversals. Our model has been live since 2014 and it always behaves as expected, not deviating much from the historical back testing.
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