100 Years: Charles Dow to Quants to Predictive Analytics for Everyone
Ask any behavioral finance theorist or even a psychologist, and they'll tell you that people are hard wired to react to events and situations in an eerily consistent fashion. We overreact to news, both good and bad. We follow the herd, and we think the status quo will go on indefinitely. These patterns of behavior repeat in the market, but only segments of the investment population have been able to figure out how to profit from this information -- until now.
New predictive analytics technologies are coming to the forefront to handle all kinds of big data questions. For the financial markets, they are now able to provide the broader investment community with statistical validation of the predictive nature of price trends. Companies are also providing the transparency and probabilities to give investors the tools to utilize the statistics across investment functions. What took so long?
Investors started to research and identify the repeatable nature of price trends more than a century ago. One in particular, Charles Dow, started publishing his market trend analysis, which has developed into a body of research now called technical analysis. Decades of work combined to generate a set of defined patterns and indicators that investors had seen repeat in the markets time and again with consistent forward outcomes. Today price trend analysis like technical analysis or momentum are fairly common and well verified in the trading community, but less so with institutional money managers.
Certain kinds of price trends like momentum have achieved broad academic and market validation, but for the most part, price trend analysis and technical analysis have seemed to lack the statistical validation to get broader adoption. Fundamental analysis is the 800-pound gorilla in the active management space, and though most would agree that price trends have impact, investing philosophies are often like political parties. Most people do not straddle the fence.
The other likely inhibitor of wider adoption is that many consider the use of price trends and technical patterns to be more art than science. In fact, there are market technician designations that cover a tremendous field of work, and it is a challenging craft to perfect. Some of the most well-respected technical analysts on the Street have been studying price trends for 40 years or more. In addition to the barriers in gaining competence, investors are inherently cynical. Since technical analysis of price and volatility trends is based on "empirical experience," it has lacked the support of the academic community and the necessary supporting statistical evidence.
The hard proof has come over the past 20 years in the form of quantitative analysis and systematic trading strategies. Quants employ data scientists and build models to automatically take advantage of predictable market movements, specifically with security prices and recurring patterns of investor behavior. Momentum, mean reversion, and statistical arbitrage are common forms of strategies that have been generating consistent returns for years.
The success of quantitative investing has certainly brought the necessary statistical validation to the broader investment community, and some of the largest and most successful hedge funds in the world are systematically oriented, including Bridgewater, RenTec, Winton, DE Shaw, Two Sigma, and many more. The problem is that their techniques are even more complex than technical analysis and way more opaque. Quants are extremely proprietary, understandably not wanting to share their "special sauce" on how they are able to take advantage of these predictable market movements, and they rarely publish results.
So then, we have pockets of the investment community that have been recognizing and profiting from the impact of price trends for years, but with the broader investment community sitting on the sidelines. People talk about the impact disruptive technologies are having in the marketplace, and it's truly applicable in this case. We are now sitting on the precipice of a paradigm shift in price trend analysis. Why?
As I stated at the opening, technology can now tackle the issue of verifying the predictive nature of price trends and provide all investors with the necessary transparency and action-oriented information to incorporate it. For example, EidoSearch applies pattern search technology to generate predictive analytics from big financial data.
New predictive analytic technologies, when implemented correctly, are also transparent, with historical analogs and underlying statistics, and not just delivered as a "signal." Fundamental investors can now get customized return and volatility projections for trade and investment decisions, with the robust research validation and probabilities to back them up. These technologies also represent a significant evolution over both technical and quantitative analysis of price trends. New techniques are dynamic, allowing for analysis of all patterns triggered by things like behavior, events, or news as they unfold in the market. They are not constrained to a set of "defined" or formulaically described patterns of investor behavior.
Investors are already incorporating these insights into their idea generation, portfolio monitoring, and risk management efforts to objectively answer questions like:
- Is this a good entry point?
- Should we lock in gains at this point?
- What are some good shorts with low probable upside?
- How does the market typically react to this type of binary event?
Investor behavior repeats in the markets. Technicians have seen the impact for centuries, and quants have systematically researched and profited from this information for decades. The tools are finally emerging to enable all investors to profit from incorporating predictive analytics and probabilities into their investment process, no matter what their discipline.Dave is the VP of Sales and Marketing of EidoSearch. He has over 14 years of proven success working in the Financial Services vertical. Mr. Allen was most recently GM for Americas at TIM Group, the world's leading Alpha Capture network, where he ran sales and service ... View Full Bio