ABOUT US

  • A History of Looking Forward

    Newfound Research is the pioneer of dynamic, volatility-adjusted momentum models and one of the first to utilize absolute momentum for risk management in "go-to-cash" strategies.

Who We Are

Newfound Research designs and delivers quantitatively-enabled, tactical investment strategies. We balance a disciplined, research-driven approach with prudent strategy design to deliver intuitive, repeatable results. Newfound also partners with select asset management firms to collaboratively build investment solutions utilizing our tactical investment philosophy. Newfound’s strategies, whether direct or collaborative, strive to solve an identifiable investment problem and are distinguished by three qualities: a simple objective, a consistent process, and a thoughtful design.

 

Newfound was co-founded by Tom Rosedale, CEO, and Corey Hoffstein, CIO, in August 2008 to license data from the tactical investment algorithms researched and developed by Corey from 2007-2008.  In the last five years, our models have been utilized to help drive the investment decisions for billions of dollars in assets.

 

Our Story


Our Investment Philosphy

Hundreds of years of Tulipmanias, Mississippi Schemes, South Sea bubbles, dot-com booms and housing busts demonstrate that humans are often irrationally driven by greed & fear.

 

Cognitive biases make objective decision making difficult. Repeated over time, these biases compound creating negative investment results. The objectivity of quantitative metrics eliminates cognitive biases.

 

We believe that long-term consistency in performance and risk-management is achievable through a dynamic, quantitatively-driven process.

Why Quantitative?

Objectivity

Quantitative analysis eliminates cognitive biases and as a result controls these compounding sources of investment risk

Consistency

Models are consistent: for the same inputs, they give the same outputs, making conceptualizing their expected behavior in different market environments easier.

Breadth

Quantitative methods allow us to explore, analyze and surface meaning from data that may otherwise be intractable

Transparency

A model is merely a set of rules -- or a recipe -- which makes the process fully transparent. When viewed this way, the "black box" becomes transparent.

The Four Tenets of Quantitative Integrity

Building Models on a Solid Foundation

Robust

Models should be developed to be robust over a broad range of asset classes and a great depth of time-frames to prevent over-optimization to a specific instrument or market cycle.

Adaptive

The Greek philosopher Heraclitus said, “the only constant is change,” which holds especially true for market dynamics. Therefore, models should constantly update their internal metrics to stay relevant to current market environments.

Reactive

Predictive models are most effective when current market conditions mirror history. We believe exogenous events cannot be predicted and fall outside of historical data. Therefore, models should be reactive, i.e. durable and flexible in changing markets.

Simple by Design

Our research shows that simple models tend to be more robust than complicated models in uncertain and complex environments. By reducing a model’s complexity to the fewest necessary factors, the risk of over-optimization to historical data is reduced.

Understanding our Flagship Model

Dynamic

A dynamic window governs what information the model evaluates. As significant information flows into the market more frequently, the dynamic window will shrink, becoming more adaptive to short-term changes. As more time elapses between significant information, the dynamic window expands, becoming more robust to short-term fluctuations.

Volatility-Adjusted

Volatility provides context for returns.

Our thesis is that when significant information moves into the market, a security’s price should react beyond what can be explained as day-to-day market noise.

Momentum

1. Securities that go (up / down) in value tend to keep going (up / down) in value

2. Securities which (out / under)-perform their peers tends to continue to (out / under)-perform


Our models are designed to harvest momentum in an efficient way, seeking to avoid whipsaw risks and limit transaction costs

The People

Executive Team

Tom Rosedale

Co-founder, Chief Executive Officer and Chief Compliance Officer

Corey Hoffstein

Co-founder, Chief Investment Officer and Chief Technology Officer

Investment Team

Justin Sibears

Managing Director / Portfolio Manager

Andrew Gogerty

Vice President

Nathan Faber

Associate

Sales & Marketing

John Mannix

Executive Vice President

Paula Boyd

Senior Vice President

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