In the revised edition of The Incredible Shrinking Alpha, Larry Swedroe and Andrew Berkin make the case that investors are better off choosing passive investments because markets have become more efficient as managers became more skilled.

Consistent with misapprehensions expressed during other recent market crises, there has been a chorus of alarmist speculation about the actions and state of risk-parity strategies during the current crash. We felt it would be helpful to revisit the concept of risk parity and take a snapshot of how a typical global risk parity strategy might have been expected to behave this year.

By diversifying across many equally legitimate parameter choices – an ensemble – investors may be able to preserve expected performance with a higher degree of stability.

A new paper analyzed global multi-asset factor premiums over an unprecedented sample of 217 years. The findings carry important implications for quantitative asset management.

I’ve spent a great deal of time in past articles discussing the merits of portfolio optimization. In this article I will examine the merits and challenges of portfolio optimization in the context of one of the most challenging investment universes: managed futures.

In this article we put our optimization machine framework to the test. Specifically, we make predictions about which portfolio methods are theoretically optimal based on what we’ve learned about observed historical relationships between risk and return. Then we test these predictions by running simulations on several datasets.

While novice investors typically stumble onto the concept of trend following in the context of stock-market timing, professionals know that trend following is not about using trends to time one or two individual markets. Modern professional trend followers often trade dozens of futures markets across equities, bonds, currencies, commodities and more obscure markets like carbon offsets.

The evaluation of alternatives introduces an extra dimension into the equation that investors don’t need to think about with traditional equity funds. It’s the concept of capital efficiency.

Larry Swedroe and Kevin Grogan have created a near-perfect guide for practitioners and investors who are concerned about prospective returns from stocks and bonds in the current environment. The book explains how to think about the value of diversification and presents at least five novel strategies with exhaustive attention to detail.

In most parts of Canada we have very distinct seasons. Some months of the year are temperate and relatively dry, while other months are cold and snowy. As a result, most Canadian towns of any size have stores that sell skis and bikes.

Here’s a new bet with Warren Buffett based on a portfolio oriented around risk parity and factors.

Investors are struggling to achieve long-term return targets in today’s low yield environment. To close the gap, many investors feel forced into concentrated equity portfolios.

This article will tackle the “p-hacking” issue and propose a framework to help those who embrace evidence-based investing to make judicious decisions based on a more thoughtful interpretation of finance research.

Michael Edesess’ article, The Trend that is Ruining Finance Research, makes the case that financial research is flawed. In this two-part series, I will examine the points that Edesess raised in some detail.

In this article, we examine whether it pays to account for differences in the path assets take to produce their momentum. All other things equal, do investors express a short-term preference for assets that have produced their returns with less risk, where risk is measured broadly as having delivered a smoother ride?

In our last post, we covered the importance of a well-designed investment universe as a precondition for thoughtful diversification. In this second article on Dynamic Asset Allocation for Practitioners, we will explore several methods for measuring price momentum to compare and contrast their utility under different portfolio concentration and asset universe specifications.

In 2012 we published a whitepaper entitled “Adaptive Asset Allocation: A Primer” in which we built upon the simple, robust momentum framework proposed by Mebane Faber in his 2009 study “Relative Strength Strategies for Investing.”

In August 2016, Bank of America Merrill Lynch (BAML) wrote a research note characterizing risk parity as one of the central causes of equity market losses in late 2015. The note had all the hallmarks of a compelling plot line, replete with weapons of mass destruction, billion-dollar bets, and evil villains.

Adam Butler introduces a simple but novel innovation for modeling equity market valuations. There are reasons to believe average valuations should rise through time in response to changes in market structure. We discuss the conditions that might lead to higher valuations through time, and present a model to account for it.

Advisors should define risk as the probability that clients won’t meet their financial goals. Advisors should have the singular objective of minimizing this risk. This definition profoundly shifts the conversation away from volatility and losses, and toward strategies that achieve minimum required returns.

North American equities led the way in 2016, providing double digit returns and bolstering investor confidence. As expected, the recent strength has naively led investors to flock into US equity funds in what may possibly be the tail end of US equity dominance over global equity markets.

I’m starting to feel like a rancorous curmudgeon, but I am frustrated by some of the misguided commentary on asset allocation and how diversification is a myth.

For evidence, look no further than sales of bottled water in the first world. Our ancestors spent hundreds of billions of dollars developing the infrastructure to deliver potable water to every home, yet we spend billions each year to purchase bottled versions of what we can get for free almost anywhere. Boom – I just blew up the very foundation of economics.

Benjamin Graham famously said that “In the short run, the market is a voting machine but in the long run, it is a weighing machine.” But this is not quite correct.

Smart beta. Empirical finance. Evidence-based investing. These terms, which were in the periphery of the investment vernacular just 10 years ago, have become the investment world’s most popular memes today. Why?