As we leave 2016 behind and prepare for 2017, I wanted to share some of the themes we have recently been speaking and writing about. Over the last quarter, we penned four articles, appeared in three videos, and were quoted several times in additional articles.
Here are links to some of the aforementioned media spots:
The Benefits of Defined Outcome Investing, Nasdaq: A discussion on Exceed and the benefits of Defined Outcome investing
What is in Store for Markets in 2017, Voice of America: A read on VIX and what is in store for 2017 – one item discussed was whether VIX futures were pricing in too much complacency in the face of an elongated bull cycle and a new President with aims to disrupt existing political processes
Joe Halpern joined Jill Malandrino, Markets Reporter for the popular Voice of America segment on Nasdaq Facebook Live to discuss market volatility going into the national election and what may be in store come next week. Please listen in to learn what the VIX may be telling us.
Last week I penned an article in the November issue of Investment Advisor (a ThinkAdvisor publication); the article discusses how the VIX communicates expected volatility over the next 30 days.
Although VIX is always an important indicator to watch, in early 2016 it has provided particularly keen insights leading up to the Brexit vote and now is doing the same for the U.S. election cycle. As an FYI, VIX has jumped 50% in the last week (from 13 to 19), a sign of just how wild an election this is turning out to be. Interestingly, the VIX futures curve is partly in backwardation – both November and December expirations are closer to an 18 handle. This is communicating an expectation of higher volatility and uncertainty going into the election next week, with an expected lull in the action and hopefully more certainty thereafter.
Low volatility funds have been hot, hot, hot – the top two domestic based ETFs in the category, USMV and SPLV, now have over $20 billion in assets between them, of which $8 billion has come in during the last six months (40% of total AUM).
At first glance, this popularity is understandable: the concept is straightforward and logical, the pitch is compelling, and risk-adjusted performance has been strong.
However, neither ETF has gone through a significant market correction, so a real concern is that investors do not have a good grip on the potential downside risk of these strategies. Thankfully, the indexes that both ETFs follow either existed or were backtested (Is a backtest trustworthy? Sometimes! Learn more) prior to 2008, providing a glimpse of how these strategies should have worked in a past downturn as well as a basis to analyze how they may act in future downturns.
Part one of a series of articles on product development
“I have never seen a bad backtest” is an often stated criticism of backtesting that has a high degree of truth to it – many strategies launch with strong backtests yet do not pan out as intended.
In truth, a well-designed backtest is a key tool among a number of tools that should be used for financial product manufacturers and asset managers to develop and vet investment strategies. Yet, many backtests have critical flaws inherent within them. Today, I will explore some of the general flaws frequently found in poorly designed backtests, as well as methods which a prospective investor can use to “kick the tires” on a backtest to separate the well designed from the flawed.
Check out our webinar on Beta vs. Delta.
Beta is one of the classic measurements within the financial industry. It is one of the first measurements shown on Yahoo Finance, right under the bid-ask and earnings estimate. Participants use it as a general gauge of market-related risk associated with an investment. As a reminder, an investment with a Beta of 0.8 is generally supposed to participate in 80% of a market move. So if the market increases 10% the investment should move up 8% and in a down 10% environment it should move down 8%. If only it was so simple…
Beta is so well known that most people have not reviewed the basics of its calculation in a while, nor do they remember its drawbacks – let’s do some Beta 101!
Beta is essentially the slope of the best fit line between the investment being studied (one axis of the graph) and the market (the other axis of the graph).