Are returns this year actually different than what can be expected from a typical year? Is the variance actually different than what can be expected from a typical year? Those are fairly light, easy to answer questions. We can use tests for equality of means or equality of variances. But how about

Factors, or “style” investing, seems to be all the rage these days, including the use of factors in fixed income (here, here and here are good places to start). However, many of these strategies focus on CUSIP level bond selection. This means executing a strategy with a fair amount of turnover

Author: Wes Gray. Wes is the CEO/CIO of Alpha Architect. He has published multiple academic papers and four books, including Quantitative Value (Wiley, 2012), DIY Financial Advisor (Wiley, 2015), and Quantitative Momentum (Wiley, 2016). After serving as a Captain in the United States Marine Corps,

This research note was originally published by the CFA Institute’s Enterprising Investor blog. Here is the link. SUMMARY Micro caps are commonly perceived as highly risky, but potentially also highly rewarding Smalls caps generate more attractive risk-return ratios than micro caps on index level

Is it possible to time factors? (An old blog on the topic here and Jack discussing on a podcast here) Are there financial and economic indicators that can be used to predict factor returns? Are timing models just luck? What are the Academic Insights? YES. The authors use Fama-French 5 Factors

Financial markets produce more than one risk-free interest rate. This is because there are several separate market segments where structured trades replicate such a rate. Differences in remuneration arise for two reasons. First, financial frictions can prevent arbitrage. Second, some risk-free

September 2018 Trend Following: DOWN -1.41% / YTD: -8.85% Please find this month’s report of the Wisdom State of Trend Following. Performance is hypothetical. Chart for September: Wisdom State of Trend Following - September 2018 And the 12-month chart:

Not long ago I used to teach investment management courses to Master’s students (MBAs and MS Finance types). A core aspect of my course was so-called modern portfolio theory. We did a lot of math and problem-sets to make it feel like we were doing something useful. But I can summarize the core

“How can a q-theoretic model price momentum?” is a new paper by Robert Novy-Marx and goes right to the heart of an intense debate ongoing in empirical asset pricing — can neoclassic economic models explain the so-called momentum anomaly? A quote from the start of the paper, which answers the

Recent asset allocation articles (tactical or otherwise) that you might have missed: Market Timing the Credit Cycle (EconomPic) Jake looks at forward returns based on the width and direction of the credit “quality spread” (high yield minus investment grade OAS). Below we’ve reproduce Jake’s

Let’s start with a simple question: what is the first thing to think about when you create a portfolio? I’m sure several ideas spring to mind, but let’s go to the heart of the matter: what is the relationship between the assets in a portfolio? That is one of the greatest managers’ concerns.

Artificial Intelligence is deemed to be the main driver of the 4th Industrial Revolution. IDC predicts that investment in AI will grow from $12bn in 2017 to $57.6 by 2021, while Deloitte Global predicts the number of machine learning pilots and implementations will double in 2018 compared to 2017.

The paper investigates the following research question: Are left-tail vs. right-tail correlations symmetric for the majority of risky assets (including size and styles)? Is left-tail vs. right-tail correlations between stocks and hedge funds styles symmetric? Is left-tail vs. right-tail correlations

Risk tolerance, capacity, and need all factor into determining whether a portfolio is appropriate for an investor. Capacity and need are generally straightforward to quantify and map to an appropriate portfolio, but risk tolerance is more difficult, with many questionnaires potentially

Global factor performance in the first three quarters of 2018 is comparable to 2017 However, regional factor performance diverges, reflecting changes in monetary and trade policies Low Volatility leads and Value lags INTRODUCTION We present the performance of seven well-known factors on an annual

This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies are

Not all market participants respond to changing conditions instantaneously, not even in the FX market. Private investors in particular can take a long while to adapt to changes in global interest rate conditions and even institutional investors may be constrained by rules and lengthy process. A

Autumn is my favorite time of year. Football (and more importantly as a Bills fan, fantasy football) is back, everything tastes like pumpkin, and I don’t get sweaty walking around outside. It’s also the start of the cryptocurrency bull season! Or is it? Let’s find out. It’s already started:

Value at Risk and Expected Shortfall are related to the risk taken by a portfolio but… Which one is the best? Let’s learn together the differences between these two measures. Risk measures Coherence is really important when defining a risk measurement. If the measure is not coherent, it will not

Early in the summer, I was on a podcast with Corey Hoffstein discussing momentum investing. During the discussion, Corey asked me a question regarding risk versus mispricing, specific to the momentum anomaly. We frequently cite the behavioral explanation for momentum–investors tend to underreact

We’ve spent a great deal of time in past articles discussing the merits of portfolio optimization. In this article we will examine the merits and challenges of portfolio optimization in the context of one of the most challenging investment universes: Managed Futures. Futures exhibit several

We introduce the simple arithmetic of portfolio construction where a strategy can be broken into a strategic allocation and a self-financing trading strategy. For long/flat trend equity strategies, we introduce two potential decompositions. The first implementation is similar to equity exposure with

Liquid alternatives offer hedge fund strategies in mutual fund format The correlations to the S&P 500 have been high, even of market neutral funds Diversification benefits have therefore been limited DISRUPTING THE HEDGE FUND INDUSTRY Liquid alternatives have been heralded as hedge funds for

To most investors, short selling is a shadowy, mysterious corner of the markets. Many do not make use of shorting - and I suspect a majority don't understand how to glean insights from trends in short selling activity. Over the past several years, I've traded short about as often as long

Understanding quantitative equity investments means understanding a significant portion of market positions. Motivated by the apparent failure of the capital asset pricing model and the efficient market hypothesis, a large share of equity investors follows stylized “factors” that are expected to

Hedging With Volatility Mario Alagoa (Sacred Heart University) May 9, 2018 A risk-averse investor with a long equity position is presumably interested in identifying a hedging strategy that protects the value of that investment. The common approach encompasses using either financial derivatives or

You can watch the video via the link below: Video Summary Ryan and I discuss three articles published on our blog this week. First, we examine a paper by Linda Zhang investigating the volatility of leveraged ETFs. Second, we discuss an article (and corresponding video and PPT slides from Wes)

Over the last few years, you’ve likely heard the following competing narratives: ­ “Credit spreads are tight, a sign of exuberance among investors that are willing to overlook risk. This will end in tears.” “Credit spreads are tight, reflecting an environment of high economic growth and low

The Test Driven Development (TDD) philosophy improves your productivity and helps you write better code. But if you are new at it, you might find some trouble with its procedures. Let’s dive into a simple example that (hopefully) will help you solve it. When applying TDD methodology, the objective

I have spoken a fair amount lately about the “split” market, and how that has historically been followed by declines. But not all kinds of splits are bad. Wednesday we saw the SPX rise while the RUT closed lower. That is not unusual on a 1-day basis. But it has now been several weeks in which

This is a test of the tactical asset allocation strategy “Accelerating Dual Momentum” (ADM) from EngineeredPortfolio.com. ADM is especially aggressive strategy that ties together multiple concepts from other TAA models that we track. Results from 1990 to the present, net of transaction costs,

My post last week on the analysis of SCTR produced lots of emails and comments with great ideas. One idea that I liked was a simple rotation strategy using SCTR. I mentioned in the post that maybe using SCTR as ranking method would produce different results. Normally I don’t post this quickly but

We’ve covered momentum investing extensively over the years, to include 94 posts, a book on the subject, and numerous discussions on various podcast outlets. There are a few things one notices after thinking about a topic for so long: You forgot half of the things you read and/or wrote (yes, we

I think if you're reading this blog, you're probably already a knowledgeable options trader, and have heard of maximum pain theory - an idea that market moves in a path that hurts ( causes losses ) most amount of market participants. In options it is typically stated that simulating

This post will investigate using Principal Components as part of a momentum strategy. Recently, I ran across a post from David Varadi that I thought I’d further investigate and translate into code I can explicitly display (as David Varadi doesn’t). Of course, as David Varadi is a quantitative

A primer on beta convexity and its applications is given in the following post: The essential idea is to evaluate the beta of stock during down-markets, separately from periods when the market is performing well. Beta convexity is a measure of how stable a stock beta is across market regimes, and by

The paper investigates the following research question: What has the absolute risk behavior of leveraged products been historically? Did they behave as intended by design? Is the leverage multiple a reliable indicator of the volatility multiple? Is the leverage multiple a reliable indicator over

Our whitepaper “The Optimization Machine: A General Framework for Portfolio Choice” presented a logical framework for thinking about portfolio optimization given specific assumptions regarding expected relationships between risk and return. We explored the fundamental roots of common portfolio

Trend-following strategies exploit the fact that investors exhibit behavioral biases that cause trends to persist. While many investment strategies have a concave payoff profile that reaps small rewards at the risk of large losses, trend-following strategies exhibit a convex payoff profile, one that

Short-term momentum persists in common equity factors The persistence is strong in Value and Dividend Yield However, these results conflict with short-term mean-reversion on equity index level INTRODUCTION When Trump won the US presidential election in November 2016, small and cheap stocks started

This post has two goals. I hope to make you think about your graphics, and think about the future of data-visualization. An example is given using some simulated time series data. A very quick read. In visualization, like in programming, presenting or any other skill, there is much to learn. Also

One indicator that has gotten some play in the news lately is the Hindenburg Omen. In last weekend’s subscriber letter I discussed the Hindenburg Omen signal in detail. (Click here for a free trial.) A core premise behind the Hindenburg Omen is that there are a large number of stocks hitting both

A late edition of the State of Trend Following report, showing a strong return for August and a YTD figure back in the black. Please check below for more details. Detailed Results The figures for the month are: August return: 6.74% YTD return: 3.36% Below is the chart displaying individual system

Even if you’ve never heard of it, the Law of Large Numbers is something that you understand intuitively, and probably employ in one form or another on an almost daily basis. But human nature is such that we sometimes apply it poorly, often to great detriment. Interestingly, psychologists found

quity return dispersion is measured as the standard deviation of returns across different stocks or portfolios. Unlike volatility it can be measured even for a single relevant period and, thus, can record changing market conditions fast. Academic literature has shown a clear positive relation

The 2014 study by Andrea Frazzini and Lasse Heje Pedersen, “Betting Against Beta,” found strong support for low-beta strategies. I’ve previously written on low-beta strategies here. This paper finds that, for U.S. stocks, the betting against beta (BAB) factor (a portfolio that holds low-beta

You can watch the video via the link below: Video Summary Ryan and I discuss three articles published on our blog this week. First, we examine a summary by Larry Swedroe that highlights the Betting Against Beta (BAB) factor and dives into two new papers examining when the BAB factor performs well.

Overall the last few months, I’ve had several consulting client’s strategy use SCTR for either a ranking or a filter. I finally got curious about the predictive ability of SCTR. How good is? I could find no information on how each of the ranking buckets did X days later on StockCharts.com. Maybe

Is it possible to build a simple systematic approach that beats investing in complex factor models? The research team here has proposed that a simple formula based on low return volatility, high net payout yield (dividends +/- stock buybacks), and strong price momentum gives investors exposure to