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

Class imbalance can seriously damage the precision of your binary classifier. In this post you will learn some simple ways of evening the size of your classes before training to prevent your classifier from cheating. The class imbalance problem Binary classification is a very common problem in

In our previous post, we touched on FX rates and their impact on international ETFs like EFA or EEM. In short, because international ETFs trading in the US are denominated in USD, most are affected not just by changes in underlying assets, but also by changes in the exchange rate between USD and

Below I’ve collected links to some of my favorite white papers and presentations on volatility. I’ve organized them in the following categories: Volatility Concepts & Volatility Trading Probability Distributions—Normal and Otherwise The VIX and VIX Futures Volatility Contagion—Will Short

Constructing an asset allocation that never lost money over given rolling periods leads to unsettling allocations: large positions in small-caps, long-term U.S. Treasuries, and precious metals. In many investment analyses, past results may be a downright misleading guide to the future because one

This article examines the magnitude of exposures to a set of systematic factors present in widely accepted Benchmarks (S&P500, the Russells, and MSCI global indices) and how they change over time. The authors use conventional style factors of value, size, quality, momentum, and minimum

In this article, we are going to develop a machine learning technique called Deep learning (Artificial Neural network) by using tensor flow and predicting stock price in python. At the end of this article you will learn how to build artificial neural network by using tensor flow and how to code a

Higher volatility & dispersion imply higher stock market risks The relationship between correlation and risk is not linear However, these market technicals do not behave consistently across time INTRODUCTION Financial reporters frequently comment on stock market technicals like volatility and

Few weeks ago Dr Jonathan Kinlay from Quantitative Research and Trading blog published a series of excellent articles on volatility. I wanted to review and comment on the notes. Forecasting Volatility in the S&P500 Index Modeling Asset Volatility Long Memory and Regime Shifts in Asset Volatility

Forward earnings yields and equity carry are plausible indicators of risk premia embedded in equity index futures prices. Data for a panel of 25 developed and emerging markets from 2000 to 2018 show that index forward earnings yields have been correlated with market uncertainty across countries and

Recent asset allocation articles (tactical or otherwise) that you might have missed: We Are All FX Traders Now (Alpha Scientist) Because international ETFs trading in the US (ex. EFA or EEM) are denominated in USD, most are affected not just by changes in the underlying assets, but also by changes

This study investigates the relation between a comprehensive set of firm-specific attributes and future equity returns for a sample of stocks from 27 emerging markets. Univariate analyses based on equal-weighted portfolio returns reveal that the low beta, firm size, book-to-market ratio, momentum

Can the monetary policy environment be used to predict global equity market returns? Should we overweight/buy countries with expansionary monetary policy regimes and underweight/sell countries with contractionary monetary policy regimes? In twelve of the fourteen countries studied, both nominal and

Mutual funds exhibit momentum when measured by their one-year performance Momentum disappears when more reasonable fund selection criteria are applied Performance does not seem effective for fund selection for a full market cycle CHASING PERFORMANCE Chasing mutual fund performance suffers from a bad

Inflation at the producer level (derived from the Producer Price Index – PPI) is arguably an advance indicator for inflation downstream at the consumer level (derived from the Consumer Price Index – CPI). Do investors therefore reliably react to changes in PPI as an indicator of the future

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

Beta herding means convergence of market betas of individual stocks that arises from investors’ biased perceptions. Adverse beta herding denotes the dispersion of such betas that arises from a reversal of the bias. A new paper suggests that overconfidence in predictions of overall market direction

Nothing is more frustrating than a long piece of code with no standard way of naming elements, presenting code or organizing files. It’s not only unreadable but more importantly not reusable. Unfortunately, unlike other programming languages, R has no widely accepted coding best practices. Instead

We’re in unique position to analyze the behavior of Tactical Asset Allocation investors. Our platform helps members analyze 40+ published TAA strategies from many angles, including: historical performance, tax efficiency, exposure to rising interest rates, etc. Members can combine those strategies

We dissect the performance of factor-based equity portfolios using a characteristics-based multi-factor expected return model. We show that generic single-factor portfolios, which invest in stocks with high scores on one particular factor, are sub-optimal, because they ignore the possibility that