Today we will be exploring the second chapter of our newest online portfolio selection module, momentum. Momentum strategies have been a popular quantitative strategy in recent decades as the simple but powerful trend-following allows investors to exponentially increase their returns. This module

Value investing is struggling big time! As of March 2020, Value factor is down -51% from the peak reached 14 years ago. It is the longest and largest drawdown in value’s recent history. Many value investors have already rotated into growth. The remaining diehards also want to quit. Even Warren

In a comment on my previous post, visualising Oanda's orderbook, a reader called Darren suggested that I was over complicating things and should perhaps use a more established methodology, namely Market Profile. I had heard of Market Profile before Darren mentioned it, but had always assumed

As AUM in merger arbitrage has increased, alpha decreased Investors can access merger arbitrage via hedge funds, bank indices, and ETFs The strategy is not as uncorrelated from equities as likely perceived by allocators INTRODUCTION Working in the restructuring team of a corporate finance boutique

An equilibrium model for U.S. Treasury yields explains how macroeconomic trends and related expectations for future short-term interest rates shape the yield curve. Long-term yield trends arise from learning about stable components in GDP growth and inflation. They explain the steady rise of

Tactical Asset Allocation (TAA) dodged the worst of the bear in February and March, but trailed the big bounce in April. Entering May, TAA remains stubbornly defensive. We track 50+ TAA strategies sourced from books, papers, etc., allowing us to draw broad conclusions about TAA as a style. In the

April finished with a 12.7% gain for the SPX. That is the strongest 1-month gain since January of 1987. In last night’s subscriber letter I decided to look back at all other instances following 1-month SPX (or its predecessor the S&P 90) gains of 10% or more. The table below shows all

A common question we receive at Alpha Architect is the following: Why do you focus on EBIT/TEV as a value screen for stocks instead of the more traditional measures such as book to price? In short, we believe stocks are ownerships in businesses (I know that sounds crazy coming from a quant shop!).

In this article I use the random forest algorithm to forecast mid price dynamic over short time horizon i.e. a few seconds ahead. This is of particular interest to market makers to skew their bid/ask spread in the direction of the most favorable outcome. Most if not all the literature on the topic

In the eye of the recent storm, with VIX up over 50, many traders were looking to “short the VIX” using products like TVIX. “Surely it’s going to coming back down?” Well yeah, it will, eventually, but that doesn’t mean that you can profitably short VIX products. First, some basics…

Artificial Neural Networks (ANN) have been applied with success to many daily tasks that needed human supervision, but due to its complexity, it is hard to understand how they work and how they are trained. Along this blog, we have deeply talked about what Neural Networks are, how they work, and how

With a growing popularity of cryptocurrencies and their increasing year-over-year traded volumes, crypto algo-trading is a next big thing! If you study this market closely you will notice that it offers quick gains in much shorter unit of time comparing to stocks or FX. No wonder why a participation

Over the last 20 years equity markets and ETFs did a significant part of their total performance over night. This article will examine the relationship of in-session moves vs. the out-of-session moves of ETFs and commodities. The overnight risk premium As an investor you can expect to get paid for

Larry Swedroe recently wrote a post titled “Is there a Tail Risk Premium in Stocks.” This post is a good complement to Larry’s as this paper proposes two new measures of systematic tail risk and explores whether they are associated with a significant risk premium. The first measure, Extreme

Online Portfolio Selection is an algorithmic trading strategy that sequentially allocates capital among a group of assets to maximize the final returns of the investment. Traditional theories for portfolio selection, such as Markowitz’s Modern Portfolio Theory, optimize the balance between the

Few years ago I published two post trying to give simple explanations and intuition behind complicated formulas used for calculating vol indexes. However few of you emailed that some charts are missing from these older posts, and for technical reasons since I could not restore them, I decided to

In past research we have explored the potential benefits of how-based diversification through the lens of pay-off functions. Specifically, we explored how strategic rebalancing created a concave payoff while momentum / trend-following created a convex payoff. By combining these two approaches, total

Tail risk funds tend to be most in demand when they are least attractive Short-term bonds provided similar benefits to tail risk funds The TAIL ETF closely replicates the performance of tail risk funds INTRODUCTION In a year where the S&P 500 lost more than 30% in a few weeks, there are few

For simulating stock prices, Geometric Brownian Motion (GBM) is the de-facto go-to model. It has some nice properties which are generally consistent with stock prices, such as being log-normally distributed (and hence bounded to the downside by zero), and that expected returns don’t depend on the

Meb Faber is a co-founder and the Chief Investment Officer of Cambria Investment Management. His speciality is quant investing. Meb is the host of The Meb Faber Show podcast and has authored numerous white papers and books. He is a frequent speaker and writer on investment strategies and has been

Our last post discussed using the discounted cash flow model (DCF) as a method to set return expectations that one would ultimately employ in building a satisfactory portfolio. We noted that if one were able to have a reasonably good estimate of the cash flow growth rate of an asset, then it would

Howell E. Jackson (Harvard Law School) and Steven L. Schwarcz (Duke U.) April 19, 2020 The coronavirus has produced a public health debacle of the first-order. But the virus is also propagating the kind of exogenous shock that can precipitate – and to a considerable degree is already precipitating

My earlier post of 26th March shows code to visualise the most recent instantaneous snapshot of Oanda's order book, realised as a horizontal bar chart superimposed over a price chart. Below is a screen shot of a different type of chart designed to show the historical order book, which is

This is a test of the flagship proprietary strategy from Paul Novell’s Investing for a Living. Paul has been kind enough to share his strategy rules to allow for independent verification of his results. SPY-COMP is like Growth-Trend Timing and a handful of other tactical strategies we track, in

Similar to some better-known factors, such as size and value, time-series momentum (TSMOM) historically has demonstrated abnormal excess returns. For the less familiar with trend following it’s worth your time to review Alpha Architects white paper on trend following here. TSMOM is measured by a

The first quarter of 2020 has been one of the most challenging times in the post World War II era. The crash in oil prices due to geopolitical reasons and the COVID-19 global pandemic were the dominant themes. Financial markets act as bellwethers and give us a reflection of the overall sentiment for

Recent actions in WTI Futures pricing on Apr 20, 2020 caused my curiosity to have a deep look at intraday crude oil price time-series. With no surprise, I couldn’t find any free and effortlessly available dataset on the Internet. This is a common problem for lots of quants and data analysts:

How long will the recession last? How deep will it be? What are the long-term implications for the economy, markets, and society? The global pandemic has ushered in a period of extreme uncertainty and investors are left with too many unanswered questions and afraid for their portfolios. Where do we

Has the market sell-off and subsequent bounce treated all stocks the same? A good portion of the bull market move from 2009 to 2019 has been led by the big-cap stocks. Did they hold up better during the March sell-off? What about with the bounce? Did the smaller-cap stocks have a bigger bounce? The

The Black-Scholes formula can be used to create a hedge for an option. However, this model is derived in continuous time. What happens when we use it to hedge an option in discrete-time? European options are financial securities which give their holder the right (but not the obligation) to buy or

We’ll be talking about Paul Novell’s flagship SPY-COMP strategy on the blog tomorrow. The strategy uses monthly economic data, like the kind available from the FRED database. We’ve covered a handful of strategies like this in the past (think Philosophical Economics’ Growth Trend-Timing).

In the short video below, I show how to compute Active Share. The accompanying excel file with the formulas can be found here. I start by computing the active share for two hypothetical funds, and then examine the active share of a few live ETFs.

I am not a fan of most equity factors, but if any equity factor exists, it is the value factor. Graham and Dodd, Warren Buffet, Fama and French have all highlighted value as an investment strategy. Its essence is the ratio of a backward-looking accounting value vs. a forward-looking discounting of

For the past decade, asset managers have been educating clients about factor investing as it became the new norm. And yet after all these years, portfolios are still composed of one factor: Equity Beta. Among many questionable assertions and assumptions behind factor investing (our thoughts here,

To describe the impact of social distancing, a theory of communication is developed and described comprehensively in this article. The focus is on the relative importance of worker interactions, the cost of those interactions and their impact on the size of wage subsidies intended as compensation

Factor investing in fixed income has been heralded as the next frontier in asset management Smart beta fixed income ETFs in the US manage only slightly more than $2 billion of assets Defensive strategies reduced drawdowns during the ongoing coronavirus crisis INTRODUCTION Investing is becoming more

Since 2009, any decision to de-risk in a trend equity portfolio has largely been the wrong decision. At the time of writing, we implement a 1-month tranching process in most of our trend mandates, which has the effect of dollar-cost averaging signal changes over a 1-month period. We adopted this

Concept: Dual momentum trading strategy based on Rate of Change (ROC). Research Goal: Performance verification of dual momentum signals. Specification: Table 1. Results: Figure 1-2. Trade Filter: Long Filter: Slow Rate of Change (ROC1) is above zero. Short Filter: Slow Rate of Change (ROC1) is below

Optimisation tools have a knack for seducing systematic traders. And what’s not to love? Find me the unique set of parameters that delivered the greatest return in my ten-year backtest. And do it in under five seconds. That’s certainly attractive. But do you want to hear something controversial?

This months project is a new indicator by John Ehlers, first published in the S&C May 2020 issue. Ehlers had a unique idea for early detecting trend in a price curve. No smoothing, no moving average, but something entirely different. Let’s see if this new indicator can rule them all. The basic

Building on the concepts presented in my Dividends Are Different article, here we present data and observations highlighting the relationship between inflation and 1) company fundamentals, 2) dividends, and 3) stock market movements. 1 We look at empirical data to investigate how inflation relates

Are you doing independent factor research? Have you spent countless hours on Ken French’s website? Do you run factor regressions for “fun”? Congrats — you are officially a finance geek and you will probably benefit from our new factor investing library. Our library has over 300 factors to

Tick data is the most granular high-frequency data available, and so is the most useful in market microstructure analysis. Unfortunately, tick data is also the most susceptible to data corruption and so must be cleaned and conditioned prior to being used for any type of analysis. This article,

Tactical Asset Allocation (TAA) weathered the storm in February and March, significantly paring down losses vs conventional buy & hold. So far it has trailed the bounce in April, but these are early days. We track 50+ TAA strategies sourced from books, papers, etc., allowing us to draw some

One of the keys to running a successful systematic trading business is a relentless focus on high return-on-investment activities. High ROI activities include: Implementing new trading strategies within a proven framework. An example might be to implement a portfolio of pairs trades in the equity

It has been well documented both that stock returns have much fatter tails than a normal distribution would generate, and that tail events occur much more frequently than a normal curve would predict. 1 For example, Benoit Mandelbroit and Richard Hudson examined the daily index movements of the Dow

After our little detour into GARCHery, we’re back to discuss capital market expectations. In Mean expectations, we examined using the historical average return to set return expectations when constructing a portfolio. We noted hurdles to this approach due to factors like non-normal distributions,

My last two posts have shown Octave functions that use the Oanda API to access and download data. In the first of these posts I said that I would post more code for further functions as and when I write them. However, on further reflection this would be unnecessary as the generic form of any such

Many machine learning algorithms rely on distances between data points as their input, sometimes the only input, especially so for clustering and ranking algorithms. The celebrated k-nearest neighbors (KNN) algorithm is our example chief, but distances are also frequently used as an input in the

In a previous post, we showed that unhedged currency exposure adds unrewarded risk to our investment, hurting risk-adjusted-performance. This risk should either be neutralized through passive hedging; or mitigated and turned into profit with an active overlay, the latter being what ETS has been