I’m here today to talk about the Stochastic Portfolio Theory (SPT). SPT is a relatively new portfolio management theory. It was first introduced in 1999 by Robert Fernholz. In my opinion, SPT is very attractive for several reasons: it’s theoretical, it’s not very well known and, most

Wednesday is a Fed Day. Fed Days have historically shown an upside tendency. I have documented this tendency in great detail over the years, with the most complete documentation coming in The Quantifiable Edges Guide to Fed Days. Based on what the market did Tuesday, this does not seem to be the

If you ask your typical long-only investor (or financial advisor) how momentum is doing this year they’ll likely say, “Amazing!” This statement will almost surely be based on the fact they own (or know about) the iShares “Momentum Factor” Fund (Ticker: MTUM). MTUM is on fire year to date

The most recent "analysis" seemingly spreading like wildfire across the perma-bear community was performed by Horizon Kinetics in their most recent quarterly commentary. Their claim is that the price-to-earnings of the Nasdaq (or any index really) is much higher than reported because we

What are the research questions? Market globalization is said to be the culprit of decreased benefits of international diversification. In 1995, a US investor investing in Vodafone had exposure to 99% of UK based sales. The same investor in 2012 is exposed to UK sales only for 8% while at the same

Order book imbalance strategies have been a big alpha source in automated market making. Tick by tick observations provide important information about general market sentiment and direction, and high frequency trading firms (HFTs) have been very efficient at trading on this information at very low

Most trading models I see are missing an important concept. It’s not a terribly difficult concept, but it is an important one. It’s not at all strange that most traders, in particular on the retail side, are missing this point. Most trading books skip over it. Most books gloss over it, or just

Calculating an optimal portfolio from a set of capital market assumptions (CMAs) is a straightforward quantitative exercise, but the results are highly dependent on the assumptions holding in the future. Any portfolio that is initially assumed to be optimal will be sub-optimal if any single assumed

In my previous blog post we considered the general weighted moving average. In this post we aim to give an overview of some specific types of moving averages. Specifically, we cover “ordinary” moving averages and mention some examples of exotic moving averages. Ordinary Moving Averages These are

I’ve long been interested in the behavior of corporate insiders and how their actions may impact their company’s stock. I had done some research on this in the past, albeit in a very low-tech way using mostly Excel. It’s a highly compelling subject, intuitively aligned with a company’s

Earlier this year, I attended the Google Next conference in San Francisco and gained some first hand perspective into what’s possible with Google’s cloud infrastructure. Since then, I’ve been leaning on Google Cloud Platform (GCP) to run my trading algorithms (and more) and it has become an

The accuracy of U.S. stock return forecasts based on the cyclically-adjusted P/E (CAPE) ratio has deteriorated since 1985. The issue is not the CAPE ratio, but CAPE regressions that assume it reverts mechanically to its long-run average. Our approach conditions mean reversion in the CAPE ratio on

RCM Alternatives has a great piece (HT Tadas) out outlining what the VIX is, the market for VIX related products, and how to think about volatility as an asset class. It also happens to contain my new favorite quote for anyone thinking about trading volatility: Still, if you cannot see the VIX

In this article Frank Smietana, one of QuantStart's expert guest contributors describes the Python open-source backtesting software landscape, and provides advice on which backtesting framework is suitable for your own project needs. Backtesting is arguably the most critical part of the

What are the research questions? Do variations in aggregate measure of size and activity of sell-side analysts affect the quality of research produced by that industry? Do those same variations in aggregate measures of size and activity of sell-side analysts affect optimism bias in the research

In last week’s commentary, we outline a number of problems faced by tactical asset allocators in actually implementing their views. This week, we explore popular methods for translating a combination of strategic views and tactical views into a single, comprehensive set of views that can be used

This is the third part in a series describing how to approach the creation of a new trading strategy, including everything from idea generation, universe selection, data generation, proper in/out of sample testing, necessary considerations before live trading and the eventual big decision: do I want

Breadth momentum extends traditional absolute momentum approaches for crash protection. Breadth momentum quantifies risk at the universe level by the number of assets with non-positive momentum relative to a breadth protection threshold. Vigilant Asset Allocation matches breadth momentum with a

We study the performance of a comprehensive set of equity premium forecasting strategies that have been shown to outperform the historical mean out-of-sample when tested in isolation. Using a multiple testing framework, we find that previous evidence on out-of-sample predictability is primarily due

Last time, we talked about how to identify stationary time series. Today we continue this line of thought by defining cointegration and looking at its usage in trading. In particular, we will discuss how a pairs trading strategy works. Motivation If we remember that stationarity assumes that a mean

One of the basic principles of technical analysis is that “prices move in trends.” Traders firmly believe that these trends can be identified in a timely manner and used to generate profits and limit losses. Consequently, trend following is arguably one of the most widespread market timing

There have been hundreds of research papers on relative strength momentum since the seminal work by Jegadeesh and Titman in 1993. [1] Relative momentum has been shown to work in and out-of-sample within and across most asset classes. Theoretical results have been consistent, persistent, and robust.

What would you think of a quant strategy that only invests in the most profitable companies? Would it under perform the market or beat the market? If you’re an efficient market person you may think that higher profitability must be priced into equities and therefore at best the strategy would

Continuing from the last post, I will show how using different definitions of passing our out-of-sample test can change our results. How luck can play a role if you use only one strategy to test in out-of-sample. How you split your in-sample(IS) and out-of-sample(OOS) can change results. The

Any frequent reader of our blog knows we are fans of momentum investing. At this point, investment professionals should know that momentum historically works, that momentum is painful, and we have our own opinions on how to implement momentum investing via our Quantitative Momentum Index. Sometimes

We are rather used to reading this disclaimer (or some variation thereof) in mutual fund prospectuses or investment vehicle webpages. Despite warnings, investors and advisors insist on considering past performance (and some other related metrics) as important factors in asset selection. But, are

Newfound specializes in systematic, factor-based approaches to constructing tactical portfolios. While we believe factors like value, momentum, carry, and trend are applicable at the asset class level, care must be taken in designing tactical allocation portfolios. We outline four considerations

What are the research questions? Do factors offer superior diversification benefits relative to assets because factors are less correlated with each other? Does consolidating a larger set of assets into a smaller set of factors reduce noise? Are investors more skilled at relating current information

This article is on the analysis of intra-arrival times of future contract trades, analysing market behaviour, and identification of other particpants’ trading strategy. Intra-arrival time has close relationship with the quantity of each trade. One reason behind this is that many participants use

Compared with machine learning or signal processing algorithms of conventional trading strategies, High Frequency Trading systems can be surprisingly simple. They need not attempt to predict future prices. They know the future prices already. Or rather, they know the prices that lie in the future

In the previous post I revealed a web scraping trick that allows us to defeat AJAX/JavaScript based web pages and extract the tables we need. We also covered how to use that trick to scrape a large volume of options prices quickly and asynchronously using the combination of aiohttp and asyncio. The

As my co-author Andrew Berkin, the director of research for Bridgeway Capital Management, and I explain in our new book, “Your Complete Guide to Factor-Based Investing,” there is considerable evidence of cross-sectional return predictability. Citing more than 100 academic papers, we present the

Traditional portfolio management focuses explicitly on the trade-off between risk and return. Anecdotally, investors often care more about the growth of their wealth. Due to compounding effects, wealth is a convex function of realized returns. Within, we explore geometric mean maximization, an

LASSO stands for Least Absolute Shrinkage and Selection Operator. It was first introduced 21 years ago by Robert Tibshirani (Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B). In 2004 the four statistical masters: Efron, Hastie, Johnstone and

June 2017 Trend Following: DOWN -3.44% / YTD: -16.88% The whole first half of 2017 was negative, with the June result following the same trend. The YTD figure is now well in the red and it would take a good reversal of that equity curve to erase the losses through the second half of the year. Below

This the third in my Hedge Fund Hacks series in which I dig just below the surface of some of the common hedge fund performance statistics. In the previous post I highlighted some of the ways in which Compound Annual Growth Rate can be distorted by chance. In this post I provide a simple hack to

While I am a believer of APT more than of CAPM, I will share some of my findings on CAPM. CAPM has many flaws: there are capital taxes, high transaction cost on illiquid securities with few floating shares, licensed leveraged funds do influence prices with outsized positions, different analyst has a

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

In the previous installment, we discussed the use of a popular asset allocation/market timing rule (10M SMA rule hereafter) to size a short option position. The strategy did not work well as it was the case in traditional asset allocation. We thought that the poor performance was due to the fact

Real estate investment trusts (REITs) are often considered to be a distinct asset class. But, do REITs deserve this designation? While exact definitions for asset class may vary, a number of statistical methods can provide strong evidence either for or against the suitability of the designation. The

Be sure to check out our guest post over at research supersite Alpha Architect: Tactical Asset Allocation: Does the Day of the Month Matter? Backtests of long-term strategies like tactical asset allocation are usually shown trading at the end of the month, both because it makes the analysis simpler

This Free Friday, Free Friday #19, is a user submission! It is a long/short strategy for $IWM - the Russell 2000 ETF. Both the long and the short strategy only have two rules each and only hold for 1 day. Below I’ve posted the long strategy on the left and the short strategy on the right. Short

US Sector Rotation with Five-Factor Fama-French Alphas G. Sarwar (University of Greenwich), et al. June 16, 2017 In this paper we investigate the risk-adjusted performance of US sector portfolios and sector rotation strategy using the alphas from the Fama-French five factor model. We find that

Most long-term approaches to investing, like tactical asset allocation or factor investing, are designed to trade infrequently, generally once a month or once a quarter. This is a feature, not a limitation. Trading infrequently forces a strategy to ignore day-to-day noise and focus on long-term

So far, we’ve discussed the importance of investment universe selection and price momentum in designing a robust asset allocation methodology. If you haven’t read those articles, we would strongly encourage you to do so before proceeding with this one. We lay most of the explanatory and

You’ll recall, I had Andy Kershner on the podcast a few episodes back. Towards the end of that episode, Andy briefly mentioned a cloud-based algo development platform and fund, CloudQuant, which is a subsidiary of Kershner Trading Group… I mention this, because with me on this episode is Morgan

This article is the final project submitted by the author as a part of his coursework in Executive Programme in Algorithmic Trading (EPAT™) at QuantInsti™. Do check our Projects page and have a look at what our students are building. Introduction The Dispersion Trading is a strategy used to

Motivation Trading has gotten a lot faster over the last two decades. The term “short-run trader” used to refer to people who traded multiple times a day. Now, it refers to algorithms that trade multiple times a second. Some people are worried about this new breed of short-run trader making

Why Ferrari or Rolex does not price their products at 149.999 or 12.999 but most of the items you see in your supermarket is priced like 4.99? Because Ferrari never likes to position itself as a bargain. Did you know that we tend to chose the price with less syllables even if the two prices have the

I’m very pleased to announce my DataCamp course on Visualizing Time Series Data in R. This course is also part of the Time Series with R skills track. Feel free to have a look, the first chapter is free! Course Description As the saying goes, “A chart is worth a thousand words”. This is why