Anyone who follows our website should be familiar with the extensive evidence behind our favorite stock selection strategies: Value Investing Momentum Investing The evidence suggests that high-conviction ( We document why high conviction is important for both value and momentum strategies here and

In recent articles we were talking about PCA and ISOMAP, as techniques for dimensionality reduction. On this occasion, we put the focus on T-SNE, in relation with visualization and understanding of multidimensional datasets in a low dimension space, where the human eye can find patterns easily.

It's been a while since my last post. I had planned on writing this particular article about three months ago, but work got in the way of my writing and testing Over the next few weeks I will try to close out this series on momentum rotation using my 60 day ROC example written for AmiBroker.

Algorithmic trading is a field that’s generally quite daunting to beginners, forcing them to juggle learning advanced programming techniques and market mechanics. Throughout the process there’s usually not a lot of guidance, and even less coding examples. Our goal is to demystify this process

Introduction A blog series to contrast the key distinctions between trend following and countertrend strategies during building, testing and trading. In this post we examine the effects of data integrity and simulated trade sample size on backtested performance. Price Data Integrity One of the major

This is a quick update post to let readers know that the pre-order release of Advanced Algorithmic Trading has had a new update, adding over 50 pages of material. This brings the current release up to 250 pages. To access the new content, customers simply need to follow the download link received in

In this final leg of The Checklist tour we'll be looking at the Dynamic Allocation step and touch briefly on ex-post Performance Analysis. Dynamic Allocation Essentially this involves repeating the previous 9-steps on a periodic basis (e.g. a sequence of monthly allocations) according to a

Brexit might have been globally thought of as bad news for the markets, but it was good for trend following. It marked a quick up movement in last month’s performance, quickly reversing the negative performance of the month to turn it back positive, after the 23rd June vote. The YTD performance is

Alpha is the holy grail of asset management: risk-free excess returns generated by investment skill. Alpha is one of the most commonly quoted summary statistics – yet measuring alpha is surprisingly difficult. Without an understanding of measurement uncertainty, fit of our model, or even the risk

The month of June started positive for the trend following index, before a V-shaped movement pre/post-Brexit, that ended the month in positive territory. The YTD figure is still in the red. Please check below for more details. Detailed Results The figures for the month are: June return: 2.94% YTD

Maxime Fages Maxime’s career spanned across the strategic aspects of value and risk, with a particular focus on trading behaviors and market microstructure over the past few years. He embraced a quantitative angle in M&A, fund management or currently corporate strategy and has always been an

We are now collecting a lot of data. This is a good thing in general. But data collection and data storage capabilities have evolved fast. Much faster than statistical methods to go along with those voluminous numbers. We are still using good ole fashioned Fisherian statistics. Back then, when you

As sources and volumes of news have grown, so has the techniques to gather, extract, aggregate and categorise them. Important news can result in large positive or negative returns. However, owing to many news sources, we need to ask a fundamental question: Is news analytics profitable in every

This week on our Masters in Business podcast, we speak with Wes Gray, former Captain in U.S. Marines, and founder of Alpha Architect. He studied economics at Wharton, graduated with honors before getting his MBA and PhD at University of Chicago. Instead of heading to Wall Street like so many MBAs,

Recently a range of alternative risk premia products have been developed promising investors hedge fund/CTA like returns with higher liquidity, transparency and relatively low fees. The attractiveness of these products rests on the assumption that they can deliver similar returns. Using a novel

Factor models are not just for long-term investors. They can help traders find out why their strategies are suffering. This talk highlights the difference between factor and "alpha" models, and what short-term factors traders can use.

Charlie Bilello, one of my favorite follows on Twitter, analyzed the relationship between market valuation and future returns (over various time horizons) in a recent post Valuation, Timing, and a Range of Outcomes. The post contained some very insightful tables, such as the one below, where he

Is a 100% stock allocation crazy? As long as one addresses their needs for liquidity (as to avoid extracting capital from the markets at bad times) and can tolerate the market price volatility, a 100% or near-100% allocation to equities is not as outlandish as one might suspect. Focusing on

In my 10+ years’ full-time trading career, I have found very few tools and tactics that would get my attention so deeply as Market Internals. In 2014, I spent about 6 months in a row with this unique traders tool, exploring its possibilities every single day, searching for new and creative

In a new SeekingAlpha contribution (pending approval) we combine PAA’s protective multi-market breadth approach with a generalized momentum metric based on correlation hedged returns. The resulting model is called Generalized Protective Momentum (GPM). In this blogpost the correlation hedge is

I am in the process of learning to code in Python and am, I must admit, no programming genius. So I was delighted to see that George Pruitt, best known for his book on TradeStation’s EasyLanguage (Building Winning Trading Systems with TradeStation) had written a new book that covered not only the

One of the dangers of being a quantitative investor is that when you see patterns in historical data you might wrongly assume they will repeat. Put another way, you might believe an effect is driven by a genuine relationship, when in reality the results are spurious and the result of luck. We wrote

Investors equate “alpha” to outperformance. A high alpha fund presumably delivers substantial excess returns relative to its benchmark. True alpha is short-hand for manager skill. Statistically, alpha simply is the result of a linear regression between two return streams. The regression finds

In this post we see how to compute historical volatility in python, and the different measures of risk-adjusted return based on it. We have also provided the python codes for these measures which might be of help to the readers. Introduction Volatility measures the dispersion of returns for a given

Summary Most advisors have a fund checklist or screen: a list of selection criteria they employ to help determine whether a fund is worthy of further evaluation. The vast majority of checklists we see employ a performance screen based on a 3- or 5-year period. We believe that employing such a

I still have a Ken Griffey Jr. Rookie Card. To be honest, I don’t even know where the thing is, but I hope it is it worth a ton of money at this point (although I doubt it). So disclaimer up front: I dabbled in baseball card trading back in the day. And for all of you out there who used to trade

It’s been well-documented that, in equity investing, assets have earned premiums because they are exposed to the risks of a certain factor. Given that the literature provides us with a veritable factor “zoo” (there are more than 300), for investors to consider adding exposure to a factor, it

The best quant mashup links for the two weeks ending Saturday, 06/25 as voted by our readers: Recommended Reading [Robot Wealth] Binary Options: Scam or Opportunity? [Financial Hacker] Some harmless data-mining: Testing individual words in EDGAR filings [Greg Harris] Simple Machine Learning Model to

We show that the market for baseball cards exhibits anomalies that are analogous to those that have been documented in financial markets, namely, momentum, price drift in the direction of past fundamental performance, and IPO under performance. Momentum profits are higher among active players than

As traders, we spend a lot of time thinking about our entries into a trade. What stock, commodity or currency to choose, when is the best timing, etc. But what if the entries don’t matter? What if trading is all about the exits? Ok, that’s a really simple-minded statement, but I’m a little

While it’s certain that short-term volatility exchange traded products (ETPs) like VXX, TVIX, and UVXY are doomed to march towards zero, their decay rates are not consistent. Things like bear markets and big corrections can cause big upward swings. On the downside, the term structure of VIX

Machine Learning world is quite big. In this blog you can find different posts in which the authors explain different machine learning techniques. One of them is clustering and here is another method: Hierarchical Clustering, in particular the Ward’s method. You can find some examples in

If there’s one thing I’ve done a lot of over the last few years, reading would be it. I’ve devoted a great deal of time to devouring any material that I thought might give me an edge in my trading – textbooks, academic papers, blog articles, training courses, lecture notes, conference

There is a lot more luck involved in investing than people think. I’m not saying there isn’t skill involved in investing or that there aren’t ways to outperform the market over time. Even if you have a process that can be shown to outperform the market over long time periods, there can be a

For those who prefer a little more rigor in their quantitative research, I can offer more a somewhat more substantive statistical argument in favor of the IBS indication discussed in my previous post. Specifically, we can show quite convincingly that the IBS process is stationary, a highly desirable

In some ways, investing is simple. After all, we all want the same things. High returns. Low volatility. Small max drawdowns. Unfortunately, it’s very difficult–if not impossible–to have your cake and eat it too. There are always tradeoffs among these desires that have to be managed by

In the previous article on the Cointegrated Augmented Dickey Fuller (CADF) test we noted that one of the biggest drawbacks of the test was that it was only capable of being applied to two separate time series. However, we can clearly imagine a set of three or more financial assets that might share

Python has emerged as one of the most popular language to code in Algorithmic Trading, owing to its ease of installation, free usage, easy structure, and availability of variety of modules. Globally, Algo Traders and researchers in Quant are extensively using Python for prototyping, backtesting,

"Predicting rain doesn't count. Building arks does." Warren Buffett, The Oracle of Omaha (born 1930) In this penultimate leg of the tour we'll be visiting 2 more attractions along Via Meucci, Construction and Execution. Construction Portfolio Construction is another yuge! topic.

We’re recently getting more and more contracts of developing systems for trading binary options. This calls for a closer look. Binary options resemble financial instruments, but are widely understood as a scheme to separate naive traders from their money. And indeed, binary options brokers make no

This post will cover a function to simplify creating Harry Long type rebalancing strategies from SeekingAlpha for interested readers. As Harry Long has stated, most, if not all of his strategies are more for demonstrative purposes rather than actual recommended investments. So, since Harry Long has

My last post, “Will bonds deliver crisis alpha in the next crisis?,” created quite a stir on the blogosphere. The underlying assumption of the analysis is that stocks are a core component of a portfolio and bonds are included to diversify the portfolio. The key takeaway from my analysis is that

A common way to describe a mean reversion trade is a rubber band that stretches away and then snaps back. Something that Steve, my trading buddy, and I discuss when a trade keeps going against us is that the rubber band has broken. I have never tested that concept. Meaning after N day sell-off, are

How fast should individuals plan to grow net worth as they age? To investigate, we examine median levels of household (1) total net worth and (2) net worth excluding home equity from several vintages of U.S. Census Bureau data. We make the following head-of-household age cohort assumptions: “Less

In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of a

There are a wide variety of Machine Learning techniques that help us to solve Big Data problems. In this post we talk about how to apply Lasso Regression in Portfolio Management. You may have heard of this technique in the past, for that reason I’ll try to explain it in a brief introduction. Lasso

Today we'll be visiting 2 sites along Via Meucci, Evaluation and Attribution. Evaluation We need some way to measure the goodness of the ex-ante portfolio across the scenarios from the Aggregation step, and for this Meucci introduces the concept of a Satisfaction index. Given the distribution

Traders in the derivative market often exercise one of the following: Call option or Put Option. “Call option” is a financial contract between a buyer and seller, whereby the buyer has the right, but not the obligation, to buy an agreed quantity of a financial instrument from the seller of the

In the previous article on cointegration in R we simulated two non-stationary time series that formed a cointegrated pair under a specific linear combination. We made use of the statistical Augmented Dickey-Fuller, Phillips-Perron and Phillips-Ouliaris tests for the presence of unit roots and

Think only a bear market can keep returns of a 60/40 near 0%... think again. Given the huge opportunity cost of allocating to cash or bonds at current yield levels, even generally optimistic return assumptions for stocks are enough to keep portfolio level returns near 0% real. The goal of this post