This paper investigates the size, value and momentum effects in 18 emerging stock markets during the period 1990−2013.We find that size and momentum strategies generally fail to generate superior returns in emerging markets. The value effect exists in all markets except Brazil, and it is robust to

I'm very proud of the following graph. Below I've shown the average number of clickthroughs a link receives from our website (excluding RSS, Twitter and Stocktwits) broken out by the number of votes cast by our readers. Votes by Clickthroughs Clearly (and way more starkly than I expected)

This review will review the “Adaptive Asset Allocation: Dynamic Global Portfolios to Profit in Good Times – and Bad” book by the people at ReSolve Asset Management. Overall, this book is a definite must-read for those who have never been exposed to the ideas within it. However, when it comes

In my previous posts I was talking about my experience learning the basics of service oriented applications. After many days and nights struggling with all the theory, practicing and trying different concepts and libraries, it forced me to go two steps back and watching the whole “big picture”

If you're working with daily data (without access to intraday data) and need to calculate volatility, then using close-to-close squared returns is by far not the best way to go. Trades and quants know that it is a very noisy metric, and come up with few work-arounds. In this post I will do a

Summary Style boxes give us the impression that "growth" and "value" sit at opposite ends of the spectrum. In reality, whether a company is growing or shrinking ("growth") is independent of whether a security is cheap or expensive ("value"). To align with the

Managing risk via tactical asset allocation (TAA) offers a number of encouraging paths for limiting the hefty drawdowns that take a toll on buy-and-hold strategies. But what looks good on paper can get ugly in the real world. There's a relatively easy fix, of course: consider the total number

I recently read “Adaptive Asset Allocation” ( link to the book) by Butler, Philbrick and Gordillo of ReSolve Asset Management. The book is the culmination of research developed over the years by the ReSolve team towards the next generation approach of dynamic asset allocation. The core

One of the most fertile areas of research is in factor rotation. Any asset class, investment strategy, or factor, despite working well over time, goes through periods of over and underperformance. Those periods set the stage for future reversion, and are largely due to fund flows and people chasing

For those of you who have been following my blog posts for the last 6 months will know that I have taken part in the Executive Program in Algorithmic Trading offered by QuantInsti. It’s been a journey and this article serves as a report on my final project focusing on statistical arbitrage, coded

These are the best quant mashup links for the week ending Saturday, 02/27 as voted by our readers: Build Better Strategies! Part 3: The Development Process [Financial Hacker] Volatility Futures and S&P500 Performance [Blue Sky AM] New Book from GestaltU: Adaptive Asset Allocation [Amazon]

Last month a millennial emailed me saying he liked my book. But he wondered if the outperformance of dual momentum would disappear if he used dollar cost averaging (DCA) because he would not be able to buy cheaply during bear markets. This is because dual momentum reduces bear market drawdowns. I

About this Course Our Python 1-day intensive course is addressed to all who wishes start programming in Python language straight away! We will cover the fundamentals of Python (2.7, 3.5), numerical aspects of coding, and over 100 individually crafted examples covering various applications coming

Key Points 1. Factor returns, net of changes in valuation levels, are much lower than recent performance suggests. 2. Value-add can be structural, and thus reliably repeatable, or situational—a product of rising valuations—likely neither sustainable nor repeatable. 3. Many investors are

This is my fourth article in a series devoted to helping investors stay disciplined in the face of market volatility—and even lengthy periods of underperformance by risky assets. The first was a December 2015 post dealing with what I call “investment depression.” The second was a January post

A question… When an overvalued security continues rising in price, does that mean the valuation indicator is broken? If you listen to many investors, the answer would be “yes.” An oft-repeated phrase I hear goes something like: “ABC valuation indicator has been flashing expensive since XX/XX

We’ve discussed the use of predictive regressions in the past. Here is an article to learn a bit more about the technique. And while the idea sounds cool, and could even be relabeled a low-tier “machine-learning” technique if someone wanted to sell the idea, we can’t find anything exciting

First draft of 'JavaScript for Financial Analysts' Chapter 16. ~ This book was aimed at introducing a VBA replacement. No doubt VBA has its place, but it is also stuck in that same niche, unable to evolve and in turn not giving VBA developers a chance to grow. Set in stark contrast is the

The period May 1 to the turn of the month of November (last five trading days October) has historically produced negligible returns. The rest of the year (late October to the end of April) has essentially all the year's gains. In this paper we show that there is a statistically significant

Tomas Nesnidal has been a full-time trader for over 11 years, specializing in automated algorithmic trading strategies. He has experience with a number of trading styles, including option trading, spread trading, statistical arbitrage and market internals but in this episode we’re going to discuss

This is the third part of our interview with a senior quantitative portfolio manager at a large hedge fund. In the first part, she discussed the theoretical phase of creating a quantitative trading strategy. In the second part, she described the transition into “production.” This interview

One question often asked in forums and blogs is how to adjust stock prices in order to take into account dividend payments. There are several reasons why we may be interested in adjusting stock prices: Analyzing total returns taking into account dividend reinvestments for reporting (performance,

This is the third part of the Build Better Strategies series. In the previous part we’ve discussed the 10 most-exploited market inefficiencies and gave some example algorithms for trading strategies. In this part we’ll analyze the general process of developing a model-based trading system. As

One of the most commonly cited maxims is that market timing is impossible. In fact, empirical evidence makes a compelling case that market timing is feasible and can yield substantial economic benefits. What’s more, we even understand why it works. For the typical portfolio investor, applying

In the previous article in the Advanced Trading Infrastructure series I discussed and presented both the code and initial unit tests for the Position class that stores positional information about a trade. In this article we will consider the Portfolio class, used to store a list of Position

Do Volatility Futures Provide Useful Information for Future S&P500 Performance? Volatility or VIX Futures are based on the S&P500 index and are calculated from the implied volatility of different option strike prices across different expiration periods. In contrast to the VIX index, VIX

Investors often focus their analysis on benefits. In the finance industry, we’ve distilled this down to a single metric: alpha. Benefits and risk require separate analysis. Increasing benefits does not necessarily reduce risk or even leave it unchanged. In practice, increasing alpha can actually

Risk is not a simple entity, it comes in many flavours, and requires respect and consideration even when you least expect. If one was to try ‘totally avoid’ risk in their market endeavours they would most likely just be holding cash – where are the returns in that? The truth is that in almost

Python in Sydney: Course+Workshop Wednesday, March 16, 2016

I’ve been off the beaten path for the last few weeks in East Africa, so I’m long overdue one of these “best of” posts. Below are the best quant mashup links while I was away, as voted by our readers: Stock Market Prices Do Not Follow Random Walks [Turing Finance] Fitting time series models

Given the downturn in the energy sector and the persistent economic weakness abroad, investors have become increasingly focused on the possibility of a U.S. recession. In this piece, I’m going to examine a historically powerful indicator that would seem to rule out that possibility, at least for

That graph looks like a bunch of spaghetti, I realize. But I’ll explain! I’m back testing Genotick. It’s an open-source machine-learning java script. Probably to the developer’s dismay, I’m always throwing things at it to make it break. Much like a small child throwing a temper tantrum,

I've recently read a great post by the turinginance blog on how to be a quant. In short, it describes a scientific approach to developing trading strategies. For me personally, observing data, thinking with models and forming hypothesis is a second nature, as it should be for any good engineer.

In my previous post, I introduced the messaging topic. Now its time to talk about what I found on the message framework universe. To get a overview about past and upcoming topics, please have look here: Content++. There were several message frameworks I was come across and played around. The first

Psychology research suggests that when we make predictions, we suffer from “representative bias,” and mistakenly overweight observations that fit a particular narrative, and fail to consider base rate probabilities. For example, if we flip a coin 5 times and it shows up H, H, H, H, H, we may

In this post, I continue trying to fit the daily log returns of TASI index using heavy-tailed distributions. In the previous post, I used Pareto distribution to model TASI index’s left tail. In this post, I use Student t distribution. Recently, Student t distribution has been used widely by

Analyzing history as a guide to the future is riddled with caveats, but if you’re mindful of the limitations there’s a mother lode of perspective waiting to be mined in the cause of modeling relationships in macro and markets. One of the more useful techniques in this corner: impulse-response

In our 2016 Market Outlook (available on our website), we discuss expected real returns for U.S. equities over the next decade. The picture isn't pretty. A bear market may be just what the doctor ordered. U.S. Large-Cap Expected Real Return Forecast Horizon Jack Bogle 2.0% 10 Years Research

Blackjack odds are as good as you’ll get at most casinos. In most cases, the casino has just a 1% edge versus the gambler. So in a given night, you can go on a great run and win a lot of money playing blackjack. But of course if you played every day, all day, your odds of a sustained run steadily

The existence of risk premia has been widely documented in the academic literature over the past decades. Until now they have typically been handled as separate phenomena for specific markets or asset classes and thus examined independently. This study analyses risk premia across a variety of asset

For almost five decades, the literature on the investment performance of mutual funds has found that very few managers possess sufficient stock-picking or market-timing talent to allow them to consistently and reliably produce positive risk-adjusted performance after considering their fees. In other

This is the second part of our interview with a senior quantitative portfolio manager at a large hedge fund. In the first part, we covered the theoretical phase of creating a quantitative trading strategy. In this part, we cover the transition into “production.” You can read the first part of

The world of finance is no stranger to fashion and Low volatility equity investing has recently attracted serious interest from the investment community. Its popularity has led to doubts regarding the valuation level for this overcrowded arena. Just look at the current market caps of the most

If you own last year’s laggards you are probably wondering what all the fuss over the market is about. It has been tough sledding for the leaders so far this year as they have underperformed the laggards by quite a bit. In one of the models we track, the laggards moved in to positive territory

I read a blog post recently that began “suppose you have a trading system that works well on low-volatility days…” and I thought, hmm. Is that a thing? Is there an edge to low-volatility days vs high volatility days? Let’s turn this blog post into a speculator’s version of Dude, What Would

Josh Brown (i.e. The Reformed Broker) recently shared the aptly titled post How to Make Volatility Your Bitch highlighting how dollar cost averaging into a volatile market can lead to higher overall returns: Door number one – you spend 15 years putting $1000 into an investment every month for 15

We are happy to announce PortfolioEffectEstim toolbox availability for both R & MATLAB. It is designed for high frequency market microstructure analysis and contains popular estimators for price variance, quarticity and noise. For R https://cran.r-project.org/web/packages/PortfolioEffectEstim/

Summary Active strategies are often defined by the factor tilts they take on. For factor tilts to continue to out-perform the market over the long-run, they must exhibit premium volatility that causes short-term under-performance. Since alpha is zero-sum, investors that fold during periods of

We demonstrate that weak trading signals, which do not offer high risk-adjusted returns on their own, can be combined into a powerful portfolio. In other words, no need for holy grails when researching signals. We start our experiment with some key assumptions. We have 20 signals with annualized log

Quandl will soon be offering intra-day data (1 min bars). Rock on ! I was kindly given some data to test out (see below). I can’t say much more than this but keep an eye out for an official announcement soon 🙂 With both QuantGo and Quandl offering reasonably priced intra-day data, smaller trading