One of the most underestimated feature of the financial asset distributions is their kurtosis. A rough approximation of the asset return distribution by the Normal distribution becomes often an evident exaggeration or misinterpretations of the facts. And we know that. The problem arises if we(...)

While the underperformance of high yield bonds since my post The Case Against High Yield has certainly made high yield bonds more attractive (yields went from sub 6% to north of 8%), I still prefer the risk/return profile of a stock/bond allocation (more here). For those that are looking for a(...)

Our Quantitative Momentum (QM) system seeks to identify stocks with the highest quality “momentum.” We consider the term momentum to mean a continuation of past returns—past winners tend to be future winners, while past losers tend to be future losers. How can we exploit this phenomenon? At Alpha(...)

I’ve recently written a few posts about the persistency of cross-sectional momentum. But it seems that eventually stocks that go up have to come down. Not only is this somewhat intuitive, but the existence of stock price reversals is also well documented. But actually momentum persistence and price(...)

Everybody knows about the Central Limit Theorem, but have you ever seen a visual demonstration? The central limit theorem states that, given certain conditions, the mean of a large number of iterates of independent random variables, will be approximately normally distributed, regardless of the(...)

To date on QuantStart we have considered two major quantitative backtesting and live trading engines. The first arised from the Event-Drive Backtesting series I wrote back in March 2014. The second is QSForex, an open-source backtest and live trading engine that hooks into the OANDA Forex Broker(...)

With Januaries (a month in which lagged "losers" typically outperform lagged "winners") excluded, the average monthly return to a momentum strategy for U.S. stocks was found to be 59 bps for non-quarter-ending months but 310 bps for quarter-ending months. The pattern was(...)

Jeff Swanson's Trading System Success web site is often worth a visit for those looking for new trading ideas. A recent post Seasonality S&P Market Session caught my eye, having investigated several ideas for overnight trading in the E-minis. Seasonal effects are of course widely(...)

As a financial analyst or algo trader, you are so often faced with information on, inter alia, daily asset trading in a form of a daily returns matrix. In many cases, it is easier to operate with the return-series rather than with price-series. And there are excellent reasons standing behind such(...)

It is important to know the difference between high frequency and low frequency trading before discussing the specific trading strategies. Opinions tend to differ on what constitutes high frequency but by and large there is a consensus that the duration of asset holding period is very low, ranging(...)

Ever since the global financial crisis, the real interest rates of developed economies have remained in negative territory. Nominal interest rates hover near zero, and inflation rates, although quite low for historical standards, have remained positive (in most countries, at least on average).(...)

First draft of 'JavaScript for Financial Analysts' Chapter 10. ~ D3 is a foreboding beast. It eschews classic programming styles in favour of a more functional approach. Luckily however, if you have come this far, get ready to sit back and enjoy of the fruits of your labour. Almost every(...)

OK, I will admit I am a bit late with this one. I’ll go ahead and blame “The Holidays”. Anyway, if you were wondering when it might be a good time to hold real estate stocks, the answer might well be, um, “Now”. (Jay Kaeppel Interview at BetterSystemTrader.com) Favorable Seasonal Period for Real(...)

The Ivy Portfolio spreadsheet track the 10 month moving average signals for two portfolios listed in Mebane Faber’s book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that have trading signals based on long-term(...)

The best quant mashup links for the week ending Saturday, 11/28 as voted by our readers: Frog in the Pan: Identifying the Highest Quality Momentum Stocks [Alpha Architect] Better Tests with Oversampling [Financial Hacker] Bring More Data [Dual Momentum] A framework for rapid and robust system(...)

Andrew Gibbs has been involved in the financial markets since 2001 and is the founder and CEO of Halifax New Zealand. Andrew has extensive experience in all forms of equity and derivative contracts, managing millions of dollars and trading a number of markets around the world. In this episode we(...)

Stop-loss strategies are commonly used by investors to reduce their holdings in risky assets if prices or total wealth breach certain pre-specified thresholds. We derive closed-form expressions for the impact of stop-loss strategies on asset returns that are serially correlated, regime switching,(...)

We contrast the time-series and cross-sectional performance of three popular investment strategies: carry, momentum and value. While considerable research has examined the performance of these strategies in either a directional or cross-asset settings, we offer some insights on the market(...)

We show that the standard equation-by-equation OLS used in performance evaluation ignores information in the alpha population and leads to severely biased estimates for the alpha population. We propose a new framework that treats fund alphas as random effects. Our framework allows us to make(...)

Predicting volatility is a very old topic. Every finance student has been taught to use the GARCH model for that. But like most things we learned in school, we don't necessarily expect them to be useful in practice, or to work well out-of-sample. (When was the last time you need to use(...)

Somewhat related to the idea of acceleration that I have been writing about recently, is the concept of persistent momentum. That is, do stocks that have performed well over several periods, beat those that have done well for only one period? This idea was tested by Hong-Yi Chen, Pin-Huang Chou and(...)

The PCA Model in the FX Market: Economic Factors and Volatility Modelling

Risk-based asset pricing theory suggests, simply, that assets bearing a higher risk should compensate investors with higher returns. While most papers investigating the risk-return relationship of assets are focused on equity markets, surprisingly few studies explore this phenomenon in currency(...)

Several studies have attributed the high excess returns of the momentum strategy in the equity market to investor behavioral biases. However, whether momentum effects occur because of investor underreaction or because of investor overreaction remains a question. Using a simple model to illustrate(...)

First draft of 'JavaScript for Financial Analysts' Chapter 9. ~ The web dominates our communication. The driver of this crushing victory? The humble webpage increasingly coupled with JavaScript. Up until now we have focused on the basics of how to code JavaScript in a functional manner,(...)

Momentum has received a lot of attention in the asset-pricing literature over the past several decades, and for good reason. Trending behavior is a staple in markets. In contrast with other pricing “anomalies”, short-term return persistence—positive and negative—is a robust factor across asset(...)

This is the first article in a series where we will look at the backtest results of selling at-the-money (ATM) options straddles on the Russell 2000 index (RUT). In the prior series, we looked at the performance of this same strategy on the SPX. For background on the setup for the backtests, as(...)

Important preface: This post is in no way intended to showcase a particular trading strategy. It is purely to share and demonstrate the use of the framework I’ve put together to speed the research and development process for a particular type of trading strategy. Comments and critiques regarding(...)

The enterprise multiple (EM) predicts the cross section of international returns. The return predictability of EM is similarly pronounced in developed and emerging markets and likewise strong among small and large firms. An international portfolio of low-EM firms outperforms a portfolio of high-EM(...)

There are a number of ways to become more confident in the idea of factor investing. The simplest is to just compare the results of factor portfolios to those based on other methods. This will show outperformance but it won’t give us a reason for the outperformance. So anything that can give us(...)

In this post I am going to take a look at what an investor can do to improve a hedge fund investment through the use of dynamic capital allocation. For the purposes of illustration I am going to use Cantab Capital’s Aristarchus program – a quantitative fund which has grown to over $3.5Bn in assets(...)

First draft of 'JavaScript for Financial Analysts' Chapter 9. ~ The web dominates our communication. The driver of this crushing victory? The humble webpage increasingly coupled with JavaScript. Up until now we have focused on the basics of how to code JavaScript in a functional manner,(...)

I often read that valuations don't matter over the short-term (a case often cited against market timing). Over very short periods (hours, days, etc...) this certainly may be true, but while there can be a lot of variability around month-to-month or year-to-year performance, I completely(...)

We test a frog-in-the-pan (FIP) hypothesis that predicts investors are inattentive to information arriving continuously in small amounts. Intuitively, we hypothesize that a series of frequent gradual changes attracts less attention than infrequent dramatic changes. Consistent with the FIP(...)

The last few months have seen a flurry of activity in terms of new courses being created for the R programming language. Udemyis one such online venue that provides a surprisingly broad array of topics related to the R language. These topics include statistical analysis, regression, data science,(...)

Summary Due diligence is an important practice in our industry – and one that should be ever-evolving. There are some questions we receive on due diligence questionnaires that are well intentioned, but we think can be improved. Finally, in doing due diligence, we think that after the question(...)

The more data you use for testing or training your strategy, the less bias will affect the test result and the more accurate will be the training. The problem: price data is always in short supply. Even shorter when you must put aside some part for out-of-sample tests. Extending the test or(...)

Historically Thanksgiving week has shown some very strong tendencies. The table below is one I have shown a few times over the years. I decided to update it again this year. 2015-11-23 image1 Monday and Tuesday don’t show anything suggesting an edge. Monday’s total return was actually negative(...)

The best quant mashup links for the week ending Saturday, 11/21 as voted by our readers: Unsupervised candlestick classification for fun and profit – part 2 [Robot Wealth] Searching for an Efficient Market Regime Filter [Helix Trader] How the Number of Firms and Holding Periods Affect Momentum(...)

Since my last post I have been doing a fair bit of online research and fortunately I have discovered the following papers, which mesh nicely with what I am trying to do with Conditional Restricted Boltzmann Machines to model time series:- Deep Learning Architecture for Univariate Time Series(...)

Jay Kaeppel has over 25 years experience in the financial markets. He has worked as the Head Trader for a CTA and published a number of popular trading books on Futures, Options and Stock Market Seasonality. He also spent a number of years writing a weekly column titled “Kaeppel’s Corner” and(...)

Matt wrote me a while back about how thinking about Value and Growth lead you to Mean Reversion and Momentum. I like connections. Here's the line of reasoning. Value stocks are priced low by whichever definition you feel like using, but when investing in value stocks you are betting against(...)

Several months ago we posted an article called “Bring Data” where we showed the importance of having abundant data for system development and validation. This was further reinforced to us recently when someone brought us some additional U.S. stock sector data. Previously, we only had sector data(...)

This study investigates whether the risk adjusted returns of a global REIT portfolio would be enhanced by adopting a trend following strategy (which is an absolute concept), a momentum based strategy (which is a relative concept and requires individual country allocations), or indeed a combination(...)

In the last two posts I wrote about acceleration, where returns over consecutive periods are increasing. I’ve received several emails about the idea. These investors (with about 80 years of experience between them) really like the concept. It resonated with the way they saw the world. When looking(...)

Does the Thanksgiving holiday, a time of families celebrating plenty, give U.S. stock investors a sense of optimism that translates into stock returns? To investigate, we analyze the historical behavior of the S&P 500 Index during the three trading days before and the three trading days after(...)

Check out our new books section, curated by Jacques Joubert of Quants Portal. The backstory: I wanted to put together a collection of quantitative trading books as deep and wide as our quant mashup. The problem was that, because of my “get to the point” nature, my reading consists mostly of posts(...)

There has been a great deal of focus by the academic community in recent years on fine-tuning the various factor models used to explain the differences in returns of diversified portfolios. Marie Lambert, Boris Fays and Georges Hubner contribute to the literature with their 2015 paper, “Size and(...)

Kewei Hou and Roger Loh have a fun paper on the idiosyncratic volatility puzzle, which is set to be published in the Journal of Financial Economics. The idiosyncratic volatility puzzle is associated with the empirical evidence which suggests that stocks with higher idiosyncratic volatility(...)

First draft of 'JavaScript for Financial Analysts' Chapter 8. ~~ As we saw in the previous chapter, doing things asynchronously is really appealing when you can pull it off elegantly. A bit like juggling, there's a lot going on, but a skilful juggler only ever interacts with one ball(...)