In an earlier post I was looking at distance measures for clustering. In a still earlier post I had referred to analyzing hedge fund regulatory data using clustering to try to put the funds into groups by inferred strategy. I had to solve a problem with clustering that has being bothering me for a

The concept of diversification is based on the concept that a trader can reduce his risk exposure by entering several positions at the same time. The success of a traders portfolio is therefore based on reducing risk rather than maximizing returns. A trader should be able to withstand a string of

A few weeks back i wrote a post including the source code for a Monte Carlo simulation function in R. The idea was to randomly sample daily returns produced by a backtest and build a confidence interval distribution of the middle 50% and 90% of returns. Since then Brian Peterson got in touch with me

Conventional momentum strategies rely on 12 months of past returns for portfolio formation. Novy-Marx (2012) shows that the intermediate return momentum strategy formed using only twelve to seven months of returns prior to portfolio formation significantly outperforms the recent return momentum

Summary Many tactically risk-managed strategies use trend following to manage the risk of severe drawdowns, but in sideways markets, like those experienced in 2011 and 2015, trend following ends up lagging the market by buying high and selling low. As with insurance policies or static allocations to

This paper documents a new empirical fact. Long-short anomaly returns are strongly related to the day of the week. Anomalies for which the speculative leg is the short (long) leg experience the highest (lowest) strategy returns on Monday. The exact opposite pattern is observed on Fridays. The

What is measurement error bias? Errors-in-variables, or measurement error situation happens when your right hand side variable(s); your x in a y_t = \alpha + \beta x_t + \varepsilon_t model is measured with error. If x represents the price of a liquid stock, then it is accurately measured because

The best quant mashup links for the two weeks ending Saturday, 04/23 as voted by our readers: Lossless Compression Algorithms and Market Efficiency? [Turing Finance] You can’t beat all the chimps [Following the Trend] My Year-Long Experience as the Fastest Form-4 Trader [Greg Harris] Are 3-year

Mad Men watchers may recognize the name Bernbach from the quote above. Bernbach is referred to in the second season as the innovative competitor firm that challenges Sterling Cooper's orthodoxy. Bill Bernbach was the brain behind several successful campaigns, including Avis' We Try Harder

Some weekend reading for trend-followers who want to question their beliefs. Valeriy Zakamulin is an animal when it comes to generating research on moving averages. We’ve done a lot of the same work, but we’re too lazy to tabulate the results in an academic paper format. king of ma The king of

The Market Portfolio is NOT Efficient: Evidences, Consequences and Easy to Avoid Errors Pablo Fernandez (University of Navarra), et al. March 16, 2016 The Market Portfolio is not an efficient portfolio. There are many evidences that tell us that: the equal weighted indexes have beaten their

fidlr is an RSutio addin designed to simplify the financial data downloading process from various providers. This initial version is a wrapper around the getSymbols function in the quantmod package and only Yahoo, Google, FRED and Oanda are supported. I will probably add functionalities over time.

If history is any guide, we’re standing at the edge of 40%–96% returns over the next two years. This isn’t wishful thinking or wild speculation. I’m not selling anything. Rather, I’m just reporting historical gains from a market set-up that’s repeating itself right now. So what’s going

This paper considers several popular portfolio implementation techniques that maximize exposure to value and/or momentum stocks while taking into account transaction costs. Our analysis of long-only strategies illustrates how a strategy that simultaneously incor- porates both value and momentum

R/Finance 2016 is less than a month away and, as always, I am very much looking forward to it. In past years, I have elaborated on what puts it among my favorite conferences even though I am not a finance guy. R/Finance is small, single track and intense with almost no fluff. And scattered among the

In this post we discuss sentiment analysis in brief and then present a basic sentiment analysis model in R. Sentiment analysis is the analysis of the feelings (i.e. attitudes, emotions and opinions) which are expressed in the news reports/blog posts/twitter messages etc., using natural language

The trend following model by Kaufman says that trading by the direction of the trend is a conservative approach to the markets. Kaufman’s Market Efficient Model states that longer trends are the most reliable but they respond rather slowly to changing market conditions. The main argument of the

I apologize in advance for this rather "wonkish" post, which is aimed chiefly at the high frequency fraternity, or those at least who trade intra-day, in the equity markets. Such minutiae are the lot of those engaged in high frequency trading. I promise that my next post will be of more

Bagging and Boosting are both ensemble methods in Machine Learning, but what is the key behind them? Bagging and Boosting are similar as they are both ensemble techniques, where a set of weak learners are combined to create a strong learner that obtains better performance than a single one. So,

The Shiller cyclically adjusted (for inflation) price-to-earnings ratio—referred to as the CAPE 10 because it averages the last 10 years’ earnings and adjusts them for inflation—is a metric used by many to determine whether the market is undervalued, fairly valued or overvalued. Employing a

In this paper, we employ a unique dataset of actual US dollar (USD) forward positions against a number of currencies taken by so-called Commodity Trading Advisors (CTAs). We investigate to what extent these positions exhibit a pattern of USD carry trading or other patterns of currency trading over

Jacques Joubert of Quants Portal, curator extraordinaire of the books at Quantocracy, has collaborated with Robot Wealth to add the humble beginnings of a Machine Learning section to our library. Denizens of Quantocracy know Robot Wealth well. Within months of launching his blog, RW had already

Developing confidence about a portfolio strategy’s track record (or throwing it onto the garbage heap), whether it’s your own design or a third party’s model, is a tricky but essential chore. There’s no single solution, but a critical piece of the analysis for estimating return and risk,

In a commentary a few weeks ago entitled Growth Is Not “Not Value,” we discussed a problem in the index construction industry in which growth and value are often treated as polar opposites. This treatment can lead to unexpected portfolio holdings in growth and value portfolios. Specifically, we

This is not quant related, but I found it interesting and thought it worth sharing for the benefit of our friends in the quant blogosphere. Long-time readers remember that we rebranded from The Whole Street to Quantocracy at the start of April, 2015. The rebranding came with changes to our site, but

In Hacking The Random Walk Hypothesis we applied the NIST suite of cryptographic tests for randomness to binarized daily market returns. Overall the NIST suite failed on the data. This result was taken to mean that markets are not quite the "coin flipping competition" famously posited by

This is a quick update to let the QuantStart community know what has been happening in the last few months as it has been an exciting time "behind the scenes" of the site. Firstly, I spoke at the Quantopian QuantCon conference in New York last week. The conference was absolutely fantastic,

Factors are a way to identify unique alpha sources. Factors often have a “light” and “dark” side. While the light side is expected to outperform the dark side, often the light side also outperforms the market and the dark side underperforms the market. The outperformance and underperformance

This post will shed light on the values of R^2s behind two rather simplistic strategies - the simple 10 month SMA, and its relative, the 10 month momentum (which is simply a difference of SMAs, as Alpha Architect showed in their book DIY Financial Advisor. Not too long ago, a friend of mine named

The prediction of extreme rare events (EREs) in the financial markets remains one of the toughest problems. Firstly because of a very limited knowledge we have on their distribution and underlying correlations across the markets. Literally, we walk in dark, hoping it won’t happen today, not to the

Backtesting and execution are such key parts of algorithmic trading so choosing the wrong platform can have a huge impact on our trading. There are loads of trading platforms available and a lot of considerations which need to be made when choosing one that suits our needs, so in this episode

Comparing a strategy’s performance to a Buy-and-Hold strategy is quick and easy. But there is a good chance it might not be appropriate and adds as much value as the time it took to research…zero. So when i see an article comparing a particular strategy to its Buy-and-Hold equivalent dating back

To install Systematic Investor Toolbox (SIT) please visit About page. The overlay strategy is the market neutral strategy that can be applied to benchmark to improve benchmark's performance. The new strategy weights are equal to benchmark weights plus the overlay weights. Below I will present a

Towards the end of this section, Taleb inserts a sidebar as follows: Consider the right tail K^{+}\in \mathbb{R}^{+} and the left tail K^{-}\in \mathbb{R}^{-} . Without specifying the support of the distribution: Definition 1.3 (Probability swamps payoff (thin tails)). \lim_{K^{+ }\rightarrow\infty

It is a long established fact that a reasonably well behaved chimp throwing darts at a list of stocks can outperform most professional asset managers. While there would be obvious advantages with hiring chimps over hedge fund traders, such as lower salaries and better manners, there are also a few

The 5 Mistakes Every Investor Makes is a recent book I read by Peter Mallouk, the #1 Investment Advisor in America. (I’m not poking fun, that’s just what it says on the cover.) In general it is an easy to read book that it quite reasonable it its advice, and you can get a free copy from their

Justin and I will be speaking on panels in New York City in May. May 3rd – 3:10pm – Princeton Club in New York I will be sitting on a panel titled Advancements in Asset Allocation at WealthManagement.com's BUILD conference. Here is a quick description of the panel: The level of

Disclaimer: I am not posting this at the behest of the developers of Zorro, nor do I receive any form of payment or commission for this post. I felt that I should relay this experience because it was an example of customer service that went way above and beyond the call of duty in terms of its

Here’s a free system for you. I call it the “SPY RSI No Lie” system. It’s called that because I like stupid titles, and internal rhymes are an added plus. I read a post on Jeff Swanson’s System Trader Success recently about using a short-period RSI value to trigger trades with the S&P

Recently I have been researching longer term hold strategies. I wondered which indicators by themselves would show an edge 3 to 6 months out. I am not looking to create a strategy from the indicator alone but want to know is there a statistical edge with it. Naturally, I started with my favorite

As quants, we’re all aware that every model has a shelf-life. Sooner or later, the ideas and techniques behind every “proprietary” analytical technique diffuse into the broader world, at which point that technique is no longer the source of a competitive edge or alpha. What’s less well

I read a very interesting post from AlephBlog which led me to another blog called Philosophical Economics. It’s a long and in depth article I had to read a few times to understand but the basic gist of it is that when investors are under allocated to equities, future returns are better than when

Justin and I submitted a paper for the NAAIM Wagner 2016 competition. Unfortunately, it didn't place. The good news is that we can share it with everyone that much earlier! The paper is about trying to time factor premiums using the same behavioral biases that we believe cause them. Here is the

In my previous post, I looked at the historical performance of investing in low volatility stocks and identified that outperformance from the factor tends not to be very consistent over time, but is instead clustered. That raised some questions on whether volatility is a true investment factor, or

Patrick O’Shaughnessy has a great post, The More Unique Your Portfolio, The Greater Its Potential, outlining how active share is what drives the level of potential before fee excess return for an active manager. If you allocate to active managers... go through it twice. As Patrick notes: If there

Twitter seems to be a favorite dataset for financial researchers. Researchers keep trying to map tweets to profits. For example, we covered an idea related to this almost 5 years ago: Is trading with twitter only for twits? We had another post that was released about a year after our original

Pretty obviously, he had been making creative use of the "money management" techniques so beloved by futures systems designers. I invited him to consider how it would feel to be trading a 1,000-lot E-mini position when the market took a 20 point dive. A $100,000 intra-day drawdown might

Many asset management decisions are based on the three-year track record. Three-years is suspiciously close to a common rule-of-thumb for calculating statistics, but in this case, it is a misapplication. With many strategies, short-term luck swamps long-term skill. Combining strategies can reduce

In our previous post on Machine learning we derived rules for a forex strategy using the SVM algorithm in R. In this post we take a step further, and demonstrate how to backtest our findings. To recap the last post, we used Parabolic SAR and MACD histogram as our indicators for machine learning.

You can find registration information and agenda details on the conference website. Or you can go directly to the Cvent registration page. Note that registration fees will increase by 50% at the end of early registration on May 6, 2016. The conference will take place on May 20 and 21, at UIC in