Quantocracy

Quant Blog Mashup

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Best Links of the Last Two Weeks

The best quant mashup links for the two weeks ending Saturday, 04/23 as voted by our readers:

We also welcome one blog making its first ever appearance on the mashup:

And finally, the latest from Quantocracy:

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Votes by Clickthroughs

[click graph to enlarge]

Your votes matter to the quant community.

The graph to the right shows 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.

A core goal of Quantocracy is to have a positive impact on our corner of the financial world by rewarding the best work, and encouraging the best minds to keep writing.

As the graph makes clear, the citizens of Quantocracy are doing just that (way to go guys). Links with 11 or more votes receive nearly 6-times as many clickthroughs as a link with no votes (wow).

If you haven’t done so already, we invite you to register to vote and be a part of the effort. Your votes matter to the quant community.

Read on Readers!
Mike @ Quantocracy

Quantocracy’s Daily Wrap for 04/22/2016

This is a summary of links featured on Quantocracy on Friday, 04/22/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book Added: Machine Learning with R [Amazon]

    Machine learning, at its core, is concerned with transforming data into actionable knowledge. This makes machine learning well suited to the present-day era of big data. Given the growing prominence of a cross-platform, zero-cost statistical programming environment there has never been a better time to start applying machine learning to your data. Whether you are new to data analytics or a
  • PDF: Combining Value and Momentum [Gerstein Fisher]

    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 outperforms a strategy that combines pure-play value and momentum portfolios that are formed
  • 50% Returns Coming for Commodities and Emerging Markets? [Meb Faber]

    If history is any guide, were standing at the edge of 40%96% returns over the next two years. This isnt wishful thinking or wild speculation. Im not selling anything. Rather, Im just reporting historical gains from a market set-up thats repeating itself right now. So whats going on? Well, imagine a rubber band. If you stretch it only slightly then let it go, its not going
  • Minimum volatility: what’s in a name? [Factor Investor]

    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 and Volkswagen's Think Small. The quote couldn't be more applicable to many of the Smart
  • The Moving Average Research King: Valeriy Zakamulin [Alpha Architect]

    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. Weve done a lot of the same work, but were too lazy to tabulate the results in an academic paper format. king of ma The king of moving average research. Check these papers out: Revisiting the Profitability of Market Timing with
  • Research Review | 22 Apr 2016 | Risk Analysis [Capital Spectator]

    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 market-value weighted indexes for many years, many easy-to-build portfolios (some smart-beta,

Quantocracy’s Daily Wrap for 04/21/2016

This is a summary of links featured on Quantocracy on Thursday, 04/21/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Introducing fidlr: FInancial Data LoadeR [R Trader]

    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. As usual with those things just a kind reminder: THE SOFTWARE IS PROVIDED AS IS, WITHOUT
  • Get ready for R/Finance 2016 [Revolutions]

    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 esoterica of finance and trading there has, so far, always been a rich mix of mathematics, time
  • Sentiment Analysis in Trading Explained Using R [Quant Insti]

    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 processing tools. Natural language processing (NLP) in simple terms refers to the use of computers to

Quantocracy’s Daily Wrap for 04/20/2016

This is a summary of links featured on Quantocracy on Wednesday, 04/20/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Kaufman’s Market Efficiency Model [Milton FMR]

    The trend following model by Kaufman says that trading by the direction of the trend is a conservative approach to the markets. Kaufmans 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 Market Efficiency Model is that an adaptive method must be applied to the markets for proper trend
  • CAPE 10 Ratio In Need Of Context [Larry Swedroe]

    The Shiller cyclically adjusted (for inflation) price-to-earnings ratioreferred to as the CAPE 10 because it averages the last 10 years earnings and adjusts them for inflationis a metric used by many to determine whether the market is undervalued, fairly valued or overvalued. Employing a 10-year average for earnings, instead of the most current 12-month earnings, was first suggested by
  • Information Content of Pre- and Post-Market Trading Sessions [Jonathan Kinlay]

    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 general application. Pre- and Post Market Sessions The pre-market session runs from 8:00 AM ET, while
  • What is the difference between Bagging and Boosting? [Quant Dare]

    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, lets start from the beginning: What is an ensemble method? Ensemble is a Machine Learning concept in
  • Analysis of US Dollar Carry Trades in the Era of ‘Cheap Money’ [Quantpedia]

    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 the recent period of the ultra-loose US monetary policy. Our analysis indeed shows that USD positions

Quantocracy’s Daily Wrap for 04/19/2016

This is a summary of links featured on Quantocracy on Tuesday, 04/19/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Machine Learning Section Added to Our Library with Robot Wealth [Quantocracy]

    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 become one of the top rated quant bloggers here at Quantocracy (a feat only matched by Financial
  • A Better Way To Run Bootstrap Return Tests: Block Resampling [Capital Spectator]

    Developing confidence about a portfolio strategys track record (or throwing it onto the garbage heap), whether its your own design or a third partys model, is a tricky but essential chore. Theres no single solution, but a critical piece of the analysis for estimating return and risk, including the potential for drawdowns and fat tails, is generating synthetic performance histories with
  • A Closer Look At Growth and Value Indices [Flirting with Models]

    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 may end up tilting more toward shrinking, expensive companies in both growth and value indices. 2D

Machine Learning Section Added to Our Library with Robot Wealth

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 become one of the top rated quant bloggers here at Quantocracy (a feat only matched by Financial Hacker). For a taste of the Robot Master’s brain, check out this brilliant article applying Machine Learning:

http://robotwealth.com/machine-learning-financial-prediction-david-aronson/

RW represents a prototypical example of the quality of workmanship we hope to foster here. RW can be found on his website at RobotWealth.com, or on Twitter at @Robot_Wealth.

Without further ado, the humble beginnings of our Machine Learning library. Have a suggestion for a book to include here? Contact Jacques via LinkedIn, Twitter or email.

Machine Learning with R
Machine Learning with R
An Introduction to Statistical Learning with Applications in R
An Introduction to Statistical Learning with Applications in R
Applied Predictive Modeling
Applied Predictive Modeling
The Elements of Statistical Learning
The Elements of Statistical Learning
Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments
Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments

How Changing our Brand Supercharged Our Growth on Twitter

This is not quant related, but I found it interesting and thought it worth sharing for the benefit of our friends in the blogosphere.

Long-time readers remember that we rebranded this site from The Whole Street to Quantocracy at the start of April, 2015. Although the rebranding included changes to our website, nothing other than our name and profile pic changed on our Twitter feed. Both the subject of our tweets, and the way in which we formed our tweets, remained the same.

But interestingly, look at the impact of the rebranding on the number of new Twitter followers per day (dotted line marks the date of rebranding):

Followers per Day

In the seven months before the rebranding, we averaged 1.8 new followers per day or 648/year, but in the seven months after, 5.6 per day or 2038/year. That’s more than a 3-fold increase.

Note that we didn’t see even a remotely similar increase in site traffic, and we didn’t do anything radically different in terms of how we promoted the Twitter feed. In other words, the increase wasn’t the result of pushing more users to Twitter. Rather, it was a change in how the Twitter community perceived our Twitter account.

I realize that I just discovered what any first year marketing major could have told me in two seconds, but as a quant nerd, I tend not to think in these terms. The purist in me says that all that matters is the substance of what we do, but as the numbers clearly show, that’s naive.

If the goal of Quantocracy is to build and support this community of quants, then it’s also my responsibility to consider how I “market” this site. I get the heebeegeebees just using that word, but if a simple branding change means that the next amazing piece from Turing Finance, or Quant Start, or Financial Hacker, or Robot Wealth or any of the other 100+ kick ass quants included on the mashup gets more of the recognition that it deserves, then marketing becomes just as important as the substance of what we do. Lesson learned.

Mike @ Quantocracy

Quantocracy’s Daily Wrap for 04/16/2016

This is a summary of links featured on Quantocracy on Saturday, 04/16/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Taleb: Silent Risk, Section 1.3 [Blue Event Horizon]

    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 }E\left [ X\mid_{X> K^{+}} \right ]=K^{+}\textup{and}\lim_{K^{- }\rightarrow-\infty }E\left [

Quantocracy’s Daily Wrap for 04/15/2016

This is a summary of links featured on Quantocracy on Friday, 04/15/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • You can’t beat all the chimps [Following the Trend]

    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 practical obstacles to such hiring practices. For those asset management firms unable to retain the
  • Benchmark Plus [Systematic Investor]

    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 benchmarks performance. The new strategy weights are equal to benchmark weights plus the overlay weights. Below I will present a very simple example. The Benchmark portfolio is a market cap weighted country portfolio. The Overlay
  • The 5 Mistakes Every Investor Makes [Meb Faber]

    The 5 Mistakes Every Investor Makes is a recent book I read by Peter Mallouk, the #1 Investment Advisor in America. (Im not poking fun, thats 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 website. The five mistakes are: Market Timing Active Trading Misunderstanding Performance and