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Quantocracy’s Daily Wrap for 04/24/2016

This is a summary of links featured on Quantocracy on Sunday, 04/24/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Last Two Weeks [Quantocracy]

    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 cant beat all the chimps [Following the Trend] My Year-Long Experience as the Fastest Form-4 Trader [Greg Harris] Are 3-year track records meaningful? [Flirting with Models] The Changing Generations of Financial Data [Quandl]
  • New Book Added: Intro to Statistical Learning with Applications in R [Amazon]

    An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant

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

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

Quantocracy’s Daily Wrap for 04/14/2016

This is a summary of links featured on Quantocracy on Thursday, 04/14/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Upcoming Panel Appearances [Flirting with Models]

    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 sophistication deployed in the investment solutions made available to investors continues to evolve. Many of the
  • My experience dealing with Zorro s support team [Robot Wealth]

    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 promptness and professionalism. Credit where credit is due. I have been using the Zorro platform for

Quantocracy’s Daily Wrap for 04/13/2016

This is a summary of links featured on Quantocracy on Wednesday, 04/13/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Changing Generations of Financial Data [Quandl]

    As quants, were 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. Whats less well appreciated is that a similar pattern applies to the world of data. Rare, unique and proprietary data
  • The SPY RSI No Lie Swing Trade System [Throwing Good Money]

    Heres a free system for you. I call it the SPY RSI No Lie system. Its called that because I like stupid titles, and internal rhymes are an added plus. I read a post on Jeff Swansons System Trader Success recently about using a short-period RSI value to trigger trades with the S&P 500. Jeffs post was more from a theoretical standpoint, as it used the SPX index (rather than a
  • Relative Strength Index (RSI) Analysis [Alvarez Quant Trading]

    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 Relative Strength Index, RSI. Rules Test period is from 1/1/2006 to 12/31/2015. Rules in parenthesis