Quantocracy

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Quantocracy’s Daily Wrap for 01/15/2016

This is a summary of links featured on Quantocracy on Friday, 01/15/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book Added from @QuantAtRisk: Python for Quants [Amazon]

    Python for Quants is the first book-series in the market that takes you from the absolute beginner level in Python programming towards instant applications in Quantitative Analysis, Mathematics, Statistics, Data Analysis, Finance, and Algo Trading. Written with passion, this book of unprecedented quality and in-depth coverage teaches you the essentials of Python that allow you to start coding your

Quantocracy’s Daily Wrap for 01/14/2016

This is a summary of links featured on Quantocracy on Thursday, 01/14/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Data Sources for R [Revolutions]

    Over the past few months, a number of new CRAN packages have appeared that make it easier for R users to gain access to curated data. Most of these provide interfaces to a RESTful API written by the data publishers while a few just wrap the data set inside the package. Some of the new packages are only very simple, one function wrappers to the API. Others offer more features providing functions to
  • Value Investing: Accruals, Cash Flows, and Operating Profitability [Alpha Architect]

    Accruals are the non-cash component of earnings. They represent adjustments made to cash flows to generate a profit measure largely unaffected by the timing of receipts and payments of cash. Prior research finds that expected returns increase in firm profitability. However, firms with high accruals generate lower returns than firms with low accruals, and this "accrual anomaly"
  • Noise Kills Profits (Machine Learning with Genotick) [Throwing Good Money]

    A reader on my blog (Thanks Kris!) suggested that I explore how much noise is needed to send Genotick off the deep end. Youll recall from my earlier post on the subject that I was looking for hidden biases that Genotick might have, and explored how it responded to pure and noisy sine waves of data. For those just catching up, Genotick is a free, open-source machine-learning price-prediction
  • A Multiples-Based Decomposition of the Value Premium [Quantpedia]

    We use industry multiples-based market-to-book decomposition of Rhodes-Kropf, Robinson and Viswanathan (2005) to study the value premium. The market-to-value component drives all of the value strategy return, while the value-to-book component exhibits no return predictability in both portfolio sorts and firm-level return regressions controlling for other stock characteristics. Prior results in the
  • Panic Selling, a Pause, Then Another Smash… [Don Fishback]

    Early this week, Rob Hanna at Quantifiable Edges put out some research showing what happens when you get Repeated Hard Selling at Intermediate-Term Lows. The definition he used was: S&P 500 ($SPX) closes down more than 1% for three straight days. Each close is a new 20-day low. The final close on the third day is below the 200-day moving average. Last Friday satisfied that criteria. Rob
  • Complacent Correction Cause For Concern? [Dana Lyons]

    Despite recent stock market carnage, the reaction by the VIX has been a relative yawner. Well, the New Year hangover continues. Another day, another drubbing in the stock market. With indices pushing double digit losses just 8 days into the new year, it certainly seems reasonable to expect some panic on the part of investors. However, at least based on one metric, market participants have remained

Quantocracy’s Daily Wrap for 01/13/2016

This is a summary of links featured on Quantocracy on Wednesday, 01/13/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • On The Relationship Between the SMA and Momentum [QuantStrat TradeR]

    Happy new year. This post will be a quick one covering the relationship between the simple moving average and time series momentum. The implication is that one can potentially derive better time series momentum indicators than the classical one applied in so many papers. Okay, so the main idea for this post is quite simple: Im sure were all familiar with classical momentum. That is, the
  • Could the Stochastic Oscillator be a good way to earn money? [Quant Dare]

    If you knew the future price of assets when you are creating a portfolio, it would be the best way to be a millionaire. However, this is difficult if not impossible, so what if you knew what would be the movement of the price? It could be enough to earn money! To predict the trend of the price is not a silly job and there is no method that tells you what the movement will be with a 100%
  • Does Science Advance One Funeral at a Time? [Alpha Architect]

    A really interesting paper hit the NBER wires recently. The central argument of the paper is that rock star thought leaders dominate a field, but when they die, new thought leaders are able to emerge. In summary, there seems to be a cost and a benefit attached to a powerful intellectual: On one hand, powerful leaders drive ideas forward and other researchers can stand on the shoulders of
  • Tactical Alpha Part III – Asset Allocation – Security Selection [GestaltU]

    By far the greatest source of personal consternation as a professional in markets is investors obsession with finding the best stocks, or the best stock pickers. The fact that investors pursue this objective at all undermines all meaningful arguments about efficient markets. After all, why on earth would the well informed, rational actors that constitute efficient markets spend all their time
  • RUT Straddle – Backtest Results Summary [DTR Trading]

    Over the last seven weeks we reviewed the backtest results of 28,840 short options straddles on the Russell 2000 Index (RUT). In this post, I won't discuss how these trades were structured and managed. For background on the setup for the backtests, as well as the nomenclature used in the charts and tables below, please see the introductory article for this series: Option Straddle Series –

Quantocracy’s Daily Wrap for 01/10/2016

This is a summary of links featured on Quantocracy on Sunday, 01/10/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    The best quant mashup links for the week ending Saturday, 01/09 as voted by our readers. Exploring mean reversion and cointegration: part 2 [Robot Wealth] Dear Brokers [Financial Hacker] Quant Strategies: From Idea to Execution in Python [Quant Insti] New Book from Meb Faber: Invest With The House: Hacking The Top Hedge Funds [Amazon] We also welcome one blog making its first ever appearance on
  • Interview with Michael Cook [Better System Trader]

    Weve been very lucky to have a number of trading champions on the podcast before and this episode we get to talk to another champion trader, Michael Cook, who won the World Cup Trading championships in 2007 (Futures), 2011 (Stocks) and 2014 (Futures). Michael worked in the institutional world for a number of years before leaving behind the banks and hedge funds to trade for himself. In this
  • Give me good data, or give me death [Quantum Financier]

    A good discussion not to long ago led me to start a revolution against some data management aspects of my technology stack. Indeed it is one of the areas where the decisions made will impact every project undertaken down the road. Time is one of our most valuable resources and we need to minimize the amount of it we have to spend dealing with data issues. Messy and/or hard to use data is the

Quantocracy’s Daily Wrap for 01/09/2016

This is a summary of links featured on Quantocracy on Saturday, 01/09/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Components of a black box, humans versus computers, and high frequency trading w/ @RishiKNarang [Chat With Traders]

    To start the year with a bang, I have a very special guest on the podcast this week, who Id like you to meet his name is, Rishi Narang. Rishi has an impressive background, and has been involved with financial markets for over 20 years now. He originally started out as an analyst at Citibank, prior to co-founding TradeWorx with his brother Manoj Narang (a fintech company, turned
  • RSI(2)?25 X6! [Throwing Good Money]

    Today marks the sixth day in the row that the S&P 500s RSI(2) value was under 25.* Since Jan 1 2000, this has happened only 15 times prior to today. So I thought it would be fun to see what the forward return has been after these events. Heres a handy spreadsheet. I calculated the forward return from the following days open to the close of either the 5th or 20th day. I.e. if you were

Quantocracy’s Daily Wrap for 01/08/2016

This is a summary of links featured on Quantocracy on Friday, 01/08/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Interest Rates, Tax-Selling, and Stock Return Seasonality [Alpha Architect]

    We show that interest rates drive mispricing at the turn of a tax period as investors face the trade-off between selling a temporarily-depressed stock this period and selling next period at fundamental value, but with tax implications delayed accordingly. We confi rm these patterns in US returns, volume, and individual selling behavior as well as in UK data where tax and calendar years diff er. At
  • Employment Night Hot Streak Gone Cold [InvestiQuant]

    From August of 2012 until May of 2015 the night before the US Employment Report was a strong and consistent. Over that time period ES gapped up 76% of the time and the average employment night registered 5.00 ES points. I reported on the hot streak a number of times while it was in progress. But since then employment nights have cooled off dramatically. Below is a look at how employment nights

Quantocracy’s Daily Wrap for 01/07/2016

This is a summary of links featured on Quantocracy on Thursday, 01/07/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book from Meb Faber: Invest With The House: Hacking The Top Hedge Funds [Amazon]

    Picking stocks is hardand competitive. The most talented investors in the world play this game, and if you try to compete against them, its like playing against the house in a casino. Luck can be your friend for a while, but eventually the house wins. But what if you could lay down your bets with the house instead of against it? In the stock market, the most successful large
  • Augmented Dickey Fuller (ADF) Test for a Pairs Trading Strategy [Quant Insti]

    About two weeks ago I decided to attempt to write a blog series on Pairs trading and statistical arbitrage. What I found is that everyone tends to reference the ADF test but I really dont see a lot of posts that explain the test in full. As you read about building a pairs trading strategy there is talk of testing a pair for co-integration and then you learn that they use ADF to do this. However
  • Streaming OANDA with python and ZeroMQ [Shifting Sands]

    I have been looking at its REST API for OANDA, for potential use with an FX trading system I developed. The API has two streaming endpoints, one for prices and one for account events such as trades opening and stuff like that. Asynchronous IO is always a bit fiddly, and I wanted separate processes for incoming tick data and events. This enables them to be managed separately, and generally makes

Quantocracy’s Daily Wrap for 01/06/2016

This is a summary of links featured on Quantocracy on Wednesday, 01/06/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Technologies Screening I [Algorythmn Trader]

    This is the first destination from our Roadmap where what to post about my technologies screening. This was, and still is an exciting journey and I want to do it in several parts. Feel free to comment this blog or send me a mail with suggestions and I would come over it into the next part. The good thing about my project was that I has to solve a domain specific problem so I dont need to care
  • Genotick and the Dirty Sine (Machine Learning) [Throwing Good Money]

    I have been playing around with Genotick some more, the open-source genetic learning trading software by Lukasz Wojtow. One thing that has been puzzling me is that the software seems to do well on certain types of data, but not others. And Im having trouble identifying what sort of data its good at. At first I thought Genotick might have a long bias. It does smashingly well on
  • Using Stops: The Good, The Bad and The Ugly [Alvarez Quant Trading]

    I recently gave a presentation on Better System Trader about using stops on a breakout strategy. The research produced results I was not expecting and may be surprising to you. The stops tested are No stops Maximum Loss using ATR (Intraday and End of Day) Maximum Loss using percentage (Intraday) Trailing ATR (Intraday and End of Day) Profit target using ATR (Intraday and End of Day) The Strategy

Quantocracy’s Daily Wrap for 01/05/2016

This is a summary of links featured on Quantocracy on Tuesday, 01/05/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Daily Academic Alpha: Value and Momentum in Vietnam [Alpha Architect]

    An interesting out of sample test on return drivers in the Vietnamese market from 2006 to 2014. Not surprisingly, value and momentum show some mojo – Liquidity as wellsize, not so much. But size only matters if you control your junk, apparently. This is in line with our own research and the research of many others: Value: Never buy expensive stocks. Momentum: Ride Winners and Cut Losers. Size:
  • Are Size and Book-Value Factors Really Significant? [Quantpedia]

    The Fama and French (F&F) factors do not reliably estimate the size and book-to-market effects. Our paper shows that the former has been underestimated in the US market while the latter overestimated. We do so by replacing F&F's independent rankings by the conditional ones introduced by Lambert and Hubner (2013), over which we improve the sorting procedure. This new specification
  • [Academic Paper] Positive Skewness, Anti-leverage, Reverse Volatility Asymmetry, Short Sale Constraints: Chinese Markets [@Quantivity]

    There are some statistical anomalies in the Chinese stock market, i.e., positive return skewness, anti-leverage effect (positive returns induce higher volatility than negative returns); and reverse volatility asymmetry (contemporaneous return-volatility correlation is positive). In this paper, we first confirm the existence of these anomalies using daily firm-level stock return data on the raw