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Quantocracy’s Daily Wrap for 06/26/2016

This is a summary of links featured on Quantocracy on Sunday, 06/26/2016. 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, 06/25 as voted by our readers: Recommended Reading [Robot Wealth] Binary Options: Scam or Opportunity? [Financial Hacker] Some harmless data-mining: Testing individual words in EDGAR filings [Greg Harris] Simple Machine Learning Model to Trade SPY [Alpha Plot] Want to Know the Secret to Inefficient Prices? Lazy Prices. [Alpha
  • Momentum Anomaly and Baseball Cards [Quantpedia]

    We show that the market for baseball cards exhibits anomalies that are analogous to those that have been documented in financial markets, namely, momentum, price drift in the direction of past fundamental performance, and IPO under performance. Momentum profits are higher among active players than retired players, and among newer sets than older sets. Regarding IPO under performance, we find that

Quantocracy’s Daily Wrap for 06/23/2016

This is a summary of links featured on Quantocracy on Thursday, 06/23/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Maybe the Exits are More Important… [Throwing Good Money]

    As traders, we spend a lot of time thinking about our entries into a trade. What stock, commodity or currency to choose, when is the best timing, etc. But what if the entries dont matter? What if trading is all about the exits? Ok, thats a really simple-minded statement, but Im a little simple-minded, so stick with me and lets see where this goes. I wanted to see what it would look
  • Hierarchical clustering, using it to invest [Quant Dare]

    Machine Learning world is quite big. In this blog you can find different posts in which the authors explain different machine learning techniques. One of them is clustering and here is another method: Hierarchical Clustering, in particular the Wards method. You can find some examples in Reproducing the S&P500 by clustering by fuzzyperson, Returns clustering with K-Means
  • Monthly and Yearly Decay Rates for Long Volatility Funds [Six Figure Investing]

    While its certain that short-term volatility exchange traded products (ETPs) like VXX, TVIX, and UVXY are doomed to march towards zero, their decay rates are not consistent. Things like bear markets and big corrections can cause big upward swings. On the downside, the term structure of VIX futures and the volatility of volatility can significantly impact decay rates in monthly and yearly time

Quantocracy’s Daily Wrap for 06/21/2016

This is a summary of links featured on Quantocracy on Tuesday, 06/21/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Recommended Reading [Robot Wealth]

    If theres one thing Ive done a lot of over the last few years, reading would be it. Ive devoted a great deal of time to devouring any material that I thought might give me an edge in my trading textbooks, academic papers, blog articles, training courses, lecture notes, conference presentationsanything and everything I could get my hands on. I was browsing the folder called
  • Manage Your Luck [Systematic Relative Strength]

    There is a lot more luck involved in investing than people think. Im not saying there isnt skill involved in investing or that there arent ways to outperform the market over time. Even if you have a process that can be shown to outperform the market over long time periods, there can be a great deal of variation in returns from year to year. A well designed investment model can certainly

Quantocracy’s Daily Wrap for 06/20/2016

This is a summary of links featured on Quantocracy on Monday, 06/20/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Digging Deeper into Adaptive Asset Allocation [Alpha Architect]

    In some ways, investing is simple. After all, we all want the same things. High returns. Low volatility. Small max drawdowns. Unfortunately, its very difficultif not impossibleto have your cake and eat it too. There are always tradeoffs among these desires that have to be managed by investors. Want low volatility? Be willing to accept lower returns. Want to maximize returns? You may have
  • Johansen Test for Cointegrating Time Series Analysis in R [Quant Start]

    In the previous article on the Cointegrated Augmented Dickey Fuller (CADF) test we noted that one of the biggest drawbacks of the test was that it was only capable of being applied to two separate time series. However, we can clearly imagine a set of three or more financial assets that might share an underlying cointegrated relationship. A trivial example would be three separate share classes on
  • Mini-Meucci : Appplying The Checklist – Steps 8-9 [Return and Risk]

    "Predicting rain doesn't count. Building arks does." Warren Buffett, The Oracle of Omaha (born 1930) In this penultimate leg of the tour we'll be visiting 2 more attractions along Via Meucci, Construction and Execution. Construction Portfolio Construction is another yuge! topic. In a nutshell, the overall goal is to find optimal holdings that maximize Satisfaction, subject to
  • Beginner’s Guide to Automated Trading with Python [Quant Insti]

    Python has emerged as one of the most popular language to code in Algorithmic Trading, owing to its ease of installation, free usage, easy structure, and availability of variety of modules. Globally, Algo Traders and researchers in Quant are extensively using Python for prototyping, backtesting, building their proprietary risk and order management system as well as in optimisation of testing
  • Is Internal Bar Strength A Random Walk? The Case of Exxon-Mobil [Jonathan Kinlay]

    For those who prefer a little more rigor in their quantitative research, I can offer more a somewhat more substantive statistical argument in favor of the IBS indication discussed in my previous post. Specifically, we can show quite convincingly that the IBS process is stationary, a highly desirable property much sought-after in, for example, the construction of statistical arbitrage strategies.

Quantocracy’s Daily Wrap for 06/18/2016

This is a summary of links featured on Quantocracy on Saturday, 06/18/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Monte Carlo and Arima for stock selection [Tulip Quant]

    A few days ago, in this post, I talked about how ARIMA models could be used to forecast the S&P 500 index, and use this information in order to buy or sell the index every day, if the algorithm predicts an increase or decrease in the price, respectively. In this post, I will go a step further. The idea of the trading algorithm will be the following: Given a day, for each stock of a certain
  • Binary Options: Scam or Opportunity? [Financial Hacker]

    Were recently getting more and more contracts of developing systems for trading binary options. This calls for a closer look. Binary options resemble financial instruments, but are widely understood as a scheme to separate naive traders from their money. And indeed, binary options brokers make no good impression at first look. Some are regulated in Cyprus under a fake address, others are not

Quantocracy’s Daily Wrap for 06/17/2016

This is a summary of links featured on Quantocracy on Friday, 06/17/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Invert, Always Invert: Will Stocks Diversify Bonds in the Future? [Alpha Architect]

    My last post, Will bonds deliver crisis alpha in the next crisis?, created quite a stir on the blogosphere. The underlying assumption of the analysis is that stocks are a core component of a portfolio and bonds are included to diversify the portfolio. The key takeaway from my analysis is that the crisis alpha associated with bond exposures seems to be driven by the income component of bond
  • Mean Reversion and the Broken Rubber Band [Alvarez Quant Trading]

    A common way to describe a mean reversion trade is a rubber band that stretches away and then snaps back. Something that Steve, my trading buddy, and I discuss when a trade keeps going against us is that the rubber band has broken. I have never tested that concept. Meaning after N day sell-off, are we now more likely to continue to sell off than bounce? Doing research is not always about trying to
  • A Return.Portfolio Wrapper to Automate Harry Long Backtests [QuantStrat TradeR]

    This post will cover a function to simplify creating Harry Long type rebalancing strategies from SeekingAlpha for interested readers. As Harry Long has stated, most, if not all of his strategies are more for demonstrative purposes rather than actual recommended investments. So, since Harry Long has been posting some more articles on Seeknig Alpha, Ive had a reader or two ask me to analyze his
  • Rough Net Worth Growth Benchmarks [CXO Advisory]

    How fast should individuals plan to grow net worth as they age? To investigate, we examine median levels of household (1) total net worth and (2) net worth excluding home equity from several vintages of U.S. Census Bureau data. We make the following head-of-household age cohort assumptions: Less than 35 years means about age 30. 35 to 44 years means about age 39. 45 to 54 years
  • Information Ratio Analysis of Time-Series Momentum Strategy [Quantpedia]

    In the past 20 years, momentum or trend following strategies have become an established part of the investor toolbox. We introduce a new way of analyzing momentum strategies by looking at the information ratio (IR, average return divided by standard deviation). We calculate the theoretical IR of a momentum strategy, and show that if momentum is mainly due to the positive autocorrelation in