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Quantocracy’s Daily Wrap for 11/06/2015

This is a summary of links featured on Quantocracy on Friday, 11/06/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Dividends An Illogical Preference [Larry Swedroe]

    A large body of literature examines whether managers of actively managed funds add value to their investors by generating abnormal returns. Unfortunately, not only do the vast majority fail to do so, but the evidence, as presented in my book, The Incredible Shrinking Alpha, demonstrates that the already-small percentage of managers able to beat their benchmarks has been diminishing at a
  • Screening Using False-Discovery Rates [Alex Chinco]

    1. Motivating Example Jegadeesh and Titman (1993) show that, if you rank stocks according to their returns over the previous 12 months, then the past winners will outperform the past losers by 1.5{\scriptstyle \%} per month over the next 3 months. But, the authors dont just test this particular strategy. They also test strategies that rank stocks over the previous 3, 6, and 9 months and

Quantocracy’s Daily Wrap for 11/05/2015

This is a summary of links featured on Quantocracy on Thursday, 11/05/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • GMO Flows Turn Negative – An Ominous Sign for Risk Taking [EconomPic]

    I have a ton of respect for the way in which GMO manages money (their guts to be massively contrarian if that is their view) and I think their thought leadership is about as good as it gets in the industry. That said, I have long had an issue in the way in which they think about investor behavior from a client perspective, which is they broadly ignore it. This was the genesis of my tweet from late
  • The Trinity Portfolio [Meb Faber]

    We examined 15 famous asset allocation strategies in my last book Global Asset Allocation. (If you havent read it yet Ill send you a free copy.) I would like to have included a lot more tactical ideas in the book but there is a constant struggle between keeping an idea/book simple, but satisfying the supernerds like me with enough of a deep dive into the data. Ironically I spent a ton of
  • Accessing Bitcoin Data with R [Revolutions]

    I am not yet a Bitcoin advocate. Nevertheless, I am impressed with the amount of Bitcoin activity and the progress that advocates are making towards having Bitcoin recognized as a legitimate currency. Right now, I am mostly interested in the technology behind bitcoin and the possibility of working with some interesting data sets. A good bit of historical data is located on sites like bitstamp.net
  • Daylight is Bad for Gold Stocks (Apparently) [Jay On The Markets]

    Well, at least as far as I can tell. To understand what I am talking about consider the following results generated using daily open/high/low/close data for ticker GDX (an ETF that tracks gold mining stocks). Figure 1 displays the cumulative $ gain/loss achieved by holding 100 shares of ticker GDX since it started trading in May 2006.1aFigure 1 $ gain/loss from holding 100 shares of ticker GDX
  • Deconstructing the Low-Volatility Anomaly [Quantpedia]

    We study several aspects of the so-called low-vol and low-beta anomalies, some already documented (such as the universality of the effect over different geographical zones), others hitherto not clearly discussed in the literature. Our most significant message is that the low-vol anomaly is the result of two independent effects. One is the striking negative correlation between past realized
  • SPX Straddle – 80 DTE – Results Summary [DTR Trading]

    Over the last five blog posts we looked at the automated backtest results for 4040 options straddles sold on the S&P 500 Index (SPX) at 80 days-to-expiration (DTE). Eight different loss approaches were tested on these straddles. On top of these eight loss approaches, tests were conducted with no profit taking, and profit taking at 10%, 25%, 35%, and 45% of the credit received. For background

Quantocracy’s Daily Wrap for 11/04/2015

This is a summary of links featured on Quantocracy on Wednesday, 11/04/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using random data [Investment Idiocy]

    As you might expect I spend quite a lot of my time using real financial data – asset prices and returns; and returns from live and simulated trading. It may surprise you to know that I also spend time examining randomly created financial data. This post explains why. I also explain how to generate random data for various purposes using both python and excel. I'll then give you an example of
  • Tactical Alpha in Theory and Practice (Part II): Principal Component Analysis [GestaltU]

    In Part I of this series, we explored Grinold's Fundamental Law of Active Management, and why the theory leads to misguided conclusions in the presence of asset correlations. In this article we will offer a primer on a useful tool for portfolio evaluation, Principal Component Analysis (PCA), and illustrate how PCA can help quantify the number of independent bets in a portfolio of correlated
  • An interesting look at the size anomaly [Alpha Architect]

    Many of you are probably aware of the paper from AQR entitled, Size Matters: When you control for your junk. We loved the title so much we considered it one of our Top 5 Geeky, Yet Funny, Economic Paper Titles. Of course, great papers often go unread beyond the abstract because they are a bit dense. A solution to this is to get access to the presentation version of the paper. Typically, a
  • 3 Common Backtesting Traps With Easy Solutions [Capital Spectator]

    Backtests have become the weapon of choice for rationalizing various forms of tactical asset allocation, which has become increasingly popular as a risk-management tool since the 2008 crash. The hazards of backtestingstudying how a strategy performed in the pastare well known, which leads some folks to shun the concept entirely. But thats going too far. In some respects, every investment

Quantocracy’s Daily Wrap for 11/01/2015

This is a summary of links featured on Quantocracy on Sunday, 11/01/2015. 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, 10/31 as voted by our readers: The Cold Blood Index [Financial Hacker] How to Write a Great Quant Blog [Quant Start] High Frequency Market Microstructure: Part 1 (Microstructure Noise) [Portfolio Effect] Buy the Winners [Systematic Relative Strength] Correlations Can Be Predictive [Larry Swedroe] We also welcome one blog making its first
  • The Financial Hacker s Cold Blood Index [Robot Wealth]

    This post builds on work done by jcl over at his blog, The Financial Hacker. He proposes the Cold Blood Index as a means of objectively deciding whether to continue trading a system through a drawdown. I was recently looking for a solution like this and actually settled on a modification of jcls second example, where an allowance is made for the drawdown to grow with time. The modification I
  • 10 Reasons to Use Elixir in Finance [John Orford]

    Elixir is the new hot programming language on the block. The bastard child of Ruby and Erlang. Syntax Ruby is designed like Apple designs phones. It looks and feels right. I love that the goal of Ruby language design is to reduce cognitive dissonance when implementing features. Everything has to fit together just right. Elixir has the same mindset and looks beautiful. Semantics Over a decade ago I
  • Extreme Divergence: Negative Equity Returns Ahead [Trader Edge]

    Many traders use technical and/or fundamental data, but few traders have discovered the unique benefits of using sentiment data in their investment process. Sentiment data attempts to quantify the emotional mood of investors and traders and can be used as a very effective contra-indicator. When traders are unusually complacent and overly bullish, markets tend to pull back. Conversely, when traders

Quantocracy’s Daily Wrap for 10/31/2015

This is a summary of links featured on Quantocracy on Saturday, 10/31/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hedge Fund Closet Indexing: 2015 Update [Alpha Beta Works]

    A fund must take active risk to generate active returns in excess of fees. However, some managers charge active fees but manage their funds passively. Managers also tend to become less active as they accumulate assets. This problem of hedge fund closet indexing is widespread. Over a third of capital invested in U.S. hedge funds long equity portfolios is too passive to warrant the common 1.5/15%

Quantocracy’s Daily Wrap for 10/30/2015

This is a summary of links featured on Quantocracy on Friday, 10/30/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Experts Aren’t Helpful, and Other Useful Lessons From “DIY Financial Advisor” [GestaltU]

    We draw a significant amount of inspiration for the material we cover on this blog from the publications of our financial brethren. Unfortunately, given the non-stop firehouse of information that increasingly characterizes the digital age, its nearly impossible to consume anything longer than a blog post. So its noteworthy that we were inspired to read cover to cover Wes Grey, Jack

Quantocracy’s Daily Wrap for 10/29/2015

This is a summary of links featured on Quantocracy on Thursday, 10/29/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • US recessions, the Value Factor (HML) and current status [RRSP Strategy]

    The Fama-French value factor HML exhibits a fairly reliable 4 year cycle. Growth and Value out-performance oscillates with a 4 year period (see my previous post on this). Liew and Vassilou (1999), show that annual change in HML is related to future GDP change (see my blog post here). Therefore tracking HML allows us to glean insight into upcoming economic conditions. Where are we in the current
  • High Frequency Market Microstructure: Part 1 (Microstructure Noise) [Portfolio Effect]

    Microstructure noise describes price deviation from its fundamental value induced by certain features of the market under consideration. Common sources of microstructure noise are: bid-ask bounce effect order arrival latency asymmetry of information discreteness of price changes Noise makes high frequency estimates of some parameters (e.g. realized volatility) very unstable. The situation gets
  • Cycle Factor Can Predict Returns [Larry Swedroe]

    Anna Cieslak and Pavol Povalaauthors of the paper Expected Returns in Treasury Bonds, which was published in the September 2015 issue of The Review of Financial Studiesexamined the time variation in the risk premium that investors require for holding Treasury bonds. While most of the authors analysis relies on data starting in 1971 (when data for bond maturities 10 years and longer
  • SPX Straddle – 73 DTE – Results Summary [DTR Trading]

    Over the last five blog posts we looked at the automated backtest results for 4160 options straddles sold on the S&P 500 Index (SPX) at 73 days-to-expiration (DTE). Eight different loss approaches were tested on these straddles. On top of these eight loss approaches, tests were conducted with no profit taking, and profit taking at 10%, 25%, 35%, and 45% of the credit received. For background
  • All firms can benefit from the positive influence of women [Alpha Architect]

    Marisa Mayers recent announcement that she is again pregnant, and does not plan to take maternity leave after her twins arrive, has once again raised the age-old question about how far women have really come in making a gender equitable workplace. While women are undoubtedly making progress, recent research from specialists in behavioral finance suggests that in many respects, the discussion to

Quantocracy’s Daily Wrap for 10/27/2015

This is a summary of links featured on Quantocracy on Tuesday, 10/27/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Write a Great Quant Blog [Quant Start]

    Today's post is a guest post from Jacques Joubert, who runs QuantsPortal. Jacques emailed me recently and asked if I'd be willing to contribute to a post about how to get started in quant blogging. I was more than happy to do so, and Jacques wondered if it would make a good guest post for QuantStart. Many very well respected individuals in the quant blogosphere have contributed to the
  • Why Sector Investing [Flirting with Models]

    I just came across a great post on sector investing by Dave Mazza, Head of Research for SSGA's ETF and mutual fund businesses. There is a lot of great information he walks through, but I thought there were three tidbits particularly interesting to us as risk managers. First, he points out that investing in index based sector products still offers significant diversification against single
  • Which Asset Allocation Weights Work the Best? [Alpha Architect]

    Okay, we're sold on a closet-indexing approach to the markets. Now we're investigating a variety of smart-beta products available in the market that weigh a large portfolio of stocks with some algorithm. But a natural question arises when trying to pick smart beta ETFs: What is the optimal method to weigh an index? Everyone seems to have a story these days for the "best" way to
  • 5 Words on How To Write A Quant Blog [Quant at Risk]

    Do not commence working over your blog without the vision. If you dont know where you are going, any road will get you there! You want to avoid that mistake. Spend some time dreaming of the final form of your site. Highly sought after content is important but not as much as your commitment to excel in its delivery. Write from your heart. Listen to your inner voice. Follow your own

Quantocracy’s Daily Wrap for 10/26/2015

This is a summary of links featured on Quantocracy on Monday, 10/26/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Cold Blood Index [Financial Hacker]

    Youve developed a new trading system. All tests produced impressive results. So you started it live. And are down by $2000 after 2 months. What now? Carry on in cold blood, or pull the brakes in panic? This is a situation all too familiar to any algo trader. There can be several reasons why a strategy loses money right from the start. It can be already expired since the market inefficiency
  • You do not experience summary statistics [Flirting with Models]

    In due diligence, we often evaluate summary statistics like annualized return, volatility, alpha, beta, up-capture, and down-capture. These statistics can unify years of returns into a single number. While this can be convenient for comparing different strategies, it fails to provide adequate insight into the actual week-to-week experiences an investor will face. We highlight how even in the best
  • Buy the Winners [Systematic Relative Strength]

    People come up with all kinds of reasons not to buy stocks with strong momentum. Some of the most common reasons that I hear: Stocks with high momentum are risky Stocks with high momentum are overvalued Stocks with high momentum are susceptible to reversals As for the first point, yes, buying stocks with high momentum is risky. So is buying stocks with weak momentum. As far as that goes, buying
  • A Complementary Approach To Trading Technical Indicators [System Trader Success]

    In the October issue of Futures magazine author Jean Folger discusses an important aspect when selecting two or more indicators when developing a trading system. While I dont recommend simply combining indicators to create a trading system, and I dont think thats what Folger is suggesting either, when there comes a time to introduce two or more technical indicators to a trading system,