Quantocracy

Quant Blog Mashup

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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,

Quantocracy’s Daily Wrap for 10/25/2015

This is a summary of links featured on Quantocracy on Sunday, 10/25/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    My fellow quant nerds, we need to vote more. Less than 2% of clickthroughs result in a vote. Thats just not enough. A vote doesnt mean a link is the greatest of all time, only that its good and deserves to be read by others. Higher rated links are read significantly more often, so help me to encourage bloggers to write quality content by making your voice heard. I do my part by providing
  • Highlights from Episodes 1-20 [Better System Trader]

    This weeks show is going to be a little different to previous episodes. A couple of weeks ago I went back through all the guests weve had on the show so far and realised how very fortunate weve been to have so many fantastic guests on the show, sharing their knowledge and experience, some of them with more than 50 years of trading experience! To be honest, Id actually forgotten some of

Best Links of the Week

My fellow quant nerds, we need to vote more. Less than 2% of clickthroughs result in a vote. I know we can do better. Higher rated links are read significantly more often, so help me to encourage bloggers to write quality content by registering to vote and making your voice heard. — Mike @ Quantocracy

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The best quant mashup links for the week ending Saturday, 10/24 as voted by our readers:

Links from Quantocracy:

Most Popular Books from the Bloggers at Quantocracy

Below is a list of all of the books written by all of the folks on our quantitative trading blogroll, sorted by Amazon sales rank from most to least popular. I did the legwork for a new page I’m putting together for the site (similar to what we used to have at The Whole Street), and thought it worth sharing.

Biggest non-surprise? Faber is killing it. Biggest surprise? Howard Bandy is killing it almost equally hard. Good stuff gentlemen. Click on the book title to read more at Amazon.

 

Author Book Title Rank
Meb Faber Global Asset Allocation: A Survey of the World’s Top Asset Allocation Strategies 12586
Statistical Ideas Statistics Topics 19540
Alpha Architect DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth 27849
Howard Bandy Mean Reversion Trading Systems 33223
Dual Momentum Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk 39889
Howard Bandy Quantitative Technical Analysis: An Integrated Approach to Trading System Development and Trading Management 51147
Meb Faber Global Value: How to Spot Bubbles, Avoid Market Crashes, and Earn Big Returns in the Stock Market 51706
Meb Faber Shareholder Yield: A Better Approach to Dividend Investing 54386
Howard Bandy Quantitative Trading Systems 56233
Investment Idiocy Systematic Trading: A Unique New Method for Designing Trading and Investing Systems 65183
Meb Faber The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets 78333
Following the Trend Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies 86615
Following the Trend Following the Trend: Diversified Managed Futures Trading 101297
Howard Bandy Modeling Trading System Performance 111440
Larry Connors & Cesar Alvarez Short Term Trading Strategies That Work 131942
R for Traders Quantitative Trading with R: Understanding Mathematical and Computational Tools from a Quant’s Perspective 184732
Alpha Architect Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors 186673
Factor Wave Volatility Trading 210912
EP Chan Algorithmic Trading: Winning Strategies and Their Rationale 245332
EP Chan Quantitative Trading: How to Build Your Own Algorithmic Trading Business 267062
Trader Edge Option Strategy Risk / Return Ratios: A Revolutionary New Approach to Optimizing, Adjusting, and Trading Any Option Income Strategy 298531
Larry Connors & Cesar Alvarez High Probability ETF Trading: 7 Professional Strategies to Improve Your ETF Trading 328808
Greenbackd Deep Value: Why Activist Investors and Other Contrarians Battle for Control of Losing Corporations 354828
Larry Connors & Cesar Alvarez How Markets Really Work: Quantitative Guide to Stock Market Behavior 377306
Falkenblog The Missing Risk Premium: Why Low Volatility Investing Works 492650
Trader Edge Exploiting Earnings Volatility: A New Approach to Evaluating, Optimizing, and Trading Option Strategies to Profit from Earnings Announcements 528542
Factor Wave Option Trading: Pricing and Volatility Strategies and Techniques 777402
Jay on the Markets Seasonal Stock Market Trends: The Definitive Guide to Calendar-Based Stock Market Trading 1227918
Falkenblog Finding Alpha: The Search for Alpha When Risk and Return Break Down 1243587

Quantocracy’s Daily Wrap for 10/21/2015

This is a summary of links featured on Quantocracy on Wednesday, 10/21/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How well can you scale your strategy? [QuantStrat TradeR]

    This post will deal with a quick, finger in the air way of seeing how well a strategy scalesnamely, how sensitive it is to latency between signal and execution, using a simple volatility trading strategy as an example. The signal will be the VIX/VXV ratio trading VXX and XIV, an idea I got from Volatility Made Simples amazing blog, particularly this post. The three signals compared will be
  • Stock Volatility Moves Treasurys [Larry Swedroe]

    Understanding the volatility of Treasury bond returns, as well as the volatility of both the level and slope of the Treasury term-structure, are fundamental issues in finance. Whats more, they have important implications for investors and portfolio design. Researchers have offered both theory and empirical evidence that suggest important linkages between equity risk and the Treasury bond
  • Utilizing the Value of Value to Make Value / Growth Tilts [EconomPic]

    Back in August I outlined why I thought the plain-vanilla value premium had been compressed to the point growth had and was likely to continue to outperform in my post Death of (Plain Vanilla) Value – Long Live GARP. This post is meant as a follow up and suggests a few frameworks as to how an investor might allocate based on the given "value of value". Backdrop: Value of Value Matters
  • Sir Bayes: all but not na ve! [Quant Dare]

    Is it possible to classify and predict (yes, predict!) if market trends will be bullish, bear or ranged by using a method called nave and based on something as simple as Bayes theorem is? Lets see! Predicting trends with nave Bayesian classifier Our main objective is to explore techniques of machine learning that can help us not only to label series in a posteriori analysis, but
  • Information Ratio Hypothesis Testing [John Orford]

    Spurned by reading an account of a trader who swears by machine learning, few days ago I wrote about aesthetics in finance. Maths and tech without a narrative is pointless. My own attempts at providing a narrative foundered a few months back. Suspend Your Disbelief! I started using the Sharpe as a hypothesis test. So for example, the S&P 500 (not including dividends) has a Sharpe of ~0.462
  • Insider Trading During the 8-K Trading Gap [Alpha Architect]

    SEC rules allow companies to delay the public disclosure of significant corporate events for up to 4 business days. This information is reported on an 8-K. This 4-day gap between an event and the disclosure creates an interesting situation. As an insider, if I know an 8-K is going to report news, I may want to try and trade in that 4 day window when the information is not available to the broader
  • Biotech: My love-hate relationship [Alvarez Quant Trading]

    The two charts above are from recent trades I have taken. Charts created in AmiBroker. On July 20, 2015 IBB, iShares Nasdaq Biotechnology ETF, made a closing high of 398. About three months later it closed at 289 for 27% loss. A very common thing I hear from traders is that they dont trade biotechnology or pharmaceutical stocks. I completely understand. These stocks tend to be very