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Quantocracy’s Daily Wrap for 11/11/2015

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

  • Correlation and correlation structure (3), estimate tail dependence using regression [Eran Raviv]

    What is tail dependence really? Say the market had a red day and saw a drawdown which belongs with the 5% worst days (from now on simply call it a drawdown): weekly SPY returns One can ask what is now, given that the market is in the blue region, the probability of a a drawdown in a specific stock? We all understand the concept of beta of a stock with respect to the market, the sensitivity of a
  • Momentum On Dual Momentum Portfolios [Quants Portal]

    In the first section, this article describes a Dual Momentum study over an iShares country etfs basket with a new attempt to improve this well-known investing style. I chose iShares because it is the world largest family of Exchange Traded Funds (ETFs) from BlackRock. Although different stock markets correlations have become weaker and weaker in these last 10 years, this article easily shows that
  • Hi-Lo Index as a Market Timing Indicator [Alvarez Quant Trading]

    My strategies use a market timing indicator to tell me when I should not be trading the strategy. The blog post, Avoiding Stock Market Crashes with the Hi-Lo Index of the S&P500, presented a very simple idea of using new highs vs new lows. The post tests trading the SPY & IEF but I wanted to know how well would it work on a S&P500 mean reversion strategy. The Indicator The Hi-Lo Index
  • Valuation Metrics In Perspective [Larry Swedroe]

    Its well-established in the literature that valuation metricssuch as the dividend yield (D/P) and the earnings yield (E/P), as well as its cousin, the Shiller CAPE 10provide important information in terms of future expected returns. In fact, these metrics are the best that investors have for predicting long-term equity results. For instance, the Shiller CAPE 10, a cyclically adjusted
  • Pros and Cons of New Technology-enabled Indexes [CXO Advisory]

    What are pros and cons of extending the definition of financial index beyond conventional market capitalization (buy-and-hold) weighting? In the October 2015 draft of his paper entitled What Is an Index?, Andrew Lo proposes that any portfolio satisfying three properties should be considered an index: (1) transparent (public and verifiable); (2) investable (realistic and liquid benchmark);
  • Deconstructing the Time-Series Momentum Strategy [Quantpedia]

    Moskowitz, Ooi, and Pedersen (2012) show that time series momentum delivers a large and significant alpha for a diversified portfolio of various international futures contracts over the 1985 to 2009 period. Although we confirm these results with similar data, we find that their results are driven by the volatility-scaled returns (or the so-called risk parity approach to asset allocation) rather

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 11/10/2015

This is a summary of links featured on Quantocracy on Tuesday, 11/10/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Random data: Evaluating [Investment Idiocy]

    Everyone hates drawdowns (those periods when you're losing money whilst trading). If only there was a way to reduce their severity and length…. Quite a few people seem to think that "trading the equity curve" is the answer. The basic idea is that when you are doing badly, you reduce your exposure (or remove it completely) whilst still tracking your 'virtual' p&l
  • I bought corporate bonds and all I got was this stupid currency exposure [Flirting with Models]

    Summary In the current Fed on / Fed off market environment, dollar exposure matters Currency hedged exposures have exploded in popularity in the equity space Using the experience of Canadian investors, we demonstrate the large impact that currency can have on fixed income Investors buying global bonds should consider whether currency hedging makes sense for them Currency hedging remains a
  • Making Time (Even More of) an Investor’s Best Friend [EconomPic]

    Ben Carlson of A Wealth of Common Sense blog (and author of a great book by the same name), had a recent post Playing the Probabilities outlining that time has been an investor's best friend (for those investors that have had in some cases quite a bit of time), pointing to the following table. He also shared some pretty amazing stats, including: The worst total return over a 20 year period
  • How Monday s Strong Drop May Be Setting SPX Up For A Bounce [Quantifiable Edges]

    When a market has already sold off for multiple days and the selling accelerates that can often mark a point where a bounce becomes likely. Mondays selling triggered the Quantifinder study below. All stats are updated. 2015-11-10 image1 These results appear extremely compelling. The consistency is very strong. Of course the market is always capable of doing things it hasnt before. Weve

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 11/08/2015

This is a summary of links featured on Quantocracy on Sunday, 11/08/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • [Academic Paper] Idiosyncratic Volatility, Momentum, Liquidity, and Expected Stock Returns in Developed and Emerging Markets [@Quantivity]

    Idiosyncratic Volatility, Momentum, Liquidity, and Expected Stock Returns in Developed and Emerging Markets
  • [Academic Paper] Over or Under? Momentum, Idiosyncratic Volatility and Overreaction [@Quantivity]

    Over or Under? Momentum, Idiosyncratic Volatility and Overreaction
  • Gap Pattern | Trading Strategy (Filter & Exit) [Oxford Capital]

    I. Trading Strategy Concept: Short-term momentum patterns with a trend filter. Source: Dahlquist, J. R., Bauer, R. J. (2012). Technical Analysis of Gaps. New Jersey: Pearson Education, Inc. Research Goal: Performance verification of the Gap Pattern. Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Price Gap: Low[i] > High[i ? 1]); Index: i ~ Current Bar. Short Price Gap: High[i]
  • Interview with Laurent Bernut [Better System Trader]

    Laurent Bernut was a systematic short seller with Fidelity for 8 years. His mandate was to underperform the longest bear market in modern history: Japanese equities. Prior to that, he worked in the Hedge Fund world for 5 years. He now runs an automated Forex strategy and travels the world with his family. In this episode we talk all about Short selling, creating shorting strategies, the challenges
  • Asynchronicity & Performance – ‘JavaScript for Financial Analysts’ Chapter 7 [John Orford]

    First draft of 'JavaScript for Financial Analysts' Chapter 7. ~ We are all waiting for something, and our computers are no different. Computers are built on four building blocks. CPUs, memory, hard disk and network. Our programs are only as fast as the slowest component. To put machine-scale wait times in a human context, this table normalises wait times to a base of one second.
  • [Academic Paper] Risk Premia: Asymmetric Tail Risks and Excess Returns [@Quantivity]

    Risk Premia: Asymmetric Tail Risks and Excess Returns
  • [Academic Paper] Dynamics of Expected Returns: Evidence from Multi-Scale Time Series Modeling [@Quantivity]

    Dynamics of Expected Returns: Evidence from Multi-Scale Time Series Modeling
  • [Academic Paper] Anchoring Adjusted Capital Asset Pricing Model [@Quantivity]

    Anchoring Adjusted Capital Asset Pricing Model

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 11/07/2015

This is a summary of links featured on Quantocracy on Saturday, 11/07/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

    No new links posted.

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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%

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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