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Quantocracy’s Daily Wrap for 08/20/2015

This is a summary of links featured on Quantocracy on Thursday, 08/20/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 08/19/2015

This is a summary of links featured on Quantocracy on Wednesday, 08/19/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Health of Stock Mean Reversion: Dead, Dying or Doing Just Fine [Alvarez Quant Trading]

    My second post on this blog was a look at mean reversion, Is mean reversion dead? Given I am using a new data provider(Premium Data), it has been almost two years since that post and there have been other articles on this recently, I figured it was time to check again. The research will focus on Russell 1000 stocks since 1995. The test is back to 1995 covers 3 bull markets and 2 bear ma
  • Correlation and correlation structure [Eran Raviv]

    Given a constant speed, time and distance are fully correlated. Provide me with the one, and Ill give you the other. When two variables have nothing to do with each other, we say that they are not correlated. You wish that would be the end of it. But it is not so. As it is, things are perilously more complicated. By far the most familiar correlation concept is the Pearson
  • Technical Analysis or Quantitative Analysis? [Factor Wave]

    Yesterday I had a coffee with a person I have known for 20 years. He has worked as a quantitative analyst, a trader and a finance professor for at least as that long. He is one of the most knowledgeable people I know. When he says something it is worth listening. What he said was (roughly), " I've come to believe that there is something to technical analysis".
  • Crisis Alpha: Surprising Ways to Hedge Stock Portfolio Risk [Alpha Architect]

    Investing in the current environment is difficult. Most, if not all, asset classes have high nominal prices, suggesting low nominal expected returns. Not exactly exciting. And for many investors who are retired and/or have near-term liquidity needs, investing in equity exposureswhile necessary to generate higher expected returnsalso prevents many investors from sleeping at night!
  • New academic paper related to #12 – Pairs Trading with Stocks [Quantpedia]

    We assume that the drift in the returns of asset prices consists of an idiosyncratic component and a common component given by a co-integration factor. We analyze the optimal investment strategy for an agent who maximizes expected utility of wealth by dynamically trading in these assets. The optimal solution is constructed explicitly in closed-form and is shown to be affine in the co-in

Quantocracy’s Daily Wrap for 08/18/2015

This is a summary of links featured on Quantocracy on Tuesday, 08/18/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Kalman Filter and Pairs Trading [MKTSTK]

    Imagine this scenario: you are a statistical arbitrage trader at a prop desk or HF. As such, you routinely hold an inventory of ETF exposure that you must hedge. The previous night, you instructed your overnight traders to calculate the hedge ratios for a matrix of ETFs. The next morning before the market opens, your junior traders eagerly present their result
  • The Effect of the Board of Directors [Factor Wave]

    The Quality factor is a composite measure designed to identify companies with the characteristics that typically lead to success. It is particularly useful to identify "value traps": companies which are cheap by current metrics but are losing money. I wrote a little about quality here. However, we are not so dogmatic that we won't admit that there are aspects of quality tha
  • Intertemporal PCA Analysis [John Orford]

    Taking a leaf out of Mike Harris' recent Momersion theme, here's a PCA point of view of the balance between momentum and mean reversion over the previous 10 years from the Lazy PCA tool. August 2015 – 2014 PCA fits momentum and mean reversion components to the daily returns, they balance each other out here, which means the market is somewhat efficient (i.e. 'momersio
  • State of Trend Following in July: UP [Au Tra Sy]

    July saw a bounce back up in the index after several months of downwards action. The YTD performance is still negative though. Please check below for more details. Detailed Results The figures for the month are: July return: 3.86% YTD return: -1.47% Below is the chart displaying individual system results throughout July:

Quantocracy’s Daily Wrap for 08/17/2015

This is a summary of links featured on Quantocracy on Monday, 08/17/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Introduction to Monte Carlo Analysis Part 1 [Quants Portal]

    The Monte Carlo, filled with a lot of mystery is defined by Anderson et al (1999) as the art of approximating an expectation by the sample mean of a function of simulated variables. Used as a code word between Stan Ulam and John von Neumann for the stochastic simulations they applied to building better atomic bombs (Anderson, 1999), the term Monte Carlo evolved into a method used in a
  • The Sustainable Active Investing Framework: Simple, But Not Easy [Alpha Architect]

    The debate over passive versus active investing is akin to Eagles vs. Cowboys or Coke vs. Pepsi. In short, once our preference for one style over the other is established, it becomes a proven fact or incontrovertible reality in our minds. This post is not meant to convert a passive investor into an active investor; however, we do explain why we believe some active investing
  • Strategy Gamma Overview [John Orford]

    Economics 101 tells us that people have 'convex' utility curves. Which means there are diminishing returns to having more, but losing what you currently have diminishes your well being precipitously. Convexity is such a human property, it shows up again and again in unexpected places. Eyeballs, boobs and butts to name a few examples. I
  • Interview with Larry Williams [Better System Trader]

    On the show this week we have Larry Williams who has been trading futures and stocks for over 50 years. In 1987 he won the world cup trading championship, turning $10,000 in to over $1.1 million in 12 months, that's a cool 11,000% return and the highest return to ever be achieved in that competition. 10 years later his daughter won the same competition with a 1000% return a
  • Downloading Stock Market News for Specific Symbols [Godel’s Market]

    Grabbing the data. How do you grab the latest news on your favorite ticker symbol? It all starts with the following URL. https://www.google.com/finance/company_news?q=SPY&output=rss You'll want to change "q=SPY" to whatever symbol you're interested in. You can add something like the following to the end if you'd like m
  • Can managed futures manage rising rates? [Flirting with Models]

    Summary Rising interest rates are on the horizon somewhere Yield curve dynamics including the absolute level of rates, their direction of change, and the slope of the yield curve all play an important role in the returns for managed futures The cost of carry in shorting fixed-income futures means that commodity trading advisors (CTAs) may fail
  • Autoregressive Moving Average ARMA(p, q) Models for Time Series Analysis – Part 1 [Quant Start]

    In the last article we looked at random walks and white noise as basic time series models for certain financial instruments, such as daily equity and equity index prices. We found that in some cases a random walk model was insufficient to capture the full autocorrelation behaviour of the instrument, which motivates more sophisticated models. In the next couple of articles w
  • Weather and the Markets [Factor Wave]

    It should be fairly obvious to anyone who has been involved with investing for any time, that traders decisions are heavily influenced by their mood. Actually, some interesting recent research has shown that people generally make decisions intuitively before using their conscious thought processes to justify them. No one is actually all that rational. So perhaps it should b
  • RUT Strangle – High Loss Threshold – 59 DTE [DTR Trading]

    This post reviews the backtest results of selling one-lot options strangles on the Russell 2000 Index (RUT), initiated at 59 days-to-expiration (DTE). The results in this post were derived from 2312 individual trades entered by the backtester. The results are grouped by the delta of the short strikes. For example, a 4 delta strangle is constructed by selling a -4 delta put, and selli

Quantocracy’s Daily Wrap for 08/14/2015

This is a summary of links featured on Quantocracy on Friday, 08/14/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Some More on Stock Splits [Factor Wave]

    About a month ago I started to answer a reader's question about stock splits. I was initially diverted by the "low price effect" and then forgot to revisit the topic. In addition to the fact that a split reduces the price, it is also a distinct event and we can study the dynamics of the stock price before and after the split. And many, many people have… Befor
  • Fractal Strategy Applied to Indonesian Index [John Orford]

    When I lived in New York, every other night I'd have a drink with our head of financial engineering. Beer in the winter, G&Ts in the summer. In any case once he was telling me how in Japan even ordering coffee was tricky, because the Japanese didn't want to cause offence by not knowing English well, and he being somewhat familiar of Japanese culture, wanted to be polite as

Quantocracy’s Daily Wrap for 08/12/2015

This is a summary of links featured on Quantocracy on Wednesday, 08/12/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Absolute Strength Momentum: Guley And Petkova (2015) [Flirting with Models]

    In May 2015, Huseyin Gulen and Ralitsa Petkova published "Absolute Strength: Exploring Momentum in Stock Returns" (SSRN). In the paper they outline their new concept of absolute strength momentum. Momentum, in its traditional form, was a relative strength concept. Momentum took the cross-section of returns across securities, bough the "winners" and sold the "
  • Equal Weighting Investigation [John Orford]

    I landed in a town in Western Sumatra called Padang a few days after an earthquake hit. 7 or 8 on the Moment Magnitude scale. Just as in finance there are various ways of measuring quakes. The Richter scale measures ground motion whereas the more modern Moment Magnitude scale measures energy released. In any case my favourite measure of earthquake size is the n
  • 3-Bar Momentum Pattern | Trading Strategy (Entry) [Oxford Capital]

    I. Trading Strategy Concept: Short-term momentum pattern with trend filter. Source: Hill, J. R. (1977). Stock & Commodity Market Trend Trading by Advanced Technical Analysis. Hendersonville, N.C.: Commodity Research Institute, Ltd. Research Goal: Performance verification of 3-Bar Momentum Pattern. Specification: Table 1. Results: Figure 1-2. Portfolio: 42 futures markets f
  • Python Backtesting Libraries For Quant Trading Strategies [Robust Tech House]

    Frequently Mentioned Python Backtesting Libraries It is essential to backtest quant trading strategies before trading them with real money. Here, we review frequently used Python backtesting libraries. We examine them in terms of flexibility (can be used for backtesting, paper-trading as well as live-trading), ease of use (good documentation, good structure)
  • Volatility Breakout Model | Trading Strategy (Benchmark) [Oxford Capital]

    I. Trading Strategy Concept: Volatility breakout strategy based on price deviations defined by Minkowski Distance where: Upper_Band = Mean + (Multiple Deviation); Lower_Band = Mean ? (Multiple Deviation); Deviation((Close)k=1,,K, Mean) = (?|Close ? Mean|? K)1/?. Minkowski Distance has two special cases: (a) when ? = 1 (Manhattan Distance), the above formula reflects

Quantocracy’s Daily Wrap for 08/11/2015

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

  • Vectorised Backtest in R [Quants Portal]

    In the previous 3 articles I discussed backtesting a trading strategy in Excel using the vectorised methodology. This article will cover the same strategy but in R. This article is more of a supplement to the already published article by Joshua Ulrich on FOSS Trading and is for readers looking for more examples. Before we get started, Id like to point out how
  • Update on the MOOC Machine Learning for Trading [Augmented Trader]

    If you want to be sure to be notified about enrollment opportunities, please sign up to follow my blog. I will post that information on this blog. The old course Weve had four very successful sessions of my MOOC Computational Investing, Part I at Coursera. The Coursera run included over 170,000 students with a 5% completion rate. The Coursera course f
  • War and the Markets [Factor Wave]

    This post is based on an article I wrote for Active Trader Magazine. "Buy to the sound of cannons, sell to the sound of trumpets." -Lord Nathan Rothschild, 1810 The Rothschilds were one of the worlds richest families and formed a modern financial dynasty. In 1815 they were rumored to have made a fortune when they used a carrier pigeo
  • When do equity anomalies have the highest return? During earnings announcements… [Quantpedia]

    Authors: Engelberg, McLean, Pontiff Title: Anomalies and News Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2631228 Abstract: Using a sample of 97 stock return anomalies documented in published studies, we find that anomaly returns are 7 times higher on earnings announcement days and 2 times higher on corporate news days. The effects are similar on both the long and short
  • Dual Momentum August Update [Scott’s Investments]

    Scotts Investments provides a free Dual ETF Momentum spreadsheet which was originally created in February 2013. The strategy was inspired by a paper written by Gary Antonacci and available on Optimal Momentum. Antonaccis book, Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk, also details Dual Momentum as a total portfolio strategy. My

Quantocracy’s Daily Wrap for 08/10/2015

This is a summary of links featured on Quantocracy on Monday, 08/10/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Bring Data [Dual Momentum]

    When doing financial modeling, one of the first things to look at is if your empirical work makes sense. In other words, are there valid economic reasons why a model should work? This can help you avoid drawing erroneous conclusions based on creative data mining.[1] Next, you should look for robustness. This can take several forms. One of the most common robustness tests i
  • Death of (Plain Vanilla) Value – Long Live GARP [EconomPic]

    Warren Buffett made news this morning, not just for making the largest acquisition of his career, but for making it at a relatively lofty 22x earnings multiple. Reuters reports: Warren Buffett is paying a hefty price for the biggest acquisition of his career, now that his Berkshire Hathaway Inc has agreed to buy Precision Castparts Corp in a merger valuing
  • What is the difference between Relative Strength and Trend Following? [Flirting with Models]

    After publishing our Two Centuries of Momentum article last week, we received a number of requests for our thoughts on the recent underperformance of multi-asset, relative strength portfolios. Now, we tend to fall more on the trend following side of momentum. So we wanted to spend some time talking about the difference between relative strength and trend following.
  • Wisdom State of Trend Following – July 2015 [Wisdom Trading]

    Summer bounce for our Wisdom State of Trend Following report. A strong up month ends the downslide seen in the second quarter and ensures the YTD performance is more comfortably in the black. Below is the full State of Trend Following report as of last month. Performance is hypothetical. Chart for July: Wisdom State of Trend Following – July 2015
  • Improving The Simple Gap Strategy Part 5 [System Trader Success]

    In the last article of the series, Improving The Simple Gap Strategy Part 4, I continued my attempt to improve the Simple Gap strategy by testing dynamic stops and targets. As it turned out these did not seem to offer much benefit. In this article Im going to take what we have learned over the past couple of articles to create a modified version of the Simple Gap strategy and test it o
  • Show yourself (look under the hood of a function in R) [Eran Raviv]

    Open source software has many virtues. Being free is not the least of which. However, open source comes with ABSOLUTELY NO WARRANTY and with no power comes no responsibility (I wonder..). Since no one is paying, by definition it is your sole responsibility to make sure the code does what it is supposed to be doing. Thus, looking under the hood of a function written by someone else i
  • Tradelib is Open Source [Quintuitive]

    Tradelib is my framework which I have been using for backtesting and signal generation in my futures trading. My feeling is that it might be useful to others, and I have decided to open source it. Unfortunately, I dont have the time at the moment to open source any strategy implemented with it, and I am also too lazy to provide a step-by-step guide for it. If you have an i
  • RUT Strangle – High Loss Threshold – 45 DTE [DTR Trading]

    This is the first article in a series that will review the performance of selling options strangles on the Russell 2000 Index (RUT). 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 Strangle Series – Higher Loss Thresholds This post looks at selling on

Quantocracy’s Daily Wrap for 08/07/2015

This is a summary of links featured on Quantocracy on Friday, 08/07/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Battle Of New Factor Models [Larry Swedroe]

    In their groundbreaking paper, Digesting Anomalies: An Investment Approach, Kewei Hou, Chen Xue and Lu Zhang proposed a new four-factor asset pricing model that goes a long way toward explaining many of the anomalies neither the Fama-French three-factor nor subsequent four-factor models could explain. The study, which was published in the March 2015 issue of The Review of
  • Momentum Strategies [Quants Portal]

    Pinto, Henry, Robinson and Stowe (2010) define momentum indicators as valuation indicators that are based on the relationship between price or another fundamental, earnings for example, to a time series of its historical performance or to the fundamentals expected future performance values. When the strategy uses earnings then it is an earnings momentum strategy and in the case of usin
  • Hello, Market Maker! [MKTSTK]

    As we have made clear in the past, we are fascinated by the economics of open source software. This business model makes sense for massively scalable and ubiquitous bits of technology, but surely it must be anathema to the closed world of trading, right? This has an intuitive appeal, we know of people that have made millions off of the information acquired overhearing conve
  • Selecting an Appropriate Benchmark [Quantlab.co.za]

    Introduction I have the privilege of working with two of the sharpest minds in the industry. Last week I had a discussion with them via email about selecting a suitable benchmark for the strategies I run. I was specifically questioning them on the use of cash returns as a benchmark. This is a contentious issue in the industry – many folk disagree with cash as a benchmark be
  • The Junkie Market, Part lll – Too Many NYSE AND Nasdaq Highs & Lows [Dana Lyons]

    This brief post will serve as the coup de grace for our Junkie Market series. By that, we are referring to days on which there are numerous (in this case, at least 100) new 52-Week Highs AND 52-Week Lows. We have covered such occurrences on the NYSE and the Nasdaq exchanges. If youll recall, these events tended to pop up near cyclical market tops. Thus, the forward returns in t

Quantocracy’s Daily Wrap for 08/05/2015

This is a summary of links featured on Quantocracy on Wednesday, 08/05/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Two Centuries of Momentum [Flirting with Models]

    A momentum-based investing approach can be confusing to investors who are often told that chasing performance is a massive mistake and timing the market is impossible. Yet as a systematized strategy, momentum sits upon nearly a quarter century of positive academic evidence and a century of successful empirical results. Our firm, Newfound Research, was found
  • Maximum Loss Stops: Do you really need them? [Alvarez Quant Trading]

    We hear it all the time. You must use stops. And most of us use them. But do you know how they change your strategy results? Are they improving your results by giving you higher CAR or lower maximum drawdown? Recently I was speaking with a reader about this topic and he insisted that it you had to have stops to trade. Well, does one? Early in my time while working with La
  • Turn of the Month Effect in Commodities [Factor Wave]

    I've been thinking about applying factor analysis to commodity futures. People have studied this idea but commodity factors have not been studied to the same degree as equity factors. This is to be expected. Stocks are parts of companies and there are many commonalities between the operations and accounting reports of companies, even those in different industries and sectors. On the oth
  • When Bonds Act Like Stocks [Larry Swedroe]

    Research into the determinants of fixed-income returns have found that a number of stock and bond market risk factors can be shown to demonstrate explanatory power beyond the standard term-structure variables. Ivelina Pavlova, Ann Marie Hibbert, Joel Barber and Krishnan Dandapaniauthors of the paper Credit Spreads and Regime Shifts, which appears in the Summer 2015 issue