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Quantocracy’s Daily Wrap for 09/21/2015

This is a summary of links featured on Quantocracy on Monday, 09/21/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Active Share Debate: AQR versus the Academics [Alpha Architect]

    There is an interesting discussion in the geeky world of academic finance literature between the intellectual muscle at AQR and academia. aqr versus the academics on active share The discussion revolves around the following question: Does Active Share matter? This is an important topic for active ETFs and Mutual Funds in the marketplace. The original paper on this measure was written by
  • Risk Management for Automated Trading I : Lack of it [Quant Insti]

    Impact of Proliferation of Automated Trading Systems and Technology on Financial Markets With the advent of automated trading everything has become computerized. Risk management takes a whole new level in this technologically fast paced world. The trends in day-to-day trading have been changing. This change has led to many automated trading failures where risk was not managed in a sound manner.
  • Correlation and correlation structure [Eran Raviv]

    This post is about copulas and heavy tails. In a previous post we discussed the concept of correlation structure. The aim is to characterize the correlation across the distribution. Prior to the global financial crisis many investors were under the impression that they were diversified, and they were, for how things looked there and then. Alas, when things went south, correlation in the new
  • Forecasting interest rates [Econbrowser]

    There was lots of action in financial markets last week, with much of the attention focused on the U.S. Federal Reserve. The interest rate on a 10-year U.S. Treasury bond edged up 10 basis points early in the week in anticipation that the Fed might finally raise its target for the short-term interest rate. But it shed all that and more after the Fed announced it was standing pat for now. Price of

Quantocracy’s Daily Wrap for 09/20/2015

This is a summary of links featured on Quantocracy on Sunday, 09/20/2015. 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, 09/19 as voted by our readers: Hacking the Random Walk Hypothesis [Turing Finance] Getting Started: Building a Fully Automated Trading System [Quants Portal] Interview with Euan Sinclair [EP Chan] Interview with Dr Ernest Chan [Factor Wave] Probability Investing [Price Acti
  • Getting Started with Javascript – First Draft [John Orford]

    First draft of 'Javascript for Financial Analysts' Chapter 1. ~ Much of our coding time is spent in an interactive environment, colloquially called the 'REPL', 'Read-Eval-Print Loop' or console. The REPL reads input, evaluates it according to our code and prints it. Javascript's REPLs, can be found in any browser, by pressing Ctrl+Shif
  • When is a Backtest Too Good to be True? Part Two [Quintuitive]

    In the previous post, I went through a simple exercise which, to me, clearly demonsrtates that 60% out of sample guess rate (on daily basis) for S&P 500 will generate ridiculous returns. From the feedback I got, it seemed that my example was somewhat unconvincing. Lets dig a bit further then. Lets add Sharpe ratio and maximum drawdown to the CAGR and compute all three for
  • Will Yesterday s Shooting Star Make Bears Wishes Come True? [Dana Lyons]

    Like its bullish counterpart, the hammer, this bearish reversal pattern has been inconsistent in its forecasting abilities, except under certain conditions. Weve covered the hammer candlestick chart pattern on a couple occasions over the past few years, most extensively in this October 2014 post. The pattern, which involves a significant selloff from the open followed b
  • SPX Straddle – 38 DTE – Manage Profits at 25% [DTR Trading]

    In this post we look at the backtest results of selling a one-lot, at-the-money (ATM) straddle on the S&P 500 Index (SPX), initiated at 38 days-to-expiration (DTE). In this third post of five on 38 DTE straddles, we look at trades that use the same loss exits as shown in the first post, and in addition, take profits at 25% of the credit received. The results displayed in this post rep

Quantocracy’s Daily Wrap for 09/18/2015

This is a summary of links featured on Quantocracy on Friday, 09/18/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Interview with Euan Sinclair [EP Chan]

    I have been a big fan of options trader and author Euan Sinclair for a long time. I have cited his highly readable and influential book Option Trading in my own work, and it is always within easy reach from my desk. His more recent book Volatility Trading is another must-read. I ran into him at the Chicago Trading Show a few months ago where he was a panelist on volatility trading, and
  • Can Investors Achieve Commodity Exposure via Equities? [Alpha Architect]

    This past year we examined the possibility of replicating commodity exposure via equities. The project was spurred by an insightful research report from MSCI, which showed some impressive results. Other research outfits have proposed similar concepts. The figure below, taken from the MSCI report, highlights how well the MSCI Select Commodity Producers Index replicates various commodity
  • An Update on Jay s Pure Momentum Sector Fund System [Jay On The Markets]

    Todays article is an update on this oldie but goodie. When people ask me if momentum investing works, at this point because I am older and (even) crankier than I used to be I typically refer them to the linked article above and grunt decide for yourself. Sorry, its just my nature. (See also: The Signpost Up Ahead: The September Danger Zone)
  • SPX Straddle – 38 DTE – Manage Profits at 10% [DTR Trading]

    In this post we look at the backtest results of selling a one-lot, at-the-money (ATM) straddle on the S&P 500 Index (SPX), initiated at 38 days-to-expiration (DTE). In this second post of five on 38 DTE straddles, we look at trades that use the same loss exits as shown in the first post, and in addition, take profits at 10% of the credit received. The results displayed in this post re

Quantocracy’s Daily Wrap for 09/16/2015

This is a summary of links featured on Quantocracy on Wednesday, 09/16/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hypothesis Driven Development Part IV: Testing The Barroso/Santa Clara Rule [QuantStrat TradeR]

    This post will deal with applying the constant-volatility procedure written about by Barroso and Santa Clara in their paper "Momentum Has Its Moments". The last two posts dealt with evaluating the intelligence of the signal-generation process. While the strategy showed itself to be marginally better than randomly tossing darts against a dartboard and I was ready to reject i
  • Out-of-sample test of market timing with moving averages or avoid death cross strategy [Quantitative Investor]

    Usign 9 equity markets I talked about in the previous post, Im going to compare avoid death cross or moving average crossover market timing rule with vanilla B&H. Formal specification of the rules used: if at day t we have for some index that MA(10) < MA(250) sell the index at the Close of day t+1 (if we hold it long) and buy 3-month T-bills if
  • The Health of Stock Mean Reversion: Reader s Ideas [Alvarez Quant Trading]

    My previous post The Health of Stock Mean Reversion: Dead, Dying or Doing Just Fine generated good readers suggestions on other ways to check on mean reversion health. Let us see what these tests tell us. The Base Test Date Range: 1/1/1995 to 6/30/2015. Entry: Stock is part of the Russell 1000 Close > $1 RSI(2)
  • ORBP with Price Channel Filter | Trading Strategy (Filter & Exit) [Oxford Capital]

    I. Trading Strategy Developer: Toby Crabel (ORBP: Opening Range Breakout Preference); Richard D. Donchian (Price Channel Filter). Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Volatility expansion with a price channel filter. Research Goal: Performance verification of a trend filter
  • Interview with Dr Ernest Chan [Factor Wave]

    Dr Ernie Chan does something difficult well: he explains quantitative trading ideas to retail traders without over-simplifying them. He has written two books," Quantitative Trading:How to Build Your Own Algorithmic Trading Business" and "Algorithmic Trading: Winning Strategies and Their Rationale" and blogs at epchan.blogspot.com. Because he operates in an fairly unusual s
  • Some Simple Shorting Systems For Downtrends [Quantifiable Edges]

    SPX closed at a 10-day high on Tuesday. New short-term (and intermediate-term) highs will sometimes get traders excited. When the market is in long-term downtrend mode, this excitement is often misplaced. Way back in a blog post on 4/3/09 I showed a number of systems that looked to sell short when the SPX made X-day highs but was below the 200ma. I have updated the results table of th
  • Corporate Sport Sponsorship and Stock Returns [Alpha Architect]

    The NFL is back!!! Unfortunately, the Eagles may need a new kickerand now we have to listen to Wes talk trash about the Cowboys victory around the office. Tragic! In the spirit of the new NFL season, I figured it was a good time to highlight a newer paper titled Corporate Sport Sponsorship and Stock Returns: Evidence from the NFL written by Assaf Eisdorfer a
  • [Academic Paper] Robust Gaussian Filtering [@Quantivity]

    Robust Gaussian Filtering

Quantocracy’s Daily Wrap for 09/11/2015

This is a summary of links featured on Quantocracy on Friday, 09/11/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Is Technical Analysis Folk Medicine? [Factor Wave]

    I've been thinking more about technical analysis. Not so much how to do it, but more about what it actually is. Some of it can be tested scientifically, but a lot can't (for more on this distinction refer to the excellent book by David Aronson, "Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals"). So TA isn't
  • Factor Models Can Only Tell You So Much [Alpha Architect]

    Factor analysis has taken the professional consultant world by storm and we are slowly seeing this analysis being used more and more by sophisticated retail investors and investment advisors. And thats greatfactor analysis is a great tool. In fact, we discuss the use of the tool and how it is useful in a recent post called, Basic Factor Analysis: Simple Tools to Understand What Drives
  • Dual ETF Momentum September 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 09/08/2015

This is a summary of links featured on Quantocracy on Tuesday, 09/08/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Book Review: DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth [Dual Momentum]

    I have always looked favorably upon do-it-yourself investing (DIY). It was a prominent feature of my own book. So Ive been looking forward to DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth by Wes Gray, Jack Vogel, and David Foulke (GVF), the managing members of Alpha Architect. GVF took on an ambitious project since they cover a broad range of su
  • Hypothesis-Driven Development Part II [QuantStrat TradeR]

    This post will evaluate signals based on the rank regression hypotheses covered in the last post. The last time around, we saw that rank regression had a very statistically significant result. Therefore, the next step would be to evaluate the basic signals whether or not there is statistical significance in the actual evaluation of the signalnamely, since the strategy fr
  • The Case for Put Writing / Further Improving PutWrite Performance [EconomPic]

    Jesse Livermore of the always interesting Philosophical Economics outlines the case for writing puts in his recent post The Worlds Best Investment For the Next 12 Months. Given this has been an area of focus for me professionally for the better part of the last 5 years (sneak preview… I love the concept), I thought I could add to the conversation. Note that some of the post below dup
  • Skewed By Randomness: Testing Arbitrary Rebalancing Dates [Capital Spectator]

    How much influence do investors have over their portfolios? Perhaps it's less than commonly assumed. The notion that randomness plays a role in money management has been widely studied in finance-Nassim Taleb's popular treatment in Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets is one example. The concept is a staple in the money game, although it's
  • Will You Be Able to Retire Without Tactical Asset Allocation? [Flirting with Models]

    Frugal Fran is a 25-year old investor at the beginning of her career making $40,000 per year. Financially savvy, she has already started planning for her retirement. She plans to retire at age 65 and follow an "own your age" policy for her stock/bond mix. Fran projects a salary increase of 1.5% per year, after inflation. When she retires, Fran would like to replace 85% of her income
  • Intro to Hidden Markov Chains [Quants Portal]

    In a situation where you wish to determine the returns on an investment, one may have all the expertise to do this but without certain information (missing pieces) it would not be possible to derive to a conclusive figure. In practical terms assume you have the value of all returns of all assets in your portfolio; without the rate at which each asset produces the returns we will not ha
  • SPX Performance Following Selloffs Into 3-Day Weekends [Quantifiable Edges]

    One of my former studies I looked at over the weekend examined how the market performed following large selloffs before U.S.-only three day weekends. These include Labor Day, Martin Luther King Day, Presidents Day, Memorial Day, and Fourth of July. Since 2000 there have been 12 instances where there was a greater than 1% selloff prior to the US-only 3-day weekend. Statistics from 1-5 d
  • State of Trend Following in August [Au.Tra.Sy]

    A positive return for the State of Trend Following index, bringing the YTD performance nearly exactly on neutral level. The big spike up seen in the last part of the month, which brought the index close to +10%, was short-lived. The index quickly reverted it with a quick spike down. Please check below for more details. Detailed Results The figures for the
  • How bad was August 2015? [Flirting with Models]

    The SPDR S&P 500 ETF SPY fell more than 6% in August Measured against other monthly returns, August 2015 was the worst month since 2012 Monthly returns are arbitrary and skew our understanding of market moves Since 2012, there have been several -6%, or near -6%, return periods Recently, in reference to August 2015, this headline appeare
  • A way to an improved Size and Value Factors [Quantpedia]

    Authors: Lambert, Fays, Hubner Title: Size and Value Matter, But Not the Way You Thought Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2647298 Abstract: Fama and French factors do not reliably estimate the size and book-to-market effects. We demonstrate inconsistent pricing of those factors in the US stock market. We replace Fama and Frenchs independent rankings with the

Quantocracy’s Daily Wrap for 09/04/2015

This is a summary of links featured on Quantocracy on Friday, 09/04/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Strategy Replication Nonlinear SVMs can systematically identify stocks with high and low future returns [Mintegration]

    Ive replicated the following academic paper from my favourite journal; Title: Nonlinear support vector machines can systematically identify stocks with high and low future returns Authors: Ramon Huerta, Fernando Corbacho, and Charles Elkan Journal: Algorithmic Finance (2013) 45-58 45, DOI 10.3233/AF-13016, IOS Press, http://algorithmicfinance.org/2-
  • Economics, Mathematics, & Common Sense [Alphamaximus]

    Almost all calculations in finance involve using log returns rather than % returns. There are a number of reasons why log returns are preferred. Estimating beta doesnt seem like a special case. But when you go through the math, something doesnt quite add up. rS1M1Pt=?+?rM+?t=S0exp(r)=M0exp(rM)=S0+wM0 Because we want to zero out market risk, so want to s
  • Benford’s Law [Factor Wave]

    Benford's Law states that in many naturally occurring groups of numbers, the small digits are seen disproportionately often. This is often applied to the leading digits of data but it is more general than that. This was first noticed by the astronomer Simon Newcomb (who also should be famous for an awesome beard!) in 1881 when he saw that the first pages in a library book of logarithms
  • Backtesting Data Independence [John Orford]

    Light is the most precious resource to a photographer, everything you can do with your camera is budgeted by the amount of light available. Financial analysis is similarly constrained by the amount of data available. So more available data is always good. With Big 'O' Sharpe you can generate as much data as the data is granular. E.g. i