Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 01/03/2016

This is a summary of links featured on Quantocracy on Sunday, 01/03/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Exploring mean reversion and cointegration: part 2 [Robot Wealth]

    In the first post in this series, I explored mean reversion of individual financial time series using techniques such as the Augmented Dickey-Fuller test, the Hurst exponent and the Ornstein-Uhlenbeck equation for a mean reverting stochastic process. I also presented a simple linear mean reversion strategy as a proof of concept. In this post, Ill explore artificial stationary time series and

Quantocracy’s Daily Wrap for 01/02/2016

This is a summary of links featured on Quantocracy on Saturday, 01/02/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • VIX Trading Strategies in November & December [Volatility Made Simple]

    Weve tested 24 simple strategies for trading VIX ETPs on this blog (separate and unrelated to our own strategy). And while I cant speak for all traders, based on all of my readings both academic and in the blogosphere, the strategies weve tested are broadly representative of how the vast majority of traders are timing these products. Below Ive shown the November/December and full year
  • Trend Following In Financial Markets: A Comprehensive Backtest [Philosophical Economics]

    My metric for everything I look at is the 200-day moving average of closing prices. Ive seen too many things go to zero, stocks and commodities. The whole trick in investing is: How do I keep from losing everything? If you use the 200-day moving average rule, then you get out. You play defense, and you get out. Paul Tudor Jones, as interviewed by Tony Robbins in Money: Master
  • Ivy Portfolio January Update [Scott’s Investments]

    The Ivy Portfolio spreadsheet track the 10 month moving average signals for two portfolios listed in Mebane Fabers book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that have trading signals based on long-term moving averages. The Ivy Portfolio spreadsheet tracks both the 5 and 10 ETF Portfolios listed in

Quantocracy’s Daily Wrap for 12/30/2015

This is a summary of links featured on Quantocracy on Wednesday, 12/30/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Towards a better equity benchmark: random portfolios [Predictive Alpha]

    Random portfolios deliver alpha relative to a buy-and-hold position in the S&P 500 index even after allowing for trading costs. Random portfolios will serve as our benchmark for our future quantitative equity models. The evaluation of quantitative equity portfolios typically involves a comparison with a relevant benchmark, routinely a broad index such as the S&P 500 index. This is an
  • Strong Rally Days Between Christmas & New Year s [Quantifiable Edges]

    The week between Christmas and New Years is often a quiet one that is not prone to large-move days. So strong rallies like we saw on Tuesday are a bit unusual this time of year. I looked back to 1970 to see what has followed other times when SPX rose over 1% on a day between Christmas and New Years. Results are below. 2015-12-30 image1 The stats here all point to a bullish edge. Most of the

Quantocracy’s Daily Wrap for 12/29/2015

This is a summary of links featured on Quantocracy on Tuesday, 12/29/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Three Value Investors Meet in a Bar [Investor’s Field Guide]

    Bill, Ernie and Samthree lifelong value investorsmet in a bar on November 30th, 2015. Bill was despondent. Hed underperformed the market by -47% over the past 10-years and was questioning his very belief in value. Ernie was happier. Hed done poorly in 2015, but over the last ten years hed outperformed the market by +19%. Sam offered to buy the next round. Hed outperformed by +52%
  • Portfolio Analysis in R: Part V | Risk Analysis Via Factors [Capital Spectator]

    In the previous installment in this series of analyzing a globally diversified portfolio we reviewed the results after adding a momentum-based risk-management system. The test suggested that a tactical overlay can be productive maybe, depending on the details. Lets continue to investigate our sample portfolio by taking a closer look at the underlying factors that are driving risk and return.
  • Upside and Downside Risks in Momentum Returns [Quantpedia]

    I provide a novel risk-based explanation for the profitability of momentum strategies. I show that the past winners and the past losers are differently exposed to the upside and downside market risks. Winners systematically have higher relative downside market betas and lower relative upside market betas than losers. As a result, the winner-minus-loser momentum portfolios are exposed to extra
  • Great Academic Research is Bursting at the Seams [Alpha Architect]

    Having been a full-time academic financial economist in a former life (still dabble, when able), I became accustomed to my annual pilgrimage to the annual American Finance Association (AFA) meeting. For the uninitiated, the AFA annual meeting is a gathering of all the major brainpower in academic finance. Getting a paper accepted into the program is a big deal for academic researchers (Ive had
  • Tis the Season for strange effects in the stock market [Alpha Architect]

    The efficient market hypothesis suggests that stock prices are always right in the sense that stock prices reflect all available information. Of course, during tax season, fundamentals go out the window: Im selling my losers, and letting my winners ride! And Im not the only investor thinking like this. But how can savvy investors leverage seasonality effects for their own

Quantocracy’s Daily Wrap for 12/28/2015

This is a summary of links featured on Quantocracy on Monday, 12/28/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • State Space Models and the Kalman Filter [Quant Start]

    To date in our time series analysis posts we have considered linear time series models including ARMA, ARIMA as well as the GARCH model for conditional heteroskedasticity. In this article we are going to consider the theoretical basis of state space models, the primary benefit of which is that their parameters can adapt over time. State space models are very general and it is possible to put the
  • Why Index Investing Wins [Larry Swedroe]

    J.B. Heaton, Nick Polson and J.H. Witte recently authored a nice short paperits all of four pagesentitled Why Indexing Works. In it, the authors developed a simple stock selection model to explain why active equity fund managers tend to underperform their benchmark index. While most of the academic literature focuses on the efficiency of the market and the higher costs of active
  • Our Favorite Commentaries from 2015 [Flirting with Models]

    This commentary is available for download here. There is an adage on Wall Street that comes around every January. And every January, we debunk it. In As Goes January, So Goes the Year, we remind readers that while the performance of markets in January will, by definition, influence the total return of the year, the returns in January say nothing about market returns in February through December.
  • Machine Learning and Mechanical Trading with Genotick [Throwing Good Money]

    Ive recently been experimenting with Genotick, which is open-source java software that attempts to discover mechanical trading systems through the use of machine learning. You can run it on just about any Mac/Windows/Linux system (although you may have additional hurdles to get java8 working at the command-line level on a Mac). Thousands of tiny programs create random rules to predict the next

Quantocracy’s Daily Wrap for 12/25/2015

This is a summary of links featured on Quantocracy on Friday, 12/25/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Build Better Strategies! Part 2: Model-Based Systems [Financial Hacker]

    Trading systems come in two flavors: model-based and data-mining. This article deals with model based strategies. The algorithms are often astoundingly simple, but properly developing them has its difficulties and pitfalls (otherwise anyone would be doing it). Even a significant market inefficiency gives a system only a relatively small edge. A little mistake can turn a winning strategy into a

Quantocracy’s Daily Wrap for 12/24/2015

This is a summary of links featured on Quantocracy on Thursday, 12/24/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • High noon for 2015 market prophets [Mathematical Investor]

    When a prophet speaketh, if the thing follow not, nor come to pass, the prophet hath spoken it presumptuously: thou shalt not be afraid of him. [Deuteronomy 18:22]. In a December 2014 Math Investor blog, we assessed how 2014 market prophets had fared (answer: not very well). Thus with the holiday season once again upon us, it is time to check scores. So how have 2015 prophets performed?
  • VBA Swap Pricing [Smile of Thales]

    VBA and Quant finance This article is actually a first part of an introductory course to VBA coding, given at Solvay School of Economics in Feb. 2014. The Excel sheet and VBA swap pricing code are attached. Visual Basic for Applications (VBA) is not trendy, properly speaking, in the financial industry. It is however massively used in many institutions for several reasons. People naturally
  • Stock Returns Around New Year s Day [CXO Advisory]

    Does the New Years Day holiday, a time of replanning and income tax positioning, systematically affect investors in a way that translates into U.S. stock market returns? To investigate, we analyze the historical behavior of the S&P 500 Index during the five trading days before and the five trading days after the holiday. Using daily closing levels of the S&P 500 Index around New
  • AmiBroker Code for the Breadth Indicator [Throwing Good Money]

    As per request, Im including the AmiBroker code for the 30% up/down last quarter in the Russell 3000 index indicator. I REALLY need to come up with a better name for it than that. How about the Haines Breadth Indicator? No, thats stupid. Magic Matts Mystical Meter? Uhsure. Its a two step process. You must do a scan every day, or as frequently as you want accurate data. It

Quantocracy’s Daily Wrap for 12/23/2015

This is a summary of links featured on Quantocracy on Wednesday, 12/23/2015. To see our most recent links, visit the Quant Mashup. Read on readers!