Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 09/12/2016

This is a summary of links featured on Quantocracy on Monday, 09/12/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Hidden Markov Models – An Introduction [Quant Start]

    A consistent challenge for quantitative traders is the frequent behaviour modification of financial markets, often abruptly, due to changing periods of government policy, regulatory environment and other macroeconomic effects. Such periods are known colloquially as "market regimes" and detecting such changes is a common, albeit difficult process undertaken by quantitative market
  • Trend Following after Drawdowns [Wisdom Trading]

    Historical Performance of Trend Following Post-Drawdown August marked a local low for our Trend Following index, reaching about two thirds of the max historical drawdown. We were commenting on the fact that, historically, drawdowns have typically proved a good time to invest or start trading a trend following strategy. This prompted us to run a test to check the historical results on the index. We
  • What The VIX Spike Is Suggesting For The Next Few Days [Quantifiable Edges]

    Fridays big drop was accompanied by a big spike in options prices as measured by the VIX. The VIX rose so sharply that it closed Friday 32% above its 10-day moving average. The study below examines stretches of 25% or more, and how the SPX has performed in the following days.
  • The Coppock Curve Applied to Global Markets [Meb Faber]

    I get most of my quant research done while trying to avoid other less interesting work. So I was curious when I saw my friend John Hussman writing about an obscure technical indicator called the Coppock Curve. I filed it away as interesting, sent it to the Idea Farm list, then moved on. But they Barry was asking me about it so that got me curious again, and I wanted to see what it might be
  • Ask Me Anything Video [Alvarez Quant Trading]

    In this short five minute video I will answer the following questions: I am interested in knowing a little bit more about your own trading. What types of strategies are you trading? Why do you not manage outside money? What are the trading books you recommend? Do you have a trading or AmiBroker or other question you want me to answer? If so, either add it to the comments below or fill in the form.
  • Applications of Graph Theory In Finance [Jonathan Kinlay]

    Very large datasets comprising voluminous numbers of symbols present challenges for the analyst, not least of which is the difficulty of visualizing relationships between the individual component assets. Absent the visual clues that are often highlighted by graphical images, it is easy for the analyst to overlook important changes in relationships. One means of tackling the problem is with

Quantocracy’s Daily Wrap for 09/07/2016

This is a summary of links featured on Quantocracy on Wednesday, 09/07/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Is momentum investing dead? Or is it just painful? [Alpha Architect]

    Sometimes even the best evidence-based active investment strategies can create a formidable challenge to investors seeking to exploit them. Case in point momentum investing. On the one hand, stock-selection momentum strategies (here is a link to more information) can have the potential to generate excess expected returns over the long run; on the other hand, these strategies sometimes generate
  • Strategy Up/Down Capture [Alvarez Quant Trading]

    A reader sent this interesting link about Up/Down Capture. The great part about this article it is something I have intuitively known about my trading strategies but never tried to quantify. This was the bump I needed to investigate this concept. When the SPY moves up on average how much does my strategy profit? When the SPY moves down how much does my strategy lose? I had fun creating an

Quantocracy’s Daily Wrap for 09/06/2016

This is a summary of links featured on Quantocracy on Tuesday, 09/06/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How a Low VIX Can Remain an Expensive Hedge [EconomPic]

    One of my favorite Twitter follows @LadyFOHF shared the below scatter chart from Morgan Stanley that attempted to map areas of the global market that were both cheap (valuation ranks at the lower end of its 10-year history) and defensive (a low or negative correlation to global equities). One of the few trades listed as having both characteristics was the VIX Index. Let's take a look. The VIX
  • J.P. Morgan Outlook Implies Satellite Bonds Are King [Flirting with Models]

    It is common for large asset management firms to publish their capital market assumptions: long-term global asset expected return and covariance assumptions. Yet many firms do not draw the link between what published capital market assumptions say and what they mean when carried through the portfolio construction process. We find several interesting results when applying simple portfolio

Quantocracy’s Daily Wrap for 09/05/2016

This is a summary of links featured on Quantocracy on Monday, 09/05/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Systematic risk management [Investment Idiocy]

    As the casual reader of this blog (or my book) will be aware, I like to delegate my trading to systems, since humans aren't very good at it (well, I'm not). This is quite a popular thing to do; many systematic investment funds are out there competing for your money; from simple passive tracking funds like ETF's to complex quantitative hedge funds. Yet most of these employ people to
  • How to Learn Advanced Mathematics Without Heading to University – Part 3 [Quant Start]

    In the first and second articles in the series we looked at the courses that are taken in the first half of a four-year undergraduate mathematics degree – and how to learn these modules on your own. In the first year we discussed the basics – Linear Algebra, Ordinary Differential Equations, Real Analysis and Probability. In the second year we built on those basics, studying Metric Spaces, the
  • Effect of Maturity Structure of Roll Yields in Commodity Futures Strategies [Quantpedia]

    We investigate the maturity-structure of roll strategy returns in the energy futures markets. Our innovation is to report and analyze the risk/return profile, the Sharpe ratio, and the asset pricing loadings of rollover strategies based on futures contracts of the same underlying commodity but with maturities between two and 12 months. We find that a conditional rollover strategy, which takes a
  • Trading on Sentiment with Richard Peterson [Better System Trader]

    Trading algorithmically based on sentiment data is a relatively new field compared to more established approaches. With the explosion of social media and computing power, the analysis of sentiment data has also increased, with some hedge funds committing considerable resources to researching the applications of sentiment data in trading. However, there is also some skepticism of the value of

Quantocracy’s Daily Wrap for 09/03/2016

This is a summary of links featured on Quantocracy on Saturday, 09/03/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Backtesting With Zipline Ii [Koppian Adventures]

    In this post, we play again little bit around with python and the pandas-library. You may want to read the first part of this series. There we have backtested a simple crossing moving average strategy in pandas. We had a long/slow moving average over the last 40 days and a fast/short moving average over the last 20 days. When the stock price rockets skywards, the short moving average is above the
  • AllocateSmartly [TrendXplorer]

    Launched only recently, AllocateSmartly.com tracks the industrys best tactical asset allocation strategies with thorough, up-to-date backtests. As of writing 16 (sub) strategies are tracked and benchmarked on near real-time basis. All of the tracked strategies are both quantitative and systematic, meaning well-defined mathematical rules govern exactly when and what to trade. Among the featured
  • Possible Addition of NARX Network to Conditional Restricted Boltzmann Machine [Dekalog Blog]

    It has been over three months since my last post, due to working away from home for some of the summer, a summer holiday and moving home. However, during this time I have continued with my online reading and some new thinking about my conditional restricted boltzmann machine based trading system has developed, namely the use of a nonlinear autoregressive exogenous model in the bottom layer

Quantocracy’s Daily Wrap for 09/02/2016

This is a summary of links featured on Quantocracy on Friday, 09/02/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • When Academics Disagree on Momentum Investing [Alpha Architect]

    The academic standard for intermediate-term momentum measurement is 12_2 momentum: simply sort all stocks based on a stocks total return over the past twelve months, ignoring the last month. (a discussion is here and here) However, a few years ago Robert Novy-Marx wrote a paper titled Is Momentum Really Momentum? Given its provocative title, this paper caught our attention! Why
  • State of Trend Following in August: Sharp Down Move [Au Tra Sy]

    It is Fall in Summer! The trend following index had a big move to the downside last month, taking the YTD performance to a negative level as well. The results are similar, over on the Wisdom State of Trend Following, a sort of version 2.0 of this report, which I write for them too. Please check below for more details. Detailed Results The figures for the month are: August return: -6.59% YTD
  • August Fall for Trend Following [Wisdom Trading]

    August 2016 Trend Following: UP -7.32% / YTD: -7.95% August was mostly one-sided, sliding down to a strong negative performance, and taking with it the Year-To-Date performance to a similar level. Interesting to note the shorter timeframes weighing on the index while the longer timeframes are still positive/neutral on a 12-month horizon (we do offer trading systems with long-term timeframes). Note