Quantocracy

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Quantocracy’s Daily Wrap for 07/07/2016

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

  • An Alternative Investment Strategy with Value and Momentum [Alpha Architect]

    Anyone who follows our website should be familiar with the extensive evidence behind our favorite stock selection strategies: Value Investing Momentum Investing The evidence suggests that high-conviction ( We document why high conviction is important for both value and momentum strategies here and here. We document how value and momentum work as a system here. But there is a potential problem: The
  • Visualizing Fixed Income ETFs with T-SNE [Quant Dare]

    In recent articles we were talking about PCA and ISOMAP, as techniques for dimensionality reduction. On this occasion, we put the focus on T-SNE, in relation with visualization and understanding of multidimensional datasets in a low dimension space, where the human eye can find patterns easily. T-SNE was developed in 2008 by Laurens van der Maaten and Geoffrey Hinton. It comprises of two main
  • Momentum Rotation 60 Day ROC System Metrics [DTR Trading]

    It's been a while since my last post. I had planned on writing this particular article about three months ago, but work got in the way of my writing and testing Over the next few weeks I will try to close out this series on momentum rotation using my 60 day ROC example written for AmiBroker. After I finish this series, I will get back to option strategy backtesting I thought it was

Quantocracy’s Daily Wrap for 07/06/2016

This is a summary of links featured on Quantocracy on Wednesday, 07/06/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Advanced Algorithmic Trading and QSTrader – Second Update [Quant Start]

    This is a quick update post to let readers know that the pre-order release of Advanced Algorithmic Trading has had a new update, adding over 50 pages of material. This brings the current release up to 250 pages. To access the new content, customers simply need to follow the download link received in the original purchase email. If the download email has been misplaced then please email
  • Mini-Meucci : Applying The Checklist – Steps 10+ [Return and Risk]

    In this final leg of The Checklist tour we'll be looking at the Dynamic Allocation step and touch briefly on ex-post Performance Analysis. Dynamic Allocation Essentially this involves repeating the previous 9-steps on a periodic basis (e.g. a sequence of monthly allocations) according to a chosen allocation policy. Examples of dynamic allocations include systematic strategies (based on
  • Intro to Algorithmic Trading with Heikin-Ashi [Quantiacs]

    Algorithmic trading is a field thats generally quite daunting to beginners, forcing them to juggle learning advanced programming techniques and market mechanics. Throughout the process theres usually not a lot of guidance, and even less coding examples. Our goal is to demystify this process and take you from beginner to quant with a hands-on lesson. Well program our own technical
  • Trend Following vs Countertrend Trading Strategies [QuantLab.co.za]

    Introduction A blog series to contrast the key distinctions between trend following and countertrend strategies during building, testing and trading. In this post we examine the effects of data integrity and simulated trade sample size on backtested performance. Price Data Integrity One of the major obstacles for traders looking to research trend following models is data. Since trend following
  • Trend Following UP in June (Thanks Brexit) [Wisdom Trading]

    Brexit might have been globally thought of as bad news for the markets, but it was good for trend following. It marked a quick up movement in last months performance, quickly reversing the negative performance of the month to turn it back positive, after the 23rd June vote. The YTD performance is slightly back in positive territory. Below is the full State of Trend Following report as of last

Quantocracy’s Daily Wrap for 07/05/2016

This is a summary of links featured on Quantocracy on Tuesday, 07/05/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Cloud-Based Automated Trading System with Machine Learning [Quant Insti]

    Maxime Fages Maximes career spanned across the strategic aspects of value and risk, with a particular focus on trading behaviors and market microstructure over the past few years. He embraced a quantitative angle in M&A, fund management or currently corporate strategy and has always been an avid open-source software user. Maxime holds a MBA from Insead and a MScEng from Ecole Nationale
  • Alpha’s measurement problem [Flirting with Models]

    Alpha is the holy grail of asset management: risk-free excess returns generated by investment skill. Alpha is one of the most commonly quoted summary statistics yet measuring alpha is surprisingly difficult. Without an understanding of measurement uncertainty, fit of our model, or even the risk factors utilized to calculate alpha, the statistic loses its applicability.
  • State of Trend Following in June [Au Tra Sy]

    The month of June started positive for the trend following index, before a V-shaped movement pre/post-Brexit, that ended the month in positive territory. The YTD figure is still in the red. Please check below for more details. Detailed Results The figures for the month are: June return: 2.94% YTD return: -1.96% Below is the chart displaying individual system results throughout June:

Quantocracy’s Daily Wrap for 07/03/2016

This is a summary of links featured on Quantocracy on Sunday, 07/03/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Human significance, economic significance and statistical significance [Eran Raviv]

    We are now collecting a lot of data. This is a good thing in general. But data collection and data storage capabilities have evolved fast. Much faster than statistical methods to go along with those voluminous numbers. We are still using good ole fashioned Fisherian statistics. Back then, when you had not too many observations, statistical significance actually meant something. It does not

Quantocracy’s Daily Wrap for 07/01/2016

This is a summary of links featured on Quantocracy on Friday, 07/01/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Video: Factor Models for Traders by EP Chan (h/t Quant News)

    Factor models are not just for long-term investors. They can help traders find out why their strategies are suffering. This talk highlights the difference between factor and "alpha" models, and what short-term factors traders can use.
  • Podcast with Wes Gray of Alpha Architect (h/t Abnormal Returns) [Big Picture]

    This week on our Masters in Business podcast, we speak with Wes Gray, former Captain in U.S. Marines, and founder of Alpha Architect. He studied economics at Wharton, graduated with honors before getting his MBA and PhD at University of Chicago. Instead of heading to Wall Street like so many MBAs, however, he joined the Marines, went to Iraq, where he embedded with the Iraqi Army as a U.S. Marines
  • Quantified News Analytics: Profitability vs Pitfalls [Quant Insti]

    As sources and volumes of news have grown, so has the techniques to gather, extract, aggregate and categorise them. Important news can result in large positive or negative returns. However, owing to many news sources, we need to ask a fundamental question: Is news analytics profitable in every situation or are there some pitfalls that needs to be avoided? Information flow in News Analytics news
  • Taxonomy of CTAs [Quantpedia]

    Recently a range of alternative risk premia products have been developed promising investors hedge fund/CTA like returns with higher liquidity, transparency and relatively low fees. The attractiveness of these products rests on the assumption that they can deliver similar returns. Using a novel reporting bias free sample of 3,419 CTA funds as a testing ground, our results suggest this assumption

Quantocracy’s Daily Wrap for 06/30/2016

This is a summary of links featured on Quantocracy on Thursday, 06/30/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Can a simple Market Internals technique actually improve trading strategy results? [Better System Trader]

    In my 10+ years full-time trading career, I have found very few tools and tactics that would get my attention so deeply as Market Internals. In 2014, I spent about 6 months in a row with this unique traders tool, exploring its possibilities every single day, searching for new and creative implementation ideas for my own automated trading systems (ATSs). With a real obsession with this concept,
  • The Case for Momentum in Expensive Markets [EconomPic]

    Charlie Bilello, one of my favorite follows on Twitter, analyzed the relationship between market valuation and future returns (over various time horizons) in a recent post Valuation, Timing, and a Range of Outcomes. The post contained some very insightful tables, such as the one below, where he shows that valuations matter… if you pay less for stocks, you will generally be provided with higher
  • Questioning Everything You Knew about Asset Allocation [Alpha Architect]

    Is a 100% stock allocation crazy? As long as one addresses their needs for liquidity (as to avoid extracting capital from the markets at bad times) and can tolerate the market price volatility, a 100% or near-100% allocation to equities is not as outlandish as one might suspect. Focusing on fundamentals and valuations instead of market prices should alleviate much of the unnecessary concern with

Quantocracy’s Daily Wrap for 06/29/2016

This is a summary of links featured on Quantocracy on Wednesday, 06/29/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Deciphering Correlation Hedged Momentum [TrendXplorer]

    In a new SeekingAlpha contribution (pending approval) we combine PAAs protective multi-market breadth approach with a generalized momentum metric based on correlation hedged returns. The resulting model is called Generalized Protective Momentum (GPM). In this blogpost the correlation hedge is deciphered. The correlation hedge is a simplified version of Keller and Butlers EAA-formula (see
  • Pruitt, The Ultimate Algorithmic Trading System Toolbox [Reading the Markets]

    I am in the process of learning to code in Python and am, I must admit, no programming genius. So I was delighted to see that George Pruitt, best known for his book on TradeStations EasyLanguage (Building Winning Trading Systems with TradeStation) had written a new book that covered not only the TradeStation platform but also AmiBroker, Excel (with VBA), and Python. The Ultimate Algorithmic