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Quantocracy’s Daily Wrap for 05/19/2019

This is a summary of links featured on Quantocracy on Sunday, 05/19/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Adaptive Huber Regression [Eran Raviv]

    Many years ago, when I was still trying to beat the market, I used to pair-trade. In principle it is quite straightforward to estimate the correlation between two stocks. The estimator for beta is very important since it determines how much you should long the one and how much you should short the other, in order to remain market-neutral. In practice it is indeed very easy to estimate, but I

Quantocracy’s Daily Wrap for 05/17/2019

This is a summary of links featured on Quantocracy on Friday, 05/17/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Future of QTPyLib [Ran Aroussi]

    I released the first version of QTPyLib, my Python library for algo traders, in 2016. If you had told me then that I would still be working on it three years later, I probably wouldn't have believed you. But guess what? That's precisely where I'm doing 🙂 The first release of QTPyLib was a basic engine for live trading using Interactive Brokers. That's it. Nothing more. Nothing
  • Financial Experts Ignoring Better Statistical Methods? [CXO Advisory]

    Why are expert economic and financial (econometric) forecasters so inaccurate? In his April 2019 presentation package for a graduate course at Cornell entitled The 7 Reasons Most Econometric Investments Fail, Marcos Lopez de Prado enumerates shortcomings of standard econometric statistical methods, which concentrate on multivariate linear regressions. In contrast, advanced computational

Quantocracy’s Daily Wrap for 05/15/2019

This is a summary of links featured on Quantocracy on Wednesday, 05/15/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Backtesting Bias: Feels Good, Until You Blow Up [Robot Wealth]

    In an ideal trading universe, wed all have a big golden causation magnifying glass. Through the lens of this fictional tool, youd zoom in and understand the fleeting, enigmatic nature of the financial markets, stripping bare all its causes and effects. Knowing exactly what causes exploitable inefficiencies would make predicting market behaviour and building profitable trading

Quantocracy’s Daily Wrap for 05/14/2019

This is a summary of links featured on Quantocracy on Tuesday, 05/14/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Inflation Makes the ‘Value’ Factor a Sector Bet [Fortune Financial]

    There have been numerous attempts to explain the lackluster performance of value investing so far this decade, which is currently on pace for its worst annualized performance for a decade since the 1930s: Without getting into the arguments made by others, which have been debated elsewhere, I will take a deeper look into what I think is the likeliest explanation for this phenomenon, although it is
  • A Laboratory for Machine Learning in Finance [Quants Portal]

    In the summer of 2018 we attended a conference organized by Quantopian in which we heard Dr. Marcos Lopez de Prado outlined the challenges of building successful quantitative investment platforms. His book, Advances in Financial Machine Learning provides solutions to many of the problems faced by the quantitative finance community. We, however, could not find a cogent implementation of these ideas
  • Shiny New Toys [CSS Analytics]

    Its been a long time folks, but we have some shiny new toys in the works. Current trends in the industry and working with data scientists has made me a believer in the benefits of using a machine learning approach. I have always been a proponent of theory-free approaches on this blog as long as they are designed with robust architecture. In contrast, strict adherence to simplistic theories
  • Why The Failed Bounce Is Not A Signal To Sell [Quantifiable Edges]

    After closing at a 20-day low on Thursday, the market put in a bounce attempt on Friday. Mondays decline to a new low meant that initial bounce attempt failed. But in last nights subscriber letter we saw several studies that showed the failed bounce was more likely to see another bounce attempt than it was to sell off further. The study below triggered in yesterdays Quantifinder,

Quantocracy’s Daily Wrap for 05/13/2019

This is a summary of links featured on Quantocracy on Monday, 05/13/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Fractional Differentiation [Quants Portal]

    In this article we delve into the challenge of making an asset price series stationary (for reasons discussed below) and preserving as much memory/signal from the original series. We take inspiration from Chapter 5 of the Advances in Financial Machine Learning (AFML) by Dr. Marcos Lopez de Prado therein he discusses fractionally differencing the time series (as opposed to integer differencing). A
  • Member Analysis: The Effect of Combining Strategies on Timing Luck [Allocate Smartly]

    We enjoy hearing from members about their experiences using our platform to analyze and combine tactical asset allocation strategies. We do a bad job of sharing that feedback with other members, and thats a shame, because theres often a lot of wisdom in it. So lets change that. What follows is an email from member Mark demonstrating the benefit of combining strategies not just on
  • Country Rotation with Growth/Value Sentiment [Flirting with Models]

    Value investing has not only underperformed with regard to security selection, but also country selection over the last decade. In an effort to avoid country value traps, we set out to design two signals that might better confirm when a country is likely to exhibit positive re-valuation. We find that one of the signals exhibits curious results, leading us to develop an entirely new metric for
  • 10 Large Scale Factor Anomaly Studies with Definitions [Two Centuries Investments]

    A Taxonomy of Anomalies and their Trading Costs 2015, Robert Novy-Marx and Mihail Velikov (with data) and the Cross-Section of Expected Returns, 2013, Campbell Harvey, Yan Liu, Caroline Zhu (factor list) A Comparison of New Factor Models, 2014, Kewei Hou, Chen Xue, Lu Zhang The Supraview of Return Predictive Signals, 2012, Jeremiah Green, John Hand, Frank Zhang Does Academic Research Destroy
  • Short Selling + Insider Selling = Profitable Strategy? [Alpha Architect]

    What are the research questions? This study uses a long and comprehensive time series covering 1977-2014, with just under 180,000 quarterly observations for trades of short sellers and demand for shares by corporate insiders. (see here for a related paper we covered recently that talks about informational advantages). The data is used to construct practical trading strategies utilizing in
  • SPX Iron Condor – 2018 Review [DTR Trading]

    In this post we'll look at how the SPX iron condor has been performing since I last analyzed its results back in 2016 (here). For this article, we'll just look at the following variations and how they performed from January 2007 through December 2018: 66 DTE – 25 pt wings, 12 Delta (200:50) / 2 DTE – exit if the trade has a loss of 200% of its initial credit OR if the trade has a profit
  • Hedge Fund ETFs [Factor Research]

    Core hedge fund strategies are available as low-cost and transparent ETFs The performance of hedge fund ETFs has been comparable to that of their benchmarks ETFs have only captured 1% of hedge fund assets INTRODUCTION As Amazon has been decimating large parts of the retail industry over the last two decades, ETFs have done the equivalent to the mutual fund industry in the financial world. Today
  • Welcome to Investor IQ [CSS Analytics]

    There is some interesting new content on the CSSA blog that will be very useful for readers. Investor IQ is currently a free tool that shows basic trend signals (Buy, Hold or Sell) for a wide range of US and Canadian ETFs as well as a relative strength ranking. The signals will be updated as of the close of Friday and posted on Monday morning. This feature is currently in Beta and will be expanded

Quantocracy’s Daily Wrap for 05/12/2019

This is a summary of links featured on Quantocracy on Sunday, 05/12/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Edge of Technical Indicators [Philipp Kahler]

    Classical technical indicators like RSI and Stochastic are commonly used to build algorithmic trading strategies. But do these indicators really give you an edge in your market? Are they able to define the times when you want to be invested? This article will show you a way to quantify and compare the edge of technical indicators. Knowing the edge of the indicator makes it an easy task to select
  • Systematic trading strategies: fooled by live records [SR SV]

    Allocators to systematic strategies usually trust live records far more than backtests. Given the moral hazard issues of backtesting in the financial industry, this is understandable (view post here). Unfortunately, for many systematic strategies live records can be even more misleading. First, the survivor bias in published live records is worsening as the business has entered the age of mass
  • Alternative data for FX [Cuemacro]

    I recently visited the USA. I managed to visit a number of different cities. Whilst I was there primarily for work, I managed to squeeze in a few days to look around the various cities I visited. I visited Philadelphia for the first time, and I saw Independence Hall and the Liberty Bell, both of which I strongly recommend you see. Im a big foodie (as Im sure you may have guessed by reading

Quantocracy’s Daily Wrap for 05/10/2019

This is a summary of links featured on Quantocracy on Friday, 05/10/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Don’t Be A Value Hero [Quiet Quant]

    Lets imagine a world where value stocks actually provide some outperformance at some point In a world like that, are there any simple rules one could implement into their value system to help avoid falling knives? The optimist in me says yes, but the realist says nope. Turns out, it is probably somewhere in between. The test is pretty simple: U.S. Common Stocks (Top 50% of Market)
  • Going with the FX flow [Cuemacro]

    In this paper, we discuss using CLS intraday hourly flow data to understand FX markets. Using two different trading strategies (daily and hourly) against a generic trend model, we find that CLSs flow data relating to funds and non-bank financial firms (NBFIs) tends to have a positive contribution to spot returns when viewed on an aggregate contemporaneous basis. By contrast, flows from buy-side
  • Research Review | 10 May 2019 | Tail Risk [Capital Spectator]

    Tail Risk Management for Multi-Asset Multi-Factor Strategies David Chambers (University of Cambridge), et al. January 8, 2019 Multi-asset multi-factor portfolio allocation is typically centred around a risk-based allocation paradigm, often striving for maintaining equal volatility risk budgets. Given that the common factor ingredients can be highly skewed, we specifically incorporate the notion of
  • CBI Hits 10+ While $SPX is in a Long-Term Uptrend [Quantifiable Edges]

    It is notable that the Quantifiable Edges Capitulative Breadth Indicator (CBI) closed at 10 on Thursday. Below is a study that shows other times the CBI reached 10 while the SPX was above its 200ma. 2019-05-10 A very high percentage of instances closed higher when looking out 4 or more days. The numbers certainly seem to point to a bullish edge. Below is a profit curve that assumes a 5-day holding
  • State of Trend Following in April [Au Tra Sy]

    Positive month for the State of Trend Following index. YTD fighting back to the zero line Please check below for more details. Detailed Results The figures for the month are: April return: 2.89% YTD return: -1.6% Below is the chart displaying individual system results throughout April:

Quantocracy’s Daily Wrap for 05/09/2019

This is a summary of links featured on Quantocracy on Thursday, 05/09/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The True Cost of Hedging S&P Downside [Movement Capital]

    Hedging sounds like a smart thing to do. But has it actually worked? This post examines the historical costs and benefits of hedging stock exposure with SPY puts. Interest in hedging strategies tends to increase as market volatility rises. There are many ways to hedge, and a common method is to overlay SPY puts to protect existing stock exposure. Being long a put option offers limited downside and
  • Buying Stocks Trading Above 10x Sales-A Good Idea? [Alpha Architect]

    Early last week, Meb Faber included me on a conversation on buying stocks trading at 10x their companys revenue (sales). Is this a good idea and how did it do in the past? Given that most known factors have underperformed over the past 10 years, I was interested in seeing if a somewhat crazy strategy(1)buying stocks trading above 10x salesworked over the past 10 years. Of

Quantocracy’s Daily Wrap for 05/08/2019

This is a summary of links featured on Quantocracy on Wednesday, 05/08/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trade Cost Optimisation [Scalable Capital]

    We discuss two major challenges when implementing a dynamic portfolio strategy in practice: Minimising trading costs and enforcing a no-fractional-dealing condition. To master these challenges, we present a flexible and efficient trade cost optimisation algorithm that can be combined with a wide variety of portfolio optimisation approaches. We explain what characterises a trade cost optimisation
  • Comparing Tactical Asset Allocation ETFs to Public TAA Strategies [Allocate Smartly]

    In this post we compare the performance of the 49 tactical asset allocation strategies that we track to 7 ETFs that provide all-in-one exposure to TAA. We were inspired by James Picernos Capital Spectator to run this analysis, so weve appropriated his list of 6 ETFs, and added Meb Fabers GAA (it would be a travesty not to include the godfather of modern TAA in the mix). Of the 7 ETFs,

Quantocracy’s Daily Wrap for 05/07/2019

This is a summary of links featured on Quantocracy on Tuesday, 05/07/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • F@ck Everything… We re Going 120/80 [EconomPic]

    Jeremy had spent most nights over the previous 30+ years on this earth in search of the next big ETF. After all, you dont aspire to be at the forefront of innovative ways for marrying the benefits of the exchange-traded fund structure with goals that are associated with active managers by sitting around and doing nothing. The problem was for as much as he searched and probed, the same
  • Democratize Quant 2019 Recap [Alpha Architect]

    We did it. We democratized quant for one more year. Last year, we suffered through a 50% drawdown in attendance due to a perfectly timed snow storm. This year the weather cooperated with us and we were able to get everyone there. Full access to presentation videos and the accompanying slides (when available) are available on the following recap website. (content is password-protected as per
  • Option-Based Strategies: Opt In or Opt Out? [Factor Research]

    Option-based strategies generated better risk-adjusted returns than the S&P 500 over the last 30 years Investors should be wary of buying options and focus on harvesting the volatility risk premium by writing options Option-based strategies are an interesting alternative to long-short equity hedge funds for reducing risk BUYING VERSUS SELLING OPTIONS The investment banking divisions of Goldman
  • Tax-Managed Factor Strategies [Alpha Architect]

    The authors decompose strategy returns into factor alpha, tax alpha, and residual return for 6 tax-managed versus and 6 tax-indifferent factor strategies and for one indexing strategy. In contrast to other studies, where the impact of starting date dependence is eliminated, this research generates a range of outcomes by initiating each strategy at regular intervals over a 10 year investment
  • SPX Straddle – 2018 Review [DTR Trading]

    In this post we'll look at how the SPX straddle has been performing since I last analyzed its results back in 2015 (here). For this article, we'll just look at the following variations and how they performed from January 2007 through December 2018: 59 DTE – (25:10) / 2 DTE – exit if the trade has a loss of 25% of its initial credit OR if the trade has a profit of 10% of its initial