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Quantocracy’s Daily Wrap for 06/26/2019

This is a summary of links featured on Quantocracy on Wednesday, 06/26/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Graph algorithms and currency arbitrage, part 2 [Reasonable Deviations]

    In the previous post (which should definitely be read first!) we explored how graphs can be used to represent a currency market, and how we might use shortest-path algorithms to discover arbitrage opportunities. Today, we will apply this to real-world data. It should be noted that we are not attempting to build a functional arbitrage bot, but rather to explore how graphs could potentially be used
  • Trend Following: The Epitome of No Pain, No Gain [Alpha Architect]

    One of the recurring themes we see in our research is the concept of no pain; no gain. Or as Corey Hoffstein says, No pain, no premium. Cliff Asness may put it best when he says that some strategies require that you hold on to them like grim death. Bottom line: nothing is easy in financial markets. Pain is viewed slightly differently for academic economists versus the rest of us.
  • Large-Cap Price-to-Book Investing: What is Dead May Never Die [Alpha Architect]

    In the great book and series Game of Thrones, the inhabitants of the Iron Islands have a saying What is Dead May Never Die which is to be replied with But rises again harder and stronger. I am reminded of this saying as more and more market commentators and practitioners declare that value investing is dead and cite its terrible performance over the last 10 years (and even longer for
  • Ichimoku Trading Strategy With Python [Python For Finance]

    I thought it was about time for another blog post, and this time I have decided to take a look at the Ichimoku Kinko Hyo trading strategy, or just Ichimoku strategy for short. The Ichimoku system is a Japanese charting and technical analysis method and was published in 1969 by a reporter in Japan. I thought I would spend this post on the creation of the indicator elements themselves,

Quantocracy’s Daily Wrap for 06/24/2019

This is a summary of links featured on Quantocracy on Monday, 06/24/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Backtesting a sentiment analysis strategy for Bitcoin [Augmento]

    TL;DR: We developed a strategy using Augmento sentiment signals, and backtested it on Bitmex XBTUSD to generate a positive return between 2017 and 2019. Creating algorithms to trade Bitcoin is hard, and finding good data that is independent of the price but still correlated with the market is even harder. Sentiment data could be the answer, but its often hard to use for algorithmic trading, and
  • Generating Financial Series with Generative Adversarial Networks Part 2 [Quant Dare]

    This is a follow-up post to a recent post in which we discussed how to generate 1-dimensional financial time series with Generative Adversarial Networks. If you havent read that post yet we suggest you to do so, since it introduces the building blocks used in this one. Here we will go over the process behind generating multidimensional time series with GANs, the challenges behind this task and
  • Flirting with Models – Season 2 [Flirting with Models]

    With a 5-star rating on iTunes, we are proud to say that Season 1 of our podcast Flirting with Models received a tremendously warm welcome. And so were happy to announce that Season 2 is now available! You can listen to the new season on: iTunes Stitcher Google Play TuneIn Android The Interviews S2E1 Daniel Grioli Thinking like a Fox S2E2 Benn Eifert Volatility Investing
  • Mapping My Mind: Value Factor [Factor Research]

    There is consistency in the performance of the Value factor across markets and asset classes Allows to create a coherent framework of how to think about Value Suggests a global driver of factor performance INTRODUCTION Our research aims to educate investors by bridging the gap between academic literature and practical investing. In contrast to our usual research notes, this one is more personal as

Quantocracy’s Daily Wrap for 06/23/2019

This is a summary of links featured on Quantocracy on Sunday, 06/23/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • DeepTrading with Tensorflow IV [Todo Trader]

    fter you have trained a neural network (NN), you would want to save it for future calculation and eventually deploying to production. So, what is a Tensorflow model? Tensorflow model contains the network design or graph and values of the network parameters that we have trained. Important Note: I know that the reader is impatient to use real data from the financial markets. Please be patient, I
  • Post Opex Weakness Typical in June [Quantifiable Edges]

    In March I discussed how the weeks following options expiration in March, June, and September have been the worst 3 weeks of the year. Below I have updated the June stats and profit, which I also showed last June. 2019-06-23 The strong, steady downslope and bearish numbers suggest we are entering a very weak seasonal period. It will be interesting to see how the market holds up this week, and
  • Process Noise Covariance Matrix Q for a Kalman Filter [Dekalog Blog]

    Since my last post I have been working on the process noise covariance matrix Q, with a view to optimising both the Q and R matrices for an Extended Kalman filter to model the cyclic component of price action as a Sine wave. However, my work to date has produced unsatisfactory results and I have decided to give up trying to make it work. The reasons for this failure are unclear to me, and I

Quantocracy’s Daily Wrap for 06/21/2019

This is a summary of links featured on Quantocracy on Friday, 06/21/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Bond. Treasury Bond [Robot Wealth]

    The Federal Reserve publishes the yield-to-maturity of US Treasury bonds. However, the actual returns earned by investors are not publicly available. Nor are they readily and intuitively discerned from historical yields, since a bonds return equals its yield only if its yield stays constant and if all coupons (cash payments) are reinvested at that same yield (Tuckman and Angel, 2013,
  • Trading China A-Share Stocks Based On Social Media Data Analysis In Python [Quant Insti]

    In this article, we will understand how natural language processing, sentiment analysis and social media play a role in the share markets with the help of Python. This would be explained with respect to the trading in China markets A-share stocks. This article is the final project submitted by the authors as a part of their coursework in the Executive Programme in Algorithmic Trading (EPAT) at

Quantocracy’s Daily Wrap for 06/20/2019

This is a summary of links featured on Quantocracy on Thursday, 06/20/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Matter of Scale [Quant Dare]

    When dealing with mathematical modeling, choosing the right scale to frame the equations can make the difference between a successful and lasting model, or poor description of reality. In todays post, we explore two important scaling procedures that arise in finance: the annualisation of returns and volatility. These are common terms in the industry and building bricks to many other metrics, so

Quantocracy’s Daily Wrap for 06/19/2019

This is a summary of links featured on Quantocracy on Wednesday, 06/19/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • DeepTrading with TensorFlow III [Todo Trader]

    We are now closer to applying our knowledge of neural networks (NN) to our trading systems. But, we still have to tune our rudiments a bit on TensorFlow. If you are not yet familiar with our supervised machine learning flowchart, take a look at the first two posts in this series. DeepTrading with Tensorflow DeepTrading with TensorFlow II As usual, the calculations contained in this post are part
  • A Python Implementation of Triangles for Visualising Long-Term Investment Metrics [Scalable Capital]

    We introduce triangle plots for visualising long-term investment metrics. Return triangles are well suited to showcase the performance of a strategy or asset for a huge number of possible subperiods. Sensitivity analysis with respect to the length of the holding period as well as the start and end dates can thus be easily performed and visualised. The pairwise comparison of two assets or

Quantocracy’s Daily Wrap for 06/18/2019

This is a summary of links featured on Quantocracy on Tuesday, 06/18/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Shannon Entropy: A Genius Gambler’s Guide to Market Randomness [Robot Wealth]

    Before you commit your precious time to read this blog post, I need to warn you that this is one of those posts that market nerds like myself will get a kick out of, but which probably wont add much of practical value to your trading. The purpose of this post is to scratch the surface of the markets from an information theoretic perspective, using tools developed by none other than the father
  • Factor Investing Research On Steriods [Alpha Architect]

    What are the research questions? Do the most prominent long/short factors value, momentum, carry, and defensive survive out of sample? Can long/short factors be timed? What are the Academic Insights? YES. All of the factors exist out of sample, albeit their magnitudes are generally muted.(1) NOT REALLY. After a mind-numbing battery of tests, the evidence is mixed and inconsistent across

Quantocracy’s Daily Wrap for 06/17/2019

This is a summary of links featured on Quantocracy on Monday, 06/17/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Time-Series Signals and Multi-Sector Bonds [Flirting with Models]

    We expand last weeks commentary to explore momentum, carry, value, and long-term reversal signals in a time-series context. Using these signals, we generate long/short portfolios for each asset class. We use a sub-sampling methodology to bootstrap and annualized return distribution. We find that the signals are only selectively significant, and rarely consistent. We believe this initial study
  • A Horse Race of Liquid Alternatives [Factor Research]

    Investors can access alternative strategies via mutual funds and ETFs Most of these show moderate to high correlations to equities, which is concerning Bonds would have been a better diversifier in recent years INTRODUCTION Investing is challenging as it is complex and complicated, which requires continuous learning and updating of mental frameworks. Conflicts and contradictions are found

Quantocracy’s Daily Wrap for 06/15/2019

This is a summary of links featured on Quantocracy on Saturday, 06/15/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • DeepTrading with TensorFlow II [Todo Trader]

    OK, you know what tensors are or perhaps you dont, but you are sure you want to use TensorFlow to trade with it. This post introduces you to how to create elemental NN tensors in TensorFlow. This is the second post of the serie, so you need to be familiarized with the concepts exposed in the first post DeepTrading with Tensorflow. Tensors Tensors (of order higher than two) are data structures
  • DeepTrading with TensorFlow [Todo Trader]

    Do you want to maximize your trading knowledge using TensorFlow? Here are several tips that will surely help you. Introduction Within TodoTraders commitment related to the generation and dissemination of knowledge, I want to offer a series of tutorials on the use of TensorFlow for algorithmic trading. The objective of these tutorials, which will be published periodically, is to offer in a
  • Natural language processing for financial markets [SR SV]

    News and comments are major drivers for asset prices, maybe more so than conventional price and economic data. Yet it is impossible for any financial professional to read and analyse the vast and growing flow of written information. This is becoming the domain of natural language processing; a technology that supports the quantitative evaluation of humans natural language. It delivers textual

Quantocracy’s Daily Wrap for 06/12/2019

This is a summary of links featured on Quantocracy on Wednesday, 06/12/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Market Timing with a Canary, Gold, Copper, LQD, IEF and much more [Alvarez Quant Trading]

    One commonality in my strategies is the inclusion of a market timing component. This could be a signal to go into cash or reduce position size or enter a safe ETF. This applies to my swing trading strategies, my monthly rotation strategies and my Tactical Assert Allocation strategies. As a researcher, I am always on a looking to improve this part of my strategies. There have been a handful
  • The Threat of Rising Rates and the Impact on TAA vs B&H Investing [Allocate Smartly]

    Weve written a lot here and on our sister site BetterBuyAndHold.com about the threat of rising interest rates. You can read some of our past work projecting returns for Treasury ETFs and other interest rate sensitive assets here and here. In a nutshell, assuming that were near the tail end of this 37+ year march lower in interest rates, and in the coming decade(s) rates either rise or remain