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Quantocracy’s Daily Wrap for 06/08/2018

This is a summary of links featured on Quantocracy on Friday, 06/08/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Kelly versus Classical portfolio theory, and the two kinds of uncertainty premium [Investment Idiocy]

    Since I was a young lad there has been an ongoing fight in Financial Academia 'n' Industry between two opposing camps: In the red corner are the Utilitarians. The people of classical finance, of efficient frontiers, of optimising for maximum return at some level of maximum risk. In the blue corner are the Kellyites. Worshipping at the feet of John Kelly and Ed Thorpe they have only one
  • Update on Improved Currency Strength Indicator [Dekalog Blog]

    Following on from my previous post I have now slightly changed the logic and coding behind the idea, which can be seen in the code snippet below Essentially the change simultaneously optimises, using Octave's fminunc function, for both the gold_x and all currency_x geometric multipliers together rather than just optimising for gold and then analytically deriving the currency multipliers. The

Quantocracy’s Daily Wrap for 06/06/2018

This is a summary of links featured on Quantocracy on Wednesday, 06/06/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Machine Learning for Financial Market Prediction With Sklearn and Keras [Alpha Architect]

    Recently, Wes pointed me to this interesting paper by David Rapach, Jack Strauss, Jun Tu and Guofu Zhou: Dynamic Return Dependencies Across Industries: A Machine Learning Approach. The paper presents a strategy that forecasts industry returns and shows excellent historical returns. In this piece, we explore the strategy and then try to improve the results with more sophisticated machine

Quantocracy’s Daily Wrap for 06/05/2018

This is a summary of links featured on Quantocracy on Tuesday, 06/05/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in May [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help you follow these strategies in
  • The Strength Of Two Unfilled Up Gaps & A 50-Day High [Quantifiable Edges]

    One interesting study that I discussed in last nights subscriber letter considered the fact that SPY left an unfilled upside gap for the 2nd day in a row while closing at a 50-day high. The results table I shared can be found below. 2018-06-05 The size of the follow-through isnt terribly large, but it has been quite consistent that some follow through was achieved in the next few days. The
  • Currency Management with FX Style Factors [Quantpedia]

    Currency hedging is often approached with an all-or-nothing mentality: either full hedging of all foreign exchange (FX) positions or no hedging at all. As a more nuanced alternative, we suggest systematically harvesting the benefits of the FX style factors carry, value and momentum. In particular, we demonstrate how these factors can expand the opportunity set of traditional asset allocation when

Quantocracy’s Daily Wrap for 06/04/2018

This is a summary of links featured on Quantocracy on Monday, 06/04/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • RavenPack Research Symposition – Generation AI: The New Data-Driven Investor [Raven Pack]

    The RavenPack Research Symposium returns to New York on September 12th, register to receive updates on the agenda. RavenPack Research Symposium: Generation AI: The New Data-Driven Investor RavenPacks events have become global, with attendance exceeding 250 buy-side professionals at the London Big Data and Machine Learning Revolution in April 2018. RavenPack Research Symposium returns to New
  • ETF Rotation Strategies in Zorro [Robot Wealth]

    At Robot Wealth we get more questions than even the most sleep-deprived trader can handle. So whilst we develop the algo equivalent of Siri and brag about how we managed to get 6 hours downtime last night, we thought wed start a new format of blog posts answering your most burning questions. Lately our Class to Quant members have been looking to implement rotation-style ETF and equities
  • A Season for Sectors [Flirting with Models]

    Seasonality is an effect that shows up in data but is difficult to justify from a theoretical perspective using behavioral, risk-based, or structural reasoning. However, diving deeper into the effect within the U.S. sectors, we find that seasonality has been economically significant and surprisingly robust to specification methods over the past 75 years. Furthermore, it is not explained away when
  • The Inconsistent Performance of Value and Size Factors in the Chinese A-Share Market [Alpha Architect]

    What are the research questions? Does the Fama-French size factor explain the cross-section of stock returns in the Chinese A-share market? Does the Fama-French value factor explain the cross-section of stock returns in the Chinese A-share market? What are the Academic Insights? YES. The authors report a strong negative relationship between the size factor and returns. Out of 10
  • Factors from Scratch with Philosophical Economics (@Jesse_Livermore)

    With a million dollars to invest today, would you rather buy a portfolio of New York City taxi medallions or shares in Uber stock? When we ask investing audiences this question, the answer is almost always Uber. People tend to think in terms of fundamental growth without also thinking about price. In terms of growth and excitement, Uber has the clear edge. But in this paper we're going to
  • Market Timing with Multiples, Momentum and Volatility [Factor Research]

    Equity multiples have been elevated in recent years Using valuation multiples for allocation decisions is a challenging strategy Momentum and volatility-based strategies are more attractive INTRODUCTION In recent years the stock market in the US has been expensive on a variety of valuation multiples, which is often cited for why investing has become more difficult. However, in 2009 valuation
  • Kalman Filter Techniques And Statistical Arbitrage In China’s Futures Market In Python [Quant Insti]

    This article is the final project submitted by the author as a part of his coursework in Executive Programme in Algorithmic Trading (EPAT) at QuantInsti. Do check our Projects page and have a look at what our students are building. About the Author Xing Tao is a Bachelor in Computer Science (LZU), Masters in Information System and Management Science (PKU), and has passed CFA level 1-3 exams.

Quantocracy’s Daily Wrap for 06/03/2018

This is a summary of links featured on Quantocracy on Sunday, 06/03/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Sharpe Ratio > 1 : Careful What You Wish For [Quantum Financier]

    I had the pleasure to hang out with the good folks over at Resolve Asset Management recently. Part of our discussion centered around the differences between our two worlds. As you can imagine, prop trading is fairly different from institutional asset management. A topic of particular interest to both of us however was how to manage expectations. On their end one can imagine that in order to be
  • Cleaning data for trading [Cuemacro]

    Nobody likes doing the boring stuff. We all want to go on holiday, but packing our bags is not the fun bit. We all want to have a nice burger (well, I do), but queuing for ages at an ever popular burger joint is not what we want. Traders all want to have positive P&L, but well negative P&L happens, sometimes. When it comes to data science, in whichever industry, cleaning data is going to
  • Shapley Value Allocation of Operational Risk Capital Charges using Airport Problem Solution [Quant At Risk]

    In Financial Risk Management the most challenging part for quantitative modeling is, beyond any doubt, the Operational Risk (Ops Risk). It is defined as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. This definition includes legal risk, but excludes strategic and reputation risk. According to Basel Committee, (not only American)

Quantocracy’s Daily Wrap for 06/02/2018

This is a summary of links featured on Quantocracy on Saturday, 06/02/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A simple rule for exchange rate trends [SR SV]

    Over the past decades developed market exchange rates have displayed two important regularities. First, real exchange rates (nominal exchange rates adjusted for domestic price trends) have been mean reverting. Second, the mean reversion has predominantly come in form of nominal exchange rate trends. Hence, a simple rule of thumb for exchange rate trends can be based on the expected re-alignment

Quantocracy’s Daily Wrap for 06/01/2018

This is a summary of links featured on Quantocracy on Friday, 06/01/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Factor Regressions Problems and How to Fix Them [Alpha Architect]

    Factor Regressions are one way to ascertain a funds exposure to certain factors that an investor/advisor may want to allocate towards, such as Value, Momentum, Quality, etc. Luckily, there are some great free tools available online, such as portfoliovisualizer.com, that allows investors to run the regressions for most mutual funds and ETFs. For those interested in diving into the weeds of

Quantocracy’s Daily Wrap for 05/31/2018

This is a summary of links featured on Quantocracy on Thursday, 05/31/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Big Data and Machine Learning Revolution: Event takeaways, slides & videos [Raven Pack]

    More than 600 finance professionals registered to attend the London Revolution. An excellent group of top finance professionals shared their latest research and experience with big data and machine learning. The event took place on April 24, 2018 at the Banking Hall, one of the most exquisite venues in Central London. In case you weren't able to attend, presentation slides and video
  • Sharpening the Arithmetic of Active Management [Alpha Architect]

    For many investors, the superiority of passive investing over active investing is axiomatic (Earth to passive investors; Lunch is never free!) And why not? Study after study has demonstrated that only a small portion of actively managed funds beat their benchmarks over long time frames. A recent Wall Street Street Journal article, The Dying Business of Picking Stocks, noted that while 66% of
  • Style Investing in Fixed Income [Alpha Architect]

    The paper investigates this issue by answering the following research questions: Can common robust risk premia (value, momentum, carry and defensive) enhance returns in Fixed Income investing? Do style-based Fixed Income portfolios present diversifying potential? Is a long/short implementation necessary to reap these benefits? What are the Academic Insights? By applying style premiums to country

Quantocracy’s Daily Wrap for 05/29/2018

This is a summary of links featured on Quantocracy on Tuesday, 05/29/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Dollar-Cost Averaging: Improved by Trend? [Flirting with Models]

    The choice to lump sum invest (LSI) or dollar-cost average (DCA) is one fraught with emotion. Intuition tells us that LSI likely offers the best bet for long-term investors as markets, in general, tend to go up. However, can signals derived from simple trend models offer an edge? We find that over longer-term periods (e.g. 6- and 12-months), LSI largely dominates DCA.However, in the
  • How Seasonality The Week Of Memorial Day Has Changed Over The Years [Quantifiable Edges]

    Happy Memorial Day! The week of Memorial Day has shown some interesting seasonal tendencies over the years. But it has faltered greatly the last few. The chart below is one I have shown in the past, and have now updated. It examines SPX performance from the Friday before Memorial Day to the Friday after it. 2018-05-28 There was no substantial edge apparent throughout the 70s, but starting in 1983
  • Short-Term Return Reversals and Intraday Transactions [Quantpedia]

    I examine whether a short-term reversal is attributed to past intraday or overnight price movements. The results show that intraday returns significantly reverse in the following week, while overnight returns do not, indicating that the short-term reversal is attributed to past intraday price movements. In addition, the reversal of intraday returns is stronger for more illiquid stocks and during

Quantocracy’s Daily Wrap for 05/28/2018

This is a summary of links featured on Quantocracy on Monday, 05/28/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Mean-Reversion [Factor Research]

    The Mean-Reversion factor is driven by volatility Allocating tactically when volatility is high generates an attractive payoff profile The strategy can be considered as a tail risk hedge for equity portfolios INTRODUCTION Our most recent research note focused on the Mean-Reversion factor (please see the report Mean-Reversion Across Markets), which highlighted performance and strategy
  • An Improved Currency Strength Indicator plus Gold and Silver Indices? [Dekalog Blog]

    In the past I have blogged about creating a currency strength indicator ( e.g. here, here and here ) and this post talks about a new twist on this idea. The motivation for this came about from looking at chart plots such as this, which shows Gold prices in the first row, Silver in the second and a selection of forex cross rates in the third and final row. The charts are on a daily time scale and
  • Building A Better Trend Filter [System Trader Success]

    In this article I will create a trend filter (also known as market mode filter or regime filter) that is adaptable to volatility and utilizes some of the basic principles of hysteresis to reduce false signals (whipsaws). As you may know, I often will use the 200-period simple moving average (200-SMA) to determine when a market is within a bull or bear mode on a daily chart. When price closes above