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Quantocracy’s Daily Wrap for 10/25/2021

This is a summary of links featured on Quantocracy on Monday, 10/25/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Pairs Trading Based on Renko and Kagi Models [Hudson and Thames]

    A group of strategies, named statistical arbitrage or pairs trading strategies are well-known for being market-neutral gained their popularity among institutional and individual investors. In general, to develop a pairs trading strategy, one needs to figure out two aspects, the first is how to select assets to form a process with mean-reverting properties, and the second is how to decide when and
  • Does the Equity Market Lead the Currency Market? [Factor Research]

    Past equity market returns seem to predict currency returns Such a currency timing strategy may be interesting as a diversifier However, it is difficult to rationalize the results INTRODUCTION Bloomberg TV at 08:30 am EST: The S&P 500 futures are trading lower as the US Dollar depreciated against G10 currencies overnight. CNBC at 9:45 am EST: The USD appreciated given a strong opening
  • A Complete Starter System for New Traders [Raposa Trade]

    Your biggest investment just took another move higher. It has gotten to the point that you start thinking about taking some profit off the table: its looking more and more enticing by the day! Do you do it? If youre like most investors, you cant resist taking some money today, even if it winds up costing you in the long run. Or, perhaps your brilliant investment thesis hasnt panned

Quantocracy’s Daily Wrap for 10/24/2021

This is a summary of links featured on Quantocracy on Sunday, 10/24/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Site: Is the diversification ratio time-varying? [Lucas Miranda]

    Today we are going to check whether the diversification index proposed by Choueifaty and Coignard (2008) varies over time and some characteristics of this index. The construction of this analysis will be done using python. The Bovespa Index is the main stock index in the Brazilian market and is composed of around 90 stocks. You can check the daily composition of the index here. Remember the
  • A History of Wealth Creation in the U.S. Equity Markets [Alpha Architect]

    Hendrik Bessembinder contributes to the literature on the returns to public equity investment diversification benefits with his study Wealth Creation in the US Public Stock Markets 1926-2019, published in the April 2021 issue of The Journal of Investing. The study updated his 2018 paper, Do Stocks Outperform Treasury Bills?, (Summary and More) adding three more years of data. He
  • A New parameterization of Correlation Matrices [Eran Raviv]

    In volatility modelling, a typical challenge is to keep the covariance matrix estimate valid, meaning (1) symmetric and (2) positive semi definite*. A new paper published in Econometrica (citing from the paper) introduces a novel parametrization of the correlation matrix. The reparametrization facilitates modeling of correlation and covariance matrices by an unrestricted vector, where positive

Quantocracy’s Daily Wrap for 10/22/2021

This is a summary of links featured on Quantocracy on Friday, 10/22/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Building a Raspberry Pi Cluster for QSTrader using SLURM – Part 1 [Quant Start]

    When carrying out systematic trading strategy research one of the main steps is to optimise a collection of strategy parameters to maximise or minimise some objective function. A simple example would be optimising the lookback parameters of the 'fast' and 'slow' moving averages in a trend following system to maximise the strategy's historical Sharpe ratio. Each variation

Quantocracy’s Daily Wrap for 10/20/2021

This is a summary of links featured on Quantocracy on Wednesday, 10/20/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Break into Finance: New Podcast from Quant at Risk [Quant at Risk]

    Let me kick off the series of QuantAtRisks podcasts Break into Finance. I address it to all of you who wish to join the financial industry but have no clue how to do it as well as to those of you who would like to make a change, improve your career, get better, and succeed within the industry. This podcast will be full of practical examples based on my experience across Asia, Australia, and
  • Markov chain as market predictor [Quant Dare]

    Markov chains are well-known in the world of both mathematics and finance. It is common to describe the market as a group of states, for instance bull and bear. From these two there are different ways to create a great deal of other states. If you want to establish the transition relationship between states, Markov chains are really useful. There are some articles in this blog that introduce de

Quantocracy’s Daily Wrap for 10/19/2021

This is a summary of links featured on Quantocracy on Tuesday, 10/19/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on S&P 500 [Enjine]

    Although Harry Potters world of magic exists on the same earth as our magic-less Muggle world, the worlds might as well be on different planets. Each world is governed by its own sets of rules and values, and their residents hardly ever cross each others paths. Academia and industry similarly exist as parallel worlds. In academia, a persons work is judged by its logical rigour. In
  • New Site: Options Derived Analytics [Newmark Risk]

    The Put-Call ratio is often the most commonly used Options-Implied Indicator due to it's simplicity in calculation. However there exists several variations in methodology to calculate it. In this blogpost we give an overview of these different methods and their relevance. The Put-Call ratio can be calculated using volume or open interest and it can be filtered by moneyness (ATM, ITM or OTM).
  • Beyond Hierarchical Risk Parity: Hierarchical Clustering-Based Risk Parity [Portfolio Optimizer]

    In a previous post, I introduced the Hierarchical Risk Parity portfolio optimization algorithm1. In this post, I will present one of its variations, called Hierarchical Clustering-Based Risk Parity, first described in Papenbrock2 and then generalized in Raffinot34 and in Lohre et al.5, from which the implementation in Portfolio Optimizer is inspired. Hierarchical clustering-based risk parity

Quantocracy’s Daily Wrap for 10/18/2021

This is a summary of links featured on Quantocracy on Monday, 10/18/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Pairs Trading with Markov Regime-Switching Model [Hudson and Thames]

    Traditional pairs trading strategies are prone to failures when fundamental or economic reasons cause a structural break and the pair of assets that were expected to move together are no longer having a strong relationship. Such a break may result in asset price spread having abnormally high deviations failing to revert to its historical mean values. Under these circumstances, betting on the
  • Long Volatility Strategies: Hedge Funds vs DIY [Factor Research]

    Long volatility exposure is typically achieved via hedge funds A simple DIY strategy would have generated similar attractive diversification benefits Most of the returns are explained by risk-off currencies, government bonds, and gold INTRODUCTION Do-it-yourself is the best and worst financial advice for retail investors. On the one hand, retail investors are not particularly good investors and
  • Measuring the value-added of algorithmic trading strategies [SR SV]

    Standard performance statistics are insufficient and potentially misleading for evaluating algorithmic trading strategies. Metrics based on prediction errors mistakenly assume that all errors matter equally. Metrics based on classification accuracy disregard the magnitudes of errors. And traditional performance ratios, such as Sharpe, Sortino and Calmar are affected by factors outside the

Quantocracy’s Daily Wrap for 10/14/2021

This is a summary of links featured on Quantocracy on Thursday, 10/14/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Meb’s Greatest Hits [Meb Faber]

    Weve been publishing papers, books and blog posts for over 15 years covering everything from asset allocation strategies and global value investing, to farmland investing, to startups, and even the question of whether or not institutions and endowments should just be managed by a robot. With thousands of pieces of content, we thought it was time to sift through them all and try to rank the
  • What is the Optimal Gold Allocation in a Portfolio? [Quantpedia]

    Ray Dalio, the founder of Bridgewater Associates L.P. and the creator of the All-Weather investment strategy, recommends having some gold in a contemporary environment. He states, In a world of ongoing pressure for policymakers across the globe to print and spend, zero interest rates, tectonic shifts in where global power lies, and conflict, gold has a unique role in protecting portfolios.
  • The Impact of ESG Scores on Asset Prices [Alpha Architect]

    Sustainable investing has grown substantially in recent years, demonstrating that investor demand can be driven by nonfinancial issues such as environmental (E), social (S), and governance (G) characteristics. A full list of our posts on ESG can be found here. The demand from investors who have a preference for investing based on their values could impact valuations and thus expected returns.

Quantocracy’s Daily Wrap for 10/13/2021

This is a summary of links featured on Quantocracy on Wednesday, 10/13/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The MAD indicator [Financial Hacker]

    As an application to the windowing technique described the the previous article, John Ehlers proposed a new trend indicator that he claimed is robust and yet simple. The latter is certainly true, as the MAD (Moving Average Difference) oscillator is, as the name says, just the difference of two moving averages normalized to +/-100. The MAD code in C for Zorro: var MAD(vars Data, int ShortPeriod,

Quantocracy’s Daily Wrap for 10/11/2021

This is a summary of links featured on Quantocracy on Monday, 10/11/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimal Trading Thresholds for the O-U Process [Hudson and Thames]

    Pairs trading or statistical arbitrage is a famous strategy among institutional and individual investors since the 1990s. The concept behind this kind of strategy is straightforward. If the prices of assets move together historically, this tendency is likely to continue in the future. When the spread of the prices diverges from its long-term mean, one can short sell the over-priced stock, buy the
  • Do Big Value Spreads Mean Big Returns to Value Strategies? [Alpha Architect]

    Okay, we cant keep it a secret, we are fans of value investing 1 So when Cliff Asness and his team at AQR write about value, we get excited. The analysis reported in this research confirms the relationship between static value strategies and future returns while incorporating the notion that the size of the value spread influences the size of the future value return. (you can use our free tool
  • Insider Trading: What Happens Behind Closed Doors [Quantpedia]

    Corporate insiders often have insight into a companys private information, which might help them predict how the shares price will move in the coming days. However, laws and regulations are designed to keep them from trading based on this knowledge, as it would be unfair and hurt the companys other shareholders. This includes the prohibition of insider trading or designing a 10b5-1 plan,
  • Less Efficient Markets = Higher Alpha? [Factor Research]

    Emerging market mutual fund managers struggle to outperform EM hedge fund managers failed to generate meaningful alpha EM opportunities seem to come with proportional risks INTRODUCTION Students often ask me for career advice. It is not a particularly satisfying experience. On the one hand, these are often exceptionally bright and hard-working people, with Oxford or Cambridge PhDs in chemical

Quantocracy’s Daily Wrap for 10/08/2021

This is a summary of links featured on Quantocracy on Friday, 10/08/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Three Simple Tactical FX Hedging Strategies [Quantpedia]

    There are many ways one can lose money when investing, and exchange rates are one of the potential risk factors. Luckily, there are several ways to minimize this type of loss in your portfolio. Systematic tactical FX hedging that uses currency factor strategies (for example currency carry, currency momentum and currency value) is a way of protecting an existing or anticipated position from an
  • Research Review | 8 October 2021 | Dynamic Portfolio Strategies [Capital Spectator]

    Time-Varying Factor Allocation Stefan Vincenz and Tom Oskar Karl Zeissler (Vienna U. of Economics and Business) September 15, 2021 In this empirical study, we provide evidence on how predictive information can be utilized to profitably allocate a cross-asset factor portfolio, covering various well-known factors over the asset classes equity, commodity, fixed income, and foreign exchange. We
  • ETF Liquidity Risks? A Discussion [Alpha Architect]

    Because of the complexity inherent to ETF trading in the secondary market, there are frequent misunderstandings about the relationship between the liquidity of the underlying securities and the liquidity of ETFs. Sometimes we hear that ETFs have excess liquidity to the underlying and at others, ETFs will have liquidity concerns. To get a better grasp on this relationship, well hit on the basics