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Quantocracy’s Daily Wrap for 09/14/2020

This is a summary of links featured on Quantocracy on Monday, 09/14/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Networks with MlFinLab: Minimum Spanning Tree (MST) [Hudson and Thames]

    Network analysis can provide interesting insights into the dynamics of the market, and the continually changing behaviour. A Minimum Spanning Tree (MST) is a useful method of analyzing complex networks, for aspects such as risk management, portfolio design, and trading strategies. For example, Onnela et al. (2003) notices that the optimal Markowitz portfolio is found at the outskirts of the tree
  • Keeping data vendor APIs simple [Cuemacro]

    Just imagine that every time you went into a shop, you had to change your clothes, because they had a different dress code? Say your grocer would insist on only people wearing yellow, whilst your supermarket would require red clothes only.. Ok, thats a somewhat ridiculous example, which would never happen. In practice, we can wear whatever we want (within reason), and go into whichever shop

Quantocracy’s Daily Wrap for 09/11/2020

This is a summary of links featured on Quantocracy on Friday, 09/11/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Momentum Turning Points [Allocate Smartly]

    This is a test of two recent papers: Momentum Turning Points and Breaking Bad Trends. Learn more about what we do and follow 50+ asset allocation strategies like these in near real-time. Successful trend-following strategies must balance the speed of the trading signal. If the signal is too slow, the strategy will not adapt quickly enough to changes in the actual underlying trend. If its
  • Liquidity Cascades: The Coordinated Risk of Uncoordinated Market Participants [Flirting with Models]

    This paper is unlike any research weve shared in the past. Within we dive into the circumstantial evidence surrounding the weird behavior many investors believe markets are exhibiting. We tackle narratives such as the impact of central bank intervention, the growing scale of passive / indexed investing, and asymmetric liquidity provisioning. Spoiler: Individually, the evidence for these

Quantocracy’s Daily Wrap for 09/10/2020

This is a summary of links featured on Quantocracy on Thursday, 09/10/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Positive Similarity of Company Filings and the Cross-Section of Stock Returns [Quantpedia]

    The usage of alternative data is now a main-stream topic in investment management and algorithmic trading. So lets together explore the textual analysis of 10-K & 10-Q filings and analyze how these datasets could be used as a profitable part of investment portfolios. We invite you to read this short summarization of the research. Full version can be found on the SSRN. Introduction A 10-K or
  • Can We Use the Shiller CAPE Ratio to Forecast Country Returns? [Alpha Architect]

    We all became relatively aware of the CAPE ratio when Shiller predicted the 2000 internet bubble in his book Irrational Exuberance, then after he added a touch of robustness when he called the 2007 housing crisis 1 we all became intimately aware of it. Since that time CAPE has been utilized to mark Historically, the CAPE ratio, Shillers PE, has primarily be utilized over long periods of
  • Kelly criterion: Part 2 [Quant Dare]

    When investing, we spend plenty of time thinking about which securities should we buy but we rarely wonder how much money should we allocate in each asset. Although it does not seem like an important aspect, it is crucial when defining a strategy, up to the point that it can determine the hole performance of your portfolio. In this sense, the Kelly criterion helps us selecting the optimal

Quantocracy’s Daily Wrap for 09/09/2020

This is a summary of links featured on Quantocracy on Wednesday, 09/09/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Predicting Bond Returns? Focus on GDP Growth and Inflation Indicators [Alpha Architect]

    Can the excess returns of government bonds be predicted? This is a classic research question in finance academic research circles. Sometimes practitioners, who are often buried in the more exciting parts of the financial markets, tend to forget that government bonds (do they even belong in your portfolio) are a large global asset class, representing a whopping 30% of market capitalizations across

Quantocracy’s Daily Wrap for 09/07/2020

This is a summary of links featured on Quantocracy on Monday, 09/07/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • CorrGAN: Realistic Financial Correlation Matrices [Hudson and Thames]

    There are 6 properties that empirical correlation matrices exhibit that no synthetic generation method has been able to replicate, until now. Enabling researchers to backtest strategies on an abundance of data would make our algorithms and strategies more robust, accurate, and efficient. Since historical data can be biased and does not have enough high-stress events to test multiple scenarios,
  • Volatility Hedge Funds: The Good, the Bad, and the Ugly [Factor Research]

    Volatility hedge funds provided attractive diversification benefits for equity portfolios However, long were preferable over short volatility strategies Some scepticism is required for the hedge fund index performance INTRODUCTION In finance 101, there is usually little doubt on what constitutes the major asset classes in the investment industry, i.e. there are the traditional ones like equities

Quantocracy’s Daily Wrap for 09/06/2020

This is a summary of links featured on Quantocracy on Sunday, 09/06/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Quant Blog: A Primer on State Space Models [Patrick Aschermayr]

    In my first series of posts, I will give a primer on state space models (SSM) that will lay a foundation in understanding upcoming posts about their variants, usefulness, methods to apply inference and forecasting possibilities. When talking about a state space model (SSM), people usually refer to a bivariate stochastic process , where is an unobserved Markov chain and is an observed sequence of
  • Nowcasting with MIDAS regressions [SR SV]

    Nowcasting macro-financial indicators requires combining low-frequency and high-frequency time series. Mixed data sampling (MIDAS) regressions explain a low-frequency variable based on high-frequency variables and their lags. For instance, the dependent variable could be quarterly GDP and the explanatory variables could be monthly activity or daily market data. The most common MIDAS predictions

Quantocracy’s Daily Wrap for 09/03/2020

This is a summary of links featured on Quantocracy on Thursday, 09/03/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Should you buy or sell stocks that gap down? [Quant Rocket]

    What happens when strong stocks gap down at the open? A well-known trading strategy is to buy the gap, expecting mean reversion. This post uses Zipline to explore down gaps and finds a profitable strategy based on selling, not buying, the gap. Buy the gap? Buying stocks that gap down is a common trading strategy. The reasoning behind the strategy is that bad news causes traders to enter sell

Quantocracy’s Daily Wrap for 09/02/2020

This is a summary of links featured on Quantocracy on Wednesday, 09/02/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Denoising a signal with HMM [Tr8dr]

    Most signals I deal with are noisy, reflecting noise of underlying prices, volume, vol of vol, etc. Many traditional strategies built on such indicators might either: use signal to scale into position such approaches have to deal with noise to avoid thrashing, adjusting position up and down with noise consider specific levels of the signal to signify a state for example: long {+1}, short {-1},
  • Forecast linearity and forecasting mean reverting volatility [Investment Idiocy]

    This is a blog post about forecasting vol. This is important, since as sensible traders we make forecasts about risk adjusted returns (as in my previous post), which are joint forecasts of return and volatility. We also use forecasted vol to size positions. A better vol forecast should mean we end up with a trading strategy that has a nicer return profile, and who knows maybe make some more money.

Quantocracy’s Daily Wrap for 09/01/2020

This is a summary of links featured on Quantocracy on Tuesday, 09/01/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio Optimisation with MlFinLab: Mean-Variance Optimisation [Hudson and Thames]

    For a long while, investors worked under the assumption that the risk and return relationship of a portfolio was linear, meaning that if an investor wanted higher returns, they would have to take on a higher level of risk. This assumption changed when in 1952, Harry Markowitz introduced Modern Portfolio Theory (MPT). MPT introduced the notion that the diversification of a portfolio can inherently

Quantocracy’s Daily Wrap for 08/31/2020

This is a summary of links featured on Quantocracy on Monday, 08/31/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Effects of Portfolio Construction on the Performance of Style Factor ETFs [Alpha Architect]

    Every once in a while its effective to challenge the deep-seated ideas that have been utilized to construct your portfolio. Here at Alpha Architect continuously study the literature and conduct research to derive what we believe gives investors the best shot at winning over the long-haul. This article challenges our preference for the equal-weight methodology, which ensures base-line
  • Picking Profitable Businesses Can Be Highly Unprofitable [Factor Research]

    There seems to be a relationship between the Profitability factor and interest rates The most profitable stocks outperformed the least profitable ones when market cap-weighted However, when equal-weighted, the least profitable stocks outperformed INTRODUCTION The gap between theory and reality in finance is sometimes fuzzy, at other times crystal clear. Ask an academic what explains stock returns
  • Research Review | 28 August 2020 | Portfolio Strategy [Capital Spectator]

    Fire Sale Risk and Expected Stock Returns George O. Aragon (Arizona State U.) and Min S. Kim (Michigan State U.) July 29, 2020 We measure a stocks exposure to fire sale risk through its ownership links to equity mutual funds that experience outflows during periods of systematic outflows from the fund industry. We find that more exposed stocks earn higher average returns: a portfolio that buys