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Quantocracy’s Daily Wrap for 08/20/2018

This is a summary of links featured on Quantocracy on Monday, 08/20/2018. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trading Metrics that Actually Matter [Quant Fiction]

    Traders love their performance metrics. Anyone whos used their platforms backtesting features has probably come across a few dozen of them, and everyones got their favorite. Anybody whos anybody in the finance world has one named after them: Sharpe, Sortino, Calmar, Treynor, Gartman, etc. (OK, maybe not the last one). But which ones are the most important? There should be some kind of
  • The State of Risk Management [Flirting with Models]

    We compare and contrast different approaches to risk managing equity exposure; including fixed income, risk parity, managed futures, tactical equity, and options-based strategies; over the last 20 years. We find that all eight strategies studied successfully reduce risk, while six of the eight strategies improve risk-adjusted returns. The lone exceptions are two options-based strategies that
  • Looking at Alternatives? Avoid Complexity and Magical Backtests [Alpha Architect]

    The paper investigates the following research question: Does persistence (out of sample performance) exist for alternative beta strategies sponsored by investment banks? Does adding complexity to a strategy increase the risk of backtesting overfitting? Do the strategies capture the factor exposure they seek to exploit? And, does the exposure remain consistent between backtesting and live periods?
  • On Testing Direction Prediction Accuracy [Jonathan Kinlay]

    As regards the question of forecasting accuracy discussed in the paper on Forecasting Volatility in the S&P 500 Index, there are two possible misunderstandings here that need to be cleared up. These arise from remarks by one commentator as follows: An above 50% vol direction forecast looks good,.. but direction is biased when working with highly skewed distributions! ..so it would be
  • Low Volatility, Low Beta & Low Correlation [Factor Research]

    The Low Volatility, Low Beta and Low Correlation factors are interrelated Low-risk factors generate attractive risk-adjusted returns, but require beta-neutrality Currently they feature moderate to high interest-rate sensitivity INTRODUCTION Coca-Cola versus Bitcoin Investment Trust, Mattel versus Groupon, Ventas versus Facebook. Which stocks would you prefer? These stock pairs represent low versus
  • Range-Based EGARCH Option Pricing Models (REGARCH) [Jonathan Kinlay]

    The research in this post and the related paper on Range Based EGARCH Option pricing Models is focused on the innovative range-based volatility models introduced in Alizadeh, Brandt, and Diebold (2002) (hereafter ABD). We develop new option pricing models using multi-factor diffusion approximations couched within this theoretical framework and examine their properties in comparison with the

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