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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

Quantocracy’s Daily Wrap for 08/27/2020

This is a summary of links featured on Quantocracy on Thursday, 08/27/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Pre-Election Drift – Video [Quantpedia]

    The presidential campaign is becoming hotter as we are moving closer to this years election. But we still have enough time to dig deeper into data about the past elections and prepare for the autumn. Therefore, we have prepared a short video recapitulation of our paper on the pre-election drift. Are you looking for more strategies to read about? Check http://quantpedia.com/Screener Do you want
  • How to Measure and Understand Portfolio Tail Risk Events [Alpha Architect]

    To any investor that has had the opportunity to experience a large collapse in the market, they can tell you that essentially there is nowhere to hide. Correlations of assets that were held to diversify a portfolio suddenly get very correlated in extreme market conditions aka the tails of the distribution. Much academic research has been done on the stronger dependence 1 that prevails among

Quantocracy’s Daily Wrap for 08/26/2020

This is a summary of links featured on Quantocracy on Wednesday, 08/26/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Satisficing and optimizing [OSM]

    In our last post, we explored mean-variance optimization (MVO) and finally reached the efficient frontier. In the process, we found that different return estimates yielded different frontiers both retrospectively and prospectively. We also introduced the concept of satsificing, originally developed by Herbert Simon. Simply put, satisficing is choosing the best available solution afforded by a

Quantocracy’s Daily Wrap for 08/25/2020

This is a summary of links featured on Quantocracy on Tuesday, 08/25/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Sigma Algebras and Probability Spaces [Quant Start]

    Our recent 2020 Content Survey highlighted the desire from many of you to study the more advanced mathematics necessary for carrying out applications in quantitative finance. Two of the highlighted areas were Linear Algebra for Deep Learning along with Stochastic Calculus. The latter is the underlying theoretical framework utilised for pricing derivatives contracts. Learning Stochastic Calculus

Quantocracy’s Daily Wrap for 08/24/2020

This is a summary of links featured on Quantocracy on Monday, 08/24/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Risk-Neutral Probability Distributions: CLK2020 [Quantoisseur]

    Risk-neutral probability distributions (RND) are used to compute the fair value of an asset as a discounted conditional expectation of its future payoff. In 1978, Breeden and Litzenberger presented a method to derive this distribution for an underlying asset from observable option prices [1]. The derivation of the relationship is well presented in A Simple and Reliable Way to Compute Option-Based
  • Does Gold do What it is Supposed to do? [Alpha Architect]

    The world has unquestionably be sent on a wild ride in 2020. We entered the year full of optimism and hope. Markets were at or near all-time highs, unemployment was low, living on easy street was good. Then the impact of COVID-19 ripped through the market and the economy with enough force to make the winds of even a double hurricane green with envy. This massive and rapid readjustment of the
  • Training the Perceptron with Scikit-Learn and TensorFlow [Quant Start]

    In the previous article on the topic of artificial neural networks we introduced the concept of the perceptron. We demonstrated that the perceptron was capable of classifying input data via a linear decision boundary. However we postponed a discussion on how to calculate the parameters that govern this linear decision boundary. Determining these parameters by means of 'training' the
  • How Risky Are Value Stocks? [Factor Research]

    The Value factor is often explained as representing a risk premium or a behavioral bias However, financial analysts regard cheap stocks as less risky than expensive ones Data shows that expensive stocks were riskier than cheap ones, which challenges the risk premium theory INTRODUCTION Which of the following two portfolios comprised of US stocks would you consider riskier? Portfolio A: Amazon,
  • Market-implied macro shocks [SR SV]

    Combinations of equity returns and yield-curve changes can be used to classify market-implied underlying macro news. The methodology is structural vector autoregression. Theoretical restrictions on unexpected changes to this multivariate linear model allow identifying economically interpretable shocks. In particular, one can distinguish news on growth, monetary policy, common risk premia and

Quantocracy’s Daily Wrap for 08/21/2020

This is a summary of links featured on Quantocracy on Friday, 08/21/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Petra on Programming: Four Dimensions of Strength [Financial Hacker]

    In the S&C September 2020 article Tracking Relative Strength In Four Dimensions, James Garofallou presents a metric for evaluating a securitys strength relative to 11 major market sectors and over several time periods. All this information is squeezed into a single value. Maybe at cost of losing other important information? In this article well look into how to program such a
  • Even Great Investments Experience Massive Drawdowns [Alpha Architect]

    Editors Note: The ability of value investors to adhere to their investment strategy has been put to the greatest test ever. From January 2017 through March 2020, in terms of total returns, the Russell 3000 Growth Index outperformed the Russell 3000 Value Index by 51.7 percentage points (46.7% vs. -5.0%). That drawdown was much greater than previous ones and has lasted longer. For frequent