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Quantocracy’s Daily Wrap for 08/17/2022

This is a summary of links featured on Quantocracy on Wednesday, 08/17/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Geometric Brownian Motion Simulation with Python [Quant Start]

    Generating synthetic data is an extremely useful technique in quantitative finance. It provides the ability to assess behaviour on models using data with known behaviours. This has a myriad of applications, such as testing backtesting simulators for correct functional behaiour as well as allowing potential "what if?" scenarios to be evaluated, such as for simulated crises. Synthetic data
  • Protected equity fund: Split your portfolio to better fit your hedging instruments [DileQuante]

    Imagine you are an European insurer. One of your funds is an equity portfolio of EMU stocks. Under Solvency II framework, you might want to reduce your Solvency Capital Requirement (SCR) thanks to the use of derivatives to hedge some of your equity risk. However, due to your size, the only sufficiently liquid contracts that you can use are Euro Stoxx 50 (E50) options. The problem is that your fund

Quantocracy’s Daily Wrap for 08/16/2022

This is a summary of links featured on Quantocracy on Tuesday, 08/16/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 100-Years of the United States Dollar Factor [Quantpedia]

    Finding high-quality data with a long history can be challenging. We have already examined How To Extend Historical Daily Bond Data To 100 years, How To Extend Daily Commodities Data To 100 years, and How To Build a Multi-Asset Trend-Following Strategy With a 100-year Daily History. Following the theme of our previous articles, we decided to extend historical data of a new factor, the Dollar
  • Outperformance Ain t Alpha [Factor Research]

    Outperformance and alpha are not the same One is the difference from a benchmark, the other is the unexplained return A contribution analysis helps understanding the return drivers INTRODUCTION Almost 90% of US drivers rate themselves safer and more skillful than average. Obviously, such perceptions do not reflect reality. After all, nine out of 10 people cant all be above average.

Quantocracy’s Daily Wrap for 08/15/2022

This is a summary of links featured on Quantocracy on Monday, 08/15/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Correlation and Correlation Structure (6) Distance Correlation [Eran Raviv]

    While linear correlation (aka Pearson correlation) is by far the most common type of dependence measure there are few arguably better ways to characterizeestimate the degree of dependence between variables. This is a fascinating topic I keep coming back to. There is so much for a typical geek to appreciate: non-linear dependencies, should we consider the noise in the data or rather just focus on
  • Three Strategies for Trading the Donchian Channel in Python [Raposa Trade]

    In the 1970's, Richard Donchian began the trend following trend by introducing a simple breakout trading system that would make him millions over the following decades. This system was predicated on an indicator that came to bear his name the Donchian Channel. We're going to show you how to calculate and trade the Donchian Channel with three example strategies so you can incorporate it
  • Mining Credit Card Data for Stock Returns [Alpha Architect]

    In this article, the authors explore an alternative measure of consumer demand from a unique dataset of individual credit and debit card daily transactions ( available one week after the transaction was made on average) from January 2013 to December 2019. They ask the following: Can more timely information such as daily transactions information on sales predict future earnings surprises? Can more

Quantocracy’s Daily Wrap for 08/11/2022

This is a summary of links featured on Quantocracy on Thursday, 08/11/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Log-normal Stochastic Volatility Model [Artur Sepp]

    I am introducing my most recent research on log-normal stochastic volatility model with applications to assets with positive implied volatility skews, such as VIX index, short index ETFs, cryptocurrencies, and some commodities. Together with Parviz Rakhmonov, we have extended my early work on the log-normal volatility model and we have written an extensive paper with an extra focus on modelling

Quantocracy’s Daily Wrap for 08/10/2022

This is a summary of links featured on Quantocracy on Wednesday, 08/10/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Treasury Bonds: Buy and Hold or Trend Follow? [Alpha Architect]

    We were recently asked what we thought about bonds as an investment. A lot of this was inspired by my comments on bonds via a discussion on how I personally invest. Ill repost what I said on bonds below: What are your thoughts on bonds and commodities? In general, Im not a fan of corporate bonds as a buy-and-hold asset class. Outside of treasury bonds, most bonds earn lower returns than
  • What Drives Momentum and Reversal? [Alpha Architect]

    What are the research questions? Theories abound in the financial literature explaining the drivers of momentum and reversal in one way or another. Not surprisingly, most portray the role of public and private information as key to the underlying relationships and weigh the type of information differently. For example, if the driver of momentum is a fundamental underreaction to public information,
  • Revisiting the Performance of TAA ETFs [Factor Research]

    There has been a boom in launching tactical asset allocation ETFs However, the recent track record of these has been poor Declining stock and bond markets have created a challenging environment for these INTRODUCTION Most investment strategies become popular through short rather than long periods, simply because no strategy works all the time. The longer the track record, the more explanation is
  • Research Review | 5 August 2022 | Multi-Factor Strategies [Capital Spectator]

    Combining Factors Christoph Reschenhofer (Vienna University of Economics and Business) July 2022 While the academic literature primarily investigates factor exposures based on covariances (i.e. beta exposure), most practitioners apply characteristics-based scorings to obtain factor portfolios. It hereby remains largely unexplored how firm-level characteristics can be combined to obtain optimal
  • Crashes in safe asset markets [SR SV]

    A new theoretical paper illustrates the logic behind runs and crashes in modern safe asset markets. Safe assets are characterized by stable value and high liquidity. In times of distress flight for safety increases demand for these assets, while dash for cash increases supply. However, these two are not generally in balance. If the need for liquidity is expected to dominate and dealer

Quantocracy’s Daily Wrap for 08/04/2022

This is a summary of links featured on Quantocracy on Thursday, 08/04/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Avoiding Momentum Crashes [Alpha Architect]

    In our book Your Complete Guide to Factor-Based Investing, Andrew Berkin and I presented the evidence demonstrating that momentum, both cross-sectional (CSMOM) and time-series (TSMOM), has provided a premium that has been found to be persistent across time and economic regimes, pervasive around the globe and across sectors and asset classes (stocks, bonds, commodities, and currencies),

Quantocracy’s Daily Wrap for 08/03/2022

This is a summary of links featured on Quantocracy on Wednesday, 08/03/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Avoiding Volatile Trades [Alvarez Quant Trading]

    In my last blog post, Using Historical Volatility for Parameter Adjustment, I tested using historical volatility to determine trade rules. While reading the July 2022 Technical Analysis of Stocks & Commodities, I came across an article, Is It Too Volatile To Trade? by Perry Kaufman. I always like his work so I was interested to see what he had to say. He uses standard deviation from the
  • Trend Following Says Commodities…But Nothing Else! [Alpha Architect]

    Just recently we posted the trend-following weights for our Robust Asset Allocation model. Something interesting happened the model suggested zero exposure to every asset, except commodities(1) source: https://alphaarchitect.com/indexes/trend/#trendasset My knee-jerk reaction was, Wow, never seen that before. But as is the case with all emotional reactions, it is important to not lean on
  • How heavy tails destabilize Markowitz portfolio selection [Artifact Research]

    This is the forth and final post of a short series of posts on extreme events in financial time series. In the first post, we have introduced power-law theory to describe and extrapolate the chance of extreme price movements of the S&P500 index. In the second post, we took a closer look at how statistical moments may become infinite in the presence of power-law tails, rendering common

Quantocracy’s Daily Wrap for 08/02/2022

This is a summary of links featured on Quantocracy on Tuesday, 08/02/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Effective Number of Bets: Measuring Portfolio Diversification [Portfolio Optimizer]

    Many different measures of portfolio diversification have been developed in the financial literature, from asset weights-based diversification measures like the Herfindahl Index1 to risk-based diversification measures like the Diversification Ratio of Choueifaty and Coignard2 to other more complex diversification measures. Because each of these measures usually provides information about a

Quantocracy’s Daily Wrap for 08/01/2022

This is a summary of links featured on Quantocracy on Monday, 08/01/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Slava Ukraini! Latest from Quantocracy contributor in Ukraine: Modeling Dynamics of Entire Implied Volatility Surface [Only VIX]

    There is a very cool webinar coming up next week that I suggest everyone to register and attend link Daniel Bloch, also often listed as Daniel Alexandre Bloch has contributed a lot of research on using ML for options pricing. Also Mr Block published a very thorough free textbook options pricing that I highly recommend to everyone – it reviews and evaluates most of the recent developments in
  • Why GARCH models fail out-of-sample [Artifact Research]

    This is the third post of a short series of posts on extreme events in financial time series. In the first post, we have introduced power-law theory to describe and extrapolate the chance of extreme price movements of the S&P500 index. In the second post, we took a closer look at how statistical moments may become infinite in the presence of power-law tails, rendering common estimators
  • Do Stocks Efficiently Predict Recessions? [Alpha Architect]

    What are the Research Questions? There is abundant literature on the relationship between the business cycle and future stock returns. The traditional view is that stocks are rationally priced to immediately reflect investors expectations about future economic activity and that expected excess returns on stocks are positive, vary over time, and display counter-cyclical behavior. The author asks

Quantocracy’s Daily Wrap for 07/30/2022

This is a summary of links featured on Quantocracy on Saturday, 07/30/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Practical Implementation of Strategic Allocation Bets with Black-Litterman [DileQuante]

    As a portfolio manager or as a portfolio construction analyst, the most usual way to manage a fund is to elaborate a Strategic Asset Allocation (a.k.a. SAA), that is reviewed on a mid or low frequency, on which PM or researchers add their tactical views, i.e. a Tactical Asset Allocation (a.k.a. TAA), which can be refreshed on a higher frequency. The SAA reflects the long term view of