Quantocracy

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Quantocracy’s Daily Wrap for 07/10/2020

This is a summary of links featured on Quantocracy on Friday, 07/10/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Testing expectations [OSM]

    In our last post, we analyzed the performance of our portfolio, built using the historical average method to set return expectations. We calculated return and risk contributions and examined changes in allocation weights due to asset performance. We briefly considered whether such changes warranted rebalancing and what impact rebalancing might have on longer term portfolio returns given the drag

Quantocracy’s Daily Wrap for 07/09/2020

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

  • March for the Fallen 2020: Sign-Up for The Virtual Version! [Alpha Architect]

    We are going to help make March for the Fallen a virtual event this year (September 26, 2020 at 8am). COVID is bad news, but we can turn lemons into lemonadeand we can still show gratitude for Gold Star Families by breaking into smaller groups and marching outdoors! Weve already have 20 local MFTF groups set up around the country (see below in the google sheet and at the end of this post) 1.
  • SPX Golden Cross History Since 1928 [Quantifiable Edges]

    SPX will post a Golden Cross on Thursday afternoon. A Golden Cross occurs when the 50ma crosses over the 200ma. Having the 50ma above the 200ma is commonly considered a bullish market condition and generally it is. In the 4/2/19 blog post I looked at SPX Golden Crosses dating all the way back to 12/31/1928. I have updated that research tonight with Amibroker Software and Norgate Data. Below is

Quantocracy’s Daily Wrap for 07/08/2020

This is a summary of links featured on Quantocracy on Wednesday, 07/08/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Gold Price Prediction Using Machine Learning In Python [Quant Insti]

    Is it possible to predict where the Gold price is headed? Yes, lets use machine learning regression techniques to predict the price of one of the most important precious metal, the Gold. Machine Learning in Trading We will create a machine learning linear regression model that takes information from the past Gold ETF (GLD) prices and returns a prediction of the Gold ETF price the next day. GLD

Quantocracy’s Daily Wrap for 07/07/2020

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

  • Market Return Around the Clock [Alpha Architect]

    Get your popcorn ready, the quants are about to do battle As with all good questions in academic research, there are two sides to the story. We recently published Matthew Bartolinis blog post explaining the impacts of trading costs on the Overnight Return Anomaly. This paper, takes the opposing view, providing evidence that equity market returns are positive overnight and close to zero
  • The Livermore System: Part 2 | Trading Strategy (Filters) [Oxford Capital]

    Source: Kaufman, P. J. (2020). Trading Systems and Methods (Chapter 5: The Livermore System). New Jersey: John Wiley & Sons, Inc. Concept: Trading strategy based on Jesse Livermores approach to swing trading with DeMark pivots. Research Goal: Performance verification of Pivot Size and Penetration Filter. Specification: Table 1. Results: Figure 1-2. Trade Entry/Exit: Table1. Portfolio: 42

Quantocracy’s Daily Wrap for 07/06/2020

This is a summary of links featured on Quantocracy on Monday, 07/06/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Beyond Risk Parity: The Hierarchical Equal Risk Contribution Algorithm [Hudson and Thames]

    As diversification is the only free lunch in finance, the Hierarchical Equal Risk Contribution Portfolio (HERC) aims at diversifying capital allocation and risk allocation. Briefly, the principle is to retain the correlations that really matter and once the assets are hierarchically clustered, a capital allocation is estimated. HERC allocates capital within and across the right number of
  • Heads I Win, Tails I Hedge [Flirting with Models]

    For hedging strategies, there is often a trade-off between degree, certainty, and cost. Put options have high certainty and typically offer a high degree of protection, making them costly to hold and roll over the long run. In this note, we briefly explore the application of different tactical signals to a 9-month, 25-delta rolling put strategy in an effort to reduce long-term costs. We find that
  • Factor Olympics 1H 2020 [Factor Research]

    Momentum & Quality are leading the performance scoreboard in 1H 2020 Value & Size generated negative returns, like in recent years Low Volatility failed to preserve capital during the COVID-19 crisis INTRODUCTION We present the performance of five well-known factors on an annual basis for the last 10 years. We only present factors where academic research supports the existence of positive

Quantocracy’s Daily Wrap for 07/05/2020

This is a summary of links featured on Quantocracy on Sunday, 07/05/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • R + Python = Rython [Eran Raviv]

    Enough! Enough with that pointless R versus Python debate. I find it almost as pointless as the Bayesian vs Frequentist dispute. I advocate here what I advocated there (..dont be a Bayesian, nor be a Frequenist, be opportunist). Nowadays even marginally tedious computation is being sent to faster, minimum-overhead languages like C++. So its mainly syntax administration we insist

Quantocracy’s Daily Wrap for 07/03/2020

This is a summary of links featured on Quantocracy on Friday, 07/03/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Do non binary forecasts work? [Investment Idiocy]

    This is a post about forecasts in trading systems. A forecast is a calibrated expectation for future risk adjusted returns. In more layman like terms, it is a measure of how confident we are about a bullish (positive forecast) or bearish (negative forecast). Perhaps it is easiest to think about forecasts if we compare them to what is not: a forecast is non binary. A binary trading system will
  • Combining Momentum with Long-Term Reversal [Alpha Architect]

    Two of most documented anomalies in the asset pricing literature are the momentum effect and the long-term reversal effect. Momentum is typically defined as the last 12 months of returns excluding the most recent month (i.e., months 212) because it tends to show a reversal, which some have attributed to microstructure (trading) effects in which securities that have outperformed recently tend to
  • Research Review | 3 July 2020 | Business Cycle Analysis [Capital Spectator]

    Forecasting Macroeconomic Risk in Real Time: Great and Covid-19 Recessions Roberto A. De Santis (European Central Bank) July 2020 We show that financial variables contribute to the forecast of GDP growth during the Great Recession, providing additional insights on both first and higher moments of the GDP growth distribution. If a recession is due to an unforeseen shock (such as the Covid-19

Quantocracy’s Daily Wrap for 07/01/2020

This is a summary of links featured on Quantocracy on Wednesday, 07/01/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • First Day of Month Based on Month [Quantifiable Edges]

    Since the late 80s there has been a tendency for the market to rally on the first day of the month. One theory on why this occurs is that there are often 401k inflows that are put to work on the 1st of the month. I examined this tendency and broke it down by month on the blog in 2013 and 2009. I thought it would be interesting to take another look at it today. Below is an updated version of the

Quantocracy’s Daily Wrap for 06/30/2020

This is a summary of links featured on Quantocracy on Tuesday, 06/30/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Time Series Momentum: Theory and Evidence [Alpha Architect]

    The profitability of trend-following strategies has been documented in a large number of empirical studies. The majority of these empirical studies find that these strategies are profitable in the long-run over periods ranging from 50 to 150 years. However, two issues of concern arise regarding the empirical performance of trend-following strategies. The first issue is that the researchers

Quantocracy’s Daily Wrap for 06/29/2020

This is a summary of links featured on Quantocracy on Monday, 06/29/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Trend Following Strategies Shape Return Distributions [Alpha Architect]

    Crisis Alpha is on everyones mind right now, maybe due to a bit of recency bias, but regardless of the reason thinking of and preparing for tail-risk is best done before its needed. Trend following is one such strategy that is rooted in academic research and is an enticing way to manage large drawdown risk, though not without the occasional trip on the Pain Train. The author,
  • The Variance Risk Premium: What Premium? [Factor Research]

    Harvesting the variance risk premium has a sound theoretical foundation However, actual investment products have generated poor returns Furthermore, they are correlated to equities, providing few diversification benefits INTRODUCTION Investing is akin to fighting in a never-ending war. There are long periods of peace and prosperity, but investors are frequently drawn into short-term combat,