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Quantocracy’s Daily Wrap for 03/15/2020

This is a summary of links featured on Quantocracy on Sunday, 03/15/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Petra on Programming: The Smoothed OBV [Financial Hacker]

    In his article in the S&C April 2020 issue, Vitali Apirine proposed a modified On Balance Volume indicator (OBVM). The hope was that OBVM crossovers and divergences make great trade signals, especially for stock indices. I got the job to put that to the test. The original OBV indicator was invented by Joseph Granville in 1963. It differs from other indicators insofar as it takes trade volume
  • Speeding up your Python code [R Trader]

    I know this topic is addressed on a very regular basis on the web but Im pretty sure sharing my experience will help some finance people. Im currently working on Limit Order Book modeling. This means dealing with fairly big data sets. I have around 1 million observations per stock and per day. So modeling the behavior of the order book just over 10 days is already a decent big data exercise.

Quantocracy’s Daily Wrap for 03/14/2020

This is a summary of links featured on Quantocracy on Saturday, 03/14/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Rebalancing ruminations [OSM]

    Back in the rebalancing saddle! In our last post on rebalancing, we analyzed whether rebalancing over different periods would have any effect on mean or risk-adjusted returns for our three (equal, naive, and risky) portfolios. We found little evidence that returns were much different whether we rebalanced monthly, quarterly, yearly, or not at all. Critically, as an astute reader pointed out, if
  • Low Volatility-Momentum Versus Value-Momentum Factor Portfolios [Alpha Architect]

    If an investor would state today that in ten or twenty years most portfolios would include an allocation to cryptocurrencies, they would likely be laughed at. However, a similar response would have been encountered in the Internet Bubble and someone proposed to invest in low-risk stocks. During that time, investors were ignoring boring companies like REITs or utilities and were plowing into

Quantocracy’s Daily Wrap for 03/13/2020

This is a summary of links featured on Quantocracy on Friday, 03/13/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Where Tactical Asset Allocation Stands Now (Thursday 03/12) [Allocate Smartly]

    Broadly speaking, Tactical Asset Allocation has weathered this storm reasonably well, but the last two days have been tough and we are by no means out of the woods. We track 50+ published TAA strategies, allowing us to draw some broad conclusions about TAA as a style. In the table below we show the MTD/YTD returns of these 50+ strategies: TAA began reducing exposure to risk assets back in January,

Quantocracy’s Daily Wrap for 03/12/2020

This is a summary of links featured on Quantocracy on Thursday, 03/12/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Vector Autoregression Trading Model [Robot Wealth]

    The vector autoregression (VAR) framework is common in econometrics for modelling correlated variables with bi-directional relationships and feedback loops. If you google vector autoregression youll find all sorts of academic papers related to modelling the effects of monetary and fiscal policy on various aspects of the economy. This is only of passing interest to traders. However, if we

Quantocracy’s Daily Wrap for 03/11/2020

This is a summary of links featured on Quantocracy on Wednesday, 03/11/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Do Insider Trades Provide Insights into Future Returns? [Alpha Architect]

    The volume of work that has been done on insider transactions is not inconsequential, weve covered a variety of research on the topic in several blog posts just a few of which are here and here. This is the first time we observe corporate insiders ability to overcome biases as an indicator of future returns though. Because corporate insiders are also human, they too can be subject to
  • Trading Multiple Strategies [Alvarez Quant Trading]

    Using strategy diversification is one of the easiest ways to improve the performance and reduce risk of your overall portfolio. Trading one strategy is risky because you never know when it may stop working or simply go into a period of under-performance. Given two strategies to trade, the questions I have are, what is the performance of trading them together? What percentage of the total portfolio
  • What to Do When Alpha Becomes Beta [Alpha Architect]

    In this article, the author argues that alternative risk premia (ARP) strategies undergo an evolution that begins with their inception as a pure alpha -based strategy, continuing its metamorphosis into a pure beta strategy. The inevitable transformation is brought on by a number of factors and also presents an opportunity for managers and investors alike to reassess their position on the

Quantocracy’s Daily Wrap for 03/09/2020

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

  • Build a Trading System using Statistical Methods [Milton FMR]

    Most trading systems utilize indicators as a method of trading strategy design. But before building a trading system using indicators one should ask what do they indicate? The answer to that is that most of the time they are not indicating any information that can be advantageous in building a profitable trading system. The only thing that they can be used for are as noise filters. Some indicators
  • Where Tactical Asset Allocation Stands Now (Monday 03/09) [Allocate Smartly]

    Weve fielded a lot of questions this morning about how Tactical Asset Allocation is faring this month. We track 50+ published strategies, so were able to draw some broad conclusions about the current state of TAA. Generally speaking, all is well. Individual strategies vary, but as a whole, TAA has weathered the storm so far. Most strategies are either up or near flat for the month. Why? TAA
  • Building and Regularizing Linear Regression Models in Scikit-learn [Quant Insti]

    In the last blog, we examined the steps to train and optimize a classification model in scikit learn. In this blog, we bring our focus to linear regression models. We will discuss the concept of regularization, its examples(Ridge, Lasso and Elastic Net regularizations) and how they can be implemented in Python using the scikit learn library. Linear Regression problems also fall under supervised
  • Why Trend Models Diverge [Flirting with Models]

    During the week of February 23rd, the S&P 500 fell more than 10%. After a prolonged bullish period in equities, this tumultuous decline caused many trend-following signals to turn negative. As we would expect, short-term signals across a variety of models turned negative. However, we also saw that price-minus-moving-average models turned negative across a broad horizon of lookbacks where the
  • Big Gaps Down In Already Bad Markets [Quantifiable Edges]

    SPX futures are locked limit down 5% as I write this Sunday night. The small study below looks at all other times 1) SPY was already short-term oversold (closed at a 5-day low), and 2) gapped down at least 3%, and 3) opened below the lowest close of the previous 50 days. Below is the full list of instances along with performance following each: 2020-03-08 A few notes: These numbers look pretty

Quantocracy’s Daily Wrap for 03/07/2020

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

  • The Secret to Shorting Stocks [Black Arbs]

    Misinformation is everywhere. Many people believe the key to successful short selling is simply the inversion of a successful long strategy. I also used to believe this, among other short selling myths before I took the Short Selling Course by Laurent Bernut ( This article will demonstrate the impact, just one of the revealed secrets to short selling, can have on your algorithmic strategy
  • Lagged correlation between asset prices [SR SV]

    Efficient market theory assumes that all market prices incorporate all information at the same time. Realistically, different market segments focus on different news flows, depending on the nature of the traded security and their research capacity. Such specialization makes it plausible that lagged correlations arise between securities prices, even though their specifics may change overtime.

Quantocracy’s Daily Wrap for 03/06/2020

This is a summary of links featured on Quantocracy on Friday, 03/06/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Stay Rich Portfolio [Meb Faber]

    Welcome to the second installment of our new series on generating wealth, preserving it, and then looking at a real-world illustration of strategically implementing these concepts. In our first essay, we discussed generating riches through a high-paying career, investing in public and private markets, and starting your own business. The takeaway was there is no fast safe path to riches.
  • The Gap Between Large and Small Companies is Growing. Why? [Alpha Architect]

    In my role as chief research officer for the Buckingham Family of Financial Services, I receive many questions from investors and advisors alike, asking me to address concerns they have that originate from articles they have read or statements they hear on the financial media. I thought it worth sharing my response to the questions I received about an August 2019 study published by the Harvard

Quantocracy’s Daily Wrap for 03/05/2020

This is a summary of links featured on Quantocracy on Thursday, 03/05/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How much risk should we take? [Investment Idiocy]

    This is the second of three posts aimed at answering three fundamental questions in trading: How should we control risk (previous post) How much risk should we take? (this post) How fast should we trade? (TBC) These questions are extremely important, IMHO much more important than the question of which funky indicator to use. I won't be able to discuss all the finer details of position scaling
  • Should You React To The Surge In Stock Market Volatility? [Capital Spectator]

    The coronavirus thats roiling world markets and raising questions about the economic outlook has triggered a familiar shock to stocks: higher volatility. Is this a reason to change your asset allocation, rebalance the portfolio or modify risk management decisions? Maybe, but maybe not. There is no generic answer for everyone because every investor is different due to risk tolerance, time

Quantocracy’s Daily Wrap for 03/04/2020

This is a summary of links featured on Quantocracy on Wednesday, 03/04/2020. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Graphical Lasso and its Financial Applications [Robot Wealth]

    Way back in November 2007, literally weeks after SPX put in its pre-GFC all-time high, Friedman, Hastie and Tibshirani published their Graphical Lasso algorithm for estimation of the sparse inverse covariance matrix. Are you suggesting that Friedman and his titans of statistical learning somehow caused the GFC by publishing their Graphical Lasso algorithm? Not at all. Im just setting you up to