Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 05/02/2019

This is a summary of links featured on Quantocracy on Thursday, 05/02/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tops Wobble Before Falling Over [Quantifiable Edges]

    Ive shown numerous studies in the past that suggest uptrends often become choppy before they ultimately end. It is highly unusual for an uptrend that is showing strong persistence to abruptly top out. The study below demonstrates this concept. The persistent uptrend of late has kept SPX above its short-term moving averages for an extended period. Tuesday, after 22 consecutive closes above the
  • Deep Dive into the Value Factor [Alpha Architect]

    The financial equivalent of the famous Miller Lite, tastes great, less filling debate is the debate between traditional financial economics which uses risk theories to explain asset pricing and the newer behavioral finance field that uses human behavior to provide the explanations. Unfortunately, theres no consensus on which side of the debate is correct. My own view is that both have

Quantocracy’s Daily Wrap for 05/01/2019

This is a summary of links featured on Quantocracy on Wednesday, 05/01/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Tactical Asset Allocation in April [Allocate Smartly]

    This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help
  • Convexity Explains the High BitMEX ETH Funding Rate [Falkenblog]

    BitMEX offers swaps that make it easy to lever a long or short bitcoin (BTC) and ether (ETH). The main reason it trades so much is that they are based outside of US or EU control in the little archipelago-nation of Seychelles, and also that it transacts only in Bitcoin. This combination makes it difficult for regulators to attack. Their swap contracts are like futures contracts without expiry
  • Modified Hikkake Pattern | Trading Strategy (Filter & Exit) [Oxford Capital]

    Developer: Dan Chesler, CTM, CTA. Concept: Trading strategy based on false breakouts. Research Goal: Performance verification. Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: The modified bullish hikkake pattern (a.k.a. the bullish inside day false breakout) consists of two price bars. The first bar is an inside bar. The second bar has a lower close than the first bar.
  • Compound Your Knowledge Episode 10: Factor Investing & Hedge Fund Performance [Alpha Architect]

    In this weeks video, we discuss three posts. The first post discusses the new index analysis section on our site. The second post, written by Tommi, uses Hedge Funds past performance to identify if one can predict future Hedge Fund performance. The last post discusses Wes video examining an older articleFactor Investing is Simple, but Not Easy.

Quantocracy’s Daily Wrap for 04/29/2019

This is a summary of links featured on Quantocracy on Monday, 04/29/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Momentum Is Dead! Long Live Momentum! [Robot Wealth]

    In our inaugural Algo Bootcamp, we teamed up with our super-active community of traders and developed a long-only, always-in-the-market strategy for harvesting risk premia. It holds a number of different ETFs, varying their relative weighting on a monthly basis. Were happy with it. However, the perennial question remains: can we do better? As you might expect, we found evidence suggesting that
  • Asset Allocation Roundup [Allocate Smartly]

    Four recent asset allocation articles (tactical or otherwise) that you might have missed: 1. Bond ETFs in an Era of Rising Rates (Better Buy & Hold) This is our first post from our new platform BetterBuyAndHold.com. Bonds face stiff headwinds in the coming years, and many will underperform what investors have grown accustomed to. Thats not prognostication; its a mathematical certainty.
  • Style Surfing the Business Cycle [Flirting with Models]

    In this commentary, we ask whether we should consider rotating factor exposure based upon the business cycle. To eliminate a source of model risk, we assume perfect knowledge of future recessions, allowing us to focus only on whether prevailing wisdom about which factors work during certain economic phases actually adds value. Using two models of factor rotation and two definitions of business
  • Case Study: Quantpedia’s Composite Seasonal / Calendar Strategy [Quantpedia]

    Despite the economical theory states that financial markets are efficient and investors are rational, a large ammount of research is about anomalies, where the result is different from the theoretical expectation. At Quantpedia, we deal with anomalies in the financial markets and we have identified more than 400 attractive trading systems together with hundreds of related academic papers. This
  • 12 Books on Factor Investing by Asset Managers [Two Centuries Investments]

    Quantitative Portfolio Management by Edward Qian, Ronald Hua, Eric Sorensen Expected Returns by Antti Ilmanen Quantitative Value by Wesley Gray and Tobias Carlisle Quantitative Momentum by Wesley Gray and Jack Vogel Dual Momentum Investing by Gary Antonacci Little Book that Still Beats the Market by Joel Greenblatt Complete Guide to Factor Investing by Andrew Berkin and Larry Swedroe What Works on
  • Equity Factors & The Mighty US Dollar [Factor Research]

    The US dollar had a slightly negative relationship with the stock market since 1996 Some equity factors are more sensitive to changes in the US dollar than others On average the sensitivity is zero, but as often averages are misleading INTRODUCTION The Economists Big Mac Index measures if currencies are over- or undervalued by comparing the implied versus actual exchanges rates of foreign
  • The implicit subsidies behind simple trading rules [SR SV]

    Implicit subsidies are premia paid by large financial markets participants for reasons other than risk-return optimization (view post here). Their estimation requires skill and a strong quantamental system. However, implicit subsidies are behind the popularity and temporary success of many simple trading rules, including those based on variance risk premia, contract hedge value, short

Quantocracy’s Daily Wrap for 04/26/2019

This is a summary of links featured on Quantocracy on Friday, 04/26/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Building a Robinhood Stock Trading Bot (h/t @PyQuantNews) [Kevin Guo]

    This is probably my favorite side project Ive done. Ive always been interested in algorithmic trading, and its exciting to code something that can potentially repay you in the form of cold, hard cash. The bot is written in Python and relies on two core libraries for the majority of its functionality: robin-stocks and ta. robin-stocks is a library that interacts with the Robinhood API and
  • When to Buy the Dip (h/t @PyQuantNews) [Osho Jha]

    Motivation: Buy the dipits a frustratingly simple piece of advice. Like most pieces of advice, its easier said than done and the giver of such advice has probably not attempted to practice what they preach. It induces FOMO, which leads to the hope trade, when the hope trade goes awry youre stuck as the long term investor who really believes in the
  • Buyer Beware: The Reality of Tax-Loss Harvesting Benefits [Alpha Architect]

    Tax loss harvesting is widely promoted, but we think the benefits are generally misunderstood and often overstated.(1) The benefits of loss harvesting arise from tax deferral, similar to the benefits of saving in a retirement account. The benefits of tax deferral rise and fall with expected returns and the benefits are inversely related to future tax rates. Due to the wash sale rule,
  • Is News Sentiment Still Adding Alpha? [EP Chan]

    Nowadays it is nearly impossible to step into a quant trading conference without being bombarded with flyers from data vendors and panel discussions on news sentiment. Our team at QTS has made a vigorous effort in the past trying to extract value from such data, with indifferent results. But the central quandary of testing pre-processed alternative data is this: is the null result due to the lack

Quantocracy’s Daily Wrap for 04/24/2019

This is a summary of links featured on Quantocracy on Wednesday, 04/24/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Avoiding Trades Before Earnings [Alvarez Quant Trading]

    Over my last 16 years of research, one of the most asked questions is should you not take trades before an earnings release. I could never answer this question because I did not have the data. I can easily recall trades were a stock came out with poor earnings and crashed 25%. But without testing this, I would still take stocks into earnings. Because that is how the testing was done. A few months
  • Meta-Labeling (A Toy Example) [Quants Portal]

    Welcome to the concept of Meta-Labeling. This blog post investigates the idea and tries to help build an intuition for what is taking place. The idea of meta-labeling is first mentioned in the textbook Advances in Financial Machine Learning by Marcos Lopez de Prado and promises to improve model and strategy performance metrics by helping to filter-out false positives. In this blog post we make use
  • P-hacking and backtest overfitting [Mathematical Investor]

    Recent public reports have underscored a crisis of reproducibility in numerous fields of science. Here are just a few of recent cases that have attracted widespread publicity: In 2012, Amgen researchers reported that they were able to reproduce fewer than 10 of 53 cancer studies. In 2013, in the wake of numerous recent instances of highly touted pharmaceutical products failing or disappointing
  • Podcast: Gary Antonacci: combining relative strength price momentum with absolute momentum [System Trader Show]

    Imagine that you spend a few minutes a month to manage your investment. All is rule-based, statistically significant, simple and logical. No place for discretionary decisions, no guessing, no gut feeling, no forecasting. And in the long-term, you are almost sure to beat all the actively managed investment funds on the market. Sounds like a scam? Well, everyone should verify everything, but once

Quantocracy’s Daily Wrap for 04/23/2019

This is a summary of links featured on Quantocracy on Tuesday, 04/23/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Replicating Famous Hedge Funds [Factor Research]

    Diverse hedge fund strategies can be replicated via factor-mimicking portfolios The analysis highlights that most returns are explained by factors, not alpha However, hedge funds can create value by harvesting factor returns efficiently via portfolio construction INTRODUCTION In 1973, the U.S. Food and Drug Administration (FDA) published the first regulations that required the nutrition labeling
  • The Recent $RUT / $SPX Divergence And Why It Might Be Bullish [Quantifiable Edges]

    One aspect of recent market action that is interesting is the weakness in the Russell vs the SPX over the last few days. While some may worry the divergence is concerning, an old Quantifinder study that appeared last night indicates the setup is likely suggestive of an upside edge. It looked at times the RUT closed down 3 or more days in a row and the SPX closed at a 3-day high. 2019-04-23-1 As

Quantocracy’s Daily Wrap for 04/22/2019

This is a summary of links featured on Quantocracy on Monday, 04/22/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Bond ETFs in an Era of Rising Rates [Better Buy And Hold]

    Bonds are key to a well-diversified portfolio; theyve provided both consistent returns and consistent diversification against riskier asset classes like stocks and real estate. But bonds face stiff headwinds in the coming years. Thats not prognostication, its a mathematical certainty. Its imperative that our portfolio designs account for this less optimistic future. Failing to do so
  • mlfinlab on PyPi Index [Quants Portal]

    mlfinlab is a living and breathing project in the sense that it is continually enhanced with new code from the chapters in the Advanced Financial Machine Learning book. We have built this on lean principles with the goal of providing the greatest value to the quantitative community. Currently the package contains code from the following chapters: Chapter 2: Financial Data structures: The
  • The Path-Dependent Nature of Perfect Withdrawal Rates [Flirting with Models]

    The Perfect Withdrawal Rate (PWR) is the rate of regular portfolio withdrawals that leads to a zero balance over a given time frame. 4% is the commonly accepted lower bound for safe withdrawal rates, but this is only based on one realization of history and the actual risk investors take on by using this number may be uncertain. Using simulation techniques, we aim to explore how different
  • 12 Quant Business Practices to Improve [Two Centuries Investments]

    Only showing the latest backtest versions without disclosing their out-of-sample degradation Backtesting todays static holdings (managers, asset allocations, sub-asset-classes) into the past – filled with look-ahead bias Charging fees that are on par with the tracking error of the strategy Asking candidates at job interviews to reveal interesting new factors and data-sets Publishing quant
  • Compound Your Knowledge Episode 9: Investor Confidence & Issues with Factor Investing [Alpha Architect]

    In this weeks post, we discuss two posts. The first post, written by Elisabetta, examines a new method attempting to directly measure aggregate investor overconfidence. The second post, written by Larry Swedroe, examines issues that plague Factor Investing.

Quantocracy’s Daily Wrap for 04/19/2019

This is a summary of links featured on Quantocracy on Friday, 04/19/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Multi-threading Trading Strategy Back-tests and Monte Carlo Simulations in Python [Python For Finance]

    In this post I will be looking at a few things all combined into one script you ll see what I mean in a moment Being a blog about Python for finance, and having an admitted leaning towards scripting, backtesting and optimising systematic strategies I thought I would look at all three at the same timealong with the concept of multithreading to help speed things up. So the script
  • Factor Investing is Simple, But Not Easy (Video) [Alpha Architect]

    We are creating a series of long-form educational videos that present materials often covered in our white papers. The intent of these videos is make our content more accessible to visual learners. The video below is a presentation related to a long-form post we have on a post called, The Sustainable Active Investing Framework: Simple, But Not Easy, which is a discussion about identifying

Quantocracy’s Daily Wrap for 04/18/2019

This is a summary of links featured on Quantocracy on Thursday, 04/18/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Daily Extremes – Significance of time [Philipp Kahler]

    Analysing at which time daily market extremes are established shows the significance of the first and last hours of market action. See how different markets show different behaviour and see what can be learned from this analysis. Probability of Extremes A day of trading usually starts with a lot of fantasies for the future, then we try to survive the day and end it with a lot of hope for tomorrow.
  • Gini Index For Decision Trees [Quant Insti]

    Decision trees are often used while implementing machine learning algorithms. The hierarchical structure of a decision tree leads us to the final outcome by traversing through the nodes of the tree. Each node consists of an attribute or feature which is further split into more nodes as we move down the tree. But how do we decide which attribute/feature should be placed at the root node, which
  • SPX Strangle – 2018 Review [DTR Trading]

    I've been a little curious how the SPX strangle has been performing since I last analyzed it's results back in 2015. For this article, we'll just look at the following variations and how they performed from January 2007 through December 2018: 59 DTE – 16 Delta Short Strikes (100:50) / 2 DTE – exit if the trade has a loss of 100% of its initial credit OR if the trade has a profit of

Quantocracy’s Daily Wrap for 04/17/2019

This is a summary of links featured on Quantocracy on Wednesday, 04/17/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Reliably download historical market data from Yahoo! Finance with Python [Ran Aroussi]

    Ever since Yahoo! Finance decommissioned their historical data API, Python developers looked for a reliable workaround. As a result, my library, fix-yahoo-finance, gained momentum and was downloaded over 100,000 acording to PyPi. fix-yahoo-finance aimed to offer a temporary fix to the problem by scraping the data from Yahoo! Finance and returning a the data in the same format as
  • Trading and investing performance – year five [Investment Idiocy]

    Hard to believe, but it has been five and a half years since I had to go to an office to manage other peoples money, and exactly five years since I began systematically trading my own. Time then for another annual review. Perhaps it is confusing for overseas readers, but these reviews follow the UK tax year which runs from 6th April to 5th April, rather than any logical period like a calendar year
  • Classification of Market Regimes [Quant Dare]

    Understanding classification of market regimes is fairly important in finance. It all comes down to correctly predicting the way prices are going to move. But prediction isnt the only crucial thing; knowing how to describe what has already happened is also of great importance. In this QuantDare post we look at types of classification of markets. We concentrate on their differences and suggest