Quant Mashup 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(...) 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(...) 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(...) 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(...) 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 Economist’s Big Mac Index measures if(...) 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(...) Building a Robinhood Stock Trading Bot (h/t @PyQuantNews) [Kevin Guo]This is probably my favorite side project I’ve done. I’ve always been interested in algorithmic trading, and it’s 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(...) When to ‘Buy the Dip’ (h/t @PyQuantNews) [Osho Jha]Motivation: “Buy the dip” — it’s a frustratingly simple piece of advice. Like most pieces of advice, it’s 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(...) 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(...) 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(...) 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(...) 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(...) 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(...) 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(...) 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(...) 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(...) Bond ETFs in an Era of Rising Rates [Better Buy And Hold]Bonds are key to a well-diversified portfolio; they’ve 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. That’s not prognostication, it’s a mathematical certainty.(...) 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 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(...) 12 Quant Business Practices to Improve [Two Centuries Investments]Only showing the latest backtest versions without disclosing their out-of-sample degradation Backtesting today’s 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(...) Compound Your Knowledge Episode 9: Investor Confidence & Issues with Factor Investing [Alpha Architect]In this week’s 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. 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(...) 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(...) 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(...) 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(...) 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) /(...) 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(...) 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(...) 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 isn’t the only crucial thing; knowing how to describe what has already happened is also of great importance. In this QuantDare(...) The Factors that Plague Factor Investing [Alpha Architect]For those interested in the literature on factor-based investing, a new paper by Robert Arnott, Campbell Harvey, Vitali Kalesnik and Juhani Linnainmaa, “Alice’s Adventures in Factorland: Three Blunders That Plague Factor Investing,” focuses on why, in some ways, it has failed to live up to its(...) The seven reasons most econometric investments fail [Mathematical Investor]Marcos Lopez de Prado, recently named 2019 Quant of the Year by the Journal of Portfolio Management, has released a presentation entitled The seven reasons most econometric investments fail. Lopez de Prado’s overall point is that many widely used econometric approaches in finance either rely on(...) Warren Buffet: The Greatest Factor Investor of All Time? [Factor Research]A factor exposure of Berkshire Hathaway reveals structural factor tilts Long Value, Size, Quality, and Low Volatility factors and short Growth and Dividend Yield Warren Buffet generated little alpha, but is highly skilled at harvesting factor returns SAINTS AND STAR INVESTORS The Vatican waits at(...) Aggregate Investor Confidence in the Stock Market [Alpha Architect]What are the Research Questions? A common assumption in finance theory is that agents in the stock market behave rationally. Even if temporary mispricing occurs, due to irrational beliefs or incomplete information of some agents, arbitrageurs swiftly restore equilibria. In contrast, the history of(...) The Speed Limit of Trend [Flirting with Models]Trend following is “mechanically convex,” meaning that the convexity profile it generates is driven by the rules that govern the strategy. While the convexity can be measured analytically, the unknown nature of future price dynamics makes it difficult to say anything specific about expected(...) Investment Strategy in an Uncertain World [Alpha Architect]In 1921, University of Chicago Professor Frank Knight wrote the classic book “Risk, Uncertainty, and Profit.” An article from the Library of Economics and Liberty described Knight’s definitions of risk and uncertainty as follows: Risk is present when future events occur with measurable(...) Coming Soon: Quant Minds International - May 13-17 - Vienna, AustriaQuantMinds International heads to Vienna on 13-17 May! Now in it’s 26th year, QuantMinds International brings together 400+ global quant finance experts from banks, buy-side, academia and beyond, to cover every hot topic in quant finance over the course of 5 days. Quote VIP code FKN2595QCYMU for a(...) Learning to Rank with TensorFlow [Quant Dare]Alphabet, the largest Internet-based company, has based its success on sophisticated information retrieval algorithms since its origins. Now, 20 years later, one of its divisions is open-sourcing part of its secret sauce, drawing attention from developers all over the world. Since Google was founded(...) The Problem With Unfilled Gaps Down From Intermediate-Term Highs [Quantifiable Edges]I saw some bullish studies emerge last night. But there was a study below that was not favorable that I thought readers would find interesting. One potential issue with Tuesday’s decline is that it included an unfilled gap down. Generally, an unfilled gap down from a high has more trouble quickly(...) Tail risk of systematic investment strategies and risk-premia alpha [Artur Sepp]Everyone knows that the risk profile of systematic strategies can change considerably when equity markets turn down and volatilities spike. For an example, a smooth profile of a short volatility delta-hedged strategy in normal regimes becomes highly volatile and correlated to equity markets in(...) S&P500 - when to be invested [Philipp Kahler]S&P500 – when to be invested The stock market shows some astonishingly stable date based patterns. Using a performance heat map of the S&P500 index, these patterns are easily found. Date based performance The chart below shows the profit factor of a long only strategy investing in the(...) A Remarkable New Factor: The Cash Conversion Cycle [Alpha Architect]The barrier to entry into the factor zoo has increased exponentially. Prof. Harvey (now working with RAFI) made this clear at the 2017 AFA address, when he highlighted the issue with data-mining in front of a room full of academics from top-flight research programs in the country. Prof. Harvey and(...) Equity Factor Census [CXO Advisory]Should investors trust academic equity factor research? In their February 2019 paper entitled “A Census of the Factor Zoo”, Campbell Harvey and Yan Liu announce a comprehensive database of hundreds of equity factors from top academic journals and working papers through January 2019, including a(...) The First Risk and Opportunity in Active Investing [Two Centuries Investments]What is the most significant risk in quant (and all active) investing today? The First Moment (the mean) The Second Moment (under-estimating tracking error) The Third Moment (skewness, left tails, crash risk) Mis-specified risk model (hidden factor biases, factors ‘eating’ alphas) Sub-optimal(...) Compound Your Knowledge Episode 7: Momentum & Short Sellers [Alpha Architect]In today’s video, we examine three articles from last week. The first article, written by Larry Swedroe, examines the Momentum of News. The second article, written by Wes, examines an out-of-sample test on Momentum by looking at Russian stocks in the 19th century. The third article, written by(...) Revisiting The Weird Portfolio [Flirting with Models]A few years ago, we blindly applied mean-variance optimization to a set of capital market assumptions, and The Weird Portfolio was born. This portfolio is weird because it does not look like typical investor portfolios since it tilts heavily toward credit-based and alternative asset classes. Despite(...) Multi-Factor Smart Beta ETFs [Factor Research]Investors have leaned towards multi-factor over single-factor products in recent years The factor selection and portfolio construction of multi-factor ETFs can be challenged Multi-factor ETFs often feature factors, such as growth, which are not supported by academic research while lacking exposure(...) The most overlooked aspect of algorithmic trading [EP Chan]Many algorithmic traders justifiably worship the legends of our industry, people like Jim Simons, David Shaw, or Peter Muller, but there is one aspect of their greatness most traders have overlooked. They have built their businesses and vast wealth not just by sitting in front of their trading(...) A Simple Mean Reversion Stock Trading Script in C# [Trevor Thackston]Python is not the only language In the past, I’ve published stories on Medium showing how to write algorithms that trade stocks based on company fundamentals and how to run a technical analysis day trading algorithm in the cloud. Both of those articles assumed that: Python was the language the(...) Low Volume At Highs Does Not Provide The Short-Term Bearish Edge It Once Did [Quantifiable Edges]Years ago, strong overbought readings during an uptrend were easily sold – especially when volume came in very light. But that has not held true in recent years. There were several studies I examined last night that noted the low volume, but they have all lost their edge over the last several(...) Tests of Constant and Variable Acceleration Model Kalman Filters [Dekalog Blog]In my last post I said that this next post would report the results of tests on a Constant Acceleration model Kalman filter, and the results are: fail, just like the Constant Velocity model, so I won't bore readers with reporting the details of the failed tests. However, tests of a Variable(...)