Quant Mashup PDF: Two Centuries of Value and Momentum 1800-2014 Risk Parity in Python [Quant Dare]Once we are familiar with the theory surrounding Risk Parity, it’s time to put the strategy into practice and try out the algorithm for ourselves. We discover how it works, analyse the strategy and create our own portfolios. Thanks to the posts written by T.Fuertes and mplanaslasa we already know(...) 800 Years of Risk-Free Rate [Quantpedia]This paper presents a new dataset for the annual risk-free rate in both nominal and real terms going back to the 13th century. On this basis, we establish for the first time a long-term comparative investigation of ‘bond bull markets’. It is shown that the global risk-free rate in July 2016(...) State of Trend Following in October [Au Tra Sy]Last month saw a strong upwards performance from the State of Trend Following index, single-handedly reversing half the negative performance for the year, which still stands close to double-digit territory. Please check below for more details. Detailed Results The figures for the month are: October(...) Timing TAA Strategies Based on Relative Strength: A Suboptimal Approach [Allocate Smartly]We track a wide range of tactical asset allocation strategies in near real-time (41 and counting), which members can combine into their own custom portfolios. We provide members with a wealth of data to understand how each strategy fits into a coherent trading plan, but we don’t tell members the(...) Replicating Indexes In R (Part III): Socially Responsible Investing [Capital Spectator]In previous installments of replicating indexes I profiled the style-analysis methodology and presented an example using a hedge fund index. Now let’s turn to a strategy of replicating the S&P 500 Index with a handful of stocks that are considered socially responsible investments (SRI).(...) Earning Money in Cryptocurrency Markets by Spotting Statistical Arbitrage Opportunities [Quant at Risk]When you come in contact with cryptocurrencies, e.g. Bitcoin (BTC), you quickly realise that there is no single price of BTC at any given moment. The reason is that Bitcoin is traded on different markets. It can be worth more on Coinbase exchange and less on Kraken exchange. In particular, the(...) Cointegration, Correlation and Log Returns [Quantoisseur]The differences between correlation and cointegration can often be confusing. While there are some helpful explanations online, I wasn’t satisfied with the visual examples. When looking at a plot of an actual pair of symbols where the correlation and cointegration test results differ, it can be(...) Are we misidentifying seasonal patterns as genuine earnings news? [Alpha Architect]Changes in earnings are comprised of the expected earnings number plus any seasonal component of earnings. If the seasonal component is expected then it should not affect prices in an efficient market. However, unusual returns have been documented surrounding earnings announcements at the seasonal(...) It’s Long/Short Portfolios All The Way Down [Flirting with Models]Long/short portfolios are helpful tools for quantifying the value-add of portfolio changes, especially for active strategies. In the context of fees, we can isolate the implicit fee of the manager’s active decisions (active share) relative to a benchmark and ask ourselves whether we think that(...) Integrated Value, Growth and Quality Portfolios [Factor Research]Integrated Value, Growth & Quality portfolios generated attractive returns year-to-date 2017 Sorting stocks on several characteristics results in relatively smooth performance Mitigates the issue of factor timing, but not of factor selection INTRODUCTION Year-to-date 2017 is shaping up as a(...) Application of Machine Learning Techniques to Trading [Auquan]Auquan recently concluded another version of QuantQuest, and this time, we had a lot of people attempt Machine Learning with our problems. It was good learning for both us and them (hopefully!). This post is inspired by our observations of some common caveats and pitfalls during the competition when(...) Trend Following Strong in October [Wisdom Trading]October 2017 Trend Following: UP +7.12% / YTD: -15.39% Below is the full State of Trend Following report as of last month, which saw our trend following index post a strong positive performance. Performance is hypothetical. Chart for October: Wisdom State of Trend Following - October 2017 And the(...) The Herd Effect in Financial Markets [Quant Dare]Often in financial markets, as in our daily life, we imitate the decisions of predecessors, instead of analysing available information and making our own decisions. This decision imitation could lead to collective hysteria, and investment calls may be influenced by these panicked situations. Imagine(...) Tactical Asset Allocation in October [Allocate Smartly]This is a summary of the recent performance of a wide range of excellent tactical asset allocation strategies. These strategies are sourced from books, academic papers, and other publications. While we don’t (yet) include every published TAA model, these strategies are broadly representative of(...) The ABCs of creating a mean reversion strategy – Part 2 [Alvarez Quant Trading]This post is the continuation of the steps for creating a mean reversion strategy from the first part of The ABCs of creating a mean reversion strategy – Part 1. You can also listen to part 2 of my interview on Better System Trader here. A quick recap of the topics covered in part 1. I covered(...) What Will We Talk About at the Evidence-Based Investing Conference This Year? [Alpha Architect]ack and I will be attending the Evidence-Based Investing Conference tomorrow in NYC. We’re excited to participate and be part of the crowd. Be sure to give us a holler — love to discuss whatever is on your mind! Author rendering of the scene at EBI Historically, the conversations at EBI can end(...) Do Portfolio Factors or Characteristics Drive Expected Returns? [Alpha Architect]This article examines a somewhat over-looked, but important, discussion that raged among academic researchers in the late 1990’s and early 2000’s. The topic: factors versus characteristics. What do you mean, “Factors versus characteristics?” We often highlight that the value premium can be(...) Trading Using Decision Tree Classifier Part 1 [Quant Insti]The strategy in this blog will cover no normal technical indicators, but some of my own creation. Also, we will see the difference between strategy performance on test and train data along with respect to the changes in the size of the train data and the prediction length. Unlike in my previous(...) Alternative Data: The Next Frontier of Quant? [Flirting with Models]The world is awash with new data. Satellite imagery, shipping manifests, agricultural sensors, and more can provide untapped insights. To understand how investors might benefit, we decompose investment strategies into three pieces: systematic rules, idiosyncratic decisions, and randomness. We(...) Resist the Siren Call of High Dividend Yields [Factor Research]Buying high yielding and selling low yielding stocks has been an attractive strategy since 2000 However, it has been a highly unattractive strategy over the last century Investors should resist the Siren call of high yielding stocks and focus on other factors INTRODUCTION The search for yield has(...) Launching My Subscription Service [QuantStrat TradeR]After gauging interest from my readers, I’ve decided to open up a subscription service. I’ll copy and paste the FAQs, or my best attempt at trying to answer as many questions as possible ahead of time, and may answer more in the future. I’m choosing to use Patreon just to outsource all of the(...) Academic Research Insight: Sin Stocks May Earn a "Boycott" Risk Premium [Alpha Architect]In this study, a two-factor risk model is developed assuming differing preferences for “sin” or “no-sin” stocks for two groups of investors. Social screens are built into the model by assuming a small percentage of investors are self-restricting, declining to invest in “sin” stocks.(...) Information In Volatility Structure [Tr8dr]In the prior post Information In Volatility Structure [1] applied the SABR model to fit noisy raw option price data of approximatelty 700 million prices across a 10 year history of 2700 stocks. The point was to examine a hypothesis: does supply / demand imbalance in the options market express in(...) Broken Wing Butterfly Price and Volatility - CDN [DTR Trading]In the last two posts (here, and here), we looked at how implied volatility (IV) and price of the option strikes in two broken wing butterfly (BWB) strategies changed with time. In this post, we'll look at another BWB strategy, the centered delta neutral (CDN) BWB. In this strategy, the short(...) Autumn Readings about Factor Investing [Quantpedia]Factor returns, net of changes in valuation levels, are much lower than recent performance suggests. Value-add can be structural, and thus reliably repeatable, or situational—a product of rising valuations—likely neither sustainable nor repeatable. Many investors are performance chasers who in(...) Podcast: Building Mean Reversion trading strategies with @AlvarezQuant - Part 2 [Better System Trader]And we’re back for the 2nd episode in this 3-part series on building Mean Reversion strategies with Cesar Alvarez from Alvarez Quant Trading. In the first episode we discussed the goal of Mean Reversion trading, how to select a trading universe, a number of effective techniques to measuring Mean(...) HillClimber.ai: A New Machine Learning Mashup from Long-Time Quantocracy Contributor @JacquesQuantHillClimber.ai is a curated machine learning mashup inspired by the quantitative finance blog aggregator Quantocracy. A special shout-out to Mike for all the help he provided in setting up this website. This mashup is very new and I would welcome all feedback from the community. There are many good(...) Replicating Indexes In R With Style Analysis (Part II): Global Macro [Capital Spectator]Imitation, Oscar Wilde famously observed, “is the sincerest form of flattery that mediocrity can pay to greatness.” The observation echoes the objective for using Professor Bill Sharpe’s style analysis to replicate investment indexes that, for one reason or another, can’t be purchased(...) Updating Historical Data Using Oanda's API and R [Dekalog Blog]Following on from my previous post about downloading historical data, this post shows how previously downloaded data may be updated and appended with new, more recent data without having to re-download all the old data all over again. The main function to do this, HisPricesDates, downloads data(...) Want to Learn More About Factor Investing? Read This. [Alpha Architect]Replicating Anomalies is arguably a “must read” for anyone who thinks about factor investing and is looking to improve their understanding of the space. Lu Zhang, and his colleagues, Kewei Hou and Chen Xue, spent nearly 3 years carefully compiling and replicating 447 “anomalies” identified(...) How universities are failing finance students [Mathematical Investor]One of us (Marcos Lopez de Prado) has been interviewed on the topic of educational training in the finance field by Institutional Investor. A brief synopsis of this interview is below. The full article is HERE. How Universities Are Failing Finance Students With investment shops fighting over(...) Takeaways from a Non-PHD who Powered Through a 144-page Factor Investing Paper [Alpha Architect]Wes recently challenged me with a unique proposition: Hey Ryan, read through this Replicating Anomalies paper and tell me what you think. Its a bit long, but I’m curious to hear your thoughts. Well, by “a bit long,” Wes really meant 144 pages of equations and reams of quantitative data on(...) Meta Strategy: A Smart Approach to Combining TAA Strategies [Allocate Smartly]We’re very excited for the launch of an awesome new feature for our members: Meta Strategy. We track a wide range of published tactical asset allocation strategies in near real-time (40 and counting), which members can then combine into their own custom portfolios. Our platform helps members(...) ReSolve's Buffett Bet Portfolio Based on Risk Parity and Factors [Invest Resolve]Note: This is not an official bet. We’re not interested in documenting all the potential details that would be involved, and we don’t have $1million to wager. Moreover, licensed firms are not allowed to make public fund recommendations, so the details of an official bet would have to be private(...) Are Equity Multifactor ETFs Working? [CXO Advisory]Are equity multifactor strategies, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider seven ETFs, all currently available (in order of decreasing assets): Goldman Sachs ActiveBeta U.S. Large Cap Equity (GSLC) – holds large U.S. stocks based on good value, strong(...) The Return of Free Data and Possible Volatility Trading Subscription [QuantStrat TradeR]This post will be about pulling free data from AlphaVantage, and gauging interest for a volatility trading subscription service. So first off, ever since the yahoos at Yahoo decided to turn off their free data, the world of free daily data has been in somewhat of a dark age. Well, thanks to(...) Stick to the Fundamentals and Discover Your Industry Peers [Alpha Architect]When performing multiple-based valuations, which rely on the assumption that perfect substitutes should sell for the same price, it is very important to identify companies that are truly comparable. Most analysts use industry classifications. Lee et al. (2015) note that industry classifications are(...) A Potential Winner: Buying Lottery Stocks with Low Short Interest [Alpha Architect]Kelley Bergsma & Jitendra Tayal A version of this paper can be found here Want to read our short summaries of academic finance papers? Check out our Academic Research Insight category. What are the research questions Using data from CRSP and Compustat from 1989 to 2015 the research team(...) Factor Returns: Small vs Large Caps [Factor Research]A frequent criticism of factor investing is that factor returns are stronger in small caps Our research highlights that this is not uniformly true across factors Value and Size benefit most from including small caps INTRODUCTION Factor investing can be challenged in many ways. Nearly all of the(...) Would You Invest in A Coin Flip? [Flirting with Models]For active strategies, investors often focus on the potential outperformance the strategy can create. Beyond the potential for outperformance, active strategies also introduce tracking error: extra volatility that comes from active decisions. While most view tracking error as a negative, if derived(...) Tail Risk in Term Structure Based Strategies in Commodities [Quantpedia]In this paper I document that carry trades in commodity markets are subject to potential large and infrequent losses, that is, tail risk. Also, I show that shocks to carry trades and volatility have persistent tail-specific effects which last from four to twelve weeks ahead. The main empirical(...) The ABCs of creating a mean reversion strategy – Part 1 [Alvarez Quant Trading]I was recently interviewed on Better System Trader, click here for part one of the interview, about the steps for creating a stock mean reversion strategy. I will be covering and expanding on the topics from the interview. These steps, for the most part, would apply to any strategy one is creating.(...) Trend-Following: A Deep Dive Into A Unique Risk Premium [Alpha Architect]Trend-following strategies have historically been laughed at via the modern academic finance research community. Having first-hand knowledge of that community, we can verify that academic researchers are humans like the rest of us (we checked, academics aren’t robots), and they suffer from group(...) QSTrader: A Major Update On Our Progress [Quant Start]I spoke at the Open Data Science London conference last weekend on the topic of becoming a quant. Part of the talk was aimed at educating practising data scientists on the fact that quantitative finance firms do actually contribute to, and create, many open source projects. One such project is(...) Academic Research Insight: Sentiment Feedback Strength Trading Strategy [Alpha Architect]What are the research questions? Based on the evidence that tweets are faster than news in revealing new market information, but that news is regarded a more reliable source of information, the authors propose a superior trading strategy based on the sentiment feedback strength between the news and(...) Hedging Market Crashes with Factor Exposure [Factor Research]None of the factors consistently generated positive performance during recent market crashes However, almost any factor exposure would have increased the risk-return ratio of an equity-centric portfolio Low Volatility and Mean-Reversion would have been most beneficial, Momentum least INTRODUCTION A(...) Sleuthing Out Allocations [Flirting with Models]Determining the allocations of an investment strategy is often the first step in scenario analysis, sensitivity analysis, and stress testing. For a single fund or ETF, the allocations can be found on the provider’s website or in marketing materials. However, when analyzing a larger group of funds(...) Podcast: Factor Replication with Lu Zhang [Alpha Architect]Here is a link to our podcast on Behind the Markets Wes and Jeremy speak with Lu Zhang, The John W. Galbreath Chair, Professor of Finance, at the Fisher College of Business at The Ohio State University, and co-author of the paper, “Replicating Anomalies.” The team dig into the 3-year research(...) How to Predict FX Carry Profitability [Quantpedia]In this paper, we study the effectiveness of carry trade strategies during and after the financial crisis using a flexible approach to modeling currency returns. We decompose the currency returns into multiplicative sign and absolute return components, which exhibit much greater predictability than(...)