Quant Mashup Risk Management with @InvestingIdiocy [Better System Trader]Risk Management… It’s not as sexy as the latest hot indicator… Or the undiscovered penny stock poised for an explosive move… Or the trading guru who appeared out of nowhere and is now promising to share the “secrets” to making million dollar profits overnight… But there are a whole(...) PutWrite vs. BuyWrite Index Differences [Quantpedia]The CBOE PutWrite Index has outperformed the BuyWrite Index by approximately 1.1 percent per year between 1986 and 2015. That is pretty impressive. But troubling. Yes – troubling – because the theory of put-call parity tells us that such outperformance should be almost impossible via a(...) Machine Learning: An Introduction to Decision Trees [Quant Insti]A decision tree is one of the widely used algorithms for building classification or regression models in data mining and machine learning. A decision tree is so named because the output resulting from it is the form of a tree structure. Visualizing a sample dataset and decision tree structure(...) Cointegrated ETF Pairs Part II [Quantoisseur]Welcome back! This week’s post will backtest a basic mean reverting strategy on a cointegrated ETF pair time series constructed using the methods described in part I. Since the EWA (Australia) – EWC (Canada) pair was found to be more naturally cointegrated, I decided to run the rolling linear(...) Forecasting Returns with Shiller’s CAPE and its 35-Year Moving Average [iMarketSignals]Shiller’s Cyclically Adjusted Price to Earnings Ratio (CAPE ratio) is at 27.8, which is 11.1 above its long-term mean of 16.7, signifying overvaluation of stocks and low forward returns. According to Jeremy Siegel it incorporates time-inconsistent data, and the failure to correct for changes in(...) Why Bayesian Variable Selection Doesn’t Scale [Alex Chinco]Traders are constantly looking for variables that predict returns. If x is the only candidate variable traders are considering, then it’s easy to use the Bayesian information criterion to check whether x predicts returns. Previously, I showed that using the univariate version of the Bayesian(...) A New Study Quantifies The Impact Of Time Horizon On Risk [Capital Spectator]Can you distinguish alpha from beta? Child’s play, right? Measure an investment portfolio against a relevant benchmark and, voila, all is clear. But as a new paper reminds, analyzing risk and return based on time horizon changes a black-and-white world of equity factors into 50 shades of gray.(...) Asset Allocation is Not for the Faint of Heart (Long Live Diversification) [GestaltU]I’m starting to feel like a rancourous curmudgeon, but I am frustrated by some of the misguided commentary on asset allocation and how diversification is a myth. We have posted a lot of research on fairly complex asset allocation topics, but I think many readers would be surprised to learn that I(...) A Tactical Asset Allocation Researcher You Should Know [Alpha Architect]I’m a huge fan of hard-core academics that produce incredible research, and yet, very few are familiar with their research. I call these folks, “undiscovered gems.” One might ask why undiscovered gems exist. On one hand, if a researcher produces incredible research, they should be widely(...) Playing with Docker - some initial results (pysystemtrade) [Investment Idiocy]This post is about using Docker - a containerisation tool - to run automated trading strategies. I'll show you a simple example of how to use Docker with my python back testing library pysystemtrade to run a backtest in a container, and get the results out. However this post should hopefully be(...) Essential Books on Algorithmic Trading [Quant Insti]These are some of the questions that popular forums get inundated with from aspiring novice algorithmic traders around the world. A good starting point for a wannabe trader would be to pick up a good book, immerse oneself, and absorb all that the book has to offer. This post details down the core(...) Paul Novell's Tactical Bond Strategy [Allocate Smartly]This is a test of a tactical bond strategy from Paul Novell of Investing for a Living. The model rotates among a broad basket of bond asset classes based on rules similar to Gary Antonacci’s Dual Momentum. Results from 1970, net of fees, follow. Read more about our backtests or let AllocateSmartly(...) Comparing Overlapping Systems (Part 2) [Throwing Good Money]In the last post, I compared three systems that traded the same instrument (SPY) in different ways, and also compared the combination of the three systems. Combining those systems reduced risk, which allowed us to increase our position size (either through more cash or using leverage). We could then(...) January Opex Struggles [Quantifiable Edges]Opex week in January is one that the market has seen some struggles over the last 18 years. Below is the list of January op-ex weeks from 1999 – 2016 with their full week performance results. There have been 7 years in which January op-ex week occurred in conjunction with Martin Luther King Day.(...) 45 DTE Iron Condor Results Summary [DTR Trading]This article looks at iron condors (IC) entered at 45 days to expiration (DTE). The introduction to this series, here, describes the different variations of SPX iron condors (IC) and exits that were tested. As mentioned in the 38 DTE IC results summary post, these tests covered 9 IC variations, with(...) Purifying Factor Premiums in Equity Markets [Quantpedia]In this paper we consider the question of how to improve the efficacy of strategies designed to capture factor premiums in equity markets and, in particular, from the value, quality, low risk and momentum factors. We consider a number of portfolio construction approaches designed to capture factor(...) A Caveat On Backtesting Caveats [Capital Spectator]Ben Carlson at Ritholtz Asset Management reminds us that backtesting offers no shortcuts to investment nirvana. As he correctly points out, there are numerous shortcomings in the art/science of reconstructing the historical results of an investment strategy. But it’s also true that backtesting, if(...) A Decade of Trend Following [Wisdom Trading]Last year was not a good year for trend following, with many commenting that the performance for the strategy has been declining over the last few years. We decided to look at the performance of the Wisdom State of Trend Following index on a long timeframe, to let the results speak over the long(...) It's 2017: Do You Know Where Your Risk Is? [Flirting with Models]Last week’s commentary highlighted why we believe traditionally built portfolios may face return headwinds going forward. Traditionally built stock/bond allocations also exhibit extremely high risk concentrations. Non-traditional exposures, now available as low-cost ETFs, can help introduce(...) Aluminum Smelting Cointegration Strategy in QSTrader [Quant Start]In previous articles the concept of cointegration was considered. It was shown how cointegrated pairs of equities or ETFs could lead to profitable mean-reverting trading opportunities. Two specific tests were outlined–the Cointegrated Augmented Dickey-Fuller (CADF) test and the Johansen(...) Cointegrated ETF Pairs Part I [Quantoisseur]The next two blog posts will explore the basics of the statistical arbitrage strategies outlined in Ernest Chan’s book, Algorithmic Trading: Winning Strategies and Their Rationale. In the first post we will construct mean reverting time series data from cointegrated ETF pairs. The two pairs we(...) The January Effect: An Evidence-Based Perspective [Alpha Architect]January is here again and market commentators are already telling stories about the so-called January Effect. Some articles (examples here and here) are saying the effect is an illusion, while others are claiming the effect can help you make some profits (examples here and here). Before we dig into(...) Go Skew Yourself with Managed Futures [Alpha Architect]Skewness is a statistical measure of how returns behave in the tails of a probability distribution. Wikipedia has a more robust definition of skewness with some good visuals here. If an investment (e.g., stocks) has negative skewness this means that the extreme returns are more likely to be negative(...) The Asymmetry of Reaching for Yield at Low Spreads [EconomPic]Bloomberg Gadfly's Lisa Abramowicz (follow her on twitter here) outlined in a recent piece The Credit Boom that Just Won't Die the insatiable demand for investment grade credit. Last month, bankers and investors told Bloomberg's Claire Boston that they expected U.S. investment-grade(...) Webinar: Alpha Generation 01/10/2017 [Portfolio Effect]Asset returns based on low frequency prices (e.g. end-of-day quotes) are still dominating modern portfolio analysis. To make portfolio metrics more relevant intraday and improve the precision of estimates, new data frequency needs to be explored. In this presentation we demonstrate how using high(...) Quantitative Momentum with Jack Vogel (@jvogs02) [Better System Trader]The guest for this episode is Jack Vogel from Alpha Architect, a quantitative asset management and consulting firm. Jack has published a number of papers on SSRN and also co-authored a couple of books including “Quantitative Momentum: a practitioners guide to building a momentum-based stock(...) Seasonalities in Stock Returns [Quantpedia]Existing research has documented cross-sectional seasonality of stock returns – the periodic outperformance of certain stocks relative to others during the same calendar month, weekday, or pre-holiday periods. A model based on the differential sensitivity of stocks to investor mood explains these(...) Advanced Time Series Plots in Python [Black Arbs]POST OUTLINE Motivation Get Data Default Plot with Recession Shading Add Chart Titles, Axis Labels, Fancy Legend, Horizontal Line Format X and Y Axis Tick Labels Change Font and Add Data Markers Add Annotations Add Logo/Watermarks MOTIVATION Since I started this blog a few years ago, one of my(...) Beat the Market with Meucci and Markowitz [Propfolio Management]I am very excited to finally share some of my research exploring Meucci’s (Meucci (2005)) portfolio optimization methods, and how the resulting portfolios compare to the use of historical data. For those unfamiliar with Attilio Meucci, he runs an annual Advanced Risk and Portfolio Managment(...) Writing Puts, Or Just Pretending To [Throwing Good Money]Which color do you like better? Green or brown? I’m partial to the green curve myself. That green curve comes from writing puts…sort of. Writing puts can be a lower volatility play that makes you money in choppy or flat markets, falls more softly in down markets, and seriously under-performs(...) Site News: Dabbling in Ads and Where All the Clicks Went in 2016 [Quantocracy]Two bits of site news: First, after 4+ years of running this site mostly gratis, I’ve decided to dabble in adding advertisements, so expect to begin seeing the first baby steps with a handful of ads from Google. I’ve tried to keep the ads as unobtrusive as possible and my hope is that your(...) Using Trend-Following Rules to Enhance Factor Performance [Alpha Architect]After reviewing the 2016 performance of trend-following (-18.15%), its unclear why anyone would mention the word “trend following” in a public forum. But we’ll give it a whirl anyway… The comedian Victor Borge once famously observed, “Santa Claus has the right idea – visit people only(...) N-Day exits with Mean Reversion [Alvarez Quant Trading]My last post on using PercentRank to measure mean reversion proved very popular. A reader looked at the trades and wondered if it would be best to exit after five days because the average trade with longer holds was a loser. I am surprised I have not covered this topic before. Background Early in(...) State of Trend Following in December [Au Tra Sy]Happy new year to all readers! With best wishes for your trading in the coming twelve months, which — I’m sure you’ll agree — will prove interesting from several perspectives. We start the year by looking back at the performance of trend following over the year just passed. Unsurprisingly(...) R/Finance 2017: Call for Papers [Foss Trading]The ninth annual R/Finance conference for applied finance using R will be held on May 19 and 20, 2017 in Chicago, IL, USA at the University of Illinois at Chicago. The conference will cover topics including portfolio management, time series analysis, advanced risk tools, high-performance computing,(...) A Modern, Behavior-Aware Asset Allocation [Flirting with Models]Happy New Year! To kick off the year, we want to share a white paper we penned mid-December containing our views on building a modern strategic asset allocation. The white paper covers: Why we believe tailwinds from the last 30 years are turning into headwinds for traditionally allocated stock-bond(...) Trend Following UP in December, Down in 2016 [Wisdom Trading]December 2016 Trend Following: UP +1.38% / 2016: -18.15% December closed 2016 on a slight positive note, avoiding six straight months of negative returns for our State of Trend Following index. An inflection point was felt in the markets towards the close of the year, but this was obviously not(...) Are you Ready to Witness Finance Research on Steroids? [Alpha Architect]The 2017 American Finance Association conference is kicking off later this week in Chicago. If you haven’t been before — check it out. The conference is the biggest meeting of top-tier academic researchers on the planet. You can review all the research being presented at the following link. Some(...) The Bayesian Information Criterion [Alex Chinco]Imagine that we’re trying to predict the cross-section of expected returns, and we’ve got a sneaking suspicion that x might be a good predictor. So, we regress today’s returns on x to see if our hunch is right, \begin{align*} r_{n,t} = \hat{\mu}_{\text{OLS}} + \hat{\beta}_{\text{OLS}} \cdot(...) 38 DTE Iron Condor Results Summary - Part 2 [DTR Trading]In the last post, 38 DTE Iron Condor Results Summary, I showed the backtest results from 97,416 iron condor (IC) trades. All of those test results were based on weekly expiration data at 38 days to expiration (DTE). In this post, we'll look at a few key metrics and how those metrics differ(...) Tactical Asset Allocation in December [Allocate Smartly]This is a summary of the recent performance of a number 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(...) Wakey, Wakey: Trends in Active Fund Pre-Fee Excess Returns [Basis Pointing]In a recent posting, I compared the prices of US active mutual fund to estimates of future pre-fee excess returns. In summary, I found that the annual expenses of most active funds met or exceeded a generous estimate of their potential before-fee excess returns. That is, many funds look like(...) Testing Momentum’s Robustness [Sharpe Returns]Happy new year! I have noticed that my quantitative posts get the most readership and discussion. So this year, I’ll be posting a lot more research and will start the year off by exploring momentum’s robustness. There are two good ways to test the robustness of a rules-based trading strategy:(...) Are Commodities Still a Good Portfolio Diversifier? [Dual Momentum]Overfitting the data is a serious problem when constructing financial models. One way to guard against this is to have lots of data. This helps you determine if your results are robust by seeing how they hold up over different time periods. But this assumes the underlying market dynamics remain(...) Statistical Arbitrage: Finding Correlated Stock Pairs (h/t Algotrading Reddit) [Above Index]Statistical Arbitrage , A.K.A StatArb is a pair trading strategy that invloves buying and selling a pair of stocks based on a underlying correlation between them. This correlation usually exist in a given sector or competitors, for example Pepsi (PEP) and Coca-Cola (KO) is a pretty popular pair. The(...) "Matt’s Breadth Indicator" Update [Throwing Good Money]Happy new year! It’s that time again, when everyone with a blog does a wrap up of the previous year. Here’s my look-back. Many of you follow along with the “+/-30% per quarter wider-market breadth indicator”. Which is too much of a mouthful, so I’ve humbly named it after myself instead. I(...) Genetic algorithm for trading in Cpp [Imanol Perez]This code tries to show how to use genetic algorithms to create a simple trading strategy. It is intended as a proof of concept, rather than trying to provide a ready-to-use strategy. The historical data used is the following: SP500.dat. It is the closing prices of S&P 500 from 2006/12/18 to(...) Backtesting the Implied Volatility Long/Short Strategy [Black Arbs]This is a stylized implementation of the strategy described in the research paper titled "What Does Individual Option Volatility Smirk Tell Us About Future Equity Returns?" by Yuhang Xing, Xiaoyan Zhang and Rui Zhao. The authors show that their SKEW factor predicts individual equity(...) Relationship Between the VIX and SP500 Revisited [Relative Value Arbitrage]A recent post on Bloomberg website entitled Rising VIX Paints Doubt on S&P 500 Rally pointed out an interesting observation: While the S&P 500 Index rose to an all-time high for a second day, the advance was accompanied by a gain in an options-derived gauge of trader stress that usually(...) Divide By 20: One Year later [Throwing Good Money]Happy New Year, one day early. Here’s wishing 2017 is successful for you in whichever way you define success. Aren’t calendars wonderful? A couple of days ago, up pops a reminder on my calendar to revisit a post I did a year ago. At the very beginning of 2016, I wrote a post on whether yearly(...)