Quant Mashup 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(...) Predictive Nature Of Valuations [Larry Swedroe]As we approach the end of 2016, the Shiller CAPE 10 stands at about 28, a level rarely exceeded (with the exception of in the late-1990s technology-driven bull market). Such heights cause many investors to worry about what current valuations may mean for future expected returns. I’ll try to(...) PortfolioCharts' Golden Butterfly [Allocate Smartly]This is a test of the “Golden Butterfly”, the homegrown buy & hold strategy from PortfolioCharts.com. PortfolioCharts is to buy & hold what AllocateSmartly is to tactical asset allocation, an independent and unbiased catalog of strategy performance, so when they put their stamp of(...) Trading Strategy Series with @Quantopian: Cross-Sectional Equity Mean Reversion [Quantpedia]Quantopian & Quantpedia Trading Strategy Series continues ... Now with a 4th article, again written by Matthew Lee, focused on Cross-Sectional Equity Mean Reversion (Strategy #13):(...) Most popular posts - 2016 [Eran Raviv]Another year. Looking at my google analytics reports I can’t help but wonder how is it that I am so bad in predicting which posts would catch audience attention. Anyhow, top three for 2016 are: On the 60/40 portfolio mix The case for Regime-Switching GARCH Most popular machine learning R packages(...) Reflecting on Research in 2016 [Flirting with Models]On behalf of the entire Newfound Research team, we would like to wish you and yours a happy holiday season. We treat this weekly research commentary as a sacred part of our investment process. We continue to be honored and humbled by the vast and growing number of readers it reaches, a sign of the(...) Recommended Quant Readings for you – Best of 2016! [Quant Insti]As 2016 nears its finish line, here we are with the list of recommended reading on our blog with the top-rated blog posts, as voted by you! Enjoy the last few days doing what you love most! Read on. System Architecture of Algorithmic Trading This one is straight out of a lecture in the curriculum of(...) Mean Reversion Volatility Strategy [Milton FMR]Ever wondered if you can design a profitable trading strategy by trading volatility ETFs ? Well, yes you can. Those ETFs are highly ineffective vehicles on a long term investment horizon. However short term strategies have shown to be a rewarding way to trade these ETFs. Before we move onto strategy(...) Using Absolute Momentum to Positively Skew Calendar Year Returns [EconomPic]There are instances where I "borrow" an idea from someone (actually... most of my posts were at a minimum inspired by someone else). In this case, I am stealing the initial concept from Ryan Detrick who posted the following chart of annual U.S. stock returns going back ~200 years as there(...) Time Series Momentum, Volatility Scaling, and Crisis Alpha [Alpha Architect]If you couldn’t tell from our recent monster commodity futures post, we’ve been thinking a lot about futures recently. The futures research area is relatively “fresh,” and a lot more exciting than hacking through equity stock selection research where we already understand the basic answer(...) Applying Genetic Algorithms to define a Trading System [Quant Dare]When talking about quantitative trading, there are a large number of indicators and operators we can use as a buy/sell rule. But apart from deciding what indicator we will follow, the most important part would be setting the correct parameters. So, one method we can use to find adequate parameters(...) An Effect of Monetary Conditions on Carry Trades [Quantpedia]This paper investigates the relation between monetary conditions and the excess returns arising from an investment strategy that consists of borrowing low-interest rate currencies and investing in currencies with high interest rates, so-called "carry trade". The results indicate that carry(...) Sorting Through The Factor Zoo [Larry Swedroe]As Professor John Cochrane observed, the literature on investment factors now fills a veritable “factor zoo” with hundreds of options. How do investors select from among this huge array of possibilities? Noah Beck, Jason Hsu, Vitali Kalesnik and Helge Kostka, authors of the paper “Will Your(...) 38 DTE Iron Condor Results Summary [DTR Trading]The introduction to this series, here, described the different variations of SPX iron condors (IC) and exits that were tested at 38 days to expiration (DTE). Recall, the tests covered 9 IC variations, with short strike deltas at four locations, utilizing 12 exits. In all, there were 432 test runs (9(...) Volatility Trading Strategies, A Comparison of VRP and RY Strategies [Relative Value Arbitrage]In previous posts, we presented 2 volatility trading strategies: one strategy is based on the volatility risk premium (VRP) and the other on the volatility term structure, or roll yield (RY). In this post we present a detailed comparison of these 2 strategies and analyze their recent performance.(...) Ex-ante and Ex-post Risk Model – An Empirical Test [Alphaism]Whenever constructing a quant portfolio or managing portfolio risk, the risk model is at the heart of the process. A risk model, usually estimated with a sample covariance matrix, has 3 typical issues. Not positive-definite, which means…[not invertible] Exposed to extreme values in the sample,(...) Factor Rotation: Possible, but Worth It? [Flirting with Models]With significant research into factor rotation in 2016, we expect to see more factor rotation strategies in the market in 2017. Using six popular factors (Value, Size, Reinvestment, Operating Profitability, Momentum and Beta), we explore both switching and rotation based strategies. We find(...) Vix single day spikes & their historical returns [Voodoo Markets]Taking a look at Vix single day spikes, since there have been two rather significant and rare single day spikes of 39 and 49% in 2016. Note im not talking about Vix daily swings, but single day spikes from close to close. The intention here is to gauge how Vix has historically behaved after(...) Protective Asset Allocation [Allocate Smartly]This is a test of two variations of the Protective Asset Allocation (PAA) strategy from Wouter Keller and JW Keuning’s paper: PAA: A Simple Momentum-based Alternative to Term Deposits. The strategy is notable for its aggressive use of a “crash protection” asset that has resulted in extremely(...) An Interesting Analysis of Shiller's CAPE Ratio [Quantpedia]Robert Shiller shows that Cyclically Adjusted Price to Earnings Ratio (CAPE) is strongly associated with future long-term stock returns. This result has often been interpreted as evidence of market inefficiency. We present two findings that are contrary to such an interpretation. First, if markets(...) The Price Is Wrong [Basis Pointing]In this piece, we compare U.S. equity mutual funds’ annual expenses to our estimate of their potential future pre-fee excess returns. We demonstrate that many funds are priced to fail—their fees approach or exceed their potential future pre-fee excess returns. Whereas investors might have(...) TAA Exposure to Rising Interest Rates [Allocate Smartly]Some of the tactical asset allocation strategies that we track have significant exposure to rising interest rates, or more specifically, to the types of assets that are most negatively affected by rising rates. While we don’t (yet) track every published TAA model, the strategies that we do track(...) Asset Pricing using Extreme Liquidity with Python (Part-2) [Black Arbs]POST OUTLINE Part-1 Recap Part-1 Error Corrections Part-2 Implementation Details, Deviations, Goals Prepare Data Setup PYMC3 Generalized Linear Models (GLM) Evaluate and Interprate Models Conclusions References part-1 recap In part 1 We discussed the theorized underpinnings of Ying Wu of Stevens(...) Betting on Perfection [EconomPic]Just how perfect do circumstances need to be going forward for an investor in the S&P 500 to make money? Let's take a look at one measure. The first chart plots forward 10-year returns for the S&P 500 at various 5 point "CAPE" valuation buckets (i.e. less than 10x P/E all the(...) Machine Learning for Stock Market Prediction: Global Indices [Keith Selover]When applying Machine Learning tools to market prediction, the internet is saturated with academic papers and lacking in practical code examples. In this post, it’s my goal to translate one such paper from text to code. Mark Dunne’s Undergraduate Thesis, “Stock Market Prediction“, approaches(...) Timing the Stock Market with the Shiller CAPE [iMarketSignals]The Shiller CAPE (cyclically adjusted price-earnings ratio) is typically regarded as a stock market valuation measure. When the CAPE is high stocks are supposed to be expensive, and vice-versa. The CAPE itself is not a good stock market timer. However, the CAPE can indirectly be used for market(...) A Dynamic Approach to Factor Allocation [EconomPic]ETF Trends (hat tip Josh) showed the following "quilt" of large cap factor calendar year returns in the post Low Volatility is Not a Buy and Hold Strategy. Author John Lunt's takeaway (bold mine): It is reasonable to conclude that low volatility is not a buy and hold strategy. This is(...) The Ghost of GDP Past [Flirting with Models]Summary Economic growth is a key driver of long-term stock and bond returns. Economic growth comes from two main sources: demographic changes (i.e. increases in the number of workers) and productivity growth (i.e. each worker producing more output). Historically, approximately 55% of growth has(...) Interest Rates and Value Investing [Alpha Architect]There is still no value in bonds today. Many readers just had a knee-jerk reaction and they’ve determined that I fall into one of two categories: A total idiot A total genius But let’s dig a bit deeper into the claim that bonds lack “value,” even with this quarter’s 85 basis point back-up(...) Hacking True Random Numbers in Python: Blockchain Miners [Quant at Risk]The magnitude and importance of random numbers in finance does not have to be explained. We need them. Either it is an option pricing or a Monte Carlo simulation, random numbers are with us. However, we make a trade-off: the speed in their generation versus uniqueness. That is why a widely accepted(...) The… Most… Wonderful… Weeeeek… Of…The… Yeeeaaaarrrrr!! [Quantifiable Edges]Over several time horizons op-ex week in December has been the most bullish week of the year for the SPX. The positive seasonality actually has persisted for up to 3 weeks. I’ve shown the study below in the blog many times since 2008. It looks back to 1984, which was the first year that SPX(...) Cryptocurrencies and Machine Learning with @BMouler [Better System Trader]As markets become more mature and more efficient, it can be become increasingly difficult to find sustainable edges. Many traders are looking at the same data and using the same techniques, so what are our options here? 2 of the obvious options we have are: Try to find a unique approach to the(...) Sources of Return for CTAs - A Brief Survey of Relevant Research [Quantpedia]This survey paper will discuss the (potential) structural sources of return for both CTAs and commodity indices based on a review of empirical research articles from both academics and practitioners. The paper specifically covers (a) the long-term return sources for both managed futures programs and(...) Reading Fundamental Data from Yahoo Finance [Copula.de]Recently I read a blogpost and someone was recommending the book "DIY Financial Advisor "by Wesley R. Gray, Jack Vogel and David Foulke. I believe it was the QuantStrat blog but I might be wrong. The book is a good read and also suggest a couple of simple systems any investor can implement(...) Research Review | 8 Dec 2016 | Volatility & Risk Management [Capital Spectator]How Should Investors Respond to Increases in Volatility? Alan Moreira (Yale University) andn Tyler Muir (UCLA) December 2, 2016 They should reduce their equity position. We study the portfolio problem of a long-horizon investor that allocates between a risk-less and a risky asset in an environment(...) You Probably Can't Lose [Cantab Capital]What can an interesting and surprising experiment with finance students and finance professionals tell us about financial decisions and how to maximise extracting returns from low information content systems? Introduction It is well known that humans are bad at estimating probabilities. We(...)