Quant Mashup A Closer Look At Growth and Value Indices [Flirting with Models]In a commentary a few weeks ago entitled Growth Is Not “Not Value,” we discussed a problem in the index construction industry in which growth and value are often treated as polar opposites. This treatment can lead to unexpected portfolio holdings in growth and value portfolios. Specifically, we(...) How Changing our Brand Supercharged Our Growth on Twitter [Quantocracy]This is not quant related, but I found it interesting and thought it worth sharing for the benefit of our friends in the quant blogosphere. Long-time readers remember that we rebranded from The Whole Street to Quantocracy at the start of April, 2015. The rebranding came with changes to our site, but(...) Lossless Compression Algorithms and Market Efficiency? [Turing Finance]In Hacking The Random Walk Hypothesis we applied the NIST suite of cryptographic tests for randomness to binarized daily market returns. Overall the NIST suite failed on the data. This result was taken to mean that markets are not quite the "coin flipping competition" famously posited by(...) QuantStart April 2016 News [Quant Start]This is a quick update to let the QuantStart community know what has been happening in the last few months as it has been an exciting time "behind the scenes" of the site. Firstly, I spoke at the Quantopian QuantCon conference in New York last week. The conference was absolutely fantastic,(...) Should We Embrace the "Dark Side" of Factors? [Flirting with Models]Factors are a way to identify unique alpha sources. Factors often have a “light” and “dark” side. While the light side is expected to outperform the dark side, often the light side also outperforms the market and the dark side underperforms the market. The outperformance and underperformance(...) Are R^2s Useful In Finance? [QuantStrat TradeR]This post will shed light on the values of R^2s behind two rather simplistic strategies - the simple 10 month SMA, and its relative, the 10 month momentum (which is simply a difference of SMAs, as Alpha Architect showed in their book DIY Financial Advisor. Not too long ago, a friend of mine named(...) Probability of Black Swan Events at NYSE [Quant at Risk]The prediction of extreme rare events (EREs) in the financial markets remains one of the toughest problems. Firstly because of a very limited knowledge we have on their distribution and underlying correlations across the markets. Literally, we walk in dark, hoping it won’t happen today, not to the(...) Interview with Nitesh Khandelwal of @QuantInsti [Better System Trader]Backtesting and execution are such key parts of algorithmic trading so choosing the wrong platform can have a huge impact on our trading. There are loads of trading platforms available and a lot of considerations which need to be made when choosing one that suits our needs, so in this episode(...) Benchmarks – why using a Buy-Hold strategy as a benchmark is probably doing it wrong [Open Source Quant]Comparing a strategy’s performance to a Buy-and-Hold strategy is quick and easy. But there is a good chance it might not be appropriate and adds as much value as the time it took to research…zero. So when i see an article comparing a particular strategy to its Buy-and-Hold equivalent dating back(...) Benchmark Plus [Systematic Investor]To install Systematic Investor Toolbox (SIT) please visit About page. The overlay strategy is the market neutral strategy that can be applied to benchmark to improve benchmark's performance. The new strategy weights are equal to benchmark weights plus the overlay weights. Below I will present a(...) Taleb: Silent Risk, Section 1.3 [Blue Event Horizon]Towards the end of this section, Taleb inserts a sidebar as follows: Consider the right tail K^{+}\in \mathbb{R}^{+} and the left tail K^{-}\in \mathbb{R}^{-} . Without specifying the support of the distribution: Definition 1.3 (Probability swamps payoff (thin tails)). \lim_{K^{+ }\rightarrow\infty(...) You can't beat all the chimps [Following the Trend]It is a long established fact that a reasonably well behaved chimp throwing darts at a list of stocks can outperform most professional asset managers. While there would be obvious advantages with hiring chimps over hedge fund traders, such as lower salaries and better manners, there are also a few(...) The 5 Mistakes Every Investor Makes [Meb Faber]The 5 Mistakes Every Investor Makes is a recent book I read by Peter Mallouk, the #1 Investment Advisor in America. (I’m not poking fun, that’s just what it says on the cover.) In general it is an easy to read book that it quite reasonable it its advice, and you can get a free copy from their(...) Upcoming Panel Appearances [Flirting with Models]Justin and I will be speaking on panels in New York City in May. May 3rd – 3:10pm – Princeton Club in New York I will be sitting on a panel titled Advancements in Asset Allocation at WealthManagement.com's BUILD conference. Here is a quick description of the panel: The level of(...) My experience dealing with Zorro’s support team [Robot Wealth]Disclaimer: I am not posting this at the behest of the developers of Zorro, nor do I receive any form of payment or commission for this post. I felt that I should relay this experience because it was an example of customer service that went way above and beyond the call of duty in terms of its(...) The “SPY RSI No Lie” Swing Trade System [Throwing Good Money]Here’s a free system for you. I call it the “SPY RSI No Lie” system. It’s called that because I like stupid titles, and internal rhymes are an added plus. I read a post on Jeff Swanson’s System Trader Success recently about using a short-period RSI value to trigger trades with the S&P(...) Relative Strength Index (RSI) Analysis [Alvarez Quant Trading]Recently I have been researching longer term hold strategies. I wondered which indicators by themselves would show an edge 3 to 6 months out. I am not looking to create a strategy from the indicator alone but want to know is there a statistical edge with it. Naturally, I started with my favorite(...) The Changing Generations of Financial Data [Quandl]As quants, we’re all aware that every model has a shelf-life. Sooner or later, the ideas and techniques behind every “proprietary” analytical technique diffuse into the broader world, at which point that technique is no longer the source of a competitive edge or alpha. What’s less well(...) Equity Supply/Demand Indicator [Largecap Trader]I read a very interesting post from AlephBlog which led me to another blog called Philosophical Economics. It’s a long and in depth article I had to read a few times to understand but the basic gist of it is that when investors are under allocated to equities, future returns are better than when(...) Market Timing Factor Premiums: Exploiting Behavioral Biases for Fun and Profit [Flirting with Models]Justin and I submitted a paper for the NAAIM Wagner 2016 competition. Unfortunately, it didn't place. The good news is that we can share it with everyone that much earlier! The paper is about trying to time factor premiums using the same behavioral biases that we believe cause them. Here is the(...) Volatility is a value factor [Factor Investor]In my previous post, I looked at the historical performance of investing in low volatility stocks and identified that outperformance from the factor tends not to be very consistent over time, but is instead clustered. That raised some questions on whether volatility is a true investment factor, or(...) What You Pay Matters Less than What You're Paying For [EconomPic]Patrick O’Shaughnessy has a great post, The More Unique Your Portfolio, The Greater Its Potential, outlining how active share is what drives the level of potential before fee excess return for an active manager. If you allocate to active managers... go through it twice. As Patrick notes: If there(...) Can Twitter Predict the Market's Reaction to Fed FOMC Decisions? [Alpha Architect]Twitter seems to be a favorite dataset for financial researchers. Researchers keep trying to map tweets to profits. For example, we covered an idea related to this almost 5 years ago: Is trading with twitter only for twits? We had another post that was released about a year after our original(...) High Frequency Trading: Equities vs. Futures [Jonathan Kinlay]Pretty obviously, he had been making creative use of the "money management" techniques so beloved by futures systems designers. I invited him to consider how it would feel to be trading a 1,000-lot E-mini position when the market took a 20 point dive. A $100,000 intra-day drawdown might(...) Are 3-year track records meaningful? [Flirting with Models]Many asset management decisions are based on the three-year track record. Three-years is suspiciously close to a common rule-of-thumb for calculating statistics, but in this case, it is a misapplication. With many strategies, short-term luck swamps long-term skill. Combining strategies can reduce(...) Machine Learning and Its Application in Forex Markets - Part 2 [Quant Insti]In our previous post on Machine learning we derived rules for a forex strategy using the SVM algorithm in R. In this post we take a step further, and demonstrate how to backtest our findings. To recap the last post, we used Parabolic SAR and MACD histogram as our indicators for machine learning.(...) Registration for R/Finance 2016 is open! [FOSS Trading]You can find registration information and agenda details on the conference website. Or you can go directly to the Cvent registration page. Note that registration fees will increase by 50% at the end of early registration on May 6, 2016. The conference will take place on May 20 and 21, at UIC in(...) Testing Different Momentum Rules [Backtest Wizard]In this article I will test a variety of different momentum indicators which can be used to build a long only equity portfolio which has historically outperformed the market. To begin with, we need a baseline momentum strategy… Baseline Momentum Strategy Rank stocks in the S&P500 by order of 1(...) Momentum Rotation 60 Day ROC System Results [DTR Trading]In my last post, Yahoo Data and Momentum Rotation - Analysis of 2015 Data, the big take away was the importance of performing a full download / update of historical data before generating your signals. This is particularly important when using dividend adjusted data, which is typical for most(...) Best Links of the Last Two Weeks and a Shout-Out to Quant News [Quantocracy]The best quant mashup links for the two weeks ending Saturday, 04/09 as voted by our readers: Build Better Strategies! Part 4: Machine Learning [Financial Hacker] Momentum for Buy-and-Hold Investors [Dual Momentum] A Monte Carlo Simulation function for your back-test results – in R [Open Source(...) Alpha or Assets [Investor's Field Guide]More and more investors are buying “factor” based strategies which invest using measures like valuation and low volatility, but the most popular strategies are applying factors in the wrong way. Strategies should be built for alpha, not scale—but the asset management industry has gone in the(...) Chasing the Momentum-Burst Unicorn [Throwing Good Money]A reader of my blog, Matt B., commented recently on an old post I’d written about momentum bursts. Like me, Matt was intrigued by the short 3 to 5-day momentum bursts he saw described time and again on Pradeep Bonde’s stockbee site. Those bursts look so pretty, so elegant, and more to the point:(...) Even bad strategies will perform well [Flirting with Models]Summary Following even the best practices in investing can go against us in the short run. Volatility in short-term performance is necessary for the long run outperformance opportunity to exist. However, the opposite also holds true: a strategy that will underperform over the long run should also go(...) Bollinger Bands | Trading Strategy (Setup) [Oxford Capital]Developer: John Bollinger (Bollinger Bands®). Concept: Trend-following trading strategy based on Bollinger Bands. Research Goal: Performance verification of the 3-phase model (long/short/neutral). Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Trades: Close[i − 1] >(...) Mean reversion, momentum, and volatility term structure [EP Chan]Everybody know that volatility depends on the measurement frequency: the standard deviation of 5-minute returns is different from that of daily returns. To be precise, if z is the log price, then volatility, sampled at intervals of τ, is volatility(τ)=√(Var(z(t)-z(t-τ))) where Var means taking(...) Smart Beta: Data Mining, Arbitraged Away, Or Here To Stay? [Alpha Architect]Large institutional investors have had access to low-cost "smart beta" for many years. But for retail investors and their financial advisors, "smart beta" ETFs are a welcome innovation. Instead of trying to identify an expensive manager who can pick stocks, a retail investor can(...) Testing Asset Allocation Results With Random Market Selection [Capital Spectator]Skill is a slippery concept in finance, courtesy of the shady influence of chance in asset pricing. It's also an awkward topic in just about every corner of money management because discussing it in detail invariably raises serious doubts about our ability to engineer investment results that(...) Meet the inventor and author of dual momentum investing @GaryAntonacci [Quant Investing]As a passionate value investor it took me a long time (and a lot of research) to accept that momentum is a very important factor that you must incorporate in your investment strategy if you want high returns. Momentum simply works The simple reason is that it works. I summarised the most important(...) March Madness Portfolio Challenge: All Hail Our Champion! [Skewu]With our inaugural March Madness Portfolio Challenge in the books, we’re going to cover three very important takeaways. Takeaway #1: I mean, it wasn’t even close… Yes, in this part we pay homage to our esteemed champion, who has earned the glory due unto him by leading – more or less – the(...) State of Trend Following in March [Au Tra Sy]Following two strong months to start the year, the index was down in March, but still positive overall for 2016. Please check below for more details. Detailed Results The figures for the month are: March return: -5.90% YTD return: 5.16% Below is the chart displaying individual system results(...) How to Select the Best Commodity CTAs [Quantpedia]This study documents persistent, net-of-fees, alpha-generating commodity trading advisor funds focused on commodity investment ("Commodity Funds"). The baseline for performance measurement is a new benchmark model that includes factors established in the literature. A nonparametric(...) The Myth of Scaling Out [Throwing Good Money]A common tactic for some traders is to scale out of successful positions. The logic is this: I’ve already made some money, so I want to hold onto some of that. I’ll cash out a portion of my trade now, and see how the trade continues, but with reduced risk. You see this behavior with day traders,(...) ETF-Rebalancing Cascades [Alex Chinco]This post looks at the consequences of ETF rebalancing. These funds follow pre-announced rules that involve discrete thresholds. The well-known SPDR tracks the S&P 500, but there are over 1400 different ETFs tracking a wide variety of different underlying indexes. When any of these underlying(...) Update on the Valuation Metric Horserace: 2011-2015 [Alpha Architect]Jack and I published, “Analyzing Valuation Measures: A Performance Horse-Race Over the Past 40 Years,” in the 2012 Journal of Portfolio Management. horse race Here is a summary of the research paper on our own blog. The paper asked a simple question: “Which valuation metric has historically(...) Outliers: Looking For A Needle In A Haystack [Quant Dare]Outliers are annoying. The analysis would be easier if they did not exit. Then, why not to remove them? As libesa told us in her last post titled “Machine Learning: A Brief Breakdown”, world is going crazy with Machine Learning and now we use it in all domains. In this post, we will see another(...) Detecting Human Fear in Electronic Trading: Emotional Quantum Entanglement [Quant at Risk]This post presents an appealing proof for the progressing domination of algorithmic trading over human trading. By analysing the US stock market between 1960 and 1990, we estimate a human engagement (human factor) in live trading decisions taken after 2000. We find a clear distinction between(...) Taleb: "Problems and Inverse Problems" Follow-Up [Blue Event Horizon]In my previous post I published a bunch of R Scripts that will enable a reader of Taleb's "Silent Risk", Chapter 3, Section 3.2 "Problems and Inverse Problems" to play with the ideas he presents. I thought I should discuss one of the results those scripts produce that does(...) The case for Regime-Switching GARCH [Eran Raviv]GARCH models are very responsive in the sense that they allow the fit of the model to adjust rather quickly with incoming observations. However, this adjustment depends on the parameters of the model, and those may not be constant. Parameters’ estimation of a GARCH process is not as quick as those(...) Snake Oil and Low Volatility Investing [Factor Investor]It is estimated that 180,000 Chinese immigrated to the United States in the latter half of the 19th century; many of them worked on the Transcontinental Railroad. Deeply routed in Chinese culture, the immigrants brought with them various medicinal remedies for common ailments. It was believed that(...) Yahoo Data and Momentum Rotation - Analysis of 2015 Data [DTR Trading]I've taken a bit of a break from posting options strategy research, but before I dive back in I'm going to revisit some material I posted on Momentum Rotation systems last year. If you're new to my blog you may have missed my posts related to rotation system results and data. For the(...)