Quantocracy

Quant Blog Mashup

ST
  • Quant Mashup
  • About
    • About Quantocracy
    • FAQs
    • Contact Us
  • ST

How Changing our Brand Supercharged Our Growth on Twitter

This is not quant related, but I found it interesting and thought it worth sharing for the benefit of our friends in the blogosphere.

Long-time readers remember that we rebranded this site from The Whole Street to Quantocracy at the start of April, 2015. Although the rebranding included changes to our website, nothing other than our name and profile pic changed on our Twitter feed. Both the subject of our tweets, and the way in which we formed our tweets, remained the same.

But interestingly, look at the impact of the rebranding on the number of new Twitter followers per day (dotted line marks the date of rebranding):

Followers per Day

In the seven months before the rebranding, we averaged 1.8 new followers per day or 648/year, but in the seven months after, 5.6 per day or 2038/year. That’s more than a 3-fold increase.

Note that we didn’t see even a remotely similar increase in site traffic, and we didn’t do anything radically different in terms of how we promoted the Twitter feed. In other words, the increase wasn’t the result of pushing more users to Twitter. Rather, it was a change in how the Twitter community perceived our Twitter account.

I realize that I just discovered what any first year marketing major could have told me in two seconds, but as a quant nerd, I tend not to think in these terms. The purist in me says that all that matters is the substance of what we do, but as the numbers clearly show, that’s naive.

If the goal of Quantocracy is to build and support this community of quants, then it’s also my responsibility to consider how I “market” this site. I get the heebeegeebees just using that word, but if a simple branding change means that the next amazing piece from Turing Finance, or Quant Start, or Financial Hacker, or Robot Wealth or any of the other 100+ kick ass quants included on the mashup gets more of the recognition that it deserves, then marketing becomes just as important as the substance of what we do. Lesson learned.

Mike @ Quantocracy

Filed Under: Site Announcements

Quantocracy’s Daily Wrap for 04/16/2016

This is a summary of links featured on Quantocracy on Saturday, 04/16/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 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 }E\left [ X\mid_{X> K^{+}} \right ]=K^{+}\textup{and}\lim_{K^{- }\rightarrow-\infty }E\left [

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 04/15/2016

This is a summary of links featured on Quantocracy on Friday, 04/15/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 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 practical obstacles to such hiring practices. For those asset management firms unable to retain the
  • 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 benchmarks performance. The new strategy weights are equal to benchmark weights plus the overlay weights. Below I will present a very simple example. The Benchmark portfolio is a market cap weighted country portfolio. The Overlay
  • 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. (Im not poking fun, thats 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 website. The five mistakes are: Market Timing Active Trading Misunderstanding Performance and

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 04/14/2016

This is a summary of links featured on Quantocracy on Thursday, 04/14/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 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 sophistication deployed in the investment solutions made available to investors continues to evolve. Many of the
  • 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 promptness and professionalism. Credit where credit is due. I have been using the Zorro platform for

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 04/13/2016

This is a summary of links featured on Quantocracy on Wednesday, 04/13/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Changing Generations of Financial Data [Quandl]

    As quants, were 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. Whats less well appreciated is that a similar pattern applies to the world of data. Rare, unique and proprietary data
  • The SPY RSI No Lie Swing Trade System [Throwing Good Money]

    Heres a free system for you. I call it the SPY RSI No Lie system. Its called that because I like stupid titles, and internal rhymes are an added plus. I read a post on Jeff Swansons System Trader Success recently about using a short-period RSI value to trigger trades with the S&P 500. Jeffs post was more from a theoretical standpoint, as it used the SPX index (rather than a
  • 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 Relative Strength Index, RSI. Rules Test period is from 1/1/2006 to 12/31/2015. Rules in parenthesis

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 04/12/2016

This is a summary of links featured on Quantocracy on Tuesday, 04/12/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 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 abstract: When outperformance fixation leads to large inflow temptation: premiums erode, investors
  • 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 if it's positive benefits are the product of other, more robust, investment factors. Below again
  • What You Pay Matters Less than What You’re Paying For [EconomPic]

    Patrick OShaughnessy 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 is a lot of overlap between your portfolio and the market, there is only so much alpha you can earn.
  • Equity Supply/Demand Indicator [Largecap Trader]

    I read a very interesting post from AlephBlog which led me to another blog called Philosophical Economics. Its 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 they are over allocated. It utilizes the Fed Flow of Funds report to develop a ratio of the value of
  • 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 highlight that discusses the death of a hedge fund dedicated to the idea of using tweets for profit: The

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 04/11/2016

This is a summary of links featured on Quantocracy on Monday, 04/11/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 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 Quant] Even bad strategies will perform
  • 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 the risk of making investment decisions based on results driven by luck. This makes it easier to
  • 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 make the strategy look a little less appealing. On the other hand, if you had already made millions of
  • 10 Tips to Help Discretionary Traders Compete with Quants [Greg Harris]

    I've never been a discretionary trader, but I have spent the last 10 years doing quant work: modeling, information extraction, and automation. I know the areas where quantitative methods are weakest. It seems sensible for discretionary traders to focus on these areas instead of struggling in areas where quantitative methods are well-suited: 1. Don't Use Price Data Don't focus on
  • 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. Parabolic SAR indicator trails price as the trend extends over time. SAR is below prices when prices
  • 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 Chicago. Building on the success of the previous conferences in 2009-2015, we expect more than 250
  • 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 Year Rate of Change %. Buy the top 20 strongest stocks. Exit a position if the stock falls out of
  • 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 equities and ETFs. The dividend adjustments need to be reflected in the entire series for a particular
  • Connors 2-Period RSI Update For 2015 [System Trader Success]

    Here we are four months into 2016 and Ive not updated some of the more interesting articles. One of those is Connors 2-period RSI strategy. This is a very popular trading method by Larry Connors and Cesar Alvarez. We all know there are no magic indicators but there is an indicator that certainly acted like magic over several decades. What indicator is it? Our reliable RSI indicator. The

Filed Under: Daily Wraps

Best Links of the Last Two Weeks and a Shout-Out to Quant News

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 Quant]
  • Even bad strategies will perform well [Flirting with Models]
  • The case for Regime-Switching GARCH [Eran Raviv]
  • Smart Beta: Data Mining, Arbitraged Away, Or Here To Stay? [Alpha Architect]

We also welcome one blog making its first ever appearance on the mashup:

  • Taleb: “Silent Risk”, Chapter 3, Section 3.2 “Problems and Inverse Problems” [Blue Event Horizon]

* * *

A Shout-Out to Quant News

QN Screenshot

QuantNews.com

I just wanted to take a moment to give a shout-out to fellow aggregator Quant News (Twitter: @QuantNews_com).

QN makes for an excellent pairing with Quantocracy because they fill two key gaps in our mashup: academic papers and industry news. Neither has been the main focus of our site, but both are just important as the subjects we do cover. While academia can be more difficult to digest for some readers, it’s the foundation upon which many of the more practitioner-oriented articles that you find here are built.

QN is the brainchild of Greg Harris, who can also be found on his personal quant blog at GregHarris.info and on Twitter at @GFrankHarris.

I encourage the denizens of Quantocracy to integrate QN into their daily reading, and I look forward to big things from Greg in the months and years ahead.

Read on Readers!
Mike @ Quantocracy

Filed Under: Best Of

Quantocracy’s Daily Wrap for 04/10/2016

This is a summary of links featured on Quantocracy on Sunday, 04/10/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

    No new links posted.

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 04/08/2016

This is a summary of links featured on Quantocracy on Friday, 04/08/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 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 through fits of outperformance. Performance, therefore, can be a very misleading statistic when it
  • 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] > Upper_Band[i ? 1]. Short Trades: Close[i ? 1] II. Sensitivity Test All 3-D charts are followed by 2-D
  • 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 scalebut the asset management industry has gone in the opposite direction. Most factor-based strategiescommonly called Smart Betahave hundreds of
  • Chasing the Momentum-Burst Unicorn [Throwing Good Money]

    A reader of my blog, Matt B., commented recently on an old post Id 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 Bondes stockbee site. Those bursts look so pretty, so elegant, and more to the point: so profitable. My previous research felt a little like banging my head against the wall. Trading on

Filed Under: Daily Wraps

  • « Previous Page
  • 1
  • …
  • 188
  • 189
  • 190
  • 191
  • 192
  • …
  • 219
  • Next Page »

Welcome to Quantocracy

This is a curated mashup of quantitative trading links. Keep up with all this quant goodness via RSS, Facebook, StockTwits, Mastodon, Threads and Bluesky.

Copyright © 2015-2025 · Site Design by: The Dynamic Duo