Quantocracy

Quant Blog Mashup

Quantocracy’s Daily Wrap for 05/20/2016

This is a summary of links featured on Quantocracy on Friday, 05/20/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A simple breakout trading rule (pysystemtrade) [Investment Idiocy]

    Breakout. Not the classic home arcade game, seen here in Atari 2600 version, but what happens when a market price breaks out of a trading range. The Atari 2600 version was built by Wozniak with help from Jobs exactly 40 years ago. Yes that Wozniak and Jobs. Source: wikipedia In this post I'll discuss a trading rule I use to look at breakouts. This will be an opportunity to understand in more
  • Behavioral Finance Strikes Again: Contrast Effects in Markets [Alpha Architect]

    At this point, even hard core efficient market fans will likely admit that behavior can influence investment decisions. Humans arent robots. However, just because some investors exhibit bad behavior that doesnt mean they can influence prices. As the story goes, smart investors are prepared to take advantage of profitable opportunities at a moments notice, and thus, prices are always

Quantocracy’s Daily Wrap for 05/19/2016

This is a summary of links featured on Quantocracy on Thursday, 05/19/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book from The Financial Hacker (German Language) [Amazon]

    The Financial Hacker is one of the top rated bloggers at Quantocracy. Unfortunately, this book is only available in German, but for those who sprechen die Deutsch, this is a must read.
  • New Whitepaper: Why Tactical FIxed Income is Different [Flirting with Models]

    We recently updated, expanded, and put a new face on a whitepaper we had written last year called, Why Tactical Fixed Income is Different. You can access the new paper here. In the original version, we looked at some of the reasons why a simple tactical strategy that commonly works in equities (e.g. go to cash) does not always work well in fixed income. The main takeaway of the original

Quantocracy’s Daily Wrap for 05/18/2016

This is a summary of links featured on Quantocracy on Wednesday, 05/18/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimising weights with costs (pysystemtrade) [Investment Idiocy]

    In a previous post I showed you how to use my open source python backtesting package, pysystemtrade, to estimate forecast weights and instrument weights. At the time I hadn't included code to calculate costs. Now that has been remedied I thought I should also write some code to demonstrate the different ways you can optimise in the presence of costs. You can see what else has been included in
  • A Stunning New Finding: Return Seasonalities are Everywhere [Alpha Architect]

    Weve discussed return seasonalities in the past, especially as they pertain to our approach to momentum. Turns out seasonality effects arent confined to momentum they are literally everywhere and they are incredibly strong. This paper will blow your mind once you let the results settle in a bit. Source paper Slides Turns out stock returns are lumpy across the calendar. Stocks dont
  • Machine Beats Human: Machine Learning in Forex [Jon.IO]

    Machine learning and trading is a very interesting subject. It is also a subject where you can spend tons of time writing code and reading papers and then a kid can beat you while playing Mario Kart. In the nexts posts, we are going to talk about: Optimize entries and exits. This and only this could make a ton of difference in your bank roll. Calculate position size (in case you don't like
  • Which Institution Has The Best Asset Allocation Model? [Meb Faber]

    If youre like most investors, youre asking the wrong questions. I was chatting with a group of advisors this week down in La Jolla and a question arose. Ill paraphrase: Meb, thanks for the talk. We get a steady stream of salespeople and consultants in here hawking their various asset allocation models. Frankly, it can be overwhelming. Some will send us a 50-page report, all to explain
  • The State of Risk Management [Flirting with Models]

    How effective is your method of managing portfolio risk? We compare and contrast different approaches including fixed income, managed futures, low volatility equities, and tactical to explore the relative protection they can deliver versus the return drag they can create.
  • World s Simplest Trading System [UK Stock Market Almanac]

    Heres the system: At the end of every month, if the index is above its 10-month simple moving average: the portfolio is 100% in the market if the index is below its 10-month simple moving average: the portfolio is 100% in cash And thats it. So, if we take the FTSE 100 Index as an example, if at the end of a month the FTSE 100 is above its 10-month simple moving average then either, the

Quantocracy’s Daily Wrap for 05/17/2016

This is a summary of links featured on Quantocracy on Tuesday, 05/17/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Where Do All the Clicks Go? [Quantocracy]

    Its been about a year since we launched Quantocracy. Over that time, weve sent about 450,000 clickthroughs to sites in the quant community, and that doesnt even include RSS, Twitter, StockTwits and Facebook. To all of the denizens of Quantocracy: a big mahalo, gracias, ?? and thank you for helping this community to grow. But where are all those clicks going? I view this site as more
  • Not so Simple: Valuations and Low Volatility Strategies [Alpha Architect]

    Low volatility funds are everywhere. The reasons for their proliferation are clear: Who wouldnt want to own something with the label low volatility and Recent performance has been great. Open the AUM floodgates! But perhaps not all is well in low volatility land. A recent snippet by Josh Brown hints at the idea that perhaps low volatility is overdone. Charles Bilello at Pension Partners
  • Can We Predict Forward Alternative Investment Performance? [EconomPic]

    My friend Ben from A Wealth of Common Sense poses the interesting question, How Should Alternative Investments Be Benchmarked? Please go read his post for a number of interesting thoughts on that topic. In this post, rather than rehash his arguments, I'll go a different direction and will try to articulate what drives the performance of alternatives (i.e. hedge funds / liquid alts) to see if
  • Update on Attilio Meucci’s The Checklist and ARPM Bootcamp / Code [Return and Risk]

    Last week I organised for Attilio Meucci to give a webinar to members of CFA Singapore and NUS Risk Management Institute on an Introduction to The Checklist Ten Steps for Advanced Risk and Portfolio Management. It served the dual-purpose of a professional development talk and marketing of the upcoming ARPM Bootcamp on 15-20 August in NYC. The slides can be viewed online at
  • Giving Up on Recursive Sine Formula for Period Calculation [Dekalog Blog]

    I have spent the last few weeks trying to get my recursive sine wave formula for period calculations to work, but try as I might I can only get it to do so under ideal theoretical conditions. Once any significant noise, trend or combination thereof is introduced the calculations explode and give meaningless results. In light of this, I am no longer going to continue this work. Apart from the above
  • The Fine Art of Opening Range Breakout Trading [Milton FMR]

    The goal of this research is to find various set-ups and exit strategies that could be used for trading the opening range breakouts. The time frames we will be looking at are 10min, 15min and 30min opening range breakouts. We will focus our attention on the very liquid futures markets in particular we will analyze the S&P500 futures. We would like to encourage you as the reader to participate
  • Trading With Indices [Jonathan Kinlay]

    In this post I want to discuss ways to make use of signals from relevant market indices in your trading. These signals can add value regardless of whether you trade algorithmically or manually. The techniques described here are one of the most widely applicable in the quantitative analyst's arsenal. Let's motivate the discussion by looking an example of a simple trading system trading

Where Do All the Clicks Go?

It’s been about a year since we launched Quantocracy. Over that time, we’ve sent about 450,000 clickthroughs to sites in the quant community, and that doesn’t even include RSS, Twitter, StockTwits  and Facebook. To all of the denizens of Quantocracy: a big mahalo, gracias, 謝謝 and thank you for helping this community to grow.

But where are all those clicks going? I view this site as “ours” rather than “mine”, so I think a nerd data dump is in order. As we’ve shown previously, we’re rewarding quality by sending a lot more traffic to higher rated links. That’s good, but it’s only part of the story. The chart below shows the % of all clickthroughs, by recipient. I’ve highlighted a couple of important reference points, including the ten top ranked bloggers on the mashup.

Click graph to zoom. We drill down further into these numbers in the second graph at the bottom of the page.

perc_of_clicks-20160517-pie

Calculation notes: The number in parenthesis shows the number of links from that recipient. When we launched this site, we backfilled historical links from our old site, The Whole Street. Most of those links essentially never got clicked, so we required a link to be clicked at least 10 times to be included. Links on our blogroll (in the sidebar) were also included. Books in our library (as opposed to our mashup), as well as RSS and all of our social media feeds, were excluded.

Observations:

  • We’re spreading the wealth across A LOT of sites. That’s good.
  • As previously shown, higher rated links receive the most clickthroughs per link, but in terms of total clickthroughs, quantity often matters more. For example, the three highest rated bloggers on the mashup at the moment: Financial Hacker, Robot Wealth and Turing Finance, who also receive the most clicks per link, are fairly middling in terms of total clickthroughs, because they haven’t posted often.
  • As a result, when a blog is both highly rated and posts often (ex. Alpha Architect and Flirting with Models aka “thinknewfound”), they receive an outsized portion of our total clickthroughs (Alpha Architect at 6%…wow).
  • The numbers above only show Amazon clickthroughs from our mashup. 75% of clickthroughs to Amazon are from our book library or from the widget in the sidebar. That’s good, as I don’t want books to take up too much valuable real estate on the mashup itself.
  • I don’t think that a blogger should conclude from this data simply that they should post more often. There’s real, tangible differences in the “quality” of clickthroughs. Without going into details, I can anecdotally say that a number of top ranked bloggers have found significant offline success as a result of the quality of their workmanship, despite posting infrequently. I think the inverse holds true as well.

And finally, this final chart shows all recipients of at least 0.1% of total clickthroughs (i.e. everything that got a slice of the pie chart above). Some sites may now be defunct. Click to zoom.

perc_of_clicks-20160517-bar

Quantocracy’s Daily Wrap for 05/14/2016

This is a summary of links featured on Quantocracy on Saturday, 05/14/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • 52 Pick-Up and factor investing [Factor Investor]

    Remember 52 Pick-Up? A dubious sibling, usually older, would ask if you wanted to play a game while holding a deck of cards. Emphatically, you agree, only to be showered with the deck of playing cards and told to pick them up. Wikipedia in its infinite wisdom defines 52 pick up as "a game of picking up thrown cards." In a lot of ways, the market is that devious sibling. The cards are

Quantocracy’s Daily Wrap for 05/13/2016

This is a summary of links featured on Quantocracy on Friday, 05/13/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Portfolio Construction Affects Value Funds [Alpha Architect]

    Value investing is an investment philosophy that has been extensively discussed and examined at least since the days of Ben Graham, who popularized it as a discipline in the 20s and 30s. While there are some who are dismissive of its advantages as a long-term strategy, the historical evidence is compellingly clear: Cheap stocks beat expensive stocks over time (see our simulation study as an

Quantocracy’s Daily Wrap for 05/12/2016

This is a summary of links featured on Quantocracy on Thursday, 05/12/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Deep Learning with Theano – Part 1: Logistic Regression [Quant Start]

    Over the last ten years the subject of deep learning has been one of the most discussed fields in machine learning and artificial intelligence. It has produced state-of-the-art results in areas as diverse as computer vision, image recognition, natural language processing and speech recognition. However it has also been widely hyped – the answer to all machine learning problems – and is often
  • Heatmaps in R [Quant Finance Academy]

    In exploratory data analysis, we often need to visualize our data in different formats, in order to gain more understanding about the numbers and the relationship between the parameters. One such wonderful and informative representation is the Heatmap, which is basically a colored image, the colors explain the strength of the relationship between two parameters. It normally has a dendogram