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Quantocracy’s Daily Wrap for 05/30/2016

This is a summary of links featured on Quantocracy on Monday, 05/30/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Survey of Deep Learning Techniques Applied to Trading [Greg Harris]

    Deep learning has been getting a lot of attention lately with breakthroughs in image classification and speech recognition. However, its application to finance doesn't yet seem to be commonplace. This survey covers what I've found so far that is relevant to systematic trading. Please tell me if you know of some research I've missed. Acronyms: DBN = Deep Belief Network LSTM = Long
  • Build Technical Indicators in Python [Quant Insti]

    Technical Indicator is essentially a mathematical representation based on data sets such as price (high, low, open, close, etc.) or volume of a security to forecast price trends. There are several kinds of technical indicators that are used to analyse and detect the direction of movement of the price. Traders use them to study the short-term price movement, since they do not prove very useful for
  • A Long Term Look At Memorial Week Seasonality [Quantifiable Edges]

    The week of Memorial Day has shown some interesting seasonal tendencies over the years. And for a long time it exhibited consistent bullishness. But it has faltered greatly the last several years. The chart below examines SPX performance from the Friday before Memorial Day to the Friday after it. 2016-05-30 image1 There was no substantial edge apparent throughout the 70s, but starting in 1983

Best Links of the Last Two Weeks

The best quant mashup links for the two weeks ending Saturday, 05/28 as voted by our readers:

And in case you missed it, the latest from Quantocracy:

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Votes by Clickthroughs

[click graph to enlarge]

Your votes matter to the quant community.

The graph to the right shows the average number of clickthroughs a link receives from our website (excluding RSS, Twitter and Stocktwits), broken out by the number of votes cast by our readers.

A core goal of Quantocracy is to have a positive impact on our corner of the financial world by rewarding the best work, and encouraging the best minds to keep writing.

As the graph makes clear, the citizens of Quantocracy are doing just that (way to go guys). Links with 11 or more votes receive nearly 6-times as many clickthroughs as a link with no votes (wow).

If you haven’t done so already, we invite you to register to vote and be a part of the effort. Your votes matter to the quant community.

Read on Readers!
Mike @ Quantocracy

Quantocracy’s Daily Wrap for 05/28/2016

This is a summary of links featured on Quantocracy on Saturday, 05/28/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 05/27/2016

This is a summary of links featured on Quantocracy on Friday, 05/27/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Exploring Extreme Asset Returns [Quant Dare]

    Tail or extreme assets returns have been extensively studied. In his amazing paper: Empirical properties of assets returns: stylized facts and statistical issues, Rama Cont provides a framework on statistical analysis of price variations in various types of financial markets. He presents Heavy tails in asset returns as a stylized fact, i.e., statistical properties common across a wide

Quantocracy’s Daily Wrap for 05/26/2016

This is a summary of links featured on Quantocracy on Thursday, 05/26/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Some Impressions from R Finance 2016 [Revolutions]

    R / Finance 2016 lived up to expectations and provided the quality networking and learning experience that longtime participants have come to value. Eight years is a long time for a conference to keep its sparkle and pizzazz. But, the conference organizers and the UIC have managed to create a vibe that keeps people coming back. The fact that invited keynote speakers (e.g. Bernhard Pfaff 2012,
  • Updated Dual Momentum Test [Scott’s Investments]

    I frequently get asked for updated tests on various strategies. Using Portfolio123 I ran a backtest on a Dual Momentum strategy from 1/1/2007 5/25/2016. The strategy is updated on Scotts Investments monthly, the most recent update is here. The strategy invests equally in one ETF from each of four baskets of ETFs/cash: Equities VTI, EFA, or Cash Credit Risk CIU, HYG, or Cash Real

Quantocracy’s Daily Wrap for 05/25/2016

This is a summary of links featured on Quantocracy on Wednesday, 05/25/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Forecasting the VIX to Improve VIX-Derivatives Trading [Quantpedia]

    Konstantinidi et. al. state in their broad survey of Volatility-Index forecasting: "The question whether the dynamics of implied volatility indices can be predicted has received little attention". The overall result of this and the quoted papers is: The VIX is too a very limited extend (R2 is typically 0.01) predictable, but the effect is economically not significant. This paper confirms
  • ConnorsRSI Analysis [Alvarez Quant Trading]

    A couple posts ago, I did the RSI Analysis. This post will focus on ConnorsRSI which I created while working for Larry Connors. When creating the indicator, the focus was on short-term mean-reversion results. We will look at that here but also how does it handle longer-term holds. Since I did not test this when I originally did the work, I was looking forward to seeing the results. ConnorsRSI

Quantocracy’s Daily Wrap for 05/24/2016

This is a summary of links featured on Quantocracy on Tuesday, 05/24/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A Candid Discussion with an Algorithmic Trader [Quant Insti]

    The role of Algorithm in a persons life is too substantial to be ignored. From a simple coffee-making machine to the music system in his car, from elevators to search engine like Google, all are governed by a set of logical instructions Algorithms or Algos, which enable them to respond to a persons specific requirement. With the advent of internet, Algorithmic potential has been

Quantocracy’s Daily Wrap for 05/23/2016

This is a summary of links featured on Quantocracy on Monday, 05/23/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Seasonal Effects in Equity Markets [Jonathan Kinlay]

    There are a plethora of seasonal anomalies documented in academic research. For equities these include the Halloween effect (Sell in May), January effect, turn-of-the-month effect, weekend effect and holiday effect. For example, Bouman and Jacobsen (2002) and Jacobsen and Visaltanachoti (2009) provide empirical evidence on the Halloween effect, Haug and Hirschey (2006) on the January effect,

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