Quantocracy

Quant Blog Mashup

ST

Quantocracy’s Daily Wrap for 05/29/2016

This is a summary of links featured on Quantocracy on Sunday, 05/29/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Last Two Weeks [Quantocracy]

    The best quant mashup links for the two weeks ending Saturday, 05/28 as voted by our readers: A simple breakout trading rule (pysystemtrade) [Investment Idiocy] Some Impressions from R Finance 2016 [Revolutions] Most popular machine learning R packages [Eran Raviv] Exploring Extreme Asset Returns [Quant Dare] And in case you missed it, the latest from Quantocracy: Where Do All the Clicks Go?
  • Deep Dive into Overnight vs Intra Day Returns of S&P500 Sector ETFs [KKB Research]

    This is from a talk I gave at r/finance 2016. To start, I define the Overnight Effect as buying at the close and selling at the open, and the intraday as buying at the open and selling at the close. I applied the above strategy using the 9 sector SPDRs and assuming 2bps roundtrip transaction cost. The plot wiht XLF is shown above (Financial Sector SPDR). First and foremost lets look at the
  • Podcast: Tribute to Nelson Freeburg [Better System Trader]

    Nelson Freeburg was the editor of Formula Research, a newsletter that developed systematic timing models for the stock, bond, and commodity markets. He was also a research consultant working with institutional money managers to design proprietary timing models. Nelson had been an active trader since 1980 and occasionally spoke about his work to audiences around the world. In this episode, Linda
  • Reminiscences of R in Finance 2016 [Portfolio Probe]

    When I announced R in Finance 2016 I talked about 2 days of conference and 50 speakers. I missed out the 3 days of sleep deprivation. But a pleasant 3 days of sleep deprivation it was seeing old friends and making new ones. Im not sure that Mother Mary believed me that in our house we still use the mug from the original R in Finance. Heres proof that it still survives when so many of its

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

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