Quantocracy

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Quantocracy’s Daily Wrap for 03/01/2016

This is a summary of links featured on Quantocracy on Tuesday, 03/01/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Server -I- Intro [Algorythmn Trader]

    In my previous posts I was talking about my experience learning the basics of service oriented applications. After many days and nights struggling with all the theory, practicing and trying different concepts and libraries, it forced me to go two steps back and watching the whole big picture of all. This post will be about my starting point and will be the base for many upcoming posts. The
  • Some New Developments In Volatility Calculations [Only VIX]

    If you're working with daily data (without access to intraday data) and need to calculate volatility, then using close-to-close squared returns is by far not the best way to go. Trades and quants know that it is a very noisy metric, and come up with few work-arounds. In this post I will do a very quick review of some available options, as well as new developments. I am not planning a thorough
  • A Book Review of Adaptive Asset Allocation from @GestaltU [QuantStrat TradeR]

    This review will review the Adaptive Asset Allocation: Dynamic Global Portfolios to Profit in Good Times and Bad book by the people at ReSolve Asset Management. Overall, this book is a definite must-read for those who have never been exposed to the ideas within it. However, when it comes to a solution that can be fully replicated, this book is lacking. Okay, its been a while since I

Quantocracy’s Daily Wrap for 02/29/2016

This is a summary of links featured on Quantocracy on Monday, 02/29/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Growth is not “Not Value” [Flirting with Models]

    Summary Style boxes give us the impression that "growth" and "value" sit at opposite ends of the spectrum. In reality, whether a company is growing or shrinking ("growth") is independent of whether a security is cheap or expensive ("value"). To align with the single axis expectation of "growth versus value," most index providers combine a growth
  • Tactical Asset Allocation For The Real World [Capital Spectator]

    Managing risk via tactical asset allocation (TAA) offers a number of encouraging paths for limiting the hefty drawdowns that take a toll on buy-and-hold strategies. But what looks good on paper can get ugly in the real world. There's a relatively easy fix, of course: consider the total number of trades associated with a strategy as another dimension of risk. The dirty little secret is that
  • Book Review: Adaptive Asset Allocation from @GestaltU [CSS Analytics]

    I recently read Adaptive Asset Allocation ( link to the book) by Butler, Philbrick and Gordillo of ReSolve Asset Management. The book is the culmination of research developed over the years by the ReSolve team towards the next generation approach of dynamic asset allocation. The core principles of this approach are the ability to go anywhere and adapt to changes in the economic
  • When Low Vol Becomes High Vol [Meb Faber]

    One of the most fertile areas of research is in factor rotation. Any asset class, investment strategy, or factor, despite working well over time, goes through periods of over and underperformance. Those periods set the stage for future reversion, and are largely due to fund flows and people chasing performance. Lots of the fund flows over the past # of years have gone into the marketing of low vol

Quantocracy’s Daily Wrap for 02/28/2016

This is a summary of links featured on Quantocracy on Sunday, 02/28/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    These are the best quant mashup links for the week ending Saturday, 02/27 as voted by our readers: Build Better Strategies! Part 3: The Development Process [Financial Hacker] Volatility Futures and S&P500 Performance [Blue Sky AM] New Book from GestaltU: Adaptive Asset Allocation [Amazon] Advanced Trading Infrastructure Portfolio Class [Quant Start] In Search of the Perfect Recession
  • A Statistical Arbitrage Strategy in R [Quant Insti]

    For those of you who have been following my blog posts for the last 6 months will know that I have taken part in the Executive Program in Algorithmic Trading offered by QuantInsti. Its been a journey and this article serves as a report on my final project focusing on statistical arbitrage, coded in R. This article is a combination of my class notes and my source code. I uploaded everything to

Quantocracy’s Daily Wrap for 02/27/2016

This is a summary of links featured on Quantocracy on Saturday, 02/27/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Dual Momentum and Dollar Cost Averaging [Dual Momentum]

    Last month a millennial emailed me saying he liked my book. But he wondered if the outperformance of dual momentum would disappear if he used dollar cost averaging (DCA) because he would not be able to buy cheaply during bear markets. This is because dual momentum reduces bear market drawdowns. I showed him logically that he would actually end up with more shares at a lower average cost by using
  • Python in Singapore: Intensive Workshop (Apr 7, 2016) [Quant at Risk]

    About this Course Our Python 1-day intensive course is addressed to all who wishes start programming in Python language straight away! We will cover the fundamentals of Python (2.7, 3.5), numerical aspects of coding, and over 100 individually crafted examples covering various applications coming from finance, data analysis, statistics, science, and research. Every participant will receive a free

Quantocracy’s Daily Wrap for 02/26/2016

This is a summary of links featured on Quantocracy on Friday, 02/26/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Ranking Global Stock Markets On Valuation [Meb Faber]

    A question When an overvalued security continues rising in price, does that mean the valuation indicator is broken? If you listen to many investors, the answer would be yes. An oft-repeated phrase I hear goes something like: ABC valuation indicator has been flashing expensive since XX/XX date. But the stock has gone up 900%! Therefore, ABC value indicator is broken. Is that
  • How Can Smart Beta Go Horribly Wrong? [Research Affiliates]

    Key Points 1. Factor returns, net of changes in valuation levels, are much lower than recent performance suggests. 2. Value-add can be structural, and thus reliably repeatable, or situationala product of rising valuationslikely neither sustainable nor repeatable. 3. Many investors are performance chasers who in pushing prices higher create valuation levels that inflate past performance,
  • Volatility Threatens Discipline [Larry Swedroe]

    This is my fourth article in a series devoted to helping investors stay disciplined in the face of market volatilityand even lengthy periods of underperformance by risky assets. The first was a December 2015 post dealing with what I call investment depression. The second was a January post designed to help investors deal with the worst-ever five opening trading days to a year for the

Quantocracy’s Daily Wrap for 02/23/2016

This is a summary of links featured on Quantocracy on Tuesday, 02/23/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 02/22/2016

This is a summary of links featured on Quantocracy on Monday, 02/22/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book from GestaltU: Adaptive Asset Allocation: Dynamic Global Portfolios to Profit in Good Times – and Bad [Amazon]

    Build an agile, responsive portfolio with a new approach to global asset allocation Adaptive Asset Allocation is a no-nonsense how-to guide for dynamic portfolio management. Written by the team behind Gestaltu.com, this book walks you through a uniquely objective and unbiased investment philosophy and provides clear guidelines for execution. From foundational concepts and timing to forecasting and
  • Volatility Futures and S&P500 Performance [Blue Sky AM]

    Do Volatility Futures Provide Useful Information for Future S&P500 Performance? Volatility or VIX Futures are based on the S&P500 index and are calculated from the implied volatility of different option strike prices across different expiration periods. In contrast to the VIX index, VIX Futures represent forward expectations for volatility as well as the demand for insurance against tail
  • Alpha is not a risk management technique [Flirting with Models]

    Investors often focus their analysis on benefits. In the finance industry, weve distilled this down to a single metric: alpha. Benefits and risk require separate analysis. Increasing benefits does not necessarily reduce risk or even leave it unchanged. In practice, increasing alpha can actually increase risk in many portfolios. We would like to tip our hats to N.N. Taleb, whose recent writings
  • Advanced Trading Infrastructure – Portfolio Class [Quant Start]

    In the previous article in the Advanced Trading Infrastructure series I discussed and presented both the code and initial unit tests for the Position class that stores positional information about a trade. In this article we will consider the Portfolio class, used to store a list of Position classes, as well as a cash balance. In the last month I've made a lot of progress on QSTrader, the
  • Choosing your risk [Quants Portal]

    Risk is not a simple entity, it comes in many flavours, and requires respect and consideration even when you least expect. If one was to try totally avoid risk in their market endeavours they would most likely just be holding cash where are the returns in that? The truth is that in almost all circumstances one must take at least some form of risk to have the chance of potentially

Quantocracy’s Daily Wrap for 02/21/2016

This is a summary of links featured on Quantocracy on Sunday, 02/21/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Best Links While I Was Away [Quantocracy]

    Ive been off the beaten path for the last few weeks in East Africa, so Im long overdue one of these best of posts. Below are the best quant mashup links while I was away, as voted by our readers: Stock Market Prices Do Not Follow Random Walks [Turing Finance] Fitting time series models to the forex market: are ARIMA/GARCH predictions profitable? [Robot Wealth] A Quants Approach to
  • Genotick and UPRO [Throwing Good Money]

    That graph looks like a bunch of spaghetti, I realize. But Ill explain! Im back testing Genotick. Its an open-source machine-learning java script. Probably to the developers dismay, Im always throwing things at it to make it break. Much like a small child throwing a temper tantrum, but with stocks. The previous version of the software had an added feature, which allowed for
  • In Search of the Perfect Recession Indicator [Philosophical Economics]

    Given the downturn in the energy sector and the persistent economic weakness abroad, investors have become increasingly focused on the possibility of a U.S. recession. In this piece, Im going to examine a historically powerful indicator that would seem to rule out that possibility, at least for now. The following chart (source: FRED) shows the seasinally-adjusted civilian unemployment rate in

Quantocracy’s Daily Wrap for 02/20/2016

This is a summary of links featured on Quantocracy on Saturday, 02/20/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • A simple statistical edge in SPY [Trading with Python]

    I've recently read a great post by the turinginance blog on how to be a quant. In short, it describes a scientific approach to developing trading strategies. For me personally, observing data, thinking with models and forming hypothesis is a second nature, as it should be for any good engineer. In this post I'm going to illustrate this approach by explicitly going through a number of
  • Technologies Screening -III- [Algorythmn Trader]

    In my previous post, I introduced the messaging topic. Now its time to talk about what I found on the message framework universe. To get a overview about past and upcoming topics, please have look here: Content++. There were several message frameworks I was come across and played around. The first was of course WCF comes as part of .Net and C#. This is a very convenient way to handle all the
  • Chasing Returns and Avoiding “Spaghetti against the Wall Fund Companies” [Alpha Architect]

    Psychology research suggests that when we make predictions, we suffer from representative bias, and mistakenly overweight observations that fit a particular narrative, and fail to consider base rate probabilities. For example, if we flip a coin 5 times and it shows up H, H, H, H, H, we may assume that Hs is more likely, even though the probability is still 50/50. Consider a more tangible
  • Using Heavy-Tailed Distributions with TASI: Student t Distribution [Bayan Analytics]

    In this post, I continue trying to fit the daily log returns of TASI index using heavy-tailed distributions. In the previous post, I used Pareto distribution to model TASI indexs left tail. In this post, I use Student t distribution. Recently, Student t distribution has been used widely by financial engineers as models for heavy-tailed distribution such as the distribution of financial

Quantocracy’s Daily Wrap for 02/18/2016

This is a summary of links featured on Quantocracy on Thursday, 02/18/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Low Volatility vs. High Volatility Days [Throwing Good Money]

    I read a blog post recently that began suppose you have a trading system that works well on low-volatility days and I thought, hmm. Is that a thing? Is there an edge to low-volatility days vs high volatility days? Lets turn this blog post into a speculators version of Dude, What Would Happen? The parameters: SPY, baby! From 2000 through 02/16/16. A low volatility day is
  • Make Volatility Your Friend (By Limiting Downside Volatility) [EconomPic]

    Josh Brown (i.e. The Reformed Broker) recently shared the aptly titled post How to Make Volatility Your Bitch highlighting how dollar cost averaging into a volatile market can lead to higher overall returns: Door number one you spend 15 years putting $1000 into an investment every month for 15 years, with the possibility of seeing that investment get cut in half twice. Door number two you
  • A Quant’s Approach to Building Trading Strategies: Part Two [Quandl]

    This is the second part of our interview with a senior quantitative portfolio manager at a large hedge fund. In the first part, we covered the theoretical phase of creating a quantitative trading strategy. In this part, we cover the transition into production. You can read the first part of the interview here. What does moving into production entail? For starters, I now have to worry about
  • Are Low-Volatility Stocks Expensive? [Quant Dare]

    The world of finance is no stranger to fashion and Low volatility equity investing has recently attracted serious interest from the investment community. Its popularity has led to doubts regarding the valuation level for this overcrowded arena. Just look at the current market caps of the most representative ETFs of the low volatility anomaly. If we highlighted the best known, in 2011 they began
  • What’s All The Fuss About [Systematic Relative Strength]

    If you own last years laggards you are probably wondering what all the fuss over the market is about. It has been tough sledding for the leaders so far this year as they have underperformed the laggards by quite a bit. In one of the models we track, the laggards moved in to positive territory with yesterdays price action! We track a model of the S&P 500 Sub-Industry Groups that is broken
  • New R/MATLAB Package Released: High Frequency Price Estimators & Models [Portfolio Effect]

    We are happy to announce PortfolioEffectEstim toolbox availability for both R & MATLAB. It is designed for high frequency market microstructure analysis and contains popular estimators for price variance, quarticity and noise. For R https://cran.r-project.org/web/packages/PortfolioEffectEstim/ Or via downloads section: https://www.portfolioeffect.com/docs/platform/quant/tools/r For MATLAB