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Quantocracy’s Daily Wrap for 08/02/2016

This is a summary of links featured on Quantocracy on Tuesday, 08/02/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Mailbag: How Do You Move From Quant Developer To Quant Trader? [Quant Start]

    I was emailed recently with a career-related question about jumping from one quant role to another. The question posed was "How can I make the jump from being a quant/software developer to a quant trader/researcher in a fund or investment bank?". This is certainly possible and does happen occasionally. However, it will require some extra-curricular work, and some initiative, in order to
  • Fine Wine is a Fine Addition to Your Investment Portfolio [Alpha Architect]

    Here we are in August, a great time to drinkand thinkabout wine. Of course, as a research-focused finance blog, our angle on wine is a bit different than that of Dr. Vino. A summary of the discussion: we estimate a real financial return to wine investment (net of storage costs) of 4.1%, which exceeds bonds, art, and stamps. Get your attention? Lets dive right in, but grab a glass of
  • Cassandra as a Historical Finance DB [Ryan Kennedy]

    While the explosion of noSQL database offerings of late can be daunting, each of them is typically suited for a particular purpose. Most CRUD web-applications can be comfortably done with either noSQL or a RDBMS, however for true high performance applications, the choice of database is of make-or-break importance. In this post I'll explain what we typically want from a database to store

Quantocracy’s Daily Wrap for 08/01/2016

This is a summary of links featured on Quantocracy on Monday, 08/01/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Using System Parameter Randomization To Estimate Future Returns [System Trader Success]

    You just spent a ton of time creating a trading system and being very careful not to over-optimize. You then tested it on the out-of-sample data segment and the performance looks good. What's next? Jump right into the live market? Maybe. But instead, you would like to perform one more test called System Parameter Randomization. The article, System Parameter Permutation a better
  • Paper: Stock Portfolio Design and Backtest Overfitting (h/t Abnormal Returns)

    We demonstrate a computer program that designs a portfolio consisting of common securities, such as the constituents of the S&P 500 index, that achieves any desired profile via in-sample backtest optimization. Unfortunately, the program also shows that these portfolios typically perform erratically on more recent, out-of-sample data, which is symptomatic of selection bias. One implication of
  • Empirical Analysis of Limit Order Books [Quant Insti]

    What is an Order book? With the growing popularity of Algorithmic and High Frequency Trading, study of order books has grown manifolds. Order book is essentially an electronic list of all Buy and Sell orders, arranged as per price time priority. This means that a person having higher price on the buy side or lower price on the sell side will get priority over others to execute the trade. If
  • Can Dividend (Swaps) Replace Bonds? [Flirting with Models]

    Summary As a stand-alone asset class, dividends may make an interesting alternative to fixed income: they offer low volatility, are generally robust to market crises, and may serve as an inflation hedge. Accessing dividend strips was previously restricted to institutional investors, using over-the-counter swaps or exchange traded futures. For retail investors today, the ETF DIVY enables access to

Quantocracy’s Daily Wrap for 07/29/2016

This is a summary of links featured on Quantocracy on Friday, 07/29/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Case for Hedge Funds / Creating an Ideal Liquid Alt [EconomPic]

    A hedge fund is simply a go anywhere investment vehicle that attempts to provide excess returns to cash with a low correlation to traditional asset classes (i.e. vehicles that provide alpha). Hedge funds and liquid alternatives have taken a lot of heat recently, much of it deserved, but in this post I'll outline the bull case. Specifically, this post will outline the benefit of a hedge fund
  • Clustering: “Two’s company, three’s a crowd” [Quant Dare]

    Its hard enough deciding which Machine Learning technique to use, but after selecting an appropriate clustering algorithm the next challenges begin: how good is the separation and into how many groups should you divide the data? Maybe three is not always a crowd First, lets set the scene We want to create a diversified investment strategy using a set of predictions and making use of

Quantocracy’s Daily Wrap for 07/28/2016

This is a summary of links featured on Quantocracy on Thursday, 07/28/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Asset Class Risk Premiums Explained by Skewness [Quantpedia]

    We present extensive evidence that "risk premium" is strongly correlated with tail-risk skewness but very little with volatility. We introduce a new, intuitive definition of skewness and elicit an approximately linear relation between the Sharpe ratio of various risk premium strategies (Equity, Fama-French, FX Carry, Short Vol, Bonds, Credit) and their negative skewness.
  • Momentum on Individual Stocks vs Asset Classes [Sharpe Returns]

    I had the pleasure of finally meeting Gary Antonacci earlier this year. Gary is the creator of the momentum strategy that I follow and have been discussing on this blog. I first came across his work in 2011 on the blog Abnormal Returns (which should be a daily read for investors). Gary and I have been e-mailing each other ever since. After over 4 years, it was nice to finally see him in person.
  • Beginner’s Guide to Unsupervised Learning [Quant Start]

    The majority of machine learning posts to date on QuantStart have all been about supervised learning. In this post we are going to take a look at unsupervised learning, which is a far more challenging area of machine learning. Supervised learning involves taking a number of data observations, each of which contains a feature, or predictor, vector as well as an associated output, or response. The
  • Look at Data with a Discerning Eye [Flirting with Models]

    I recently came across a graph similar to the following while doing some market research. 1 Source: Yahoo! Finance. Analysis by Newfound Research. Data from January 1951 December 2015. The argument was that the markets are getting more volatile. While this certainly looks to be the case based on the upward trend of the histogram, let's investigate the data more thoroughly and ask
  • Trading Ethereum: Making 10% every 20 minutes [Jon.IO]

    This is more of a "How to build your own algotrading strategy – the Ethereum edition" and not a "make money fast" blog post. It is also a real example with real returns (and real production errors that cost me money) where you can see how to identify opportunities, why algotrading is awesome and why risk management can save your ass. This is the another post of the series: How
  • Tight Consolidations After New Highs [Quantifiable Edges]

    The range over the last week has been extremely tight. On 7/20/16 SPY closed at a 50-day high. Every SPY close in the 5 days since 7/20 has been within the intraday range of that 7/20/16 bar. (And it wasnt even that big of a range.) It is said that consolidations are often resolved in the direction of the trend. This guideline suggests that were more likely to see another leg up from here

Quantocracy’s Daily Wrap for 07/27/2016

This is a summary of links featured on Quantocracy on Wednesday, 07/27/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Unbearable Transience of Alpha [Quandl]

    In 2004 I enjoyed my 15 minutes of fame for an article I wrote called The Tao of Alpha, in which I explained the concept of alpha as a zero-sum game. Sources of alpha in 2004 were much different than those available in the mid-1990s when I started my career and they are also different from todays. Alpha is highly transient and has been coming and going for as long as capital markets have
  • Pair Trading Strategy and Backtesting using Quantstrat [Quant Insti]

    One of my favorite classes during EPAT was the one on statistical arbitrage, so the pair trading strategy seemed a nice idea for me. My strategy triggers new orders when the pair ratio of the prices of the stocks diverge from the mean. But in order to work, we first have to test for the pair to be cointegrated. If the pair ratio is cointegrated, the ratio is mean-reverting and the greater the
  • Evidence-Based Investing Requires Less Religion and More Reason [Alpha Architect]

    During the 1600s, the Dutch had a large merchant fleet and the port city of Amsterdam was a dominant commercial hub for trade from around the world. Based on the growing influence of the Dutch Republic, in 1602 the Dutch East India Company was founded, and its evolution into the first publicly traded global corporation drove a number of financial innovations to the Amsterdam Stock Exchange,

Quantocracy’s Daily Wrap for 07/26/2016

This is a summary of links featured on Quantocracy on Tuesday, 07/26/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Paper: The Trinity Portfolio [Meb Faber]

    Lets say one sets out to design a portfolio, knowing everything we know today about investing. Where would a logical, evidence-based investor even start? Investors today have access to more market data and strategic information than at any other time in history. While beneficial in some ways, this huge volume of fragmented information presents a challenge how should one actually implement

Quantocracy’s Daily Wrap for 07/25/2016

This is a summary of links featured on Quantocracy on Monday, 07/25/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • What is the Proper Benchmark for Momentum or Trend-Following Strategies? [Blue Sky AM]

    Most academics and practitioners tend to compare momentum or trend-following strategies to a buy and hold investment strategy. They do so by comparing the results of the strategies to a benchmark that is a proxy for buy and hold. From this type of analysis many experts justify why the strategies are either superior to buy and hold, or on the contrary side why they arent worth pursuing.

Quantocracy’s Daily Wrap for 07/24/2016

This is a summary of links featured on Quantocracy on Sunday, 07/24/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Portfolio selection, Laplace equation and Random Walk [Tulip Quant]

    Suppose you would like to invest 1000$ in two stocks, and you have to decide how much money you should put into these two stocks. You could use some Modern Portfolio Theory for that, for example. However, I would like to talk about a second approach, which is quite curious in my opinion. This post is based on this text by Julio Rossi, from the University of Buenos Aires. In this text, the
  • From trading ideas to robust strategies [Better System Trader]

    To prepare for the previous episode on system trading through the Brexit, I had to dig through some of the past podcast episodes for background information. As I was going through them I realized there was so much great information there, some that I had already forgotten about. Such a shame, all that valuable trading information just sitting there, waiting for our attention, so I thought it must