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Best Links of the Week

The best quant mashup links for the week ending Saturday, 11/21 as voted by our readers:

And in case you missed it, the backstory behind our new collection of quant trading books curated by Jacques Joubert of Quants Portal.

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My fellow traders, ask not what Quantocracy can do for you, ask what you can do for Quantocracy. Vote for your favorite links on our quant mashup to encourage bloggers to write quality content. We do our part by providing this site without annoying advertising. All we ask is that you take a moment to participate in the process.

If you haven’t done so already, register to vote. Once registered, you can choose to remain logged in indefinitely, making voting as simple and painless as possible.

Read on Readers!
Mike @ Quantocracy

Quantocracy’s Daily Wrap for 11/21/2015

This is a summary of links featured on Quantocracy on Saturday, 11/21/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Bring More Data [Dual Momentum]

    Several months ago we posted an article called Bring Data where we showed the importance of having abundant data for system development and validation. This was further reinforced to us recently when someone brought us some additional U.S. stock sector data. Previously, we only had sector data from Morningstar that went back to 1992. (S&P sector data also goes back to only the early

Quantocracy’s Daily Wrap for 11/20/2015

This is a summary of links featured on Quantocracy on Friday, 11/20/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Trend Following and Momentum Strategies for Global REITs [Alpha Architect]

    This study investigates whether the risk adjusted returns of a global REIT portfolio would be enhanced by adopting a trend following strategy (which is an absolute concept), a momentum based strategy (which is a relative concept and requires individual country allocations), or indeed a combination of the two. We examine the results in terms of both a dedicated Global REIT exposure, and the impact
  • And Even More Evidence of Acceleration being Predictive [Factor Wave]

    In the last two posts I wrote about acceleration, where returns over consecutive periods are increasing. Ive received several emails about the idea. These investors (with about 80 years of experience between them) really like the concept. It resonated with the way they saw the world. When looking for stocks, they use one period to form a hypothesis (in this case that a stock has momentum) and
  • Stock Returns Around Thanksgiving [CXO Advisory]

    Does the Thanksgiving holiday, a time of families celebrating plenty, give U.S. stock investors a sense of optimism that translates into stock returns? To investigate, we analyze the historical behavior of the S&P 500 Index during the three trading days before and the three trading days after the holiday. Using daily closing levels of the S&P 500 Index for 1950-2014 (65 events), we find

Quantocracy’s Daily Wrap for 11/19/2015

This is a summary of links featured on Quantocracy on Thursday, 11/19/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • An Awesome Collection of Quant Books from Quantocracy [Quantocracy]

    Check out our new books section, curated by Jacques Joubert of Quants Portal. The backstory: I wanted to put together a collection of quantitative trading books as deep and wide as our quant mashup. The problem was that, because of my get to the point nature, my reading consists mostly of posts and papers. I dont have the temperament for the uber long-form. But I recognize that a lot of
  • A Classic Factor Model Improves [Larry Swedroe]

    There has been a great deal of focus by the academic community in recent years on fine-tuning the various factor models used to explain the differences in returns of diversified portfolios. Marie Lambert, Boris Fays and Georges Hubner contribute to the literature with their 2015 paper, Size and Value Matter, But Not the Way You Thought. In their study, the authors examined the construction
  • First draft of ‘JavaScript for Financial Analysts’ Chapter 8 [John Orford]

    First draft of 'JavaScript for Financial Analysts' Chapter 8. ~~ As we saw in the previous chapter, doing things asynchronously is really appealing when you can pull it off elegantly. A bit like juggling, there's a lot going on, but a skilful juggler only ever interacts with one ball at a time if he is juggling one handed – and two with both hands. In the same way our JavaScript
  • Daily Academic Alpha: Solving the Idiosyncratic Volatility Puzzle [Alpha Architect]

    Kewei Hou and Roger Loh have a fun paper on the idiosyncratic volatility puzzle, which is set to be published in the Journal of Financial Economics. The idiosyncratic volatility puzzle is associated with the empirical evidence which suggests that stocks with higher idiosyncratic volatility (volatility left over after controlling for "systematic" risk factors) earn lower returns. Rough
  • Time-Varying Conditional Market Exposures of the Value Premium [Quantpedia]

    Value strategies exhibit a large positive beta if contemporaneous market excess returns are positive, and a small beta if contemporaneous market excess returns are negative. Value also has a large positive beta after bear markets, but a small beta after bull markets. These facts hold for equity-value strategies in 21 countries, and to a lesser extent for three non-equity-value strategies. Betas
  • SPX Straddle – Backtest Results Summary – Part 2 [DTR Trading]

    When I posted my SPX Straddle Backtest Results Summary I didn't plan on writing a follow up article. But after that post I received several emails asking if I could present the SPX straddle results in a slightly different format. Basically tabular results in a structure similar to my iron condor and strangle results articles (here, here, and here) … with each row associated with a strategy

An Awesome Collection of Quant Books from Quantocracy

Check out our new books section, curated by Jacques Joubert of Quants Portal.

The backstory:

I wanted to put together a collection of quantitative trading books as deep and wide as our quant mashup.

The problem was that, because of my “get to the point” nature, my reading consists mostly of posts and papers. I don’t have the temperament for the uber long-form. But I recognize that a lot of readers don’t learn the way I do. They benefit more from the degree of focus that only a book can provide.

So I needed to find someone who (a) knows quantitative trading, (b) is well-respected by our readers, (c) is an avid devourer of good ol’ ink and paper, and (d) would be willing to take on such a monumental task out of love for our community (because unfortunately, Amazon links are not going to be paying anyone’s salary anytime soon).

jacques.20151117Jacques Joubert of Quants Portal fits that bill perfectly.

Jacques is a quant developer specializing in hedge funds, a top rated contributor to Quantocracy, and a major advocate for this community. He adheres to a strict monthly reading goal of at least two significant books a month, with the breadth and depth I think our readers are looking for.

Check out the fruits of Jacques’ labor, covering everything from quant trading to specific programming languages like R and Python.

I’ve asked Jacques to effectively “own” this section of Quantocracy, so I encourage readers to send your suggestions and comments about books to Jacques directly via LinkedIn, Twitter or email.

Note that when you order a book from Amazon through our site, Amazon throws a few shekels our way. There’s no additional cost to you, and it’s a great way to show your love for Quantocracy.

Check out our new books section, curated by Jacques Joubert of Quants Portal.

Categories: Quant Trading, General Quant Finance, Financial Math, C++, Python, R, Excel/VBA, Quant Jobs & Interviews, Hedge Funds, Our Bloggers

Read on Readers!
Mike @ Quantocracy

Quantocracy’s Daily Wrap for 11/18/2015

This is a summary of links featured on Quantocracy on Wednesday, 11/18/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Random data: Random wanderings in portfolio optimisation [Investment Idiocy]

    Everyone knows that the usual naive method of portfolio optimisation is, well, a bit rubbish. This isn't because the method is flawed, but it relies on the inputs being 100% accurate, or to put it another way we need to know precisely what the mean, volatility and correlation of future returns are going to be. But most peoples crystal balls are somewhat foggy. Fortunately there are a few
  • Bond Performance when Interest Rates Spike [Alpha Architect]

    The prediction of higher interest rates has been ongoing since the government went all-in on a variety of so-called inflationary efforts. Inflation hasnt happened and rates are still low across the yield curve. So-called bond vigilantes, having been wrong for 7 years now and are still calling for inflation and subsequent higher interest rates. Will higher interests happen? I dont

Quantocracy’s Daily Wrap for 11/17/2015

This is a summary of links featured on Quantocracy on Tuesday, 11/17/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Mean Reversion Case For (and Against) Strong Future Returns [EconomPic]

    Bull thesis: 15-year S&P annualized returns ending 9/30/15 came in at just under 4%. The average forward return since 1915 when returns were that level (or lower) was 15.5% annualized over the next 15 years with a standard deviation of only 2% Bear thesis: the 15-year starting point came when the previous 15 year annualized returns were just under 18% (i.e. we are still working off extreme
  • Acceleration and Momentum [Factor Wave]

    The momentum factor has been extensively studied. We know it predicts outperformance both in the absolute and in the cross section. Momentum has been studied in many markets and over extensive time periods. But a recent interesting paper instead looks at whether the change of momentum is a useful predictive factor. In The Acceleration Effect and Gamma Factor in Asset Pricing, Diego
  • David Dreman on Value Investing and Investor Overreaction [Alpha Architect]

    David Dreman is a personal hero of mine. Years ago, I stumbled on his book, Psychology and the Stock Market: Investment Strategy Beyond Random Walk, which was originally published in 1977. It had a huge impact on me. Its timeless, with lessons that still apply to value investing today. It was among the first books I read that explained clearly how investor psychology affected the stock
  • The average stock market year [UK Stock Market Almanac]

    What does an average year for the FTSE 100 Index look like? The summary pages for each month in the diary section of the Almanac have charts that show the average cumulative behaviour of the market day-by-day. These charts are produced by calculating the daily mean return for each day in the trading year over a specific period (in this case from 1984). For example, if we take the index returns on

Quantocracy’s Daily Wrap for 11/16/2015

This is a summary of links featured on Quantocracy on Monday, 11/16/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How the Number of Firms and Holding Periods Affect Momentum Funds [Alpha Architect]

    We have already documented the returns to generic momentum investing strategies. Within the fund marketplace, many investors focus on fees and less on process. For example, Morningstar highlights the fees as cost-efficient for a specific momentum fund, MTUM. However, fees are only one part of an investment decisionprocess also mattersespecially when it comes to momentum-based stock
  • David Versus Goliath [Investment Idiocy]

    Just a quick post today. As most of you know until a couple of years ago I worked for a large systematic hedge fund. Now I manage my own money. I'm doing similar things (systematically trading futures, with a holding period averaging a few weeks, and a variety of trading rules with a trend following bias). An interesting question, which I'm often asked, is can a little guy like me
  • Seasonality S&P Market Session [System Trader Success]

    In a recent article, Seasonality Study, I took a look at the classic seasonality effect as seen in the U.S. markets. Briefly recapping that article, it shows that the trading days between November through May appear to hold significant gains in the market while the trading days between June and October hold far less profit. In this article I would like to test the markets intra-day behavior
  • Two Unfilled Down Gaps For SPY Good News? [Quantifiable Edges]

    Both Thursday and Friday saw SPY leave an unfilled gap down. That is fairly unusual. In the study below I examined other times it has occurred since 2002 while SPY was below the 200-day moving average. 2015-11-16 image1 Every instance except one was higher five days later. While instances are a little low, the numbers are compelling and suggest an upside edge over the next week.

Quantocracy’s Daily Wrap for 11/15/2015

This is a summary of links featured on Quantocracy on Sunday, 11/15/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    The best quant mashup links for the week ending Saturday, 11/14 as voted by our readers: Build Better Strategies! [Financial Hacker] A Filter Selection Method Inspired From Statistics [QuantStrat TradeR] Unsupervised candlestick classification for fun and profit part 1 [Robot Wealth] Random data: Evaluating [Investment Idiocy]
  • Unsupervised candlestick classification for fun and profit part 2 [Robot Wealth]

    In the last article, I described an application of the k-means clustering algorithm for classifying candlesticks based on the relative position of their open, high, low and close. This was a simple enough exercise, but now I tackle something more challenging: isolating information that is both useful and practical to real trading. Ill initially try two approaches: Investigate whether there are
  • Searching for an Efficient Market Regime Filter [Helix Trader]

    The probability of our long term success as traders increases when we trade with the prevailing market trend. This means when trading stocks we should be buying when the overall market is rising and / or shorting when the overall market is falling. In order to filter trading opportunities therefore, we need an efficient way of determining the current market regime. In this article we'll focus
  • Trading Autocorrelation? [Quintuitive]

    Markets are very smart in absorbing and reflecting information. If you think otherwise, try making money by trading. If you are new to it, make sure you dont bet the house. In other words, markets are efficient. At least most of the time. So then why people trade? The general believe is that there are windows during which prices of certain assets are inefficient. Thus, there are opportunities
  • Can We Tell Who Trades on Which Dark Pools? [Mechanical Markets]

    Marketplace transparency ensures that investors receive a fair price and have accurate data to conduct their research. But, transparency can also make it harder for traders to conceal their intentions from competitors and counterparties. Exchanges and regulators are tasked with balancing the transparency needs of a markets customers. Dark pools, by operating with the minimal amount of
  • Interview with Thomas Stridsman [Better System Trader]

    Thomas Stridsman has over 20 years experience in the financial markets. He was an editor for Futures magazine and published two books on trading system development and money management. He is now a fund manager at Alfakraft, specialising in short-term trend following strategies with a focus on dynamic size allocation and risk distribution algorithms. In this episode we discuss strategy testing,
  • Quandl plot in Python [Smile of Thales]

    Quandl is a platform that offers free and premium access to financial and economic data. On top of this the data export is supported by many languages and softwares such as R, C#, Matlab. You can find here an exhaustive list of environments. In the following you will find an illustration of how you can retrieve data from Quandl, using the Quandl python package and then plot this data (here, Debt
  • Santa Claus is Coming to Town (I Hope!!) [Jay On The Markets]

    The renowned Santa Claus Rally is second only to Sell in May in generating a flood of articles from us market analyst types. But I havent seen too many Santa Claus Rally articles so far this year so Ive decided to try to beat the crowd. Plus rally time is (hopefully) just a short ways away. Different market analyst types define the Santa Claus Rally time period

Best Links of the Week

The best quant mashup links for the week ending Saturday, 11/14 as voted by our readers:

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parisThe prayers of everyone associated with Quantocracy go out to the people of France. I lack the eloquence to find words that could possibly begin to soften your pain, but please know that the world weeps for you, and stands united with you.

Vive la France!