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Best Links of the Week

The best quant mashup links for the week ending Saturday, 08/22 as voted by our readers:

My fellow quant traders, ask not what Quantocracy can do for you, ask what you can do for Quantocracy. Encourage bloggers to write quality content by voting for your favorite links on our quant mashup. 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 08/21/2015

This is a summary of links featured on Quantocracy on Friday, 08/21/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Parallels Of Betting & Investing [Larry Swedroe]

    Two of the most-well-known factors that help explain stock returns are the value effect (where equities with lower prices relative to metricssuch as book value, earnings, cash flow, sales and dividendstend to outperform the equities with higher prices relative to those metrics), and the momentum effect (where assets that have outperformed in the recent past tend to continue to outperf
  • Lazy Financial Strategies [John Orford]

    One of the major themes of War and Peace will resonate with all practitioners of stochastic finance. Essentially, Napoleon's nemesis, the Russian general Kutuzov, keeps dropping back before the invading French until at last he spots a weakness in the French and pounces. Tolstoy tells us that indecision and chaos is the natural state of things, and the logical c
  • Market Efficiency Hates Bad Weather [Alpha Architect]

    Building on research in psychology, we predict that unpleasant weather negatively affects capital market participants moods and activity levels, causing a muted response to information events The table below highlights that unpleasant weather seems to be correlated with slower market reactions. For example, in columns 5-8, the authors look at PEAD, or post earnings an
  • Moods and the Market [Factor Wave]

    At the start of the week I wrote a post about the effect of weather and the markets. Leo Cheng thought (quite reasonably) that this might just be data mining. If you look at enough things, some will appear to have an influence on the market just by chance. I've done a little more reading and I think that is not the case. I think the effect is real but it is weak.
  • RUT Strangle – High Loss Threshold – 66 DTE [DTR Trading]

    This post reviews the backtest results of selling one-lot options strangles on the Russell 2000 Index (RUT), initiated at 66 days-to-expiration (DTE). The results in this post were derived from 2336 individual trades entered by the backtester. The results are grouped by the delta of the short strikes. For example, a 4 delta strangle is constructed by selling a -4 delta put, and selli

Quantocracy’s Daily Wrap for 08/20/2015

This is a summary of links featured on Quantocracy on Thursday, 08/20/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 08/19/2015

This is a summary of links featured on Quantocracy on Wednesday, 08/19/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Health of Stock Mean Reversion: Dead, Dying or Doing Just Fine [Alvarez Quant Trading]

    My second post on this blog was a look at mean reversion, Is mean reversion dead? Given I am using a new data provider(Premium Data), it has been almost two years since that post and there have been other articles on this recently, I figured it was time to check again. The research will focus on Russell 1000 stocks since 1995. The test is back to 1995 covers 3 bull markets and 2 bear ma
  • Correlation and correlation structure [Eran Raviv]

    Given a constant speed, time and distance are fully correlated. Provide me with the one, and Ill give you the other. When two variables have nothing to do with each other, we say that they are not correlated. You wish that would be the end of it. But it is not so. As it is, things are perilously more complicated. By far the most familiar correlation concept is the Pearson
  • Technical Analysis or Quantitative Analysis? [Factor Wave]

    Yesterday I had a coffee with a person I have known for 20 years. He has worked as a quantitative analyst, a trader and a finance professor for at least as that long. He is one of the most knowledgeable people I know. When he says something it is worth listening. What he said was (roughly), " I've come to believe that there is something to technical analysis".
  • Crisis Alpha: Surprising Ways to Hedge Stock Portfolio Risk [Alpha Architect]

    Investing in the current environment is difficult. Most, if not all, asset classes have high nominal prices, suggesting low nominal expected returns. Not exactly exciting. And for many investors who are retired and/or have near-term liquidity needs, investing in equity exposureswhile necessary to generate higher expected returnsalso prevents many investors from sleeping at night!
  • New academic paper related to #12 – Pairs Trading with Stocks [Quantpedia]

    We assume that the drift in the returns of asset prices consists of an idiosyncratic component and a common component given by a co-integration factor. We analyze the optimal investment strategy for an agent who maximizes expected utility of wealth by dynamically trading in these assets. The optimal solution is constructed explicitly in closed-form and is shown to be affine in the co-in

Quantocracy’s Daily Wrap for 08/18/2015

This is a summary of links featured on Quantocracy on Tuesday, 08/18/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Kalman Filter and Pairs Trading [MKTSTK]

    Imagine this scenario: you are a statistical arbitrage trader at a prop desk or HF. As such, you routinely hold an inventory of ETF exposure that you must hedge. The previous night, you instructed your overnight traders to calculate the hedge ratios for a matrix of ETFs. The next morning before the market opens, your junior traders eagerly present their result
  • The Effect of the Board of Directors [Factor Wave]

    The Quality factor is a composite measure designed to identify companies with the characteristics that typically lead to success. It is particularly useful to identify "value traps": companies which are cheap by current metrics but are losing money. I wrote a little about quality here. However, we are not so dogmatic that we won't admit that there are aspects of quality tha
  • Intertemporal PCA Analysis [John Orford]

    Taking a leaf out of Mike Harris' recent Momersion theme, here's a PCA point of view of the balance between momentum and mean reversion over the previous 10 years from the Lazy PCA tool. August 2015 – 2014 PCA fits momentum and mean reversion components to the daily returns, they balance each other out here, which means the market is somewhat efficient (i.e. 'momersio
  • State of Trend Following in July: UP [Au Tra Sy]

    July saw a bounce back up in the index after several months of downwards action. The YTD performance is still negative though. Please check below for more details. Detailed Results The figures for the month are: July return: 3.86% YTD return: -1.47% Below is the chart displaying individual system results throughout July:

Quantocracy’s Daily Wrap for 08/17/2015

This is a summary of links featured on Quantocracy on Monday, 08/17/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Introduction to Monte Carlo Analysis Part 1 [Quants Portal]

    The Monte Carlo, filled with a lot of mystery is defined by Anderson et al (1999) as the art of approximating an expectation by the sample mean of a function of simulated variables. Used as a code word between Stan Ulam and John von Neumann for the stochastic simulations they applied to building better atomic bombs (Anderson, 1999), the term Monte Carlo evolved into a method used in a
  • The Sustainable Active Investing Framework: Simple, But Not Easy [Alpha Architect]

    The debate over passive versus active investing is akin to Eagles vs. Cowboys or Coke vs. Pepsi. In short, once our preference for one style over the other is established, it becomes a proven fact or incontrovertible reality in our minds. This post is not meant to convert a passive investor into an active investor; however, we do explain why we believe some active investing
  • Strategy Gamma Overview [John Orford]

    Economics 101 tells us that people have 'convex' utility curves. Which means there are diminishing returns to having more, but losing what you currently have diminishes your well being precipitously. Convexity is such a human property, it shows up again and again in unexpected places. Eyeballs, boobs and butts to name a few examples. I
  • Interview with Larry Williams [Better System Trader]

    On the show this week we have Larry Williams who has been trading futures and stocks for over 50 years. In 1987 he won the world cup trading championship, turning $10,000 in to over $1.1 million in 12 months, that's a cool 11,000% return and the highest return to ever be achieved in that competition. 10 years later his daughter won the same competition with a 1000% return a
  • Downloading Stock Market News for Specific Symbols [Godel’s Market]

    Grabbing the data. How do you grab the latest news on your favorite ticker symbol? It all starts with the following URL. https://www.google.com/finance/company_news?q=SPY&output=rss You'll want to change "q=SPY" to whatever symbol you're interested in. You can add something like the following to the end if you'd like m
  • Can managed futures manage rising rates? [Flirting with Models]

    Summary Rising interest rates are on the horizon somewhere Yield curve dynamics including the absolute level of rates, their direction of change, and the slope of the yield curve all play an important role in the returns for managed futures The cost of carry in shorting fixed-income futures means that commodity trading advisors (CTAs) may fail
  • Autoregressive Moving Average ARMA(p, q) Models for Time Series Analysis – Part 1 [Quant Start]

    In the last article we looked at random walks and white noise as basic time series models for certain financial instruments, such as daily equity and equity index prices. We found that in some cases a random walk model was insufficient to capture the full autocorrelation behaviour of the instrument, which motivates more sophisticated models. In the next couple of articles w
  • Weather and the Markets [Factor Wave]

    It should be fairly obvious to anyone who has been involved with investing for any time, that traders decisions are heavily influenced by their mood. Actually, some interesting recent research has shown that people generally make decisions intuitively before using their conscious thought processes to justify them. No one is actually all that rational. So perhaps it should b
  • RUT Strangle – High Loss Threshold – 59 DTE [DTR Trading]

    This post reviews the backtest results of selling one-lot options strangles on the Russell 2000 Index (RUT), initiated at 59 days-to-expiration (DTE). The results in this post were derived from 2312 individual trades entered by the backtester. The results are grouped by the delta of the short strikes. For example, a 4 delta strangle is constructed by selling a -4 delta put, and selli

Best Links of the Week

The best quant mashup links for the week ending Saturday, 08/15 as voted by our readers:

My fellow quant nerds, ask not what Quantocracy can do for you, ask what you can do for Quantocracy. Encourage bloggers to write quality content by voting for your favorite links on our quant mashup.

If you haven’t done so already, take a moment to 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 08/14/2015

This is a summary of links featured on Quantocracy on Friday, 08/14/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Some More on Stock Splits [Factor Wave]

    About a month ago I started to answer a reader's question about stock splits. I was initially diverted by the "low price effect" and then forgot to revisit the topic. In addition to the fact that a split reduces the price, it is also a distinct event and we can study the dynamics of the stock price before and after the split. And many, many people have… Befor
  • Fractal Strategy Applied to Indonesian Index [John Orford]

    When I lived in New York, every other night I'd have a drink with our head of financial engineering. Beer in the winter, G&Ts in the summer. In any case once he was telling me how in Japan even ordering coffee was tricky, because the Japanese didn't want to cause offence by not knowing English well, and he being somewhat familiar of Japanese culture, wanted to be polite as

Quantocracy’s Daily Wrap for 08/12/2015

This is a summary of links featured on Quantocracy on Wednesday, 08/12/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Absolute Strength Momentum: Guley And Petkova (2015) [Flirting with Models]

    In May 2015, Huseyin Gulen and Ralitsa Petkova published "Absolute Strength: Exploring Momentum in Stock Returns" (SSRN). In the paper they outline their new concept of absolute strength momentum. Momentum, in its traditional form, was a relative strength concept. Momentum took the cross-section of returns across securities, bough the "winners" and sold the "
  • Equal Weighting Investigation [John Orford]

    I landed in a town in Western Sumatra called Padang a few days after an earthquake hit. 7 or 8 on the Moment Magnitude scale. Just as in finance there are various ways of measuring quakes. The Richter scale measures ground motion whereas the more modern Moment Magnitude scale measures energy released. In any case my favourite measure of earthquake size is the n
  • 3-Bar Momentum Pattern | Trading Strategy (Entry) [Oxford Capital]

    I. Trading Strategy Concept: Short-term momentum pattern with trend filter. Source: Hill, J. R. (1977). Stock & Commodity Market Trend Trading by Advanced Technical Analysis. Hendersonville, N.C.: Commodity Research Institute, Ltd. Research Goal: Performance verification of 3-Bar Momentum Pattern. Specification: Table 1. Results: Figure 1-2. Portfolio: 42 futures markets f
  • Python Backtesting Libraries For Quant Trading Strategies [Robust Tech House]

    Frequently Mentioned Python Backtesting Libraries It is essential to backtest quant trading strategies before trading them with real money. Here, we review frequently used Python backtesting libraries. We examine them in terms of flexibility (can be used for backtesting, paper-trading as well as live-trading), ease of use (good documentation, good structure)
  • Volatility Breakout Model | Trading Strategy (Benchmark) [Oxford Capital]

    I. Trading Strategy Concept: Volatility breakout strategy based on price deviations defined by Minkowski Distance where: Upper_Band = Mean + (Multiple Deviation); Lower_Band = Mean ? (Multiple Deviation); Deviation((Close)k=1,,K, Mean) = (?|Close ? Mean|? K)1/?. Minkowski Distance has two special cases: (a) when ? = 1 (Manhattan Distance), the above formula reflects