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Quantocracy’s Daily Wrap for 09/04/2015

This is a summary of links featured on Quantocracy on Friday, 09/04/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Strategy Replication Nonlinear SVMs can systematically identify stocks with high and low future returns [Mintegration]

    Ive replicated the following academic paper from my favourite journal; Title: Nonlinear support vector machines can systematically identify stocks with high and low future returns Authors: Ramon Huerta, Fernando Corbacho, and Charles Elkan Journal: Algorithmic Finance (2013) 45-58 45, DOI 10.3233/AF-13016, IOS Press, http://algorithmicfinance.org/2-
  • Economics, Mathematics, & Common Sense [Alphamaximus]

    Almost all calculations in finance involve using log returns rather than % returns. There are a number of reasons why log returns are preferred. Estimating beta doesnt seem like a special case. But when you go through the math, something doesnt quite add up. rS1M1Pt=?+?rM+?t=S0exp(r)=M0exp(rM)=S0+wM0 Because we want to zero out market risk, so want to s
  • Benford’s Law [Factor Wave]

    Benford's Law states that in many naturally occurring groups of numbers, the small digits are seen disproportionately often. This is often applied to the leading digits of data but it is more general than that. This was first noticed by the astronomer Simon Newcomb (who also should be famous for an awesome beard!) in 1881 when he saw that the first pages in a library book of logarithms
  • Backtesting Data Independence [John Orford]

    Light is the most precious resource to a photographer, everything you can do with your camera is budgeted by the amount of light available. Financial analysis is similarly constrained by the amount of data available. So more available data is always good. With Big 'O' Sharpe you can generate as much data as the data is granular. E.g. i

Quantocracy’s Daily Wrap for 09/02/2015

This is a summary of links featured on Quantocracy on Wednesday, 09/02/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Systems building – Checks and balances [Investment Idiocy]

    Driverless cars are, apparently, very close to commercial reality. I don't know about you but there is something pretty scary about a computer being completely in control of a complex process, which could have catastrophic consequences if it went wrong. Ah it was nothing. You should have seen the other guy… (From autospies.com) That might seem a strange atti
  • How Can a Strategy Everyone Knows About Still Work? [AQR]

    Some assert that once a strategy is discovered it cant work anymore. Others, often implicitly, assume the future will look as wonderful as the past. Perhaps not surprisingly, we stake out a middle ground. Were going to argue that certain well-known classic strategies that have worked over the long term will continue to work going forward, though perhaps not at the same level and wit
  • Gray et al., DIY Financial Advisor [Reading the Markets]

    Models beat expertsor, stated more cautiously, models typically beat experts. This is the rallying cry of DIY Financial Advisor: A Simple Solution to Build and Protect Your Wealth (Wiley, 2015) by Wesley R. Gray, Jack R. Vogel, and David P. Foulke, all managing members of Alpha Architect. Whether or not you believe this claimand despite the seeming preponderance of evidence in its fav
  • Stock Returns Around Labor Day [CXO Advisory]

    Does the Labor Day holiday, marking the end of summer vacations, signal any unusual return effects by refocusing U.S. stock investors on managing their portfolios? By its definition, this holiday brings with it any effects from the turn of the month. To investigate the possibility of short-term effects on stock market returns around Labor Day, we analyze the historical behavior of the s

Best Links of the Week

The best quant mashup links for the week ending Saturday, 08/29 as voted by our readers:

We also welcome two blogs making their first ever appearance on the mashup this week:

* * *

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 08/29/2015

This is a summary of links featured on Quantocracy on Saturday, 08/29/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Multivariate volatility forecasting [Eran Raviv]

    Last time we showed how to estimate a CCC and DCC volatility model. Here I describe an advancement labored by Engle and Kelly (2012) bearing the name: Dynamic equicorrelation. The idea is nice and the paper is well written. Departing where the previous post ended, once we have (say) the DCC estimates, instead of letting the variance-covariance matrix be, we force some struc
  • Introduction to Monte Carlo Analysis Part 2 [Quants Portal]

    Markov Chains, Central Limit Theorem and the Metropolis-Hastings In the previous article I gave a generic overview of Monte Carlo as well as introduced importance sampling. We now dive deeper by giving strict definitions of some of the widely used and yet misunderstood or rather commonly neglected concepts due to its perceived importance. There after we explore the Metropol
  • Steady Vol & Big ‘O’ Sharpe [John Orford]

    Big 'O' Sharpe changes backtest starting dates day by day until the lowest Sharpe is found. When strategies rebalance on periodic basis it turns out that such very small changes cause very large differences in results. Big 'O' Sharpe is the pessimistic grumpy brother of the happy-go-lucky Sharpe ratio. On the plus side if you do get a good Big 'O' Sharpe number
  • Multiscale Noisy-Rational-Expectations Equilibrium [Alex Chinco]

    1. Motivation Evolutionarily Slow. In modern financial markets, people simultaneously trade the exact same assets on vastly different timescales. For example, a Jegadeesh and Titman (1993)-style momentum portfolio turns over half its holdings once every 6 months. By contrast, Kirilenko, Kyle, Samadi, and Tuzun (2014) estimate that high-frequency traders (HFTs) reduce half

Quantocracy’s Daily Wrap for 08/28/2015

This is a summary of links featured on Quantocracy on Friday, 08/28/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Avoiding Stock Market Crashes with the Hi-Lo Index of the S&P500 [iMarketSignals]

    This daily indicator is calculated as the ratio of the number of S&P500 stocks that have reached new 3-month-highs minus those that have reached new 3-month-lows, divided 500. Exiting and entering the stock market according the indicators signals would have avoided major drawdowns of the market during the backtest period from Jan-2000 to Aug-2015. Switching acco
  • Are Spikes Predictive? [Factor Wave]

    Yesterday I looked at stock market returns in the week and month after a large daily decline and found that it is usually a good time to buy more equities. Especially because, as long-term investors, our strongly held prior is that equity markets appreciate over time. But what about spikes? Do large one day rallies tell us anything in particular about subsequent returns?
  • Missing the Best and the Worst [Flirting with Models]

    Numerous marketing pieces circulating around the web show the detriment that trying to time the market can have on a portfolio. These pieces often look similar to this chart, which shows the cumulative growth of $1 invested in the S&P 500 ETF (SPY) assuming that a given number of best days are missed over the period from 1995-2014. Missing 0 days is equivalent to simply buying and holdi
  • Visualizing Stock Market Risk: 7/1926 to 6/2015 [Alpha Architect]

    How crazy is current market action? Not that crazy. and if you lived through 2008, definitely not that crazy. Seeing a -3%+ or a +3% observation is roughly a 1/100 event, or ~ 2.5 times a year. Obviously, return events are not independent and volatility tends to cluster, but the numbers above establish a basic starting point for discussions about
  • 5 Ways to Plot Returns [John Orford]

    There's an infinite number of ways to plot financial time series, let's look at the main ones. The most basic way is just plonking returns on a plot. This has one very nice feature. The returns are comparable across time, which makes a lot of sense, right? A return at the beginning of our backtest should probably be as important as one at the end.
  • Why Thursday s Volume Was Disappointing For Bulls [Quantifiable Edges]

    Thursdays rally was accompanied by the lightest volume in 5 days. The relatively low volume could be worrisome for bulls. The importance of volume can be seen in the studies below. The first one looks at 2%+ SPX gains when volume comes in relatively high. 2015-08-28 image1 A week later of the instances closed higher and the average instance saw the SPX up ab

Quantocracy’s Daily Wrap for 08/26/2015

This is a summary of links featured on Quantocracy on Wednesday, 08/26/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • The Trajectory of a Crash [Philosophical Economics]

    Its amazing to think that just last Monday, August 17th, the S&P 500 closed at 2102. Today, it closed at 1868, falling 11.1% in 6 trading days. The shocking speed of the decline has injected a level of fear into markets not scene since the fall of 2011, when the Eurozone debt crisis was reaching its apex. Many traders have referenced 1987 as a paradigm for what might happen in a wor
  • Quant-Trader or Trader-Quant? [MKTSTK]

    The term quant trader gets thrown around a lot these days. For any trader who has been in the industry for more than a decade, the adoption of the term is driven by survival. Theres a running joke in some HFT circles: these days, older traders would never get past HR using the same criteria by which junior traders are hired. Junior traders must be data scientists and traders.
  • Let’s talk “Year-to-Date” [Flirting with Models]

    We have a pretty arbitrary practice in the financial services industry: we reset the performance clock of portfolios to zero every January. Consider this hypothetical scenario: its December and markets are up 20% for the year. They even got a nice 5% pop in the last month. The clock strikes midnight on December 31st. We roll into January and the markets proceed to tumbl
  • Super Reliable Backtesting [John Orford]

    Big 'O' is a measure of many things, with respect to backtesting it helps because results are always ambiguous. Backtesting results are almost iffy for a variety of reasons, but a salient one is the 'day bump' problem. Say, I have a strategy that trades at the 'beginning of every month' and the results look promising. What happens to the results if

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