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Quantocracy’s Best Links in July

The best links for the month of July, as voted by our readers:

We need to vote more folks. About 1% of clickthroughs result in a vote. That’s just not enough. A vote doesn’t necessarily mean a link is the greatest of all time, it simply means that it’s good and deserves to be read by others. So let your voice be heard and encourage bloggers to write quality content. We do our part by providing this site gratis. All we ask is that you take a moment to participate in the process.

If you haven’t done so already, we invite you 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 07/29/2015

This is a summary of links featured on Quantocracy on Wednesday, 07/29/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Synchronicity [MKTSTK]

    Recently we read an excellent article on investing from Alpha Architect entitled One way to beat the market? Be different! In the article, the author shows how thinking differently from the pack can provide better performance for your investment portfolio. As often happens with lateral thinking, this article stimulated our thinking from an HFT point of view. How can thinkin
  • Trading the VIX over the Fed Announcement [Factor Wave]

    "Buy the rumor, sell the fact" is an over-used phrase traders say to describe the way the equity markets get excited by future events then lose steam when the event actually happens. Because the VIX is strongly negatively correlated with the equity markets, this could be changed to "sell the VIX before an event, buy it afterwards". In this case the event is the Fed
  • The Information from Insiders [Factor Wave]

    One of the things that everyone knows to be true is that the trades of company insiders convey valuable information. But is this really true? And are some types of trades more informative than others? If you can get hold of the relevant data, this is the sort of question that is very amenable to statistical analysis. David Cicero and Babajide Wintoki did this exercise in
  • Dynamic Markowitz Efficient Frontier [Quant Dare]

    Markowitz Model is a famous method allocated in the Portfolio Investment Theory. This model provides efficient portfolios, i.e. portfolios with the highest rentability and lowest risk possible through mathematical programming. The set of portfolios composes the efficient frontier. The strategy is based on cuadratic optimization minimazing the estimated risk and opposite rentability. The
  • Australia All Ords Steady Vol Strategy [John Orford]

    In a round about way from New York to Singapore, I landed in Oz in 2012. It was like walking into a pre '08 New York or Ireland with funnier accents. They call '08 the 'GFC' or the 'Global Financial Crisis' and talk about it in a sort of detached way – because that tidal wave never hit their shores. In any case, the 'Volatility Fighter' reminded me
  • Algorithm Aversion – Why people don’t follow the model! [Alpha Architect]

    There are many studies showing that models beat experts, including the meta-study Clinical versus mechanical prediction: A meta-analysis by Grove et al. (2000). However, given this knowledge that models beat experts, forecasters still prefer to use the human (expert) prediction as opposed to using the model. Why is this? A recent paper by Dietvor
  • Simple volatility rebalancing strategy [Volatility Fighter]

    In my posts, I often mention a volatility rebalancing strategy. Originally, this strategy supposed to rebalance a portfolio daily to local volatility measured by standard deviation. I strongly suspect, that a common retail investor will stop trying to understand this strategy right after words "standard deviation", so I propose a simplified version of this strategy. My purp

Quantocracy’s Daily Wrap for 07/28/2015

This is a summary of links featured on Quantocracy on Tuesday, 07/28/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Momentum Crashes [Quants Portal]

    Seminal work by Jegadeesh and Titman (1993) found that past winners outperform past losers over a horizon of 3-12 months. Investors thus take a long position on winner stocks and a short position on loser stocks in order to realise anomalous profits. This strategy is widely adopted and appears to be timeless in terms periodically not functioning but never completely disappearing. This p
  • Sports Betting used to explain Value and Momentum Effects [Quantpedia]

    I use sports betting markets as a laboratory to test behavioral theories of cross-sectional asset pricing anomalies. Two unique features of these markets provide a distinguishing test of behavioral theories: 1) the bets are completely idiosyncratic and therefore not confounded by rational theories; 2) the contracts have a known and short termination date where uncertainty is resolved th
  • Liquidity Premium Diminishing [Larry Swedroe]

    Liquidity can be described as the ability to trade a large number of investments quickly, at low costs and when you want to. Because it is a priced risk, liquidity and its associated price effects are an important aspect of financial markets. In illiquid markets, such as the private equity market, discounts are large and pervasive. Publicly traded equity, howev
  • [Academic Paper] Risk Premia in Option Markets [@Quantivity]

    Risk Premia in Option Markets

Quantocracy’s Daily Wrap for 07/27/2015

This is a summary of links featured on Quantocracy on Monday, 07/27/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • One way to beat the market? Be different! [Alpha Architect]

    This study was inspired by Ben Carlsons blog post a few months ago. Ben highlights Robert Hagstroms book The Warren Buffett Portfolio. The high level question is the following: How can one beat the market? Answer: To beat the market, you have to be different than the market. One simple way to do this is to hold a small number of stocks. But is
  • Improve the Simple Gap Strategy Part 4 [System Trader Success]

    In the last article of this series, Improving The Simple Gap Strategy Part 3, I tested a price-based filter on the in-sample data. This filter was based upon the price action of the previous trading day. During this test we discovered that if the previous trading day was a down-day we could open a Simple Gap trade today. On the other hand, if the previous trading day was an up-day we sh
  • The Media and Stock Returns [Factor Wave]

    I recently had a disagreement with a trader friend. He said CNBC has become a waste of time to have on. I said it has always been a waste of time to have on. His point was that there are times when has been able to give him ideas about what stocks to follow. He thought it was self-evident that stocks that were in the news would outperform the market. My guess was that it was all just ra
  • Momentum vs Moving Averages [Flirting with Models]

    Summary Trend-following is one of the oldest investment methods Labeled as technical analysis, trend-following went largely un-researched by academics Research of cross-sectional momentum exploded after Narasimhan Jegadeesh and Sheridan Titman published their seminal 1992 study, but time-series momentum remained largely ignored until after 2008
  • Low Vol vs High Beta Premium [John Orford]

    Low volatility stocks are better than those with high betas, right? Wrong! Completely and utterly wrong. High betas are costlier because as not-very-many point out – convexity or gamma is important! When the S&P is doing well the high beta index has a beta of 1.84 and when it's doing badly, 1.81. A +0.025 spread. It's a sm
  • SPX Strangle – High Loss Threshold – 73 DTE [DTR Trading]

    This post looks at selling one-lot options strangles on the S&P 500 Index (SPX), initiated at 73 days-to-expiration (DTE). The results in this post were derived from more than 2300 individual trades entered by the backtester. Other 73 DTE variations will be posted on my Twitter feed, @DTRTrading. For background on the setup for the backtests, as well as the nomenclature u

Quantocracy’s Daily Wrap for 07/24/2015

This is a summary of links featured on Quantocracy on Friday, 07/24/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Chapter 13 Summary [Meb Faber]

    This excerpt is from the book Global Asset Allocation now available on Amazon as an eBook. If you promise to write a review, go here and Ill send you a free copy. – I would classify both my mother and grandmother as traditional Southern cooks. Their style was very much of the finger variety. While they may have a broad recipe to go by, the food usually
  • Quantifiable Edges CBI Reaching Bullish Levels [Quantifiable Edges]

    One indicator starting to give bullish readings is the Quantifiable Edges Capitulative Breadth Index (CBI). It reached 8 at the close on Thursday. While 10 is the level I often refer to as a very strong bullish indication, levels as low as 7 or 8 have often been followed by market bounces when the market has been in a long-term uptrend. Below I have produced a table showing results if you entered
  • Generalising the Mojito Strategy [John Orford]

    The Mojito uses a step function to switch up allocations between the VXX and VXZ ETFs over time. A bunch of rules which says… If the spot VIX to VXV (3 month VIX future) ratio ('IVTS') is lower than 0.91 then short the VXX (short term VIX future ETF) and weight by -0.7, while long the VXZ by 0.3; and so on… Each dot on
  • The Mechanics and Dynamics of a Short Squeeze [Factor Wave]

    In a recent post I discussed how the short borrow rate could be used as a predictor of future stock returns. This prompted a reader to ask if the analysis had taken short squeezes into account. This is a good point. Because of the mechanics of short selling it is sometimes not possible to hold short positions as long as we would like. I don't think the study did completely account
  • Margin Debt Bad or Beautiful? [Jay On The Markets]

    Well here I go again breaking one of my own cardinal rules again i.e., being critical of someone elses writing. Must be getting cranky in my old age. Anyway, I recently read an article calling margin debt an indicator that predicts nothing. No the writer is actually technically correct for the most part. Still this sort of surprised me as I remember learning from Norman Fosback
  • [Academic Paper] Carry and Trend Following Returns in Foreign Exchange Market [@Quantivity]

    Carry and Trend Following Returns in Foreign Exchange Market

Quantocracy’s Daily Wrap for 07/23/2015

This is a summary of links featured on Quantocracy on Thursday, 07/23/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • P/E Attention Strategies Earn Monthly Excess Return of 1% [Alpha Architect]

    Active investors with limited attention and capital constraints use fundamental metrics to screen and sort potential investments. Price-earnings (P/E) ratios are extremely popular, and are typically calculated using four trailing quarters of net income. Changes in the rankings of published P/E ratios may influence investor attention and subsequent excess returns. From 1974-2013, decile
  • Carry: An Investing Framework [Factor Wave]

    People generally compartmentalize their knowledge. They try to think of things in terms of categories and frameworks rather than remember a bunch of disconnected facts. For example, chemists think of the world in terms of interactions between elements, astrologists (a.k.a stupid people) think of the world in terms of zodiac signs and at FactorWave we think of investing in terms of facto
  • SPX Strangle – High Loss Threshold – 66 DTE [DTR Trading]

    This post looks at selling one-lot options strangles on the S&P 500 Index (SPX), initiated at 66 days-to-expiration (DTE). The results in this post were derived from more than 2300 individual trades entered by the backtester. For background on the setup for the backtests, as well as the nomenclature used in the charts and tables below, please see the introductory article f
  • Add Junk Bonds To The Growing Pile Of Concerns [Dana Lyons]

    This weeks Charts Of The Day and blog posts have had a heavy bearish bent to them. That isnt by design. We just go where the data leads us and much of the data, in our view, is skewing to the bearish side for equities. Included in the concerning assortment of data are many examples of weakening stock market internals. That isnt the only concern, however. As todays Chart Of The Day i

Quantocracy’s Daily Wrap for 07/22/2015

This is a summary of links featured on Quantocracy on Wednesday, 07/22/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Multiple Time Frames for Scoring ETF Rotational Strategies [Alvarez Quant Trading]

    Today we have a guest post from David Weilmuenster who I worked with while at Connors Research. A widely applied technique for scoring assets in rotational systems is to rank those assets by their price momentum, or return, over a given historical window and to rotate into the assets with higher momentum. This approach seeks to capitalize on the well-demonstrated tendency f
  • Market timing with Value and Momentum [Alpha Architect]

    Yesterday we wrote a post showing a potential way to time the market using valuation-based signals. In the past we have also examined how to use momentum-based signals (moving average rules and time-series momentum) to time the market. A natural question is what happens when we combine the valuation-based signals with the momentum-based signals? Here at Alpha A
  • White Noise and Random Walks in Time Series Analysis [Quant Start]

    In the last article of the Time Series Analysis series we discussed the importance of serial correlation and why it is extremely useful in the context of quantitative trading. In this article we will make full use of serial correlation by discussing our first time series models, including some elementary linear stochastic models. In particular we are going to discuss White
  • New Academic Research: ECB predicts stock market using social data [MKTSTK]

    The European Central Bank just released a research report that might be of some interest to readers of this blog. It turns out that Social Data can be useful in predicting the stock market (go figure!): Quantifying the effects of online bullishness on international financial markets [ECB] In our work, we develop a simple, direct and unambiguous indicator o
  • Fractal mathematics used to explain #14 – Momentum Effect in stocks [Quantpedia]

    Mandelbrot has significantly contributed in many ways to the area of finance. He was one of the first who criticized the oversimplifications centered around the early stochastic process models of Bachelier utilizing normal distribution. In his view, markets were fractal and much wilder than classical theory suggests. Additionally, he was a profound critic of the efficient markets hypoth
  • [Academic Paper] Night Trading: Lower Risk but Higher Returns? [@Quantivity]

    Night Trading: Lower Risk but Higher Returns?

Quantocracy’s Daily Wrap for 07/21/2015

This is a summary of links featured on Quantocracy on Tuesday, 07/21/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Eureka! A Valuation-Based Asset Allocation Strategy that Might Work [Alpha Architect]

    Weve had a few posts showing that asset allocation systems relying on market valuation indicators (e.g., Shiller CAPE ratios) as a timing signal may end up in disappointment Can market Valuations Be Effective Market-Timing Signals? Dissecting Goldmans 99 Percentile Market-Timing Signal Nonetheless, weve continued on the quest to improve tactic
  • Systems building – execution [Investment Idiocy]

    People often get systematic and automated trading mixed up. The latter is a subset of the first. You can't have a system which is fully automated if it relies on discretionary input, no matter how small. But you can have a system which needs a human to make it run, even though there is no discretion, and its fully systematic. The main area where humans are often used with s
  • Short Rates as a Predictor of Stock Returns [Factor Wave]

    In order to sell a stock short you first need to borrow it from someone else. The way that this typically happens is that your broker takes it from another clients account and loans it to you. You can then sell it to someone else. Although this means you end up with cash in your account, individuals typically don't receive interest for this. In fact they normally pay the broker a fee. (