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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

Quantocracy’s Daily Wrap for 11/14/2015

This is a summary of links featured on Quantocracy on Saturday, 11/14/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Review: Inovance’s TRAIDE application [QuantStrat TradeR]

    This review will be about Inovance Tech's TRAIDE system. It is an application geared towards letting retail investors apply proprietary machine learning algorithms to assist them in creating systematic trading strategies. Currently, my one-line review is that while I hope the company founders mean well, the application is still in an early stage, and so, should be checked out by potential
  • CDS Inferred Stock Volatility [MathFinance.cn]

    I have written a working paper on CDS (credit default swap) implied stock volatility and found some interesting results. Post it here just in case someone is interested. Both CDS and out-of-money put option can protect investors against downside risk, so they are related while not being mutually replaceable. This study provides a straightforward linkage between corporate CDS and equity option by

Quantocracy’s Daily Wrap for 11/11/2015

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

  • Correlation and correlation structure (3), estimate tail dependence using regression [Eran Raviv]

    What is tail dependence really? Say the market had a red day and saw a drawdown which belongs with the 5% worst days (from now on simply call it a drawdown): weekly SPY returns One can ask what is now, given that the market is in the blue region, the probability of a a drawdown in a specific stock? We all understand the concept of beta of a stock with respect to the market, the sensitivity of a
  • Momentum On Dual Momentum Portfolios [Quants Portal]

    In the first section, this article describes a Dual Momentum study over an iShares country etfs basket with a new attempt to improve this well-known investing style. I chose iShares because it is the world largest family of Exchange Traded Funds (ETFs) from BlackRock. Although different stock markets correlations have become weaker and weaker in these last 10 years, this article easily shows that
  • Hi-Lo Index as a Market Timing Indicator [Alvarez Quant Trading]

    My strategies use a market timing indicator to tell me when I should not be trading the strategy. The blog post, Avoiding Stock Market Crashes with the Hi-Lo Index of the S&P500, presented a very simple idea of using new highs vs new lows. The post tests trading the SPY & IEF but I wanted to know how well would it work on a S&P500 mean reversion strategy. The Indicator The Hi-Lo Index
  • Valuation Metrics In Perspective [Larry Swedroe]

    Its well-established in the literature that valuation metricssuch as the dividend yield (D/P) and the earnings yield (E/P), as well as its cousin, the Shiller CAPE 10provide important information in terms of future expected returns. In fact, these metrics are the best that investors have for predicting long-term equity results. For instance, the Shiller CAPE 10, a cyclically adjusted
  • Pros and Cons of New Technology-enabled Indexes [CXO Advisory]

    What are pros and cons of extending the definition of financial index beyond conventional market capitalization (buy-and-hold) weighting? In the October 2015 draft of his paper entitled What Is an Index?, Andrew Lo proposes that any portfolio satisfying three properties should be considered an index: (1) transparent (public and verifiable); (2) investable (realistic and liquid benchmark);
  • Deconstructing the Time-Series Momentum Strategy [Quantpedia]

    Moskowitz, Ooi, and Pedersen (2012) show that time series momentum delivers a large and significant alpha for a diversified portfolio of various international futures contracts over the 1985 to 2009 period. Although we confirm these results with similar data, we find that their results are driven by the volatility-scaled returns (or the so-called risk parity approach to asset allocation) rather

Quantocracy’s Daily Wrap for 11/10/2015

This is a summary of links featured on Quantocracy on Tuesday, 11/10/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Random data: Evaluating [Investment Idiocy]

    Everyone hates drawdowns (those periods when you're losing money whilst trading). If only there was a way to reduce their severity and length…. Quite a few people seem to think that "trading the equity curve" is the answer. The basic idea is that when you are doing badly, you reduce your exposure (or remove it completely) whilst still tracking your 'virtual' p&l
  • I bought corporate bonds and all I got was this stupid currency exposure [Flirting with Models]

    Summary In the current Fed on / Fed off market environment, dollar exposure matters Currency hedged exposures have exploded in popularity in the equity space Using the experience of Canadian investors, we demonstrate the large impact that currency can have on fixed income Investors buying global bonds should consider whether currency hedging makes sense for them Currency hedging remains a
  • Making Time (Even More of) an Investor’s Best Friend [EconomPic]

    Ben Carlson of A Wealth of Common Sense blog (and author of a great book by the same name), had a recent post Playing the Probabilities outlining that time has been an investor's best friend (for those investors that have had in some cases quite a bit of time), pointing to the following table. He also shared some pretty amazing stats, including: The worst total return over a 20 year period
  • How Monday s Strong Drop May Be Setting SPX Up For A Bounce [Quantifiable Edges]

    When a market has already sold off for multiple days and the selling accelerates that can often mark a point where a bounce becomes likely. Mondays selling triggered the Quantifinder study below. All stats are updated. 2015-11-10 image1 These results appear extremely compelling. The consistency is very strong. Of course the market is always capable of doing things it hasnt before. Weve

Quantocracy’s Daily Wrap for 11/08/2015

This is a summary of links featured on Quantocracy on Sunday, 11/08/2015. To see our most recent links, visit the Quant Mashup. Read on readers!