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Quantocracy’s Daily Wrap for 05/01/2015

This is a summary of links featured on Quantocracy on Friday, 05/01/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • VIX Trading Strategies in April [Volatility Made Simple]

    Weve tested 23 simple strategies for trading VIX ETPs on this blog (separate and unrelated to our own strategy). And while I cant speak for all traders, based on all of my readings both academic and in the blogosphere, the strategies weve tested are broadly representative of how the vast majority of traders are timing these products. Most of these strategies turned in solid performances
  • Could Stocks AND Bonds Be Topping? [Dana Lyons]

    There is always a small but vocal contingent of market pundits calling for a stock market top. In the past few years, there has been a very large but now sheepishly quiet contingent of analysts calling for a top in bonds (i.e., rise in rates). One thing you dont hear too often, however, is a call for a major top in stocks and bonds. Now that would be a double whammy for investors! If you want
  • A Simple Test of the Predictability of Large Daily Changes in SPY [Psych Signal]

    We know market sentiment metrics used as a stand-alone signal – can predict market changes over minutes and sometimes longer. But what about the vital issue of really big day-to-day changes? And what if we add the simplest of daily price dynamics to the daily sentiment metric-based predictive model? Here we present tests of how well daily sentiments predict big market shifts. We take daily
  • Flattish years in SP by end of April $SPY [@NautilusCap]

    Flattish years in SP by end of April $SPY
  • WTI Crude up 25% in a month $USO [@NautilusCap]

    WTI Crude up 25% in a month $USO
  • Ivy Portfolio May Update [Scott’s Investments]

    Scotts Investments provides a daily Ivy Portfolio spreadsheet to track the 10 month moving average signals for two portfolios listed in Mebane Fabers book The Ivy Portfolio: How to Invest Like the Top Endowments and Avoid Bear Markets. Faber discusses 5, 10, and 20 security portfolios that have trading signals based on long-term moving averages. The Ivy Portfolio spreadsheet tracks the 5 and
  • Better portfolio building: How system returns correlate under edgeless environments [Mechanical Forex]

    The topic of system return correlations is extremely important as it forms the main pillar of successful portfolio building. Portfolio theory encourages us to put together different systems which are uncorrelated historically, such that our level of expected risk adjusted returns will increase as a result of an increase in compounding efficiency and an increased hedging of drawdown periods between
  • ETFReplay.com Portfolio May Update [Scott’s Investments]

    The ETFReplay.com Portfolio holdings have been updated for April 2015. I previously detailed here and here how an investor can use ETFReplay.com to screen for best performing ETFs based on momentum and volatility. The portfolio begins with a static basket of 14 ETFs. These 14 ETFs are ranked by 6 month total returns (weighted 40%), 3 month total returns (weighted 30%), and 3 month price volatility
  • RUT Iron Condor – Dynamic Exit – 66 DTE – 20 Delta Continued [DTR Trading]

    This post is a continuation of the prior post. In this post we will look at the backtest results for dynamic exits of the 66 days-to-expiration (DTE) Iron Condor (IC), with 20 delta short strikes, with different profit and loss exits as a percentage of the initial credit. Recall that these RUT ICs were all constructed with 20 point wide credit spreads. This is a non-directional options trading str

Quantocracy’s Daily Wrap for 04/28/2015

This is a summary of links featured on Quantocracy on Tuesday, 04/28/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Smart are “Smart Beta” ETFs? [Alpha Architect]

    Many consider smart beta to be a revolution in the asset management industry. For example, Bloomberg ran an article, Funds Run by Robots Now Accounts for $400 Billion, which caught our attention. According to this article, Smart beta, is one of the fastest growing segments of ETFs, accounting for nearly 20% of all assets in domestic ETFs as of the end of 2014. The secret sauce of
  • Can you avoid rising rates with high carry assets? [Flirting with Models]

    First: the takeaways Expected return for an asset class is a combination of carry and price appreciation If carry is high enough, it can potentially dwarf price depreciation due to rising rates Higher carry assets (e.g. high yield bonds, MLPs, REITs, bank loans, EM debt, et cetera) have historically had low-to-negative estimated duration profiles High carry assets have a variety of associated risk
  • Is That Back-Test Result Good or Just Lucky? [Adaptrade]

    When developing trading strategies, most systematic traders understand that if you search long enough, you're bound to find something that looks great in back-testing. The question is whether those great results are from a great trading strategy or because the best looking strategy was the one that benefited the most from good luck. A well-known metaphor for this is a roomful of monkeys
  • System building – Data capture [Investment Idiocy]

    A while ago I ran a series of posts on how you would write some python code to systematically trade using the interactive brokers C++ API. Whilst I hope this was helpful it was just a starting point. There are at least two major projects to undertake before one could actually trade. The first is the design of such a system. This is the subject of a book I am writing, which I hope will be published
  • RUT Iron Condor – Dynamic Exit – 66 DTE – 16 Delta [DTR Trading]

    In this post we will look at the backtest results for dynamic exits of the 66 days-to-expiration (DTE) Iron Condor (IC) options strategy, with 16 delta short strikes, with different profit and loss exits. This is a non-directional options trading strategy that seeks to profit from a market that stays within a range between the two short strikes of the Iron Condor. For some background on how the re

Quantocracy’s Daily Wrap for 04/27/2015

This is a summary of links featured on Quantocracy on Monday, 04/27/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Random Notes on Python II [Largecap Trader]

    In continuation of an old post on Python, Ive been playing around with an awesome new library built by P. Morissette simply titled BT. It includes numerous functions for back testing and displaying results & charts for daily strategies and lower frequencies. Heres an example of a simple momentum based tactical asset rotation strategy: PythonEx3 It has a function to weight stocks based on
  • Weekly Commentary A Curated Charcuterie of Links [Flirting with Models]

    Newfound will be hosting its next monthly strategy review session on Thursday, May 14th from 2:00- 2:30PM EST. Were fortunate enough to have a guest panelist joining us: Brett Hammond from MSCI. He will be discussing factor-based investing and MSCIs portfolio construction methodologies that underlying many of the ETFs Newfound utilizes. Well also be discussing how tactical strategies can
  • Alternatives To Matlab [Only VIX]

    Reader Eli asked in the comments "I used to program in Matlab a lot in the past. Now I feel that Python is a better way to go. Any thoughts? Yes, quite a few – however I also hope to hear some ideas from other readers. Matlab is an excellent tool for analytics, and I have been using it for over a decade now. However if I were starting out in quantitative finance today I would probably go with
  • 9 Mistakes Quants Make that Cause Backtests to Lie [Augmented Trader]

    Ive never seen a bad backtest Dimitris Melas, head of research at MSCI. About backtests A backtest is a simulation of a trading strategy used to evaluate how effective the strategy might have been if it were traded historically. Backtestesting is used by hedge funds and other researchers to test strategies before real capital is applied. Backtests are valuable because they enable
  • International Value Investing: Looks Like a Reasonable Bet [Alpha Architect]

    A rich body of literature has shown that value investing, or buying stocks that are cheap based on a variety of valuation metrics, is robust across different markets. For example, Fama and French (1998) highlighted the value premium across world equity markets. The authors find that value portfolios yield higher average returns than growth portfolios in 12 out of the 13 countries analyzed
  • New related paper to #21 – Momentum Effect in Commodities and #22 – Term Structure Effect in Commodities [Quantpedia]

    #21 – Momentum Effect in Commodities #22 – Term Structure Effect in Commodities Authors: Bakshi, Bakshi, Rossi Title: Understanding the Sources of Risk Underlying the Cross-Section of Commodity Returns Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2589057 Abstract: We show that a model featuring an average commodity factor, a carry factor, and a momentum factor is capable of describing
  • Upcoming Courses for 2015 [Augmented Trader]

    New 3-part course Fall 2015 I will be offering a 3 part course, CS 7646: Machine Learning for Trading, online. It is equivalent to the on campus graduate course that I teach at Georgia Tech. The three parts are: Part 1: Manipulating Financial Data in Python (about 4 weeks) Part 2: Computational Investing (about 4 weeks) Part 3: Learning Algorithms for Trading (about 7 weeks) Parts 1
  • How to Avoid Losing 95% in Ford [Jay On The Markets]

    No, were not talking resale value here (in which case losing 95% of your original investment is a distinct possibility). We are talking about stock ownership. In a nutshell, the answer is fairly simple: *It is OK to drive a Ford in late summer into fall. But it is NOT OK (apparently) to own Ford stock during late summer into fall. The History In Figure 1 you see the growth of $1,000 invested in
  • How to Trade the MACD: A High-level Analysis of the MACD Line Feature [System Trader Success]

    Moving Average Convergence Divergence (MACD) is one of the most popular technical indicators used by traders. It is a flexible indicator that can be used for determining the strength and direction of a trend. It has three distinct features and in this first post we are going to do a high-level analysis of one of those features, the MACD Line. We will compare three of the most common MACD Line sett
  • When SOX Falls As NDX Has A Strong Day [Quantifiable Edges]

    One interesting aspect of Fridays action was the discrepancy between the NDX and the SOX. While the NDX rose 1.3%, the SOX declined 1.7% which is very unusual action. Below is an updated study that looks at times the NDX rose by a least 1% while the SOX declined. Six days later 76% of the instances were losers and the average occurrence was nearly a 3% loss. That seems to be a fairly
  • Parsimony [CSS Analytics]

    Note: James Picerno of The Capital Spectator recently did an interesting piece evaluating the Self-Similarity Metric and provides some R code which is valuable for many of our readers. The principle of parsimony relates to being frugal with resources such as money or the use of computing time. It is closely tied to the principles of simplicity, elegance and efficiency. It also complements the phil
  • Lessons from the Flash Crash regulatory fiasco [Mathematical Investor]

    On April 21, 2015, the U.S. Department of Justice announced that it would press criminal charges against Mr. Navinder Singh Sarao, a 36-year-old small-time British day-trader. He is being blamed for nothing less than causing the Flash Crash of May 6, 2010, the second largest point swing (1010.14 points) and the biggest one-day point decline (998.5 points) in the history of the Dow Jones

Quantocracy’s Daily Wrap for 04/26/2015

This is a summary of links featured on Quantocracy on Sunday, 04/26/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Blast Buy & Hold with this simple Bollinger Band strategy [Better System Trader]

    In Episode 4 of the Better System Trader podcast, Nick Radge discusses some trading ideas hes used to create profitable systems. He mentions a Bollinger Band idea which is also published in his book Unholy Grails. Nick says: the strategy that we did test and showed very promising results was an entry using a Bollinger band and an exit using the opposite Bollinger band, but we use 3 standard
  • Academic Finance Research [Alpha Architect]

    Asset Allocation: Is it better to allocate portfolios to factors rather than to assets? (Cocoma, Czasonis, and etal) Tactical Asset Allocation with Market Valuations: Cant even beat the simple 60/40 rule?? (Estrada) More on Smart Beta ETFs: How Smart are Smart Beta ETFs? Analysis of Relative Performance and Factor Timing (Glushkov) Are Smart Beta ETFs a Threat to Active Fund
  • Do Iron Butterflies Need to be Adjusted? [DTR Trading]

    This post will be a quick diversion from the iron condor posts. You may have noticed on my Twitter feed that I have been running backtests on iron butterflies, straddles, and strangles, using a range of entry and exit criteria. Today we will take a look at some statistics of a medium term, 43 days to expiration (DTE), iron butterfly on the SPX, to see how different wing widths and exits impact the
  • What Works Best? Update [CXO Advisory]

    Weve updated What Works Best? to incorporate some recent research summaries and adjust interpretation of the body of research.

Quantocracy’s Daily Wrap for 04/20/2015

This is a summary of links featured on Quantocracy on Monday, 04/20/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 04/17/2015

This is a summary of links featured on Quantocracy on Friday, 04/17/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Academic Finance Research [Alpha Architect]

    Understanding Dual, Relative, and Absolute Momentum (Gary Antonacci) Long-short Strategy Simulation based on Front-Page Articles in the WSJ (Matthies and Liu) Am I My Peers Keeper? Social Responsibility in Financial Decision Making (Fulbrunn and Luhan) Employees Will Work Harder Under Loss Contracts than Under Gain Contracts? (Imas, Sadoff and Samek) Are Mutual
  • Bond/Utility Divergence a Warning Sign…for the S&P 500? [Dana Lyons]

    Given their relatively high yields, utility stocks have long been thought of as proxies, or at least competition, for bonds. And while that relationship is often overplayed (utility stocks are first and foremost, stocks), there is some credence to the notion. Since 1970, there is a 26% positive correlation in 2-month returns between 10-Year Treasuries and the Dow Jones Utility Average (
  • If US Stocks Are Expensive, How Do I Protect Myself? [Meb Faber]

    There is a lot of talk about stocks being expensive, but also a lot of people not really doing anything about it. Many simply dont know how to tackle the problem, and others dont want to think about it at all. Below, for some perspective, are historical returns to stocks since 1970 and the 10 worst months for the S&P. On average youre looking at a 11% decline, and that only happen
  • Logical Invest at the Silicon Valley chapter of the AAII & upcoming Webinars [Logical Invest]

    Logical Invest at the Silicon Valley chapter of the AAII & upcoming Webinars What an audience and what an experience! Thanks AAII Silicon Valley! As announced some weeks ago, on April 11 we hosted our first conference at the Silicon Valley chapter of the AAII (American Association of Individual Investors) in San Jose, CA. Sharing and discussing some of th
  • New related paper to #5 – FX Carry Trade [Quantpedia]

    Investors based in different countries earn different returns on same strategies because the same risks covary differently with countries' stochastic discount factors (SDFs). We document that investors in low-interest-rate countries earn more than those in high-interest-rate countries on identical carry trade strategies. We propose a novel econometric procedure to estimate country-speci
  • 1292 Days and Counting Since Last 10% Correction [Almanac Trader]

    Alright, so the S&P 500 declined 1.1% today. That is the worst daily decline since March 25, 2015 when it fell 1.46%. Within this context, todays loss seems far less worrisome than you probably heard today. But, with the current bull market well above average duration and performance since 1949 some jitteriness is to be expected. Plus it has been nearly four years since S&P 500 started
  • Forex Trading Diary #4 – Adding a Backtesting Capability [Quant Start]

    I've been busy working on the open-source QSForex system over the past week. I've made some useful improvements and I thought I'd share them with you in this forex trading diary update. In particular, I've made the following changes, which will be discussed at length in this entry: Modification to the Position object to fix an error with how position openin
  • Implied Skew Strategy [John Orford]

    Previously, I checked whether historical skewness was a good indicator to buy and sell the S&P 500. My backtesting framework can now use the implied skew index as an indicator to buy or sell. Now, the strategy buys the S&P 500 if the implied skew index has dropped day over day and vice versa. Note that the S&P 500's implied skew is permanently nega
  • Part 2: Using a Self-Similarity Metric with Intraday Data to Define Market Regimes [CSS Analytics]

    The Self-Similarity metric has been a popular series. Recently the original post was shared on Jeff Swansons popular site System Trader Success which covers a wide variety of thought provoking articles on trading system development and is worth reading. Jeff has also posted some TradeStation code for the indicator which some readers may find valuable. In a great example of vertical blogging, a
  • Graham Value Portfolio Update [Scott’s Investments]

    In January 2012 I announced a new portfolio, a Benjamin Graham inspired value stock portfolio. The Graham portfolio is an attempt to add a value strategy to Scotts Investments, which is otherwise focused on momentum, trend, income and market timing strategies. The portfolio tracks returns for a portfolio of 15 stocks selected based on a variety of valuation metrics. The criteria used to

Quantocracy’s Daily Wrap for 04/16/2015

This is a summary of links featured on Quantocracy on Thursday, 04/16/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Optimised CRBM Code for Gaussian Units [Dekalog Blog]

    Over the last few weeks I have been working on optimising the conditional restricted boltzmann machine code, with a view to speeding it up via a C++ .oct file, and in the code box below is this .oct code for the gaussian_crbm.m code in my previous post. This gaussian_crbm.m function, plus the binary_crbm.m one, are the speed bottlenecks whilst training the crbm. In the code below I have made some
  • Does This VIX Signal Indicate Trouble Ahead? [Adam Warner]

    Time for investors to go to the mattresses (again)? This, from CNBC: "Most investors have never heard of the three-month volatility index, which is known as the VXV. But the relationship between the CBOE three-month volatility index and the options exchange's more familiar 30-day volatility index, the VIX, may signal trouble for stocks. "Like the VIX, the VXV is a measure of
  • Fed needs to walk a thin tightrope ahead of 2016… [Almanac Trader]

    One clear headwind that exists for the market is the first Fed funds rate increase since June 2006. That 0.25% rate hike nudged the target rate to 5.25% and marked the last move in a major tightening cycle that began in June 2004. Including this cycle, there have been five major Fed cycles (up and down) since 1973. A major Fed cycle is defined as the overarching Federal Reserve policy with respect
  • Social data research links: oil prices, real estate, and power laws [MKTSTK]

    Oil price volatility and oil-related events: An Internet concern study perspective [ResearchGate] This paper investigates the effects of four types of oil-related events on world oil prices, using an event study methodology and an AR-GARCH model. The Internet information concerning these events, which is derived from search query volumes in Google, is introduced in an analytical framework to ident
  • The Relationship Between CAPE and Returns [EconomPic]

    As I outlined in my previous post The Relationship Between Stocks and Bonds, the S&P 500 yields 3.7% at the current 27 CAPE (cyclically adjusted P/E), attractive from a relative basis to the sub 2% yield of the ten-year treasury. That said, a 3.7% yield is quite low by historical standards. Below is a framework for thinking about why returns should be expected to be lower AND more volatile
  • Nikkei 225 daily returns heatmap [UK Stock Market Almanac]

    This article concerns the daily returns for the Nikkei 225 from 1984. Average daily returns The following table shows the average return since 1984 of the Nikkei 225 Index for each day of the year. For example, over the last 30 years the average daily return for the Nikkei 225 on 4 January has been 0.38%. In the table, positive average daily returns are coloured green, while negative average retur
  • When VIX traders bet on a rise in volatility $SPY $VXX [@NautilusCap]

    When VIX traders bet on a rise in volatility $SPY $VXX
  • Some Seasonal Strength Could Help Today [Quantifiable Edges]

    While most people are not fond of tax day in the US, it has historically seen strong inflows into IRAs and hence the stock market. This has set up the day after tax day as a strong day for the market. Below is a look at how SPX has done since 1981 on tax day. The numbers are all impressive. They suggest a seasonal wind at the markets back today. Want research like this delivered directly to
  • A Tutorial in R on Using A Hidden Markov Model (HMM) [Inovance]

    Knowing how different market conditions affect the performance of your strategy can have a huge impact on your returns. Certain strategies will perform well in highly volatile, choppy markets while others need a strong, smooth trend or they risk long periods of drawdown. Figuring out when you should start or stop trading a strategy, adjusting your risk and money management techniques, and even set