Quantocracy

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Quantocracy’s Daily Wrap for 12/25/2015

This is a summary of links featured on Quantocracy on Friday, 12/25/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Build Better Strategies! Part 2: Model-Based Systems [Financial Hacker]

    Trading systems come in two flavors: model-based and data-mining. This article deals with model based strategies. The algorithms are often astoundingly simple, but properly developing them has its difficulties and pitfalls (otherwise anyone would be doing it). Even a significant market inefficiency gives a system only a relatively small edge. A little mistake can turn a winning strategy into a

Quantocracy’s Daily Wrap for 12/24/2015

This is a summary of links featured on Quantocracy on Thursday, 12/24/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • High noon for 2015 market prophets [Mathematical Investor]

    When a prophet speaketh, if the thing follow not, nor come to pass, the prophet hath spoken it presumptuously: thou shalt not be afraid of him. [Deuteronomy 18:22]. In a December 2014 Math Investor blog, we assessed how 2014 market prophets had fared (answer: not very well). Thus with the holiday season once again upon us, it is time to check scores. So how have 2015 prophets performed?
  • VBA Swap Pricing [Smile of Thales]

    VBA and Quant finance This article is actually a first part of an introductory course to VBA coding, given at Solvay School of Economics in Feb. 2014. The Excel sheet and VBA swap pricing code are attached. Visual Basic for Applications (VBA) is not trendy, properly speaking, in the financial industry. It is however massively used in many institutions for several reasons. People naturally
  • Stock Returns Around New Year s Day [CXO Advisory]

    Does the New Years Day holiday, a time of replanning and income tax positioning, systematically affect investors in a way that translates into U.S. stock market returns? To investigate, we analyze the historical behavior of the S&P 500 Index during the five trading days before and the five trading days after the holiday. Using daily closing levels of the S&P 500 Index around New
  • AmiBroker Code for the Breadth Indicator [Throwing Good Money]

    As per request, Im including the AmiBroker code for the 30% up/down last quarter in the Russell 3000 index indicator. I REALLY need to come up with a better name for it than that. How about the Haines Breadth Indicator? No, thats stupid. Magic Matts Mystical Meter? Uhsure. Its a two step process. You must do a scan every day, or as frequently as you want accurate data. It

Quantocracy’s Daily Wrap for 12/23/2015

This is a summary of links featured on Quantocracy on Wednesday, 12/23/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 12/22/2015

This is a summary of links featured on Quantocracy on Tuesday, 12/22/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book Added: 25 Recipes for Getting Started with R [Amazon]

    R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression. You'll find recipes on reading data files, creating data frames,
  • ZIRP, And The Factors That Launched 1,000 ETFs [Investor’s Field Guide]

    The rise of smart betaor more broadly, factor investinghas coincided with a 6 year period of zero interest rates. During this period, factors have been particularly ineffective relative to longer term results. Using publicly-available data (Ken French) we can explore the recent results for the most popular stock selection factors and compare them to longer-term periods of both rising and
  • Using Market Breadth To Gauge Market Health (Part 5) [Throwing Good Money]

    This is part 5 of a multi-part series examining the use of market breadth indicators to judge the state of the market. For an overview of what Im doing, youd best start here so you can catch up: PART 1CLICK HERE. And oh yeah, we finally have an indicator that beats our baseline! Just coincidence that I left this one until the end? Perhaps This next market breadth indicator counts all
  • US Recession Callers Are Embarrassing Themselves [Macrofugue]

    Through a combination of quackery, charlatanism, and inadequate utilisation of mathematics, callers for US recession in 2016 are embarrassing themselves. Again. The most prominent reason for recession calling may well be the Institute of Supply Managements Manufacturing Purchasing Manager Index. The problem with this recession forecasting methodology is that it doesnt work. Figure 1: ISM PMI
  • In Search of Sustained Success [Systematic Relative Strength]

    How do you rate an NBA team across a decade of play? One method is Elo, a simple measure of strength calculated by game-by-game results (Source: Nate Silvers FiveThirtyEight). A description of Elo is below: Elo ratings have a simple formula; the only inputs are the final score of each game, and where and when it was played. Teams always gain Elo points for winning. But they get more

Quantocracy’s Daily Wrap for 12/21/2015

This is a summary of links featured on Quantocracy on Monday, 12/21/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Last Two Weeks [Quantocracy]

    The best quant mashup links for the two weeks ending Saturday, 12/19 as voted by our readers: Using the LASSO to Forecast Returns [Alex Chinco] pysystemtrade [Investment Idiocy] Why Does Dual Momentum Outperform? [Dual Momentum] Why doesnt the choice of performance measure matter? [MathFinance.cn] We also welcome three blogs making their first ever appearance on the mashup: Using Market Breadth
  • Returns don’t mean revert, fundamentals do [Flirting with Models]

    While prior 5-year returns for the S&P 500 have been spectacular, prior 10-year returns are still muted. Does this mean the bull market still has room to run? Prior returns, however, are not a great predictor of future returns. Fundamentals, not returns, tend to be mean-reverting. Current fundamentals are historically expensive: Shiller PE currently sits in the 89th percentile. This implies
  • Using Market Breadth to Gauge Market Health (part 4) [Throwing Good Money]

    Welcome to Part 4 of this series. Were still trying to find a market breadth indicator that gives a better health assessment than using a simple moving average on SPY. For a description of what the heck Im doing, please go back and read the first post (and the subsequent ones too): Using Market Breadth to Gauge Market Health (part 1) Back when momentum and dinosaurs ruled the earth (instead
  • Present-day great statistical discoveries [Eran Raviv]

    Some time during the 18th century the biologist and geologist Louis Agassiz said: Every great scientific truth goes through three stages. First, people say it conflicts with the Bible. Next they say it has been discovered before. Lastly they say they always believed it. Nowadays I am not sure about the Bible but yeah, it happens. I express here my long-standing and long-lasting admiration

Quantocracy’s Daily Wrap for 12/17/2015

This is a summary of links featured on Quantocracy on Thursday, 12/17/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Why Does Dual Momentum Outperform? [Dual Momentum]

    Those who have read my momentum research papers, book, and this blog should know that simple dual momentum has handily and consistently outperformed buy-and-hold. The following chart shows the 10- year rolling excess return of our popular Global Equities Momentum (GEM) dual momentum model compared to a 70/30 S&P 500/U.S. bond benchmark [1]. Results are hypothetical, are NOT an indicator of
  • Momentum: Slip Counterfactuals, the “Stale Price” Effect, and the Future [Philosophical Economics]

    The recent piece on the dangers of backtesting has attracted an unusual amount of attention for a piece on this blog. I'd like to thank everyone who read and shared the piece, and also those who offered up commentary on it. To be clear, my intent in presenting the Daily Momentum example was not to challenge the Fama-French-Asness momentum factor in specific, or the phenomenon of momentum in
  • Time-Series vs. Cross-Sectional Implementation of Momentum, Value and Carry Strategies [Quantpedia]

    We contrast the time-series and cross-sectional performance of three popular investment strategies: carry, momentum and value. While considerable research has examined the performance of these strategies in either a directional or cross-asset settings, we offer some insights on the market conditions that favor the application of a particular setting. Notable quotations from the academic research
  • Avoid Firms with CFOs that Golf All the Time [Alpha Architect]

    Chief financial officers are responsible for managing the financial reporting process. We test whether the quality of a firms financial reports is a function of the effort expended by the CFO. Using golfing records to measure leisure consumption, we first show that CFOs consume more leisure when they have lower economic incentives to work. We show further that higher levels of CFO leisure are
  • Historical SPX Performance When Rates Start To Rise [Quantifiable Edges]

    Fed announcing Wednesday that they will begin raising rates for the 1st time in 11 years. Since 1990 there have only been 4 other cycles of rate hikes. I decided to measure SPX performance from the start of those cycles. I found that one month later the stock market was trading lower every time. But one year later it was higher every time. Individual returns (based on $100k/trade) can be found in

Quantocracy’s Daily Wrap for 12/16/2015

This is a summary of links featured on Quantocracy on Wednesday, 12/16/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Financial Backtesting: A Cautionary Tale [Philosophical Economics]

    Consider the following market timing strategy, which well call daily momentum: (1) If the markets total return for the day, measured from yesterdays close to todays close, is positive, then buy the market at todays close and hold for one day. (2) If the markets total return for the day, measured from yesterdays close to todays close, is negative, then sell the market
  • Using Market Breadth to Gauge Market Health (part 2) [Throwing Good Money]

    Welcome to part two of an ongoing series, where I look at different breadth indicators and their viability in describing market health. You can read and should read! the introductory post here: Using Market Breadth to Gauge Market Health (part 1) So last post, we (ok, I, since Im doing all the work around here) established a baseline by using a moving average of SPY to tell us
  • Relationships between Factors [Factor Wave]

    It is impossible to obtain pure factor exposure. All stocks are exposed in some way to all factors. Further, the factors are all inter-related so by trying to obtain exposure to one factor in particular you will tend to get a certain type of exposure to the other factors. Very broadly Value has a negative relationship with momentum. Value has a positive relationship with (small) size.
  • Equity Curve Correlation Analysis [Alvarez Quant Trading]

    A reader recently asked how to do equity curve correlation. For detailed information on correlation you can read Correlation and dependence or for simpler explanation read Correlation at Math is Fun. For steps on how to do this in Excel, which is where of course I did it, read Correlation at Excel Easy. I will cover here how one can correlation analysis between equity curves. Correlation
  • Using Market Breadth to Gauge Market Health (part 1) [Throwing Good Money]

    We all want to know if it's the right time to trade. And we'd also like to know which direction. So for at least the last two months like forever, investors have tried to come up with ways to judge how the market is doing. One technique is to use market breadth as an indicator. There are a number of ways of doing this, but the basic idea is that you look at ALL the stocks in a particular
  • RUT Straddle – 59 DTE – Results Summary [DTR Trading]

    This is the fourth article in a series looking at the backtest results of selling at-the-money (ATM) options straddles on the Russell 2000 index (RUT). For background on the setup for the backtests, as well as the nomenclature used in the tables below, please see the introductory article for this series: Option Straddle Series – P&L Exits This post reviews the backtest results for 4120 options
  • Horrific Breadth For A Rally [Dana Lyons]

    Despite yesterdays rally in the major indices, the underlying breadth statistics were historically weak. After a steep selloff to begin the day yesterday, the stock market rallied late to close with solid gains. At least, the major large-cap averages did. The broader, smaller-cap indices mostly closed with losses on the day. Furthermore, the markets internals, e.g., Advance-Declines and New

Quantocracy’s Daily Wrap for 12/14/2015

This is a summary of links featured on Quantocracy on Monday, 12/14/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Building a backtesting system in Python: or how I lost $3400 in two hours [Jon.IO]

    This is the another post of the series: How to build your own algotrading platform. Building a backtest system is actually pretty easy. Easy to screw up I mean. Even though there are tons of excellent libraries out there (and we'll go through them at some point), I always like doing this on my own in order to fine-tune it. From all the backtesting systems I have seen, we can assume that there
  • Don t Blame Lack Of Dispersion [Larry Swedroe]

    In a recent article, Advisor Perspectives editor Robert Huebscher noted: During the last 40 years, an average of 60% of equity funds underperformed the S&P 500. But, according to the SPIVA data, 86.4% of large-cap managers underperformed their benchmark in 2014. The percentages were not much better last year for mid-cap (66.2%) or small-cap (72.9%). The article goes on to cite work by
  • When ingredients spoil [Flirting with Models]

    Summary We break portfolio construction into two unique phases: signal generation and the rules that determine allocations. We use the analogy that this process is like cooking, where our signals are the ingredients and our allocation rules are the recipe. While most firms focus their research on generating the best ingredients, we believe it is important to acknowledge up front that the
  • A Poor Man’s Magic Formula [Relative Value]

    Here's a python script I made to rank stocks according to their return on equity and trailing EV/EBITDA. I have named it the poor mans magic formula because all of the fundamental data is scraped from yahoo finance. Yahoo are friendly enough to provide this data for 'free' but have been known to block ip addresses that make too many requests in one day (15k+). Unfortunately neither

Quantocracy’s Daily Wrap for 12/13/2015

This is a summary of links featured on Quantocracy on Sunday, 12/13/2015. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Interview with Michael Bryant [Better System Trader]

    Creating robust trading strategies can be a difficult task, sometimes taking months or even years to generate something you find acceptable. Even then, once you start trading it live there is no guarantee itll work in the future. With strategy creation being such an involved process at times, how would you like it if you could just tell the computer the results you wanted and let it figure out
  • Maintaining a database of price files in R [R Trader]

    Doing quantitative research implies a lot of data crunching and one needs clean and reliable data to achieve this. What is really needed is clean data that is easily accessible (even without an internet connection). The most efficient way to do this for me has been to maintain a set of csv files. Obviously this process can be handled in many ways but I found very efficient and simple overtime to
  • The Halloween effect with python and pandas [Shifting Sands]

    The Halloween effect, aka sell in May and go away is the observation that equity market returns tend to be worse over summer time in the northern hemisphere. Anyone who has followed markets for a while has probably noticed a distinct lull over the summer period. But can we quantify this effect, does it really exist? We can and it does, and its simple to show with less than 10 lines of
  • Crude Oil and Trend Following [Wisdom Trading]

    Crude oil has been in the news a lot recently. Just last week, after the OPEC meeting, its price declined by over 10%. With a lot of volatility, we wanted to test how a trend following strategy would have performed on the futures contract in recent history. Here is a quick post showing our benchmark Wisdom State of Trend Following system and the performance it would have produced on a