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Quantocracy’s Daily Wrap for 05/13/2016

This is a summary of links featured on Quantocracy on Friday, 05/13/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How Portfolio Construction Affects Value Funds [Alpha Architect]

    Value investing is an investment philosophy that has been extensively discussed and examined at least since the days of Ben Graham, who popularized it as a discipline in the 20s and 30s. While there are some who are dismissive of its advantages as a long-term strategy, the historical evidence is compellingly clear: Cheap stocks beat expensive stocks over time (see our simulation study as an

Quantocracy’s Daily Wrap for 05/12/2016

This is a summary of links featured on Quantocracy on Thursday, 05/12/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Deep Learning with Theano – Part 1: Logistic Regression [Quant Start]

    Over the last ten years the subject of deep learning has been one of the most discussed fields in machine learning and artificial intelligence. It has produced state-of-the-art results in areas as diverse as computer vision, image recognition, natural language processing and speech recognition. However it has also been widely hyped – the answer to all machine learning problems – and is often
  • Heatmaps in R [Quant Finance Academy]

    In exploratory data analysis, we often need to visualize our data in different formats, in order to gain more understanding about the numbers and the relationship between the parameters. One such wonderful and informative representation is the Heatmap, which is basically a colored image, the colors explain the strength of the relationship between two parameters. It normally has a dendogram

Quantocracy’s Daily Wrap for 05/11/2016

This is a summary of links featured on Quantocracy on Wednesday, 05/11/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Cliff Asness’s (AQR) View on Factor Timing [Quantpedia]

    Everyone seems to want to time factors. Often the first question after an initial discussion of factors is ok, whats the current outlook? And the common answer, the same as usual, is often unsatisfying. There is powerful incentive to oversell timing ability. Factor investing is often done at fees in between active management and cap-weighted indexing and these fees have been falling
  • How To Compute Turnover With Return.Portfolio in R [QuantStrat TradeR]

    This post will demonstrate how to take into account turnover when dealing with returns-based data using PerformanceAnalytics and the Return.Portfolio function in R. It will demonstrate this on a basic strategy on the nine sector SPDRs. So, first off, this is in response to a question posed by one Robert Wages on the R-SIG-Finance mailing list. While there are many individuals out there with a
  • State of Trend Following in April [Au Tra Sy]

    The state of trend following was negative last month, as it was in March. The index is now just above the zero-line for the year, back from nearly the +20% mark a month and a half ago. Please check below for more details. Detailed Results The figures for the month are: April return: -2.35% YTD return: 2.54% Below is the chart displaying individual system results throughout April:

Quantocracy’s Daily Wrap for 05/10/2016

This is a summary of links featured on Quantocracy on Tuesday, 05/10/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

Quantocracy’s Daily Wrap for 05/09/2016

This is a summary of links featured on Quantocracy on Monday, 05/09/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Motivation: Why Do I Blog? [Quantocracy]

    A common concern I hear from many in our community of quantitative bloggers is defining their motivation to write for the long-term. Most begin writing without knowing what to expect, just happy to take a break from crunching numbers to interact with actual humans. Sometimes that optimism wanes though when the realities of lifes other responsibilities begin to pull at their time. Throw in a
  • Alternative Beta can be Great: But Beware of Data-Mining! [Alpha Architect]

    We investigate the biases in the backtested performance of alternative beta strategies using a sample of 215 commercially promoted trading strategies across five asset classes. Our results lend support to the cautions in recent literature regarding backtest overfitting and lack of robustness in trading strategy performance during the live period (out of sample). We report a median 73%
  • The two sources of outperformance [Flirting with Models]

    This blog post is available for download here. Summary When a manager outperforms, it implies that other investors have underperformed. In understanding an investment process, we believe it is critical to understand the source of this outperformance to determine whether it is sustainable or not. We believe there are two key sources of outperformance: exploiting investor behavior and being

Quantocracy’s Daily Wrap for 05/07/2016

This is a summary of links featured on Quantocracy on Saturday, 05/07/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Relative Strength Index (RSI) Model | Trading Strategy (Entry) [Oxford Capital]

    I. Trading Strategy Developer: Larry Connors (The 2-Period RSI Trading Strategy), Welles Wilder (RSI Momentum Oscillator). Source: (i) Connors, L., Alvarez, C. (2009). Short Term Trading Strategies That Work. Jersey City, NJ: Trading Markets; (ii) Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Greensboro: Trend Research. Concept: The long equity trading system based on the

Quantocracy’s Daily Wrap for 05/05/2016

This is a summary of links featured on Quantocracy on Thursday, 05/05/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How to Learn Advanced Mathematics Without Heading to University – Part 2 [Quant Start]

    In the last article in the series we looked at the foundational courses that are often taken in a four-year undergraduate mathematics course. We saw that the major courses were Linear Algebra, Ordinary Differential Equations, Real Analysis and Probability. In the "second year" of our self-study mathematics degree we'll be digging deeper into analysis and algebra, with discussions on
  • The Academic Finance Papers That Changed My Mind [Alpha Architect]

    What does it mean to be the best research? For me, this means the most influential in changing my view on the world. So the below list of best research represents the research that 1) changed my view of the world 2) helped sharpen my thinking. For context, Ive been reading source journal finance research for over 15 years. In the early days it would take me a week to grasp a paper,

Quantocracy’s Daily Wrap for 05/03/2016

This is a summary of links featured on Quantocracy on Tuesday, 05/03/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Backtesting Strategies with R (h/t algotrading Reddit) [Tim Trice]

    This book is designed to not only produce statistics on many of the most common technical patterns in the stock market, but to show actual trades in such scenarios. Test a strategy; reject if results are not promising Apply a range of parameters to strategies for optimization Attempt to kill any strategy that looks promising. Let me explain that last one a bit. Just because you may find a strategy
  • Get Rich Slowly [Financial Hacker]

    Most trading systems are of the get-rich-quick type. They exploit temporary market inefficiencies and aim for annual returns in the 100% area. They require maintenance, supervision, and regular adaption to market conditions. Their expiration is often accompanied by large losses. But what if youve nevertheless collected some handsome gains, and now want to park them in a more safe haven? Put the
  • Forecast averaging example [Eran Raviv]

    Especially in economics/econometrics, modellers do not believe their models reflect reality as it is. No, the yield curve does NOT follow a three factor Nelson-Siegel model, the relation between a stock and its underlying factors is NOT linear, and volatility does NOT follow a Garch(1,1) process, nor Garch(?,?) for that matter. We simply look at the world, and try to find an apt description of
  • Further dip in April for Trend Following [Wisdom Trading]

    Another down month for the index, with a slight loss. Two mild down months after two strong up months keep the index in positive territory for 2016. Below is the full State of Trend Following report as of last month. Performance is hypothetical. Chart for April: WSTF-201604-Index And the 12-month chart: WSTF-201604-Index-12months Below are the summary stats:

Quantocracy’s Daily Wrap for 05/01/2016

This is a summary of links featured on Quantocracy on Sunday, 05/01/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • New Book Added: Elements of Statistical Learning (h/t @Robot_Wealth) [Amazon]

    During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics.
  • Index Investing Makes Markets and Economies More Efficient [Philosophical Economics]

    U.S. equity index funds have grown dramatically in recent decades, from a negligible $500MM in assets in the early 1980s to a staggering $4T today. The consensus view in the investment community is that this growth is unsustainable. Indexing, after all, is a form of free-riding, and a market can only support so many free-riders. Someone has to do the fundamental work of studying securities in