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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

Filed Under: Daily Wraps

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:

Filed Under: Daily Wraps

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!

  • Machine learning for financial prediction: experimentation with Aronson s latest work – part 2 [Robot Wealth]

    My first post on using machine learning for financial prediction took an in-depth look at various feature selection methods as a data pre-processing step in the quest to mine financial data for profitable patterns. I looked at various methods to identify predictive features including Maximal Information Coefficient (MIC), Recursive Feature Elimination (RFE), algorithms with built-in feature

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

Motivation: Why Do I Blog?

Blogging is hard. Quant blogging is even harder.

I sometimes hear from bloggers in our community that their motivation to blog has faded. Most begin writing with little expectation, just happy to take a break from crunching numbers to interact with actual humans. Sometimes that optimism wanes though when the realities of life’s other responsibilities begin to pull at their time. Throw in a healthy dose of the troll’foolery that comes with having an Internet presence, and folks sometimes question whether it’s all worth it.

As a denizen of this community, I want to encourage folks to continue writing. I’ve spoken with a number of the top bloggers on our mashup to understand both the tangible and intangible things that motivate them. Here are the eight motivators they shared, sorted from least to most tangible:

  • Sharing for the sake of sharing:

    There is a special breed of person who enjoys sharing simply for the sake of sharing. These are the generous souls who contribute to Stack Exchange and the like. But for many, it’s not enough.

  • A means to organize and archive one’s thoughts:

    Many analytical people, myself included, tend to be easily distracted by squirrels. A blog forces one to organize and archive one’s thoughts, closing a chapter on one subject before moving on to the next.

  • Collaboration with the community:

    Many of us work on our nerd toys in isolation, and seek the feedback and collaboration that comes with being part of a community. I hear mixed responses on this. I would summarize them as this: the Internet is mostly a “taking” as opposed to “giving” place. Don’t expect an army of collaborators. Expect a very small number of people who have the potential to make a real impact on your work.

  • Advertising/affiliate marketing:

    The reality is that our niche is too small to drive significant revenue. I would say that we have a reasonably successful site as far as quantitative stuff goes, but our primary source of revenue, our book library, generates less than $200 a month, essentially all of which goes to costs. You can certainly do better, but don’t expect much here.

  • Contract work:

    Some bloggers are having success with one-off contract work (consulting, strategy development, programming, etc.) that often turns into something much bigger. This one surprised me as I didn’t realize the scale on which it was happening.

  • Career building and networking:

    There have been A LOT of success stories here. Folks are finding solid jobs by treating their site as a portfolio of their workmanship. It makes me incredibly happy to know that, along with the “contract work” above, we’re playing a small part in improving lives in the offline world.

  • Managing money:

    A number of sites manage money in some form or fashion. While they may not technically solicit business through their sites, their workmanship is on display, something that I think is much more effective in finding more sophisticated clients than the traditional approach to sales.

  • Selling something:

    This is the most direct approach: books, software, subscriptions to strategies, subscriptions to member-only content. Note that there has been a lot written about the financial benefit (or lack thereof) of selling books the traditional way (i.e. Amazon + brick-and-mortar). In short, there’s not much money there, but it’s a means to drive some other revenue stream.

That’s it. I’m sure there are more, but these are what came out of my conversations. There is of course no one-size-fits-all answer, but as a denizen of this community I hope that authors define what motivates them so that we as a community don’t lose the benefit of their knowledge.

Mike @ Quantocracy

Filed Under: Site Announcements

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

Filed Under: Daily Wraps

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,

Filed Under: Daily Wraps

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:

Filed Under: Daily Wraps

Quantocracy’s Daily Wrap for 05/02/2016

This is a summary of links featured on Quantocracy on Monday, 05/02/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

    No new links posted.

Filed Under: Daily Wraps

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

Filed Under: Daily Wraps

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