Quantocracy

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Quantocracy’s Daily Wrap for 03/16/2016

This is a summary of links featured on Quantocracy on Wednesday, 03/16/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Corey’s Take: Building a Portfolio for ReSolve s March Madness Challenge [Flirting with Models]

    The team over at ReSolve recently posted about their very unique March Madness Challenge. The crux of their idea is that the rules governing a more traditional bracket system is fundamentally flawed since it inherently reduces the sample size upon which skill is measured. For example, nearly everyone in the bracket will choose the #1 seed to beat the #16 seed in each region, eliminating the
  • Never Book a Loss (And Why That s Bad For You) [Throwing Good Money]

    I have got a great trading system for you. I mean, look at that equity curve! Its very straight, no drawdowns, and $30,000, compounded, became almost $120,000 over time. Whats the catch? They say (and Im not sure who they are) that the average retail investor hates to book a loss, and takes profits too soon. The reverse of the cut your losses early and let your profits run
  • Adding Stops and Scaling Out to a Mean Reversion Strategy [Alvarez Quant Trading]

    I came on an idea recently that I had tested. I have tested adding max loss stops to a mean reversion strategy, with no success. See this post for more on that. About eight years ago, I tested scaling out of trades. But this person claimed that adding the two together was how to improve a mean reversion strategy. Interesting idea I had not tested. I have a one question poll below about what to do
  • The Seven Deadly Sins of Quantitative Data Analysts [Quandl]

    Sooner or later, every quant is tempted by forbidden fruit. These all-too-human traits can permeate even the most sophisticated analysis. Keep these tips in mind as you develop strategies, and you just may turn vice into virtue. Quandl_7_sins_v04 (1) Download the printable version here.
  • Price Breakout with NR7 | Trading Strategy (Filter & Exit) [Oxford Capital]

    I. Trading Strategy Developer: Toby Crabel (Setup: NR7 Pattern); Laurence A. Connors, Linda B. Raschke (Entry: Price Breakout with NR7). Source: (i) Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc; (ii) Laurence A. Connors, Linda B. Raschke (1995). Street Smarts | High Probability Short Term Trading Strategies. M. Gordon
  • Testing The Beta Premise [Larry Swedroe]

    One of the most important issues in finance concerns the relationship between risk and expected return. John Lintner, William Sharpe and Jack Treynor are generally given most of the credit for introducing the first formal asset pricing model, the capital asset pricing model (CAPM), which was developed in the early 1960s. The CAPM provided the first precise definition of risk and how it drives
  • Limits of Machine Learning Part 2 [MKTSTK]

    Last weeks podcast was pretty negative on the value of machine learning in trading, so this week I wanted to provide my own counterpoint and explore life within the limits I identified earlier. Specifically, I wanted to begin mapping the things machine learning algorithms might really be great at doing in the world of trading and finance. This podcast is presented in a slightly different manner

Quantocracy’s Daily Wrap for 03/13/2016

This is a summary of links featured on Quantocracy on Sunday, 03/13/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Understanding Modern Portfolio Construction (h/t @AbnormalReturns) [Pragmatic Capitalism]

    My newest research paper, Understanding Modern Portfolio Construction, is available on SSRN. This paper is the culmination of years of work and I consider it to be the most important piece of research Ive published. I wrote this paper in much the same way that I wrote my paper, Understanding the Modern Monetary System, however, since Im not an academic economist, this paper is more along the

Quantocracy’s Daily Wrap for 03/12/2016

This is a summary of links featured on Quantocracy on Saturday, 03/12/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Careers in Quantitative Finance [Quant Start]

    "I'm actually really optimistic about the future of quants. The industry is more technical than ever, and there is as much need to understand the risks in the system as ever." – Robert C. Merton, quoted in "Risk," August 2012 In 1997, when Robert Merton won the Nobel Prize in Economics for his work on the Black-Scholes option pricing formula, the demand in the finance
  • Yes, Virginia, the Markets are Mean-Reverting [Throwing Good Money]

    Heres a stupid system. In fact, I call it the Stupid 10 Days system. You look at the last ten days of trading. If the market at the closing bell is up from the market close of 10 days ago, you buy at the next open. You hold for 10 days, then sell at the next open. A classic momentum play. Wash, rinse, repeat. And remember, you have that uncle who owns a brokerage, so you dont have to

Quantocracy’s Daily Wrap for 03/10/2016

This is a summary of links featured on Quantocracy on Thursday, 03/10/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Some Limits of Machine Learning in Trading [MKTSTK]

    Aka my first podcast. Sorry Ive been AWOL for so long; Ive been deep in the lab working on my creation. As my work-life balance has careened towards work, I have found it difficult to sit down and write like I used to, so I am giving this whole podcast thing a try So without further ado, I present a thought which occurred to me whilst gazing at the bay, why is machine learning so hard in
  • What You Don t Want to Hear About Dividend Stocks [Meb Faber]

    When was the last time you had an idea that resulted in the threat of your torture? In the early 1600s, Galileo was expanding upon Copernicus idea that the earth revolves around the sun. The easy-going church was slightly less than enthused. In short, things escalated The Pope got involved There was a trial The threat of torture Eventually, Galileo was found vehemently suspect of
  • Quant Nerds Can Be Fun Too: We’re Hosting a March Madness Challenge [GestaltU]

    This is cross-posted from SkewU, our sister blog. We dont normally do this sort of thing, but this is important because: 1. You should check out SkewU, as its quite a bit different than GestaltU. Our posts over there are more diverse and whimsical if thats something that interests you. 2. And more importantly, standard March Madness bracket rules are the most awful, terrible, nonsensical,
  • Trading the Presidential Election [Jonathan Kinlay]

    There is a great deal of market lore related to the US presidential elections. It is generally held that elections are good for the market, regardless of whether the incoming president is Democrat or Republican. To examine this thesis, I gathered data on presidential elections since 1950, considering only the first term of each newly elected president. My reason for considering first terms only

Quantocracy’s Daily Wrap for 03/09/2016

This is a summary of links featured on Quantocracy on Wednesday, 03/09/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Diversification and small account size [Investment Idiocy]

    I get occasional emails asking me to cover subjects in my blog (keep them coming! I will eventually get round to them). A pretty common one runs something like this: "I understand that diversification over instruments is the best way to improve returns- you trade almost 40 futures markets, and the likes of AHL and Winton trade hundreds. But how can someone with a small account trade enough
  • Why Python Algorithmic Trading is Preferred Choice Among Traders [Quant Insti]

    To survive in the age of robots-it is necessary to learn a programming language that makes your trading algorithms smarter and not just faster. Having knowledge of a popular programming language is the building block to becoming a professional algorithmic trader. It is not just enough if a person has love for numbers. Professionals need to put the logic using numbers into a software program to
  • A Closer Look At Ben Graham s “Net Current Asset Value” (NCAV) Rule [Quantpedia]

    Following Ben Grahams net current asset value (NCAV) rule for stock selection (net net strategy), we provide evidence that buying stocks in companies with per share NCAV greater than the current share price produced superior risk-adjusted returns over the 1975- 2010 period. The risk factors that explain the returns associated with these firms include market risk, market liquidity, a
  • Trend Following in February [Wisdom Trading]

    February 2016 Trend Following: UP +4.24% / YTD: +9.99% Another strong month for the trend following index, with a similar pattern to last month: a near-double-digit spike mid-month to finish close to +5% for the month. The YTD performance is already just 0.01% shy from the double-digit barrier. Below is the full State of Trend Following report as of last month. Performance is hypothetical. Chart
  • Sh** Happens (on Tuesday and Thursday Nights) [Throwing Good Money]

    This all started over the weekend, when I started wondering about a trade I had going. The trade hadnt hit my profit target on Friday and so carried over through the weekend. I started wondering about day-of-week seasonality and thought Id bust out the old charts and see whats up. Lets take a look at SPY from 2000 through the current date. If we buy on a given weekday at the open
  • Has the Value Investing Pain Train Ended? [Alpha Architect]

    Last year we highlighted what we deemed the value investing pain train. In 2015, cheap high-quality stocks started getting crushed by expensive junk stocks. Here is a recap of the carnage. In many respects, value investing is a lot like Terry Tate the huge office linebacker that would crush employees who made mistakes. His nickname: the pain train. SAT answer: Terry Tate is
  • State of Trend Following in February [Au Tra Sy]

    The strong January start carries on into February for the State of TF Index. The performance is already in double-digit territory for the Year-To-Date. Please check below for more details. Detailed Results The figures for the month are: February return: 3.59% YTD return: 12.51% Below is the chart displaying individual system results throughout February: StateTF February And in tabular format:

Quantocracy’s Daily Wrap for 03/08/2016

This is a summary of links featured on Quantocracy on Tuesday, 03/08/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • When Measures Become Targets: How Index Investing Changes Indexes [Investor’s Field Guide]

    In Vietnam, under French colonial rule, there was a rat problem. To solve the rat infestation, the French offered a bounty on rats, which could be collected by delivering a rats tail as proof of murder. Many bounties were paid out, but the rat problem didnt improve. Officials soon noticed rats running around without tailspeople were cutting off the tails and releasing the rats to breed,
  • NR7 Pattern | Trading Strategy (Setup & Exit) [Oxford Capital]

    I. Trading Strategy Developer: Toby Crabel (NR7 Pattern). Source: Crabel, T. (1990). Day Trading with Short Term Price Patterns and Opening Range Breakout. Greenville: Traders Press, Inc. Concept: Volatility cycles. Research Goal: Performance verification of the NR7 pattern. Specification: Table 1. Results: Figure 1-2. Trade Setup: The current daily range is narrower than the previous six days
  • Selected Interesting Papers from MFA Conference [MathFinance.cn]

    I just returned Beijing from the Midwest Finance Association 2016 Annual Meeting in Atlanta, it is my first time in America, and the life there is quite different from that in the British cities… few people in downtown, hard to go out without a car, people are less friendly (at least look like)… MFA annual conference provides a forum for the interaction of finance academics and practitioners
  • Estimating Return-Shortfall Risk For Portfolios [Capital Spectator]

    Failure isnt an option, but it happens. Modeling the possibility that a portfolio strategy will stumble isnt exactly cheery work, but its a productive and necessary exercise for stress testing what the future can do to the best-laid plans for investing. The good news is that theres a rainbow of options for estimating the potential for trouble. But its usually best to start with a

Quantocracy’s Daily Wrap for 03/07/2016

This is a summary of links featured on Quantocracy on Monday, 03/07/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Replicating Private Equity: the Impact of Return Smoothing [Alpha Architect]

    Having spent what seems like a lifetime in the financial industry at this point, Ive always had this nagging suspicion about private equity (PE): private equity investments are not special. And Ill take my hunch a bit further: public equity markets can deliver the same return profile as private equity. After all, you hear so many compelling stories about PE. PE investors have an information
  • Server -II- [Algorythmn Trader]

    In my previous post I announced that I want to try covering one feature in each post. During the days I doing this, I realized this would not work for me. I feel better in posting more frequent and discussing the code in smaller chunks. In this post I want to start creating the basic server application. Part 1: Service Host The first thing I had to deal with was the decision how to host the
  • ETFs: Process Matters As Much As Fees [Flirting with Models]

    Fees are always a prominent topic in ETF selection, but they are not the only cost associated with the product. Even with seemingly similar passive ETFs, different index construction methodologies can lead to widely varying performance. Taking a holistic view that incorporates both the investment process and the fee can lead to a selecting an ETF with a higher expense ratio if its investment
  • A Simple Measure of Overbought in NASDAQ is Suggesting a Pullback [Quantifiable Edges]

    Friday was the 4th day in a row that the NASDAQ closed higher. While this may not seem to be a big deal, it does not happen very often when the NASDAQ is trading below its 200-day moving average. The table below shows results following all times this has occurred since 2002. 2015-03-07 image1 Results here appears to be strongly bearish. And the edge persists for up to 2 weeks. The note at the

Quantocracy’s Daily Wrap for 03/06/2016

This is a summary of links featured on Quantocracy on Sunday, 03/06/2016. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Best Links of the Week [Quantocracy]

    These are the best quant mashup links for the week ending Saturday, 03/05 as voted by our readers: Quality is Rewarded: Clickthroughs vs Voting [Quantocracy] Machine learning for financial prediction: experimentation with Aronson's latest work – part 1 [Robot Wealth] Tech is Alpha [Cantab Capital] Dual Momentum and Dollar Cost Averaging [Dual Momentum] A Statistical Arbitrage Strategy in R
  • Machine Learning & SciKit Learn [Largecap Trader]

    I made the point to someone the other day that technology and coding is getting easier and easier to accomplish. I don't think I would have been able to perform 'machine learning' five years ago but with the resources available today (Python, SciKit Learn, and pages upon pages of StackOverflow) even someone like me can fit a model and build ML algorithms. Machine Learning is also
  • Podcast: Laurent Bernut – Part 2 [Better System Trader]

    Back in Episode 32 we had a chat with Laurent Bernut, a systematic short seller who spent years working in the Hedge Fund world specializing in short selling strategies. He shared loads of knowledge with us in that episode but we actually had a lot more to talk about. We ran out of time back then so in this episode were going to continue with the chat, covering a bit more on short selling,

Quantocracy’s Daily Wrap for 03/04/2016

This is a summary of links featured on Quantocracy on Friday, 03/04/2016. 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 1 [Robot Wealth]

    One of the first books I read when I began studying the markets a few years ago was David Aronson's Evidence Based Technical Analysis. The engineer in me was attracted to the 'Evidence Based' part of the title. This was soon after I had digested a trading book that claimed a basis in chaos theory, the link to which actually turned out to be non-existent. Apparently using
  • Advanced Trading Infrastructure – Portfolio Handler Class [Quant Start]

    In the current series on Advanced Trading Infrastructure we have described both the Position Class and the Portfolio Class – two essential components of a robust backtesting and live trading system. In this article we are going to extend our discussion to the Portfolio Handler Class, which will round out the description of the portfolio Order Management System (OMS). The OMS is the backbone of any
  • Trend Following Works [Larry Swedroe]

    The academic research has provided investors with strong evidence that there is a small group of factors-or sources of returns-that have provided higher returns over the long term. To be considered among this group, the evidence should have the following characteristics: Persistence-it holds across long periods of time and various economic regimes. Pervasive-it holds across countries, regions,
  • MiB: Emanuel Derman (h/t @AbnormalReturns) [Big Picture]

    In our latest Masters in Business podcast, we speak with quant and financial engineer Emanuel Derman. One of the first high-energy particle physicists to migrate to finance, he spent 17 years onWall Street, eventually becoming head of the renowned Quantitative Strategies group at Goldman, Sachs. At GS he co-developed the Black-Derman-Toy interest rate model and the Derman-Kani local volatility
  • What I’ve been reading… [Backtest Wizard]

    Was 2015 a hard year to make money if you were managing a portfolio of global asset classes? Absolutely! The Resolve Asset Management 2015 Annual Letter: "Navigating Active Asset Allocation When Diversification Fails", helps to explain why. You can read the summary of the letter and access the download link here. It's a fascinating piece of research which I would highly recommend