This is a summary of links featured on Quantocracy on Monday, 06/26/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
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Struggling Quant Episode 1: How I lost USD 500,000 [Quant Journey]STRUGGLING QUANT episode 1: How I lost USD 500.000 while figuring out the link between questions, math, stats, coding and trading Say that you are 30 years old and you have a good 25 years to work hard. Instead of going down the easy way of working for someone else during the day and killing time in the evenings and weekends, you have chosen the hard path of quantitative trading and started the
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Trading Decisions of Your Stone Age Grandpa can Make You Money in Forex [Quant Journey]Why Ferrari or Rolex does not price their products at 149.999 or 12.999 but most of the items you see in your supermarket is priced like 4.99? Because Ferrari never likes to position itself as a bargain. Did you know that we tend to chose the price with less syllables even if the two prices have the same written lenght? These are some of the pricing strategies used by marketers. This is a very
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Density Estimation Using Regression [Eran Raviv]Density estimation using regression? Yes we can! I like regression. It is one of those simple yet powerful statistical methods. You always know exactly what you are doing. This post is about density estimation, and how to get an estimate of the density using (Poisson) regression. The go-to estimator for density is currently a nonparametric (or semiparametric) kernel. This is the estimator
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Visualizing Time Series Data in R [R Trader]Im very pleased to announce my DataCamp course on Visualizing Time Series Data in R. This course is also part of the Time Series with R skills track. Feel free to have a look, the first chapter is free! Course Description As the saying goes, A chart is worth a thousand words. This is why visualization is the most used and powerful way to get a better understanding of your data. After this
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Should You Buy or Rent a GPU-Based Deep Learning Machine for Quant Trading Research? [Quant Start]We've recently been considering the field of deep learning as a modelling methodology for forming new quantitative trading models. Such models have been shown to be 'unreasonably effective' in the fields of computer vision, natural language processing and games of strategy. This motivates us to see if these models can be applied to quant trading strategies. We've so far looked
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The birth of a strategy a common effort [Quant Bear]Lets start an experiment! This post will be the first in a series on going through the process of creating a trading strategy. It will not only detail the steps that I myself curently follow when I am building a strategy, what Im hoping for is that others contribute to the process by adding their ideas, criticism, point out logical flaws etc. Maybe someone also wants to share their process.
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Duration Timing with Style Premia [Flirting with Models]In a rising rate environment, conventional wisdom says to shorten duration in bond portfolios. Even as rates rise in general, the influence of central banks and expectations for inflation can create short term movements in the yield curve that can be exploited using systematic style premia. Value, momentum, carry, and an explicit measure of the bond risk premium all produce strong absolute and
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Academic Research Insight: The Value of Crowsourced Earnings Forecasts [Alpha Architect]What are the research questions? Are crowdsourced earnings forecasts from a source such as Estimize, useful in the capital markets by capturing new information about future earnings? Does a site such as Estimize add incremental accuracy when combined with the conventional, sell-side earnings forecasts such as the IBES consensus as well as a statistical model of forecasts? Is the crowdsourced