MoneyScience News |
- Blog Post: TheFinancialServicesClub: The Digital Revolution is like Marmite for Banks
- Blog Post: TheAlephBlog: The Value That Investment Advisers Deliver
- Published / Preprint: Factor Models for Alpha Streams. (arXiv:1406.3396v1 [q-fin.PM])
- Published / Preprint: Decoding Stock Market Behavior with the Topological Quantum Computer. (arXiv:1406.3531v1 [q-fin.GN])
- Blog Post: ThePracticalQuant: Feature Engineering
| Blog Post: TheFinancialServicesClub: The Digital Revolution is like Marmite for Banks Posted: 16 Jun 2014 03:06 AM PDT I presented at a conference in Italy the other day.read more... Visit MoneyScience for the Complete Article.      |
| Blog Post: TheAlephBlog: The Value That Investment Advisers Deliver Posted: 16 Jun 2014 03:04 AM PDT I got cold-called this last week while I was away on business. Â I googled the phone number, and found that it came from Melitello Capital. Â I went through their site, and read most of their articles.read more... Visit MoneyScience for the Complete Article.    |
| Published / Preprint: Factor Models for Alpha Streams. (arXiv:1406.3396v1 [q-fin.PM]) Posted: 15 Jun 2014 05:38 PM PDT We propose a framework for constructing factor models for alpha streams. Our motivation is threefold. 1) When the number of alphas is large, the sample covariance matrix is singular. 2) Its out-of-sample stability is challenging. 3) Optimization of investment allocation into alpha streams can be tractable for a factor model alpha covariance matrix. We discuss various risk factors for alphas such... Visit MoneyScience for the Complete Article.    |
| Posted: 15 Jun 2014 05:37 PM PDT A surprising image of the stock market arises if the price time series of all Dow Jones Industrial Average stock components are represented in one chart at once. The chart evolves into a braid representation of the stock market by taking into account only the crossing of stocks and fixing a convention defining overcrossings and undercrossings. The braid of stocks prices has a remarkable... Visit MoneyScience for the Complete Article.    |
| Blog Post: ThePracticalQuant: Feature Engineering Posted: 15 Jun 2014 10:07 AM PDT Researchers and startups are building tools that enable feature discovery[A version of this post appears on the O'Reilly Data blog.]Why do data scientists spend so much time on data wrangling and data preparation? In many cases it's because they want access to the best variables with which to build their models. These variables are known as features in machine-learning parlance. For many0 data... Visit MoneyScience for the Complete Article.    |
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