Design & Analytics' Blog

Announcing: the ARIMA sector forecast report series is live

For several months now, I've been putting together an automated econometric forecasting platform.  Using a simple ARIMA model, I've created a forecast for stock sectors to inform my own short-term option trades.  Despite being a statistical model, rather than a foundational one about informationally poor stocks, I found it useful for my purposes---though I make no promises about yours---and developed this infrastructure in order to share it online.  Even if you're not interested in stock market movements, the further utility of the platform is as a demonstration of the capabilities of reports automation: this platform runs an analysis every day, makes forecasts, charts, typesets instructions and accompanying advertizements, and publishes them to PDF and in an animated gallery online.  This is an analysis that once automated, never again needs human intervention.  That's a powerful thing, especially in how it frees this human to solve new problems.

Here it is:  And here is where to sign up for the newsletter providing coverage.

Useful Asset Allocation Data Sources

Working on a project on asset allocation right now, and discovered two excellent references.  The first is a solid guide and introduction to implementing the Black-Litterman model: This reference provides useful implementations in both Excel and Matlab, as well as a discussion of the inputs.  The discussion of the controversial and elusive Tao term is particularly helpful.

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Data-driven foreign-language learning: by the numbers

This is the story of a foreign language data mashup, and how thinking about study-time as an asset with returns can make your language-learning more efficient---in theory.

I am not a linguist, a computational linguist, or a language teacher, but I travel internationally a fair amount and have had reason to half-study a few languages.  In the course of that, I've compared many different approaches and methods as an interested learner.  I've found that with simple audio tapes (like the FSI or Pimsleur) and 6 months of self-study, it's possible for a native English speaker to get to B1 or B2 conversational level in a European language---which isn't much: you can then order coffee and comment on newspaper headlines with some ease.  It takes diligence, but is doable.  However, beyond about that level, you begin to plateau.  At that point, you've learned the grammar, you've mastered the common words, you are confident that you can get around.  Before this, every single word, every single grammatical structure had comparatively large "returns" in the sense that each additional word or rudimentary grammar element came up all the time, and improved remarkably your ability to understand.

The problem is...

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Google Correlate: Take Two

I've posted before about Google correlate in Google Correlate for fun and profit. It's a fantastic platform, but I have not yet discovered any practical use cases for it.  This is still the case, but after experimenting with it more, I now have a better idea of what they would need to do (and why they can't do it), to make it more useful.

The future of finance? P2P equity and VC funding

I'm optimistic about the efficiency gains coming from direct P2P entering the finance market, and with some skeptical reservation believe that this is where finance is heading generally---disintermediation can be a beautiful thing for market efficiency and participatory transparency.  As a survey: sites like Lendingclub and Prosper have gone far already in establishing the market for P2P credit.  Kiva and Grameen have done impressive things for P2P donation and microcredit models, and Kickstarter has been exceptional in artistic donation services.  Rather than waiting for banking institutions to evaluate the profitability of their ideas or causes, individuals are gaining increasing access to funding the opportunities they support, on terms they define themselves. 

Artificial intelligence course, free from Stanford Engineering

There was a New York Times Science article yesterday on an offering from Stanford Engineering. In the spirit of the Khan Academy, which I greatly admire, an artificial intelligence course is being offered free and online, taught by Sebastian Thrun and Peter Norvig. There are currently about 63,000 registrants.

The main course information is here:

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Full text of the S&P report for the US credit downgrade, AA+

Searching for this report, I found more meta-coverage than links to the source.  Below is the full text of the document itself, and the decision rendered by S&P in the downgrade, titled "Research Update: United States of America Long-Term Rating Lowered To 'AA+' On Political Risks And Rising Debt Burden; Outlook Negative."  Reposted directly from S&P.

Google search UI color changes: good artists copy, great artists steal?

...and great google artists duplicate independently.

Although they surely arrived at it on their own, I do notice a design similarity between google's new search color palette and the one in place at Design and Analytics for several months.  The red links, the dark gray, light gray, and white---there's something to it.  Looks like Design and Analytics will have to move on to something new soon.  (Maybe we should set our logo to primary colors plus green?) 

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Data Auralization - Listening to the Dow

I was pleased to see this posted in the Alumni Notes of my Alma Mater recently---Justin Joque, a Data Librarian at the University of Michigan, put together a Data "Auralization" of the Dow from 1928 to 2011.  He uses tick data to create two audio bands, one with closing price, and one with trade volume.  Here's the Vimeo Link:

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Stanford's Data Wrangler for visual data exploration

On several quick projects and tasks, Wrangler has saved me days of brute manipulation, and helped me explore new methods faster.  It's a fantastic tool for getting your data into the format you need it, so you can start doing more interesting things with it:


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