Quantivity is pleasantly surprised to discover an increasing number of folks are deriving value from the Curated Quant Research Feed on @Quantivity. Indeed, the combo of daily curated feed with single-source retrospective search has become indispensable for personal research. Towards understanding why, Kedrosky provides nice explanation in his Curation is the New Search is the New Curation post earlier this year:

Head back to curation and watch new algos emerge on top of that next-gen curation again. Think of Twitter as a new stab at curation. Curated sites will re-seed a new generation of algorithmic search sites. In short, curation is the new search.

Indeed, intent of curation here is to maintain high signal-to-noise ratio for a mix of preprint and classics in a highly-specialized literature (i.e. combo of retail $\mathbb{P}$ and prop $\mathbb{Q}$) for which strong motivation exists elsewhere to obfuscate; and search over the stream provides ability to both rewind time and to integrate conceptual connectivity spanning time.

One addition being contemplated is keyword search over all literature cited in feed, providing deep content search over the feed. Although, unclear yet what is the best technical avenue to implement this (please comment, if you have suggestions).

So, with this positive start, curation input set is being modestly expanded to coincide with increased personal research activity and availability of several new quant sources—while maintaining the same focus and high signal-to-noise goal. Specifically, curation is expanding to include the following SSRN working papers: ARPM Series and JEL Codes G11 (Portfolio Choice), G12 (Asset Pricing), G13 (Contingent Pricing; Futures Pricing), G14 (Information and Market Efficiency), C21 (Cross-Sectional Models), C22 (Time-Series Models), C51 (Model Construction and Estimation), and C53 (Forecasting and Other Model Applications). Selection of JEL codes is data-driven: feed links were ranked by JEL classification and most cited classifications were chosen.

Authors are encouraged to ensure correct use of JEL codes, to ensure your articles are picked up.

Curious what readers think? Are there other high-value sources worth adding to curation input set? What else could make this more useful?

November 4, 2011 8:48 am

Came across this recently: http://quantpedia.com/

It’s a paid service, but seems to offer significant value add to the research papers they cover. Has anyone used this service?

November 4, 2011 11:20 am

@seth2007: two quick observations, having poked around a while: (1) literature play little to no substantive role, as purpose appears to be curation of commodity trading systems; (2) business appears to be subscription version of collective2, or similar clones, for which there is obvious question why waste commercial effort given strategies would be traded quietly if they had alpha.

November 4, 2011 10:41 pm

@quantitivity: not to sound like a shill, but I’m not sure your characterization that literature plays little role is correct. From the site: “We use a great number of finance research resources all over the world including research portals, financial journals, universities and conferences. We sift through these sources every day and search for new interesting articles and papers.”

2. November 4, 2011 12:05 pm

“strong motivation exists elsewhere to obfuscate”? Sounds a bit exaggerated. Incidentally, large market makers provide quite good monthly academic digests to their clients (e.g., Citi, SSgA, Maquairie), so I don’t see the obfuscation part. Of course, nobody who can actually profit from good ideas will ever publish them, but this is an issue orthogonal to curation.

November 4, 2011 1:37 pm

@gappy: fair points (despite being aware of counterexamples to your orthogonal consideration, I agree generally); just to clarify, obfuscation is meant to be interpreted more broadly, including academic writing style, lack of reproducible code (or worse, code which is wrong, thus invalidating the results), competitive journal publication dynamics, etc.

• November 6, 2011 5:33 pm

I completely agree on this type of negative obfuscation. Over the years, I have tried to reproduce some of the papers with the most outrageous results (e.g., L. Györfi, G. Lugosi, and F. Udina. Nonparametric kernel-based sequential investment strategies.) and have never succeeded. I later found out that some of these papers did not even use CRSP data. Other former colleagues have tested anomalies published in respected journals (e.g., the Journal of Finance) and not once have the results been replicated. I am still amazed that journals don’t require that data and code be made available. This applies to any Economics empirical papers (e.g., the Bates medal-winning AER paper on inequality of Piketty-Saez).

November 6, 2011 7:14 pm

@gappy: indeed, this is my single biggest personal pet peeve in finance; the scientific method is built upon reproducibility, which sadly never took root in financial economics. A small cynical part of me wonders how much of our canonical understanding of empirical financial economics is incorrect due to this bias.