Alternative data

Alternative Data Screener on Quantpedia

11.May 2020

Global interest in alternative datasets is growing strongly. We at Quantpedia are looking on this emerging trend with curiosity too.

We are happy to announce Quantpedia’s cooperation with DDQIR, an alternative data-driven quantitative research company, which maintains an extensive database of alternative data providers. Their PHUMA Platform contains information about the majority of available alternative datasets and detailed characterization offers the possibility for the in-depth data-discovery process. DDQIR will operate a simplified demo of their tool for us on a separate Quantpedia’s sub-page.

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Top Ten Blog Posts on Quantpedia in 2019

29.December 2019

The end of the year is a good time for a short recapitulation. Apart from other things we do (which we will summarize in our next blog in a few days), we have published around 50 short blog posts / recherches of academic papers on this blog during the last year. We want to use this opportunity to summarize 10 of them, which were the most popular (based on Google Analytics tool). Maybe you will be able to find something you have not read yet …

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Quant’s Look on ESG Investing Strategies

13.December 2019

ESG Investing (sometimes called Socially Responsible Investing) is becoming a current trend, and its proponents characterize it as a modern, sustainable, and responsible way of investing. Some people love it, others see it as just another fad that will soon be forgotten. We at Quantpedia have decided to immerse in academic research related to this trend to understand it better. How are ESG scores measured? What are the common problems in ESG data? Are there any systematic ESG factor strategies that offer outperformance? These are some of the areas we wanted to explore, and we invite you on this journey with us …

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Lexically Diverse Hedge Funds Outperform

24.October 2019

Do you want to have an outperforming hedge fund? Then write a description of your investment strategy more creatively, clearly and use more synonyms… Of course, I am just kidding. However, a recent academic study written by Joenväärä, Karppinen, Teo, and Tiu shows that text sophistication can be used to find skilled hedge fund managers. Lexical diversity is the propensity of the writer to use multiple synonyms rather than repeated words. Skilled and, therefore, cognitively gifted managers are more likely to use rich vocabulary when writing their strategy descriptions. Therefore, if you feel that your favorite manager composes clear and captivating texts, maybe he is skilled also in his primary role – investment management …

Authors: Joenväärä, Karppinen, Teo, Tiu

Title: Text Sophistication and Sophisticated Investors

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A Deeper Look on Commitments of Traders Report

27.September 2019

Sun Tzu onced wrote (paraphrasing) “know yourself, know your enemy, and you shall win a hundred battles without loss”. This proverb is true also in financial markets as it is always easier to prepare trading/investment strategy when you know who are other market participants and what their intentions probably are. A new academic research paper written by Robe & Roberts gives a more in-depth insight into the CFTC’s weekly “Commitments of Traders” report. The COT’s report offers a small number of trader groupings; therefore, its usefulness is very limited. However, Robe & Roberts use trader-level data that originate from the CFTC’s Large Trader Reporting System (LTRS), which allows them to create a very detailed look at the composition of agricultural futures markets.

Authors: Robe, Roberts

Title: Who Holds Positions in Agricultural Futures Markets

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Authoritarian Countries Have Inflated GDP

13.February 2019

There has been the shadow of suspicion that autocratic regimes are slightly manipulating GDP growth numbers. A recent academic paper offers interesting idea how to double check suspicious claims of growth …

Authors: Martinez

Title: How Much Should We Trust the Dictator's GDP Growth Estimates?

Link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3093296

Abstract:

I study the manipulation of GDP growth statistics in non-democracies by comparing the self-reported GDP figures to the nighttime lights recorded by satellites from outer space. I show that the night-lights elasticity of GDP is systematically larger in more authoritarian regimes. This autocracy gradient in the elasticity is not explained by potential differences in a large set of factors, including economic structure and levels of development, across countries with different forms of government. The gradient is larger when countries have a stronger incentive to exaggerate economic performance or when the institutions that constrain the manipulation of official statistics are weaker. I estimate that the most authoritarian regimes inflate yearly GDP growth rates on average by a factor of 1.15-1.3 and show that correcting for data manipulation provides a more nuanced view on the economic success of non-democracies in recent years.

Notable quotations from the academic research paper:

"Governments themselves usually produce economic estimates, which gives rise to a moral hazard problem, as they are constantly tempted to exaggerate just how well the economy is doing. GDP stands out in this regard as perhaps the most widely used measure of economic activity. As such, it is probably the most profi table for governments to manipulate.

This paper uses nighttime luminosity to detect and measure the manipulation of GDP growth statistics in non-democracies. GDP and nighttime lights provide complementary measures of economic activity, but while GDP is self-reported by governments and prone to manipulation, night lights are recorded by satellites from outer space and are much less vulnerable. Using panel data for 179 countries between 1992 and 2008, I study the relationship between reported GDP figures and nighttime lights across political regimes. In particular, I examine whether the same amount of growth in lights translates into systematically larger amounts of GDP growth in autocracies than in democracies.

The main result of the paper is that the night-lights elasticity of GDP is signi ficantly larger in more autocratic regimes. In other words, I find that a constant amount of growth in lights translates into higher reported GDP growth in autocracies than in democracies. A large battery of further robustness tests indicates that the autocracy gradient in the night-lights elasticity of GDP is not driven by cross-country di erences in other factors that may be potentially correlated with regime type, including geography, economic structure or levels of development.

The observed magnitude of the variation in the night-lights elasticity of GDP across regimes is substantial. The results indicate that the most authoritarian governments inflate yearly GDP growth by a factor of 1.15-1.3. I use these estimates to adjust the long-run growth rates for data manipulation in autocracies. This adjustment has important implications for our understanding of relative economic performance at the turn of the XXI century.


fastest growing countries

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