Alternative data

The Active vs Passive: Smart Factors, Market Portfolio or Both?

11.December 2020

While there may be debates about passive and active investing, and even blogs about the numbers of active funds that were outperformed by the market, the history taught us that the outperformance of active or passive investing is cyclical. As a proxy for the active investing, the new Quantpedia’s research paper examines factor strategies and their smart allocation using fast or slow time-series momentum signals, the relative weights based on the strength of the signals and even blending the signals. While the performance can be significantly improved, using those smart approaches, the factors still got beaten by the market in both US and EAFE sample. However, the passive approach did not show to be superior. The factor strategies and market are significantly negatively correlated and impressively complement each other. The combined Smart Factors and market portfolio vastly outperforms both factors and market throughout the sample in both markets. With the combined approach, the ever-present market falls can be at least mitigated or profitable thanks to the factors.

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The Knapsack problem implementation in R

16.October 2020

Our own research paper ESG Scores and Price Momentum Are More Than Compatible utilized the Knapsack problem to make the ESG strategies more profitable or Momentum strategies significantly less risky. The implementation of the Knapsack problem was created in R, using slightly modified Simulated annealing optimization algorithm. Recently, we have been asked about our implementation and the code. The code is commented and probably could be implemented more efficiently (in R or in another programming language). For example, R is more efficient with matrices, but the code would not be that “straightforward”. Lastly, the most important tuning parameter is the temperature decrease (the probability of accepting a new solution is falling with the rising number of iterations).

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ESG Scores and Price Momentum Are More Than Compatible

16.July 2020

What will happen if we mix ESG scoring with price momentum? Can we improve simple ESG investing strategy?

The pure price momentum can be combined with ESG scores using a Knapsack algorithm. Knapsack algorithm is a well-known mathematical problem of optimization, and in the case of momentum and ESG, can be used to make the momentum portfolios significantly more responsible, with lower volatility and better risk-adjusted return. The second option is to make the ESG portfolio substantially more profitable by using Knapsack algorithm to construct high ESG portfolio with large momentum. The approach resulted in a strategy with high ESG score and compared to pure momentum or momentum-ESG strategy, with significantly reduced volatility. Therefore, the ESG-momentum strategy has the best risk-adjusted return, the lowest drawdown, the lowest volatility and the most consistent returns.

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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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