Dear Client,

Please, excuse Quantpedia Pro’s occasional slow reaction times and “error 500” messages. Unfortunately, we are experiencing random service interruptions in the cloud data center we are using at that moment. We are working on mitigation steps.

I appreciate your understanding,

Radovan Vojtko
CEO, Quantpedia

Hello all,

Let’s first very quickly recapitulate Quantpedia Premium development in the previous month: Ten new Quantpedia Premium strategies have been added to our database, and ten new related research papers have been included in existing Premium strategies during the last month. Additionally, we have produced 11 new backtests written in QuantConnect code. Our database currently contains over 440 strategies with out-of-sample backtests/codes.

And now, let’s move to our Quantpedia Pro subscription offering news – Our clients often mentioned one particular report as something they would love to see in the Quantpedia Pro – it’s the Markowitz Portfolio Optimization, and we are really happy that we can announce that it’s ready 🙂

Five new strategies have been added.

Five new related research papers have been included into existing strategy reviews and two short free blog posts have been published during last few weeks. Plus, six trading strategies have been backtested in QuantConnect in the previous two weeks.

No doubt, the financialization in commodities was a significant breakpoint in markets and research as well. Many commodity strategies in Quantpedia’s screener are linked to financialization. It would be naive to think that the speculation in the commodity futures which has emerged did not influence the dynamics of the market. With the increased speculative trading, the Commodity Futures Trading Commission started collecting the net positions, but this dataset did not include all the data and often was connected with misreporting (and is not published anymore). The novel research paper of Adams, Collot and Rossi (2021) offers a different insight on this topic. It shows how to measure the influence using the term structure of commodity prices, focusing on crude oil. The authors suggest that during normal times, the term structure of crude oil futures should be smooth. They consider the term structure that starts with spot price and includes futures with one to twelve-month maturities, but they omit the one and two-month futures (since those are mostly used for speculation). The key finding is that when they estimate the missing futures based on the other prices using the smooth spline interpolation, this estimated term structure curve can be compared to the realized one. The deviation from the predicted (estimated) curve can be interpreted as the degree of speculation in commodity futures markets. As a result, with the mathematical modelling, the authors offer an interesting insight into speculation without any external datasets.

From the perspective of an indifferent observer, it seems that the world is accelerating from decade to decade. The average speed of information processing increases, and we consume more and more knowledge in a shorter and shorter amount of time. So, we have decided to start a new information stream for a people who have adjusted to this tempo.

It is striking how cryptocurrencies are both similar and dissimilar to the more established asset classes at the same time. On the one hand, many findings from traditional asset classes also apply to this novel class. On the other hand, this “new” world with its own characteristics brings many novel “problems” that attract researchers. This week’s blog presents several research papers connected to the pump and dump schemes in cryptos. These pumps and dumps are nothing new, and we already know them from the stock market. However, there are some notable differences…