Stock Returns vs Inflation Expectations

14.December 2022

What happens to the stock prices when inflation expectations decrease or increase? The authors Manav Chaudhary and Benjamin Marrow, in their paper Inflation Expectations and Stock Returns, explore this topic and find that when inflation expectation is high, stock prices also rise in their value. The evidence they present suggests that stocks have been a hedge against expected inflation for the last couple of decades and that this effect is present across stocks from all industries.

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Quantum Computing as the Means to Algorithmic Trading

9.December 2022

The topic of quantum computing has been gaining popularity recently, and both the scientific community and investors seem to have high hopes for its future. It seems that this brand-new technology could revolutionize various aspects of computing as we currently know them. Great contributions could be made in the fields of medicine and healthcare, security, and computability [1], as well as in the field of finances, which interests us here at Quantpedia the most. Quantum computers are especially great in optimization tasks, so optimizing a portfolio could be one of the key contributions in our interest. [2] In this article, we would like to introduce the concept of quantum computers, their current state, their potential use in finance, and more.

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Quantpedia in November 2022

7.December 2022

Hello all,

What have we accomplished in the last month?

– One new Quantpedia Pro report – the One-Day Shocks & Historical Event Analysis
– 10 new Quantpedia Premium strategies have been added to our database
– 13 new related research papers have been included in existing Premium strategies during the last month
– Additionally, we have produced 10 new backtests written in QuantConnect code
– And finally, 4+1 new blog posts that you may find interesting have been published on our Quantpedia blog in the previous month

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How Much Are Bitcoin Returns Driven by News?

30.November 2022

The main theme of these days in the crypto world is unmistakenly clear, it’s the mayhem connected with the collapse of the FTX empire, insolvencies of various lenders, and questions about underlying holdings in GBTC OTC ETF and reserves of exchanges and Tether (or other stablecoins as well). With new information, nothing does paint a bright picture of this industry in the financial world now and in the near future. Calls for finally working regulations are getting stronger and stronger, while politicians (and central bankers) are still active on Central Bank Digital Currencies (CBDCs) proposals. While Bitcoin survived several crypto winters, long-term investors are continuing their DCA-ing and “stashing Satoshis” Are they safe? Do they pay attention to the surrounding news? In our blog entry, we will focus on the question of how news impact Bitcoin returns, being both the most famous cryptocurrency and also the one with the highest market capitalization.

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How to Paper Trade Quantpedia Backtests

18.November 2022

Quantpedia’s mission is simple – we want to analyze and process academic research related to quant/algo trading and simplify it into a more user-friendly form to help everyone who looks for new trading strategy ideas. It also means that we are a highly focused quant-research company, not an asset manager, and we do not manage any clients’ funds or managed accounts. But sometimes, our readers contact us with a request to help them to translate strategy backtests performed in Quantconnect into paper trading or real-trading environment. The following article is a short case study that contains a few useful tips on how to do it.

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Reviewing Patent-to-Market Trading Strategies

16.November 2022

The following article is a short distillation of the research paper Leveraging the Technical Competence of a Stock for the Purpose of Trading written by Rishabh Gupta. The author spent a summer internship at Quantpedia, investigating the Patent-to-Market (PTM) ratio developed by Jiaping Qiu, Kevin Tseng, and Chao Zhang. The PTM ratio uses public information about the number and dates of patents assigned to publicly listed companies, calculates an expected market value of patents, and tries to predict future stock performance.

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