Diversification

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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How to Replicate Any Portfolio

2.November 2022

Would you like to see the performance of your portfolio 100 years back in history? Do you want to analyze the risk of your strategy under 100 years of real historical scenarios? All of these, and much more, will be soon (in a few days) available for Quantpedia Pro subscribers. How? We will explain today how we can model a 100-year history of your portfolio.

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Stock-Bond Correlation, an In-Depth Look

19.October 2022

The recent surge in global inflation sent shock waves across financial markets and affected the complicated relationship between stocks and bonds. Today, we would like to present you with a review of two interesting papers, which provide both a deep and easy-to-understand examination of the correlation structure of those two main asset classes. The first paper reviews specifics in various parts of the world, and the second one summarizes known information about the macroeconomic drivers of the US stock-bond correlation.

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Investing in Deflation, Inflation, and Stagflation Regimes

16.September 2022

Investing has been a reliable way to compound one’s inheritance over ages known throughout human history. But different monetary and fiscal situations, especially during times of uncertainty and extreme stress, force both individuals and institutions to adjust their financial habits. A recent research paper written by Guido Baltussen, Laurens Swinkels, and Pim van Vliet analyzed large samples of data starting from the 19th century and brought unique perspectives on how various asset classes perform during “quiet, good” periods and, on the other side, economic turmoil. Research summarized very actual topics of investing during those different cycles and what inflation does to returns across equities, bonds, and cash.

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A Study on How Algorithmic Traders Earn Money

13.September 2022

Our mission here at Quantpedia is to provide both retail and institutional investors with ideas for trading strategies that are easily understandable while based on and backed by quantitative academic research. Today, we present you with the results from a study that we came across. Although it’s not quantitative, but qualitative, it has really held our interest. The paper does not provide any images or figures; it is a study made from various types of surveys with answers from professionals concluded with an attention-grabbing summary table. 

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Should We Rebalance Index Changes Immediately?

30.August 2022

Passive index funds are believed to offer low fees, nearly limitless liquidity, very low trading costs and (most of the time) they beat most active managers. Although not all of the above are accurate, there are still many arguments in favour of passive indexing. However, what is often left forgotten are avoidable travails linked to index funds. In general, after an index rebalances, traditional cap-weighted index funds buy high and sell low. Their tendency to add recent highfliers and drop unloved value stocks is what causes investors to lose. Arnott et al. (2022) target the stock selection problem around index rebalancing and propose several ideas on how to adjust index strategies in order to earn above-market returns. They present simple ways to construct an index, thanks to which it is possible to reduce both negative effects of buy-high/sell-low dynamic and the turnover costs of cap-weighted indices.

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