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quantitative finance

Markets

Backtesting Series – Episode 2: Cross-Validation techniques

Download PDF Introduction As announced in our previous episode, the second article in our Backtesting series will discuss Cross Validation and introduce a new Backtesting strategy, first presented by Giuseppe Paleologo (2024). If you haven’t already, we recommend reading the first episode before proceeding with this article. Please note that Read more…

By BSIC, 8 months20 October 2024 ago
Markets

Exploring the Application of Kelly’s Criterion in Portfolio Optimization

Download PDF Introduction When managing a portfolio, the fundamental problem is to find investments with excess risk-adjusted expected rates of return. Once the manager has identified some favourable opportunities and is ready to assemble the portfolio, they still need to decide how much capital, as a fraction of the value Read more…

By BSIC, 2 years26 March 2023 ago
Markets

Sparse Gaussian Graphical Models for Pairs Trading

Download PDF Introduction In this article, we discuss an equity Pairs Trading strategy using the S&P 500 index components. Pairs Trading is a statistical arbitrage strategy that involves simultaneously taking long and short positions in two financial assets, expecting their spread to converge to the mean. However, the process of Read more…

By BSIC, 2 years19 February 2023 ago
Markets Old Articles

Dislocations Between Historical and Implied Volatility as an Indicators of Volatility Trades

Differences between historical realized volatility and option implied volatility has for long been known as a potential indicator for volatility mispricing. To our knowledge, the first well-known academic study on the topic was conducted by Goyal and Saretto in 2009 and published as the paper ‘Cross-section of Option Returns and Read more…

By BSIC, 7 years15 April 2018 ago
Markets Old Articles Quantitative Finance

When dealing with multiple stocks

In finance, a covariance matrix can be a useful tool to estimate the cross correlations between different stocks. However, historical data contains random noise, which can alter the underlying information. Here we illustrate how Random Matrix Theory can be used to filter a diagonalisable matrix and how information about the market Read more…

By BSIC, 9 years8 May 2016 ago

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