This work examines a deep learning approach to complement investors' practices for the
identification of pairs-trading opportunities among cointegrated stocks. We refer to the …

In recent times, football (soccer) has aroused an increasing amount of attention across
continents and entered unexpected dimensions. In this course, the number of bookmakers …

Machine learning research has gained momentum—also in finance. Consequently, initial
machine-learning-based statistical arbitrage strategies have emerged in the US equities …

Over the past few years, cryptocurrencies have increasingly been discussed as alternatives
to traditional fiat currencies. These digital currencies have garnered significant interest from …

Pairs trading is a strategy based on exploiting mean reversion in prices of securities. Even
though these strategies have been shown to perform well for equities, their performance is …

This paper develops a pairs trading framework based on a mean-reverting jump–diffusion
model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to …

We propose an alternative pairs trading strategy based on computing a mispricing index in a
novel way via a mixed copula model, or more specifically via an optimal linear combination …

In the financial market, commodity prices change over time, yielding profit opportunities.
Various trading strategies have been proposed to yield good earnings. Pairs trading is one …

A pairs trading strategy (PTS) constructs a mean-reverting portfolio whose logarithmic value
moves back and forth around a mean price level. It makes profits by longing (or shorting) the …

Since the introduction of the measure of economic policy uncertainty, businesses,
policymakers, and academic scholars closely monitor its momentum due to expected …