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LIBOR Fallback and Quantitative Finance [PDF]
Risks, 2019 With the expected discontinuation of the LIBOR publication, a robust fallback for related financial instruments is paramount. In recent months, several consultations have taken place on the subject.
Marc Pierre Henrard
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Finance: A Quantitative Perspective
SSRN Electronic Journal, 2017 Rossano Giandomenico
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LSTM in Algorithmic Investment Strategies on BTC and S&P500 Index
Sensors, 2022 We use LSTM networks to forecast the value of the BTC and S&P500 index, using data from 2013 to the end of 2020, with the following frequencies: daily, 1 h, and 15 min data.
Jakub Michańków +2 more
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Efficiency of the Moscow Stock Exchange before 2022
Entropy, 2022 This paper investigates the degree of efficiency for the Moscow Stock Exchange. A market is called efficient if prices of its assets fully reflect all available information.
Andrey Shternshis +2 more
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Sentiment correlation in financial news networks and associated market movements
Scientific Reports, 2021 In an increasingly connected global market, news sentiment towards one company may not only indicate its own market performance, but can also be associated with a broader movement on the sentiment and performance of other companies from the same or even ...
Xingchen Wan +5 more
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Applying Hybrid ARIMA-SGARCH in Algorithmic Investment Strategies on S&P500 Index
Entropy, 2022 This research aims to compare the performance of ARIMA as a linear model with that of the combination of ARIMA and GARCH family models to forecast S&P500 log returns in order to construct algorithmic investment strategies on this index.
Nguyen Vo, Robert Ślepaczuk
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Artificial Neural Networks Performance in WIG20 Index Options Pricing
Entropy, 2021 In this paper, the performance of artificial neural networks in option pricing was analyzed and compared with the results obtained from the Black–Scholes–Merton model, based on the historical volatility.
Maciej Wysocki, Robert Ślepaczuk
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Parameter Learning and Change Detection Using a Particle Filter with Accelerated Adaptation
Risks, 2021 This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters.
Karol Gellert, Erik Schlögl
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