Pricing estimation of a barrier option in an IoT scenario

Cuomo, Salvatore; Somma, Vittorio Di; Piccialli, Francesco

doi:10.1016/j.future.2018.01.027

Cited by 8 publications

(1 citation statement)

References 13 publications

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“…Apart from machine learning, many researchers even used the Internet-of-Things (IoT) for estimating rates of different sectors. Such models were used by Salvatore, Vittorio, and Francesco, who used IoT for estimation of a European barrier price [7] and determining the fluctuation and also for estimating the simultaneous buying and selling prices [8]. From statistical to deep learning, different models along with hybrid models have arisen on this occasion.…”

Section: Introductionmentioning

confidence: 99%

A Review on Recent Advancements in FOREX Currency Prediction

Islam¹,

Hossain

Rahman³

et al. 2020

Algorithms

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In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny from researchers all over the world. Due to its vulnerable characteristics, different types of research have been conducted to accomplish the task of predicting future FOREX currency prices accurately. In this research, we present a comprehensive review of the recent advancements of FOREX currency prediction approaches. Besides, we provide some information about the FOREX market and cryptocurrency market. We wanted to analyze the most recent works in this field and therefore considered only those papers which were published from 2017 to 2019. We used a keyword-based searching technique to filter out popular and relevant research. Moreover, we have applied a selection algorithm to determine which papers to include in this review. Based on our selection criteria, we have reviewed 39 research articles that were published on “Elsevier”, “Springer”, and “IEEE Xplore” that predicted future FOREX prices within the stipulated time. Our research shows that in recent years, researchers have been interested mostly in neural networks models, pattern-based approaches, and optimization techniques. Our review also shows that many deep learning algorithms, such as gated recurrent unit (GRU) and long short term memory (LSTM), have been fully explored and show huge potential in time series prediction.

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Section: Introductionmentioning

confidence: 99%