Digitalisation and Big Data Mining in Banking

Silva

2018

Research in Economics

Self Cite

Titl eFo r e c a s ti n g UK Co n s u m e r P ric e Inf a tio n u si n g Inf a tio n Fo r e c a s t s Typ e Articl e U RL h t t p s:// u al r e s e a r c h o nli n e. a r t s . a c. u k/id/ e p ri n t/ 1 3 2 4 2/ D a t e 2 0 1 8 Cit a tio n H a s s a ni, H . a n d Silv a, E.S. (2 0 1 8) Fo r e c a s ti n g UK Co n s u m e r P ric e Inf a tio n u si n g Inf a tio n Fo r e c a s t s . R e s e a r c h in E c o n o mic s, 7 2 (3). p p . 3 6 7-3 7 8. IS S N 1 0 9 0-9 4 4 3 C r e a t o r s H a s s a ni, H . a n d Silv a, E.S. U s a g e G u i d e l i n e s Pl e a s e r ef e r t o u s a g e g ui d eli n e s a t h t t p:// u al r e s e a r c h o nlin e. a r t s. a c. u k/ p olici e s. h t ml o r al t e r n a tiv ely c o n t a c t u al r e s e a r c h o nli n e@ a r t s. a c. u k . Lic e n s e: C r e a tiv e Co m m o n s Att ri b u tio n N o n-c o m m e r ci al N o D e riv a tiv e s U nl e s s o t h e r wi s e s t a t e d, c o py ri g h t o w n e d by t h e a u t h o r AbstractThe inflation rate is a key economic indicator for which forecasters are constantly seeking to improve the accuracy of predictions, so as to enable better macroeconomic decision making. Presented in this paper is a novel approach which seeks to exploit auxiliary information contained within inflation forecasts for developing a new and improved forecast for inflation by modelling with Multivariate Singular Spectrum Analysis (MSSA). Unlike other forecast combination techniques, the key feature of the proposed approach is its use of forecasts, i.e. data into the future, within the modelling process and extracting auxiliary information for generating a new and improved forecast. We consider real data on consumer price inflation in UK, obtained via the Office for National Statistics. A variety of parametric and nonparametric models are then used to generate univariate forecasts of inflation. Thereafter, the best univariate forecast is considered as auxiliary information within the MSSA model alongside historical data for UK consumer price inflation, and a new multivariate forecast is generated. We find compelling evidence which shows the benefits of the proposed approach at generating more accurate medium to long term inflation forecasts for UK in relation to the competing models. Finally, through the discussion, we also consider Google Trends forecasts for inflation within the proposed framework.

Section: Discussionmentioning

confidence: 99%

Forecasting UK consumer price inflation using inflation forecasts

Silva

2018

Research in Economics

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“…Besides a few systematical reviews of big data and its techniques, applications and challenges in a broad sense (see [20,[28][29][30]), there have been a number of subject-specific review papers that summarise big data applications in its selected subject (see, for example, crime analysis [13], causality analysis [31], petroleum industry [32], banking [1], blockchain and cryptocurrency, [2], etc.). This section further categorizes big data research in climate change mainly into five topics: energy efficiency and intelligence; smart farming, agriculture and forestry; sustainable urban planning and infrastructure; natural disaster and disease assessment; and other advanced supports.…”

Section: Big Data Research Of Climate Change By Topicsmentioning

confidence: 99%

“…Big data analytics have been rapidly developing along with the emerging needs of big data technologies in numerous subjects (see, for example, [1,2]). The accessibility, availability and exponentially growing quantity of big data have further promoted the corresponding technological advancements and practical implementations.…”

Section: Introductionmentioning

confidence: 99%

Big Data and Climate Change

Huang

Silva

2019

BDCC

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Climate science as a data-intensive subject has overwhelmingly affected by the era of big data and relevant technological revolutions. The big successes of big data analytics in diverse areas over the past decade have also prompted the expectation of big data and its efficacy on the big problem—climate change. As an emerging topic, climate change has been at the forefront of the big climate data analytics implementations and exhaustive research have been carried out covering a variety of topics. This paper aims to present an outlook of big data in climate change studies over the recent years by investigating and summarising the current status of big data applications in climate change related studies. It is also expected to serve as a one-stop reference directory for researchers and stakeholders with an overview of this trending subject at a glance, which can be useful in guiding future research and improvements in the exploitation of big climate data.

“…For instance, big data analysis is widely used to resolve financial and economic issues. In banking, big data mining is used for risk management, security and fraud detection and strategic planning [100]. Furthermore, the big data technologies are closely related to blockchain technology and cryptocurrencies [101].…”

Section: Big Data Solutionsmentioning

confidence: 99%

Big Data and Energy Poverty Alleviation

Yeganegi

Beneki

et al. 2019

BDCC

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The focus of this paper is to bring to light the vital issue of energy poverty alleviation and how big data could improve the data collection quality and mechanism. It also explains the vicious circle of low productivity, health risk, environmental pollution and energy poverty and presents currently used energy poverty measures and alleviation policies and stresses the associated problems in application due to the underlying dynamics.