Visualizing Financial Data

Rodriguez, Julie; Kaczmarek, Piotr

doi:10.1002/9781119183563

Cited by 9 publications

(2 citation statements)

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“…We briefly summarise the survey in Section 2. Additionally, Rodriguez and Kaczmarek published a "Visualising Financial Data" textbook [89]. As such, it is not the focus of our survey.…”

Section: Business Financementioning

confidence: 99%

Visualising Business Data: A Survey

Roberts

Laramee

2018

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A rapidly increasing number of businesses rely on visualisation solutions for their data management challenges. This demand stems from an industry-wide shift towards data-driven approaches to decision making and problem-solving. However, there is an overwhelming mass of heterogeneous data collected as a result. The analysis of these data become a critical and challenging part of the business process. Employing visual analysis increases data comprehension thus enabling a wider range of users to interpret the underlying behaviour, as opposed to skilled but expensive data analysts. Widening the reach to an audience with a broader range of backgrounds creates new opportunities for decision making, problem-solving, trend identification, and creative thinking. In this survey, we identify trends in business visualisation and visual analytic literature where visualisation is used to address data challenges and identify areas in which industries use visual design to develop their understanding of the business environment. Our novel classification of literature includes the topics of businesses intelligence, business ecosystem, customer-centric. This survey provides a valuable overview and insight into the business visualisation literature with a novel classification that highlights both mature and less developed research directions.

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“…We briefly summarise the survey in Section 2. Additionally, Rodriguez and Kaczmarek published a "Visualising Financial Data" textbook [89]. As such, it is not the focus of our survey.…”

Section: Business Financementioning

confidence: 99%

Visualising Business Data: A Survey

Roberts

Laramee

2018

Information

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“…Financial data, such as stock/fund prices and economic indicators, has been widely used by traders and investors to guide their investment decisions. Many visualization approaches have been proposed to support interactive analysis of financial data in the past decades [KCA ∗ 16, DML14, Teg99, RKD16, TLL ∗ 20, LWW ∗ 20]. Since the target users are often not visualization experts, classical designs such as line charts and bar charts are popular in financial visualization for better usability [CGK ∗ 07,ZJGK10,SB13, YSZ ∗ 19, YBL ∗ 19].…”

Section: Related Workmentioning

confidence: 99%

iQUANT: Interactive Quantitative Investment Using Sparse Regression Factors

Yue

Wang

et al. 2021

Computer Graphics Forum

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The model‐based investing using financial factors is evolving as a principal method for quantitative investment. The main challenge lies in the selection of effective factors towards excess market returns. Existing approaches, either hand‐picking factors or applying feature selection algorithms, do not orchestrate both human knowledge and computational power. This paper presents iQUANT, an interactive quantitative investment system that assists equity traders to quickly spot promising financial factors from initial recommendations suggested by algorithmic models, and conduct a joint refinement of factors and stocks for investment portfolio composition. We work closely with professional traders to assemble empirical characteristics of “good” factors and propose effective visualization designs to illustrate the collective performance of financial factors, stock portfolios, and their interactions. We evaluate iQUANT through a formal user study, two case studies, and expert interviews, using a real stock market dataset consisting of 3000 stocks × 6000 days × 56 factors.

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