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Electronic finance (e-finance) is mainly concerned with the automation of traditional activities in the finance domain and
their associated processes. In particular, trading has become more and more a global activity because of the recent technological
developments that have facilitated the instantaneous exchange of information, securities and fund...
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... available; however, participants such as brokers can generate their own analytics based on raw historic market data. As mentioned earlier, market information dissemination is very crucial to the fairness and efficiency of a capital market and hence contributes to its attractiveness to traders and encourages companies to be listed on the market. Fig. 2 illustrates the overall information flow across the trading processes for an order-driven market structure which is derived from the way the Australian Stock Exchange (ASX) (www.asx.com.au) operates. It comes in the shape of a continuous cycle in which we identify five phases: pre-trade analytics, trading, post-trade analytics, ...
Citations
... Structured market information includes real-time trading data and events such as orders, trades, quotes, indices, and announcements [9]. It also includes historical information such as past trading data and companies' periodic reports. ...
This paper presents a literature survey of how machine learning techniques are being used in the area of electronic financial market trading. It first defines the essential components of an electronic trading system. It then examines some existing research efforts in applying machine learning techniques to the area of electronic trading, examining the target areas, methods used and their purpose. It also identifies the gaps and opportunities for further research in this new expanding field.
... Despite the various standardisation efforts underway within the industry (Dabous and Rabhi, 2008), a complete and concise view of the information's form, structure and content is still as elusive as ever. This is because each system sees information from a unique perspective that depends on its role in the trading cycle, how the market is designed, the trading processes in place etc. Determining a common vocabulary and reference data is hampered by the complexity of the domain which is still evolving (e.g., new financial instruments are being created all the time). ...
Due to immense amounts of data being generated from financial markets in many different formats, professionals and academics face interoperability problems when analysing such data. This paper proposes a data model that gives a coherent view of the information available from financial market data repositories. The novel features of this data model include: modelling the behaviour of an electronic market as an extensible event-based class hierarchy, and using ontologies to represent financial data as a set of inter-related and meaningful events. Using this data model, we develop interoperable web services that process the data at a high level of abstraction using a Service-Oriented Architecture.
Robo-Advisors guide investors through an automated investment advisory process, recommend personalized portfolio assignments based on their individual risk-affinity as well as investment goals and rebalance the portfolio automatically over time. Giving basic investment advice to customers, it can provide a useful way to reduce risk by diversifying and mitigating biases, while keeping a certain degree of performance at low costs. To verify these claims we conduct a sophisticated analysis of recommended portfolios of 36 Robo-Advisors, based on six distinct model customers with different risk-affinities and investment horizons, resulting in 216 recommended portfolios. We find that the analyzed Robo-Advisors provide distinct recommended portfolios for the different risk/investment horizon combinations, while sharing similarities in used products for portfolio allocation. We also find issues within the recommended portfolios, e.g. a low degree of distinctiveness between different investment horizons and a high amount of equities even in the short-term investment horizon.
