e-book Quantitative analysis in financial markets

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Most global teams were able to get their reports before they started working, due to the time difference, except for the Australia and Japan teams. The number of FactSet licenses used by the client and Aranca came down drastically, as the report generation work stabilized. Ultimately, client saved significant amount of money while producing reports that were accurate and uniformly branded. A large global asset manager has observed that they have been seeing an increase in the number of RFPs floated by their clients.

This demanded a review of the RFP process and identified the importance of increasing the efficiency of the process. A team visited the UK office of the client to understand the process followed, get trained and document it. All the data inputs like AUM, short-bios of key people etc. The team initially used the client Sharepoint site to collect and automate these inputs.

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The client also had subscribed to the Qvidian database, but was not actively using it. Aranca team got involved in updating the Qvidian database and automation, so that most of the answers for standard questions could be picked up from relevant previous RFPs.

The client was able to complete more RFPs with better timelines and accuracy. Since Aranca team was able to take care of all the standard questions, client was able to get more time to think about the specific solutions and strategies. With the success of UK process, it was subsequently rolled out to other offices.

A large global ETF provider and asset manager was planning an innovative solution to empower investors to understand and decide the risk-return trade-off of their investments, and hence selling the new ETF products.

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Journal of Financial and Quantitative Analysis, Cambridge University Press | IDEAS/RePEc

The plan is to allow large investors to assess the risk and return of their entire portfolio, along with any additional investments in some of the client ETFs to their portfolio of investment, on the go. A team of multi-skilled associates was deployed to create the tool, that could be hosted in the public website of the client.

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A risk and return attribution framework and tool was developed, in discussion with the client. The client was able to create a unique product to empower the investors to decide their portfolio composition based on their risk appetite and future wealth expectations. By creating this, the client was able to create a digital marketing buzz in the industry, on a cost effective manner.

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Client is the capital market research team of a large global asset manager. The researchers in the produce high quality research on topics pertaining to their business, and is often data driven. However, the reusability of these research is limited as the codes are often ad-hoc and inefficient, not linked directly to the data sources, and hence takes long time to run and get results. A multi-skilled team was set up to understand the research paper, data and the code. Based on the assessment, the team would clean-up the code and make it efficient or write an altogether new code to create a full-fledged ready-to-use tool.

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Once the testing is done, would work with the client IT security team to host the tool over the intranet and make it available to all relevant users. These hosted tools are often managed by the Aranca team. Most commonly and regularly used tool based report production was also taken up by the Aranca team. The client was able to convert their internal IP to an easy to use tool, at a cost effective manner.

Often, these tools are developed in open source resources like R, so that there are no additional costs. The knowledge of Aranca team about the internal databases and systems allowed a seamless production, deployment and maintenance. Write To Us.

RFPs are as vital as they are time-intensive. The credit crisis that followed soon after further shook investor confidence in the markets. The growth of multi-asset portfolios in recent years has created a need to look beyond traditional asset allocation strategies. Different economic regimes produce significant impact. Automated solutions can now provide investment advice at costs ranging between 0. Turning Data into Insights. A trusted research partner to some of the world's best financial institutions.

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Pricing Models. Statistical Analysis.

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Return Analytics. Risk Analytics. FoF Performance Analytics. Dr Wei Wei. This unit covers statistics and econometric tools to assess the time series properties and distributional properties of financial series. It teaches how to model and estimate the single-factor and multiple-factor capital asset pricing models; and conduct diagnostic checks and reliable statistical inferences on various risk-return relationships and financial market hypotheses.

It also introduces recent literature on modelling, estimating and forecasting financial markets' volatility; and parametric and nonparametric methods to estimate the value at risk and expected shortfall. Statistical software will be used to carry out financial data analysis and applied research projects. Minimum total expected workload to achieve the learning outcomes for this unit is hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities.