BAML

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(Bank of America)

Letizia Pepe <letizia.pepe@baml.com>

Piers Thompson <piers.thompson@baml.com>

2016

We are thinking of asking the students to develop a platform that allows trading algorithms to be interactively developed and tested (both back-tested and tested against live market data) and compare performance.

Feedback: Your suggestion has some similarities to this project form 2014, so you might like to think of ways that it could be updated or adapted: Algo-Trading Game

Edited to length:

Simulated Stock Exchange

Previous (2015) project

Financial Trading Trends


Global real-time information rules the financial markets. Institutions need to make use of complex modelling tools to predict trends and stay ahead of the curve. However, it's currently very difficult to get access to this information without a subscription to various services (e.g. Bloomberg).

With the abundance of data on the web, we now think that there is an opportunity to go outside the usual sources and begin sourcing data from places outside of the norm. For example, as the influence of social networks continues to increase, so does the likelihood of stories and individuals influencing global markets on a more regular basis. Think how a possible tweet from a high profile celebrity may adversely affect the stock price of a certain consumer product, for instance.

The goal of this project is to create a system that models the impact of various sites on financial trends. The system will update itself with information on financial markets and then detect the trends between this data and various news sources. It should potentially look to gather data from a variety of different sources, and build out a model that represents the relations between stories and financial information, presenting it for the user to browse.

Some areas we would consider thinking about are: how you model the data both financially and news related, how you store the scraped data, how to identify a tolerance for variations and the ability to allow a user to specify their own data source.

Revision:

Data analytics on actual trades

Aim: Parties involved in OTC trading are obliged to make public the details of trades, in real time. This was intended to increase the transparency, fairness and efficiency of the OTC markets. However, although the data is public, it is not easy to view and analyse and therefore the aim of increased transparency is imperfectly realised. The aim of this project is to provide a convenient means of accessing, viewing and analysing OTC trade data.

Differences in pricing models used by the participants in OTC market result in inconsistencies in prices at which derivatives products are traded. Market participants can benefit from seeing, in real time, the current prices at which the derivatives are being traded.

A U.S. regulation requires that all firms under its jurisdiction report their trades, with limited details, to a common repository within a set time since they were traded. This repository is available for public viewing and contains information about OTC product volumes and prices.

For this project we would like you to provide a convenient user-interface for this data. This should allow users to see current and historic prices for selected derivatives products. Additional functionality might be added as time allows, such as the automated identification of pricing anomalies, trending and alerts.

Further revision:

Over-the-counter (OTC) trading of financial products is less regulated than exchange trading, but also less transparent. To improve market fairness and efficiency, near-realtime details of OTC trades must therefore be placed in a public repository. However, since this data is not easy to view and analyse, the aim of increased transparency has not been achieved. The aim of this project is to provide a convenient means of accessing, viewing and analysing OTC trade data. This should provide realtime data on current prices and trading volumes, historic trends, and automated identification of pricing anomalies and trend alerts.

Can you give a reference to the repository that the team would be relying on, and specification of its public interfaces?