Corporate Data Architecture – Fast Data and Big Data.

•July 21, 2014 • 2 Comments

The VoltDB blog has a number of interesting articles on Corporate Data Architecture.  The Fast Data stack is somewhat different from a lambda architecture that has been discussed on various blog in the context of real-time big data.  Clearly Fast Data is a VoltDB database based on VoltDB’s view of the world. However, summingbird and other such stacks also have merit.  As does samza and Kafka.

Lets assume I want to serve knowledge and analytics from ingesting web site click data, pricing, execution and trade data, to power a salespersons trading cockpit.  What should/could I use?

Collateral Management view of Team Resourcing – Part 6

•July 20, 2014 • Leave a Comment

I’m back to coding, but this time in native Neo4j.  The aim to modelling teams, and time lines of teams, is wanting the ability to ask the system “What is the best team for x?”.  Which leads to a recent article on Moneyball.

Billy Beane analyzed the data on players’ performance and used the models’ outputs to select players

Food for thought

TDD Resistence

•July 20, 2014 • 1 Comment

Ian’s talk on TDD: Where Did It All Go Wrong? is worth a watch.  The problem Ian outlines is known by I suspect a large percentage of development teams.

Avoid testing implementation details, test behaviors
– A test-case per class approach fails to capture the ethos for TDD. Adding a new class is not the trigger for writing tests. The trigger is implementing a requirement.
– Test outside-in, (though I would recommend using ports and adapters and making the ‘outside’ the port), writing tests to cover then use cases (scenarios, examples, GWTs etc.)
– Only writing tests to cover the implementation details when you need to better understand the refactoring of the simple implementation we start with.endencies

XP – Software Development Best practices

•July 20, 2014 • 2 Comments

iMogital states quite simply that Scrum/Kanban will not tell your developers how to develop.  XP has 12 practices derived from software engineering best practices – TDD, Paired Programming, Coding Standards being a few.  CodeCentric touch on the same issue.  I suspect continuous integration, should really be continuous delivery these days.  Net out, if your development teams are not familiar with XP, maybe its finally time to help them get educated, and move down the XP road.

InfoQ has a recent article on engineering practices, offering the following equation:

Scrum + Extreme Programming (XP) = Agile

One of the key call-out’s from the InfoQ article is that good engineers don’t drop best practices in high stress situations.  Its unfortunate that often when there is a time crunch, testing is the first thing to get dropped.  Engineers often perceive that due to time pressure, feature complete at any cost is acceptable.  Unfortunately, often the team hasn’t asked the hard question back to management/stakeholders – you often can’t have your cake and eat it.

Agile Release Train

•July 16, 2014 • 1 Comment

SAFe’s overview of the agile release train is worth reading.  Release trains aren’t new, they been around for years in both agile and non-agile organisations. Release trains aid in a consistent push to production, and work around certain black-out dates when production can’t be touched e.g. Christmas, end of month etc.  Sometimes certain train dates are also aligned to key business deliverables which although maybe anti-agile is some ways, are from a commercial perspective relevant.

One item that is often not well discussed around agile iterations is pre-iteration dependencies.  Specifically these occur around interface boundaries, and the user interface (particularly if its complex).  Complex interactions can clearly be broken into smaller stories, but sometimes there are dependencies and assets (business workflows etc) that maybe required in preparation prior to entering the development iteration.

FX Agency Model and FlowMonsters

•July 14, 2014 • Leave a Comment

Interesting read in Financial New this week on Faros Trading, and the agency intermediary model.  Even with the flowmonsters, there is opportunity for regional banks to specialise in home currency pairs. Breaking into the flowmonster space is costly from a technology perspective – problematic in post Basel III era.  The top four banks have a combined share of 53.5% of the FX market.

Bank Optimisation

•July 8, 2014 • Leave a Comment

Morgan Stanley/Oliver Wyman has an interesting read on Mis-allocated Resources: Why Banks Need to Optimise Now.  Decreased margins require banks to understand their advantage, and leverage it to clients.  Optimisation is strongest in Fixed Income – no surprise.

About equities:

Distribution and research are two of the biggest challenges.Investors we met highlighted that quality content and senior coverage were amongst the top differentiators between banks or boutiques that they used.

Other interesting commentary:

The vast majority of IT, processing and support behind banking services is delivered in-house with platforms that are highly duplicative across players and offer very little by way of competitive advantage. At the same time the banks have suffered rising costs of infrastructure even while their profits have been dropping.

Technology investment has a critical role to play in delivering on the optimisation agenda, for example in supporting market structure change, and in tackling longstanding sources of inefficiency in bank processing. A shift in gear is required, away from reactive regulatory remediation towards a more strategic infrastructure change program, and we are already seeing the leading banks start to make this transition

Technology investment has a critical role to play in delivering on the optimisation agenda, for example in supporting market structure change, and in tackling longstanding sources of inefficiency in bank processing. A shift in gear is required, away from reactive regulatory remediation towards a more strategic infrastructure change program, and we are already seeing the leading banks start to make this transition

Research is a differentiator

Distribution:

“The sell-side has built up multiple overlapping sales functions as new channels have emerged (generalists, research sales, specialists, sales traders, electronic sales, regional sales, delta one sales). These could be justified when
investors turned over portfolios at least once per year and paid blended rates of 10bps / 4c per share, but those conditions are not coming back”

Technology areas of interest (quoted again from the article):

  • Fixed Income market connectivity
  • Corporate treasurers integration (payments, liquidity management, hedging)
  • Electronification of Equity derivatives
  • Using customer data across the bank to drive insight- pattern analysis
  • Improved understanding of economics of client business
  • Client self-service and dynamic reporting
  • Asset optimisation solutions, across risk, collateral, settlement and legal entity optimisation
  • Reference data control and quality assurance
  • Retooling research and analytics – speaks to the above point

 

The value of wealth management clients to a Wholesale bank is very high, given the synergies in transaction execution, asset management and content

 
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