How Machine Learning Pushes Us to Define Fairness

  • David Weinberger – As we look at higher levels of abstraction — from using sliders to adjust the mixes in the bins, to questions about optimizing possibly inconsistent values — ML is teaching us that fairness is not simple but complex, and that it is not an absolute but a matter of trade-offs. 
  • Financial Research: The Final Frontier for Fintech Innovation

    Rowland ParkOf course, Refinitiv (formerly known as Reuters) and Bloomberg terminals have been a mainstay of trading desks for decades, but now firms are using algorithms to transform headlines into data which can be utilized by both human traders and algorithms, to drive trading decisions.The volume and lack of innovation in the world of financial research means that it is very difficult for market participants to effectively handle and consume the information they are receiving, leading to less-effective outcomes.The opportunity now is to use smart technology to transform the liability of information overload in financial research into the asset the analysis was designed to be in the first place.

    Morningstar : Announces Planned Acquisition of Financial Planning Software Provider AdviserLogic

    PRNewswire – “Morningstar believes in the value of financial advice, and we share a common mission with advisers to empower investor success. We’re excited to expand our ability to support advisers at a critical time for the industry by welcoming AdviserLogic into the Morningstar family,” said Jamie Wickham, managing director of Morningstar Australasia. “Financial planning software is at the heart of the advice process. Combined with Morningstar’s deep data, analytics and research, AdviserLogic’s focus on user experience and advice workflow will enable us to elevate and differentiate our technology solutions for advisers—to support them in running an efficient and compliant practice; and deliver improved outcomes for their clients.”

    CAT Resurrects the Age-Old Question ‘Build vs. Buy?’

    Alex Rabaev – Overall, in-house built solutions are not replaceable, but it may be more practical to consider outside solutions. The decision is never one dimensional and never in the moment, as it will transcend scope and time. Your decision should balance practical short-term considerations and long-term strategy/vision.

    Algo Wheels: Best Execution, Workflow Solution, or Both?

    Larry Tabb – Algo wheels help buy-side firms automate their algorithmic workflow and rationalize their usage of broker algorithms. The wheel not only simplifies the difficulty of allocating order flow to a specific broker, it also helps the buy-side trader ascertain the quality of the broker’s algos given differing liquidity patterns and trading situations. … When used for best execution a broker wheel pits similar algorithms against each other using A/B-type testing strategies. … Normalizing disparate algorithms to measure performance and ensure best execution are the algo wheel’s killer application. … But algo wheels don’t guarantee best execution by themselves. … As algo wheels gain traction, TABB Group sees buy-side firms supporting two different types of tools. The first set includes more generic algorithms that fit into an algo wheel, which will be used for more traditional VWAP, TWAP, IS, or dark accumulation strategies; and the second set contains those more customized algos that will be tailored to specific situations. … Increasingly, the buy-side trader’s job will be focused on ascertaining the appropriateness of using a wheel, and those times when a more specific and customized tool will provide a better outcome.

    Buy-Side Trend Watch: Harnessing Alpha With Innovation

    Wayne CurryBespoke dashboards that mingle internal and financial data, visualize ideas, and share the results across the firm can also enhance the scalability and productivity of the idea generation process. This strategy boosts capabilities and delivers transparency more efficiently.

    Delivering Algo Performance, Regulatory Conformance and System Integrity Through Enhanced Market Replication
    Iain Greer – Firms need to fully embrace realistic market solutions, provide differentiation from fragmented and limited market simulation environments, and adopt solutions which allow them to quickly and efficiently represent:

    • The different trading strategies of market participants, such as high-frequency traders (HFT), investment managers or competing executions desks
    • The micro-structure of exchanges, including the execution policies, order types, speed bumps or auction rules.
    • The latency and locations of different exchanges or execution venues.
    • The bank’s own internal infrastructure, including smart-order routers, circuit breakers, client on-boarding, and trade processing critical to success.
    • An unlimited number of future scenarios, including regulators’ stress tests, and measure their impact in a safe, virtual environment.