https://tabbforum.com/opinions/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.
https://tabbforum.com/opinions/buy-side-trend-watch-harnessing-alpha-with-innovation/ Wayne Curry - Bespoke 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
https://tabbforum.com/opinions/delivering-algo-performance-regulatory-conformance-and-system-integrity-through-enhanced- 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.
https://www.toptal.com/project-managers/agile/agile-documentation?utm_campaign=PM_Blog&utm_source=hs_email&utm_medium=email&utm_content=77279650&_hsenc=p2ANqtz-80sqyi3ooRWDXor8tc0PcQ2nZcDpXkd5D3J6_HDCuC36Rhim0syrjzgbGWe2tw5ixH7gtbgDTrbQeOvjcrdnpZwwtjEA&_hsmi=77279650 VINOD SUKUMARAN - "Agile Documentation: Balancing Speed and Knowledge Retention" For many project managers, it’s not a big stretch to understand how the Waterfall phases are turned into sprints—the same work is accomplished; it’s just organized in a different way. However, the removal of most documentation is a harder pill to swallow as it underlines a completely different way of working. It requires loosening the reins of control, embracing the unknown, and empowering the delivery team to make decisions on the spot. Additional added October 4, 2019 What Is Agile Methodology: A Primer On Moving Fast https://angel.co/blog/agile-methodology-a-primer-on-moving-fast?utm_source=platform-newsletter&&utm_campaign=platform-newsletter-100319&alla%5Bsource%5D Caleb Kaiser - If you’re joining an engineering team for the first time or just looking for a refresher, this primer will get you up to speed with a functional understanding of agile methodology, its core components, leading benefits, and popular delivery implementations.
https://tabbforum.com/opinions/new-and-improved-algorithms-empower-the-buy-side/ Larry Tabb - As a result, brokers are re-investing in their infrastructure and trying to leverage new technologies and data science to make their trading algorithms better, more efficient and more effective.
https://tabbforum.com/opinions/survival-of-the-fittest-modernizing-capital-markets-infrastructure/ Monica Summerville - While financial institutions have invested billions of dollars, pounds and euros on implementing once-state-of-the-art systems, demands from both regulators and clients for ever-greater transparency into data and its analysis can mean tenfold increases – or more – in the amount of data generated. In addition, relying on “start of the day” or “end of day” data often is no longer acceptable. Instead, more functions are requiring near- or fully real-time access to data and analytics, which compounds the data architecture challenge.
https://thefinanser.com/2019/08/where-top-us-banks-are-betting-on-fintech.html/ Chris Skinner - Citi has backed 4 blockchain, 3 capital markets, and 3 payments & settlement startups since 2017. Generally, these investments fit into the banks’ larger strategy of building open banking infrastructure. In March, Citi announced plans to build a “digital consumer payments business for institutions,” and there are rumors Citi may launch a Banking-as-a-Service platform.
https://www.datanami.com/2019/09/17/whats-the-difference-between-ai-ml-deep-learning-and-active-learning/ Kiran Vajapey - Today, the terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably. While the terms are related, they mean different things. We map out how they all relate to one another, so your team can find the best candidates, best approaches and best frameworks as you embark upon your AI journey.
https://tabbforum.com/opinions/trading-favors-the-technologist-the-buy-side-technology-arms-race/ Campbell Peters - While buy-side firms have built out their technology and analytics teams considerably, most firms still outsource execution algos from their brokers. This is especially true for fundamental firms, as quantitative firms are more likely to develop some of their algos in-house. These quant firms have been the most willing to adopt emerging technologies, such as machine learning and AI, since they have the resources to develop and test the functionality in-house if needed.
https://tabbforum.com/opinions/buy-side-turning-to-technology-to-meet-todays-challenges/ Monica Summerville - The practical reality of this means robotic process automation (RPA), as opposed to AI – e.g., machine learning (ML) and Natural Language Processing (NLP) techniques – are more likely to be implemented to start.