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Kumaran Vijayakumar, Co-Founder and CEO, DataDock Solutions

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Manage episode 524502465 series 2516749
Content provided by Dean Curnutt. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Dean Curnutt or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Kumaran Vijayakumar has spent his career in the equity derivatives market, first as an exotics trader and later in running large risk-taking desks in listed and OTC options. Now, the CEO of DataDock Solutions, a firm he Co-Founded in 2018, Kumaran and his team are developing analytical tools that allow sell-side flow desks to better understand the risks they take and clients they take it for. Our discussion explores the challenges inherent in evaluating client flow, and how data-centric infrastructure has changed the way risk is assessed.

With the premise that “what you can measure you can manage and improve”, we discuss DataDock’s efforts to build tools capable of ingesting large-scale trade history and simulating outcomes at the most granular level. In equity derivatives, where trades move quickly and visibility is often instantaneous, desks have historically made decisions based on memory and anecdotal assessments of “good” versus “bad” flow. Kumaran describes this as a space where information is abundant, but structured insight often lags execution speed.

Our discussion highlights a key theme: not all flow that loses money is detrimental, and not all flow that is profitable is necessarily strategic. Instead, Kumaran notes that client value emerges when one analyzes trade behavior across time, including delta hedge quality, volume risk transfer, roll probability, expected event-driven distribution, and the role of flow as portfolio offset rather than standalone P&L.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Kumaran Vijayakumar.

  continue reading

238 episodes

Artwork
iconShare
 
Manage episode 524502465 series 2516749
Content provided by Dean Curnutt. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Dean Curnutt or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Kumaran Vijayakumar has spent his career in the equity derivatives market, first as an exotics trader and later in running large risk-taking desks in listed and OTC options. Now, the CEO of DataDock Solutions, a firm he Co-Founded in 2018, Kumaran and his team are developing analytical tools that allow sell-side flow desks to better understand the risks they take and clients they take it for. Our discussion explores the challenges inherent in evaluating client flow, and how data-centric infrastructure has changed the way risk is assessed.

With the premise that “what you can measure you can manage and improve”, we discuss DataDock’s efforts to build tools capable of ingesting large-scale trade history and simulating outcomes at the most granular level. In equity derivatives, where trades move quickly and visibility is often instantaneous, desks have historically made decisions based on memory and anecdotal assessments of “good” versus “bad” flow. Kumaran describes this as a space where information is abundant, but structured insight often lags execution speed.

Our discussion highlights a key theme: not all flow that loses money is detrimental, and not all flow that is profitable is necessarily strategic. Instead, Kumaran notes that client value emerges when one analyzes trade behavior across time, including delta hedge quality, volume risk transfer, roll probability, expected event-driven distribution, and the role of flow as portfolio offset rather than standalone P&L.

I hope you enjoy this episode of the Alpha Exchange, my conversation with Kumaran Vijayakumar.

  continue reading

238 episodes

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