Episode 16: Kris Verma on Kelly Criterion Trading Stats



Who Is Kris Verma?

Kris Verma is a successful pharmacist and sports better turned day trader. After retiring from being a pharmacist, Verma decided to apply his statistical edge in sports betting to the markets. The result has been stellar, with over $1million in profits in just a few short years.

Kris Verma is a statistician of sorts. His approach to trading and betting is deeply rooted in mathematics. As the saying goes, an edge is nothing more than a probable outcome in your favor. Sure, you’re going to lose some, but as long as the winners outweigh the losers over time, you come out on top. Verma has taken this to a whole new level.

The Kelly Criteria and Verma’s Formula

On Kris’s blog, he discusses the basis for his formulaic approach to the markets. It is based upon the Kelly Criterion, which allows Chris to calculate his statistical edge and optimal position sizing according to backtested data.

Kelly Criteria Chart

As you can see, there is a point of diminishing returns if you size in too much (blue line). Optimal position sizing keeps your risk (volatility) in check if your data is accurate. Kris mentions this at time stamp 53:18 in the interview.

In the video, Kris shares a link to a template for his strategy in a spreadsheet. You can find that link here:

Kris discusses this around 1:05:00 in the video.

Kris Verma Interview Topics and Chapters

  • Verma’s Background on Stats and Mathematics – 1:00
  • Ego vs. Backtesting / Discretion vs. Systematic – 10:00
  • How to find an edge – 19:42
  • The NNVC trade explanation – 23:40
  • Kris on Trading Psychology – 36:30
  • A+ Setups: Day 2 Short into Resistance – 39:25
  • Habits of Winning/Losing Traders – 44:43
  • Using Kelly Criteria to determine position sizing – 57:15
  • Trading Database Template – 1:09:35
  • Liquidity Traps and changing markets – 1:21:45
  • Basic Kelly Criteria calculator -1:27:42
  • Accountability – 1:32:30


Image and article originally from tradingsim.com. Read the original article here.