Skin in the game: if risk managers are so smart why are they not millionaires?

I started writing yet another article trying to convince risk managers to grow their quant competencies, to integrate risk analysis into decision-making processes and to use ranges instead of single point planning… but then I thought… why bother… why not show how risk analysis helps make better risk based decisions instead?

After all, this is what Nassim Taleb teaches us. Skin in the game.

So I sent a message to the Russian risk management community asking who wants to join me to build a risk model for a typical life decision? 13 people responded, including some of the best risk managers in the country, and we set out to work.

We decided to solve an age-old problem – win the lottery. With the help from David Vose and his free ModelRisk we set out to make history (not really, been done before, still fun though).

Here is some context:

• lotteries are an excellent field for risk analysis since the probabilities and range of consequences are known
• in Russia, as in most countries of the world, lotteries are strictly regulated
  There is a rule when a large amount accumulates, several times a year it is divided among all the winners. This is called roll-down.
• if no one takes the jackpot before or during the roll-down, then the whole super prize is divided between all other winners
• so the probability of winning is the same as usual, but the winnings for each combination can be significantly higher if no one wins the jackpot.

And so we set out to test our risk management skills in a game of chance.

8.06.2019

Whatsup group created. Started collecting data from past games.

9.06.2019

Placing small bets to do some empirical testing.

10.06.2019

First draft model is ready…

11.06.2019 

Running monte-carlo simulations to find most optimal strategies.

To be continued. I will keep you posted on the developments.

– – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – – –

P.S. By the way, this is how the MIT students, the Goldman Sacks employee and the family of retired mathematicians did it and earned good money.

P.P.S. Good luck solving this puzzle with a heatmap :))