# Risk Managing Mechanism

## Process & Mechanics

The final Execution Price offered to the trader is calculated by adding Risk Premium to the position value calculated by Black-76. Depending on whether the trader's position is long or short, a different formula is applied as follows:

Risk Premium moderates the supply and demand for options trading by incentivizing trades that lower the risk of the OLP and disincentivizing trades that increase the risk. Based on this market-friendly mechanism, the individual risk of an OLP is adjusted so that it remains close to zero.

**Trades that Increase OLP Risk:**Increases the amount of Risk Premium to be paid for Long positions and decreases the amount of Risk Premium to be received for Short positions, thus discouraging trades that increase the risk of OLP**Trades that Decrease OLP Risk:**Reduces Risk Premium applied to Longs and Shorts, allowing them to trade at narrower spreads, which in turn encourages more frequent trades that reduce the risk of OLP

Stochastic Simulation of Risk PremiumMoby's Risk Premium allows us to control the risk of OLP while providing traders with a cost-effective price compared to major CEXs. The Greeks Weight used to calculate Risk Premium is calculated through the following method.

Calculate market spread by collecting bid/ask spread data for options over time from major CEXs

Set Target Spread per term based on market spread

Create a random sample of Model Trade and Model Risk Premium by dividing trader types based on the following trade preferences

L / S:Long/Short Preference(Preference for the direction of the option position)

C / P: Call/Put Options Preference

A / O: Moneyness Preference(Near ATM / Far OTM preference)

D / W / M: Preference for DTE (2 days or less / greater than 2 days, but less than or equal to 90 days / greater than 90 days)ex.LCAD: Trader with the preference of [Long/Call/Near ATM/DTE<2]Set objective functions for Target Spread and Model Risk Premium by Trade Preference, and estimate Greeks Weight based on GMM(Generalized Method of Moments) estimation, which adjusts the objective functions to be close to zero

To verify the capability of the risk management mechanism, we conducted a stochastic simulation. We set a dismissing point and conduct random trading only when the discount rate of risk premium to market spread is above the predetermined dismissing point. We found that in about 50-80% of the trials, OLP was able to provide narrower spreads than the major CEXs while keeping the Greeks of OLP neutral.

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