Risk in a very abstract form can be defined as uncertainty in the system. Risk management thereby is key to pulling off any bet or endeavour. It keeps us in business and reduces the effect of luck. It’s the proportion of luck in a gamble/bet. In poker terms, an 80% chance of winning has less risk than a 50% chance of winning the bet.

“You cannot swim for new horizons until you have the courage to lose sight of the shore.”

William Faulkner

In markets, you are looking to trade risk for returns. The goal is to trade lots of returns for as little risk as possible. You cannot win if you don’t bet/participate in the hand. But, the intent is to only play hands where we have a good chance of winning by minimising and managing risk.

Besides seeking return generating signals, managing risk is the most important aspect of any process. Including planning your life, job or any other endeavour.

Wearing a seat belt is not necessary but wearing one, once can significantly reduce the chance of a fatality or serious injuries. Risk management at work.

Another popular example is taking up a job. Where one seeks fixed income in exchange for any value generated for the business. The business is the entity that seeks risk by taking the other side of the trade though they need to manage risk well to stay in business.

Two of the highest paying jobs are sales and of a trader. Both carry significant risk in comparison to other stable jobs. This higher risk comes with greater rewards in terms of huge bonuses on high performance.

Un-certainty comes in different forms and thereby, there are multiple kinds to it. Broadly, there is an average risk with a decision and the worst-case situation with risk. In the car analogy, the average risk is either getting hurt or being in an accident. The worst-case risk is death.

The risk of accident can further be broken down into multiple subsets which can originate from over-speeding, other drivers, bad roads, pedestrians and so on. Similarly, every trade can have multiple types of risk.

Some of the above definitions are fluidic. Often when we trade, we looking to exchange between the risks and continue to make money through it. As situations change, the different risk goes up and down and accordingly, we try to adjust the situation.

As per the efficient market hypothesis, there is no free lunch and you get excess returns for taking on more risk.

Risk Management

Now that, we know some broads categories of risk. When trading or running a business. You intend to continue the trade/business while managing/hedging risks.

In a trading context, the risk is managed through a bunch of steps.

A business might be looking to hedge several of its risks:

For an engineering system. Risk management can manifest as

Quantifying Risk

Where ever possible, risk needs to be quantified and accounted for. This is needed to be able to make a decision or call based on the assessment. In trading, the risk of a portfolio is quantified as the volatility of its returns.

One of the most widely used metric being the Sharpe ratio. Sharpe Ratio is defined primarily as returns upon standard deviation of returns over the specific period of interest. 1 being decent and 2.5 is great.

Drawdown is used to quantify the risk of the worst-case form. Defined as the maximum fall in portfolio returns from its absolute peak. Smaller the drawdown, the greater the portfolio resilience.

Though, very elaborate explanations. Both the metrics above are based on past historical data and assume future market conditions to be similar to the past.

This snippet from the mutual funds Sahi hai portal reflects the market risks. The offer clearly stating that they cannot promise similar performance if the market conditions deviate significantly from the preceding times.

In technology systems, you make money when systems are up 24*7, 365 days. This need for resilient systems brings risk management to the forefront of software engineering, especially when designing and operating at scale. System’s risk is defined as downtime.

A well-designed architecture is up 99.99% of the time but hacked together components can face frequent outages. The risk metric here, being the uptime for the system. The greater, the better is the system.

Conclusion

While not revenue-generating, an understanding of risk for the domain and it’s management is key to be able to stay in the business and derive the full value out of the operation.

Some of the key things to do would be to identify the key risks being assumed. What moves them up or down. While, all risks cannot be handled at a startup phase but it should be clear, which ones are being ignored and what that could mean for the business or the trading strategy.

Originally published at https://statarb.in.

Startups & Analytics