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 in the sales and trading industry carry significant risk in comparison to other stable jobs. This higher risk comes with greater rewards in terms of huge bonuses on high performance.
Types of Risk
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 risks.
- Market Risk :
- Equity Risk
- Interest Risk
- Currency Risk
- Concentration Risk: This can manifest into liquidity risk. This is one of the many risks undertaken by Greensill and resulted in its eventual collapse. Supply chain financing and Greensill has been excellently covered here.
- Credit Risk :
- Inflation Risk :
- Longevity Risk :
Some of the above definitions are fluidic. Often when we trade, we look 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.
- A country which opens operations in new country gets exposed to currency risk.
- When you invest into a company, you are taking on equity risk.
- When you lend money to a friend, relative. You take on credit risk. The risk of not getting the money back.
- Savings in form of cash lose value due inflation and thereby cash carries inflation risk and so on..
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 broad 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.
- Macro Risk (Overall equity market tanking /going up): Appropriate allocation can hedge this risk. Think of a combination of equity and bonds.
- Equity Market Risk: A long short fund can deal with this. By not being net long or short. We can hedge market movements.
- Sector Risk: A specific sector due to some policy or other reasons could go up or down. Tax reforms for a sector can make the firms in it soaring. Different sectors diversification can eliminate this risk.
- Idiosyncratic Risk: The risk specific to a company. Some fraud promoter or a new policy. The one way to deal with this is to trade a lot of instruments/stocks. This way, the random events would in a long run cancel each other.
A business might be looking to hedge several of its risks:
- Currency Risk: A business like Infosys which does business in the US dollars and costs money in Rupees. Need to hedge the currency conversion risk.
- Insurance: There are a lots of transactional risks when doing business such as fire insurance, counter party risk when buying anything and so on. Insurance firms help with risks such as fire and counter party risk for business deals can be handled using banks.
For an engineering system. Risk management can manifest as
- Planning servers and architecture for 2-10x the traffic depending upon the stage of product.
- Having backups and recovery as a part of system. Risk management in this context, is designed to deal with the absolute worst case situation.
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 metrics is 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 states 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. Downtime is an example of system risk here.
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
One good analogy is to understand that while steering the wheel is necessary, breaks play a pivotal role and should be deployed as and when needed. This ensures, we survive and get through the journey.
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.