Risk is an integral element of returns in the realm of finance. However, that does not mean one should accept the inherent risk of an investment as fate and leave it so. That’s why investors, managers, corporate bodies, inter alia, try to mitigate the inherent risk by means of risk management.
In this article
What is Risk Management?
Risk management, as per several definitions, is a three-step process. It involves the identification of threats or downsides to an outlay and analysing them through standard mathematical approaches or other means; eventually deriving measures to mitigate the same.
Risk management is an integral component in the world of finance and prevalent everywhere. For instance, banks analyse the risk associated with an applicant before sanctioning a loan in order to minimise instances of delinquency. Similarly, investors opt for futures and options contracts to deal with stock markets as a means to mitigate losses from market volatilities.
The primary basis for risk management is risk tolerance. An ‘all size fits all’ financial risk management style, therefore, does not apply anywhere. There is no rule of thumb when it comes to risk management strategies, and managers shall design a portfolio based on an array of factors, the primary one being an individual’s risk tolerance.
An investor with a low-risk aptitude will definitely manage or have their portfolio managed in order to maximise the safety of corpus rather than the magnification of returns. Ipso facto, risk management is a complex procedure, but paramount nonetheless. Incompetent risk management can bring financial ruin.
How does Risk Management Work?
As mentioned earlier, the risk is an inseparable element of returns, the two sides of the same coin.
Plus, risk shall not always be subject to a negative connotation, since it can go the other way as well. Essentially, this term refers to any deviation from the projection. Therefore, it can either deviate positively or negatively.
And that’s precisely why risk correlates with returns. The degree of risk of an investment is also an indication of the scale of returns one could earn from it. The higher the risk, the greater are the chances of high return.
Individuals can calculate the risk of an investment option either in absolute terms or in relation to something, like a market index. A common metric that managers use to determine the potential and absolute risk of an investment option is the standard deviation. It’s a statistical instrument that provides the dispersion of outcomes around a mean or central tendency.
To calculate standard deviation as witnessed in an investment option, individuals need to take into account its historical returns across a period.
The standard deviation is a measure of how the returns have fluctuated over that period from the average. It can be better understood with an example.
Risk management example:
If the standard deviation for a particular stock is 12% and its average return is 15%, then its returns can be plus or minus 12% the average return at any given point in time.
Furthermore, if the returns across a period are normally distributed, i.e. bell-curve distribution, then the returns will most likely be one SD from the average returns for about 2/3rd of the time, and two SDs from the average return for about 95% of the time.
Therefore, if considering the above example, then about 67% of the time returns will be 12% above or below the average of 15%, and 24% above or below the average of 15% for about 95% of the time.
For adequate risk management in stocks, an investor would then have to consider whether they are willing to go for that kind of deviation or not.
What are the Types of Risk Management?
One can broadly classify risk management styles into two categories: passive management and active management.
One critical measure used in passive risk management is the drawdown. It denotes any period during which a specific asset suffers returns that are negative in relation to a previous high. That way, investors learn how risky a specific asset was vis-á-vis a market index like Nifty 50.
Investors predominantly use the measure of beta for this purpose, which is based on covariance. The beta risk of an asset can be either above 1 or below 1, and it refers to the degree of correspondence of such asset’s returns with market returns. A beta value above 1 means that asset is more volatile than the market and vice versa.
For example, if an equity-based mutual fund has a beta value of 1.3 in relation to Sensex, then a 100% increase in that index’s return would translate to a 130% increase in that MF’s returns and vice versa. Similarly, if the beta value of an asset is below 1, let’s say 0.9, then a 100% change in the market return would result in a 90% change in its own returns.
Passive risk managers can implement strategies to increase the beta risk exposure of a specific portfolio in order to enhance its return capability. It is ideal for moderate to high risk-takers.
On the other hand, they can also choose to reduce the beta risk exposure of a portfolio, and consequently decreasing its return capability. That is ideal for low risk-takers.
While passive management follows market returns more or less, active risk management involves striving to beat that market return. It goes beyond market risk. Active management strategies aim to capitalise on a number of factors that are unrelated to market returns, like leveraging stock, position-sizing, etc. to earn returns above that.
However, by doing so, managers also expose investors to greater risk or alpha risk. Therefore, active management is mostly carried out by seasoned investors or individuals with a high-risk aptitude.
Naturally, active risk management involves a higher cost, mostly based on the alpha factor a manager provides on a specific asset. For instance, if a fund manager can show that she employs specific strategy/strategies to earn returns 2% higher than the market index on an average annualised basis, then she can charge an amount based on that 2% excess income.
Risk Management and Behavioural Finance
In 1979, Amos Tversky and Daniel Kahneman introduced the prospect theory, which showed the asymmetry between perception and significance of gain and loss. The two economists demonstrated that individuals were more averse to losing out on their money and put only half as much heft to the idea of earning gains.
By nature, investors are more risk-averse than they are gain-seekers. Therefore, investors want to know the worst downside of an investment option commonly in absolute terms rather than the extent of its deviation.
For that reason, investors use a statistical measure called Value at Risk. Through this measure, investors learn the maximum extent of loss they could suffer across a specific period and the probability of that extent being true. An example would be: “The highest loss is Rs.5000 on investment of Rs.20000 in ABC equity over 3 years, and that merits a 90% level of confidence.”
The level of confidence denotes the probability that if the worst is to come, one could lose Rs.5000 from the given specifics. The rest percentage, 10% in this case, is an error of margin, meaning losses could be worse than estimated.
Nevertheless, due to the VAR’s concrete representation of loss, risk management becomes a lot simpler, especially to uninitiated investors.