Understanding Risk in terms of Behavioral Finance

A fundamental idea in finance is understanding risk and return relationship. The greater the amount of risk that an investor is willing to take on, the greater the potential return. The reason for this is that investors need to be compensated for taking on additional risk.


Loss Aversion

Loss Aversion refers to perople’s tendency of avoiding losses when risking money for profits. Individuals are far more affected by losses than equivalent gains (loss aversion), and this behavior is made worse by frequent monitoring (myopia). In terms of trading, myopia refers to micro-management of position (frequently scaling in/out of the position).

Individuals tend to be much more willing to take risks with what they consider “found money” than with money that they have earned (called house money effect). As an example, traders tend to take more risk when achieve abnormal profits (feeling lucky).

There are two scenarios where risk aversion seems to decrease and even be replaced by risk seeking. One is when individuals are offered the chance of making an extremely large sum with a very small probability of success (long shot bias). The other is when individuals who have lost money are presented with choices that allow them to make their money back (break even effect).

When faced with risky choices, whether in experiments or game shows, individuals often make mistakes in assessing the probabilities of outcomes, over estimating the likelihood of success, and this problem gets worse as the choices become more complex.

Systematic Risk:

  • The risk inherent to the entire market or entire market segment. Also known as “un-diversifiable risk” or “market risk.”
  • Interest rates, recession and wars all represent sources of systematic risk because they affect the entire market and cannot be avoided through diversification.
  • Whereas this type of risk affects a broad range of securities, unsystematic risk affects a very specific group of securities or an individual security. Systematic risk can be mitigated only by being hedged.
  • Even a portfolio of well-diversified assets cannot escape all risk.

Unsystematic Risk:

Company or industry specific risk that is inherent in each investment. The amount of unsystematic risk can be reduced through appropriate diversification. Also known as “specific risk”, “diversifiable risk” or “residual risk”.

For example, news that is specific to a small number of stocks, such as a sudden strike by the employees
of a company you have shares in, is considered to be unsystematic risk.


  • A measure of the volatility, or systematic risk, of a security or a portfolio in comparison to the market as a whole. Also known as “beta coefficient”.
  • Beta is calculated using regression analysis, and you can think of beta as the tendency of a security’s returns to respond to swings in the market. A beta of 1 indicates that the security’s price will move with the market.
  • A beta of less than 1 means that the security will be less volatile than the market. A beta of greater than 1 indicates that the security’s price will be more volatile than the market. For example, if a stock’s beta is 1.2, it’s theoretically 20% more volatile than the market.
  • Many utilities stocks have a beta of less than 1. Conversely, most high-tech NASDAQ-based stocks have a beta of greater than 1, offering the possibility of a higher rate of return, but also posing more risk.

Unlevered Beta:

A type of metric that compares the risk of an unlevered company to the risk of the market. The unlevered beta is the beta of a company without any debt. Unlevering a beta removes the financial effects from leverage.

This number provides a measure of how much systematic risk a firm’s equity has when compared to the market. Unlevering the beta removes any beneficial effects gained by adding debt to the firm’s capital structure. Comparing companies’ unlevered betas gives an investor a better idea of how much risk they will be taking on when purchasing a firms’ stock.

Risk Modelling


Note that all of the models of risk and return in finance agree on the first two steps. They deviate at the last step in the way they measure market risk, with

  • The CAPM, capturing all of it in one beta, relative to the market portfolio
  • The APM, capturing the market risk in multiple betas against unspecified economic factors
  • The Multi-Factor model, capturing the market risk in multiple betas against specified macro economic factors
  • The Regression model, capturing the market risk in proxies such as market capitalization and price/book ratios