The Nobel Prize, Systematic and Specific Risks of a Stock

In December 2007, a 70 year old molecular geneticist named Mario Capecchi Ramberg was awarded the prestigious Nobel Prize in Physiology or Medicine for his scientific discoveries. The early years of his life, however, did not look very promising...

Born in Italy in October 1937, Mario Capecchi Ramberg lost his father during the Second World War, while his mother was arrested and imprisoned in Dachau, a German concentration camp. Without parents, Mario went from a foster family to the streets, surviving for many years by wandering from town to town. In 1945, his mother was released and found him sick, exhausted and illiterate.

In 1946, mother and son left for the United States where Mario attended primary school despite his delay in academic learning and lack of knowledge of English. He continued his studies and eventually obtained a PhD in biophysics from Harvard University in 1967.

This true story is symbolic.

Generally, a novice investor has little knowledge of the stock market. So you could say that they are disadvantaged, not physically, but psychologically. They are in some ways "illiterate" regarding the market environment. Slowly, painfully and patiently, they learn the basics, and not without making mistakes. They overcome difficulties with effort and perseverance through courses, studying and formulating theories to finally achieve the success they hoped for. This is the exciting work of a researcher.

The purpose of this article is to add to the knowledge of the investor, to help them achieve their personal Nobel Prize, even if it's unknown to the world. This success is deserved since the investor at the end of his apprenticeship knows how to choose investments, analyze portfolio profitability, refine the knowledge acquired and apply common sense. They become a hunter of profit. Their greatest lesson could be summarized as: the market is not rationally predictable and that, thanks to their personal talents and preparation, they will use techniques to make a profit nevertheless.

There are two types of risk the investor takes when buying a security: the company-specific risk and general market risk. The first is called specific risk and the second is systematic risk. From the investor's perspective, specific risk is more dangerous in my opinion that systematic risk.

Examples of specific risk (SP):

Lower or higher than expected earnings
Change in consumer taste
Legal proceedings
Strikes
Obtaining or loss of a contract
Management errors
Analyst recommendations

An example of risk 2 is BlackBerry, which, with the arrival of the Apple iPhone, quickly lost its leadership in the smart phone market.

Examples of systematic risk (SY):

General market moves
Economic developments (recessions)
Inflation
Interest rates
Changes in government (politics)

An example of risk A is the dependence of the Canadian financial market from the US market. A positive or negative performance of US indexes promotes the same trend in Canadian indices.

Plausible combinations created by both types of risk are:

Sharp Stock increase: favourable SY + favourable SP
Sharp stock decline: unfavourable SY + unfavourable SP
Small stock increase: favourable SY + unfavourable SP (or vice versa)
Small stock decline: unfavourable SY + favourable SP (or vice versa)

The combinations are plausible; but lack an important element: what is the impact of each risk on the overall risk of a stock? The answer would give us a measure of one type of risk relative to the other and it would better qualify the profit opportunities of a stock.

We answer this question with some calculations.

Here are the formulas:

Specific risk of stock = total risk of the stock - systematic risk
The total risk of a stock = stock volatility squared
Systematic risk of a stock = stock beta squared x market volatility squared
% specific risk vs. total risk = Specific risk of stock / total risk of stock

1) Here is the data for an example from July 21, 2015:
Volatility of CNQ = 23.6% or 0.236 (Montreal Exchange)
Beta of CNQ = 1.26 (Yahoo!)
Market volatility = volatility of XIU = 13.96% = 0.14 (Montreal Exchange)

Here are the calculations:
Total risk of the issue = 0.236 x 0.236 = 0.0557 (Formula 2)
Systematic risk of CNQ = (1.26 x 1.26) x (0.14 x 0.14) = 1.5876 x 0.0196 = 0.0311 (Formula 3)
Specific risk of CNQ = 0.0557 – 0.0311 = 0.0246 (Formula 1)
% of specific risk of CNQ relative to the total risk of CNQ = 0.0246 / 0.0557 = 44% (Formula 4)

2) Here is the data for a second example from July21, 2015:
Volatility of BCE = 15.78% or 0.1578 (Montreal Exchange)
Beta of BCE = 0.56 (Yahoo!)
Market volatility = volatility of XIU = 13.96% = 0.14 (Montreal Exchange)

Here are the calculations:
Total risk of the issue = 0.1578 x 0.1578 = 0.0249 (Formula 2)
Systematic risk of BCE = (0.56 x 0.56) x (0.14 x 0.14) = 0.3136 x 0.0196 = 0.0061 (Formula 3)
Specific risk of BCE = 0.0249 – 0.0061 = 0.0188 (Formula 1)
% of specific risk of BCE relative to the total risk of BCE = 0.0188 / 0.0249 = 76% (Formula 4)

In light of the two examples above, we can see that the influence of specific risk factors in relation to systematic risk is based on the volatility of the stock and its beta.

3) Now here is the data of an example of a fictitious stock
Volatility of X = 15.78% or 0.1578
Beta of X = 1.00
Market volatility = volatility of XIU = 13.96% = 0.14 (Montreal Exchange)

Here are the calculations:
Total risk of the issue = 0.1578 x 0.1578 = 0.0249 (Formula 2)
Systematic risk of X (fictitious stock) = (1.00 x 1.00) x (0.14 x 0.14) = 1.00 x 0.0196 = 0.0196 (Formula 3)
Specific risk of X = 0.0249 – 0.196 = 0.0053 (Formula 1)
% of specific risk of X relative to the total risk of X = 0.0053 / 0.0249 = 21% (Formula 4)

By comparing the second and third example, we can deduce that when volatility is equal, the higher the beta and the more the stock price depends on systematic risk factors and less on specific risk factors.

4) Here is an example of the data for another fictitious stock:
Volatility of Y = 50% or 0.50
Beta of Y = 1.26
Market volatility = volatility of XIU = 13.96% = 0.14 (Montreal Exchange)

Here are the calculations:
Total risk of the issue = 0.50 x 0.50 = 0.025 (Formula 2)
Systematic risk of Y (fictitious stock) = (1.26 x 1.26) x (0.14 x 0.14) = 1.5876 x 0.0196 = 0.0311 (Formula 3)
Specific risk of Y = 0.025 – 0.0311 = 0.2189 (Formula 1)
% of specific risk of Y relative to the total risk of Y = 0.2189 / 0.025 = 82% (Formula 4)

With the first and fourth examples, it is possible to observe that when beta is equal, the higher the volatility, the more the stock price depends on specific risk factors and less on systematic risk.