For a millennium, mankind attempted to define and measure risk.
From the time of Pascal and Golton to today's forerunners in academia, people have been trying to define and measure risk. There doesn't seem to be a way to mathematically beat risk and make financial markets and economies free of risk until we properly define and measure risk.
With the invention of probability study, math opened a new door for people. In the 1660s, a man named John Graunt was the first person to use probability studies in real-world statistical research. Gruant's methods were used by many people before they became the same ones that insurance companies still use today to figure out how much to charge for insurance. Probabilistic study is a useful mathematical tool for figuring out how likely it is that different things will happen, but it has some flaws. It had flaws that made it useless for helping to stop or predict the Great Depression, the World Wars that followed, and each market crash that came after. Probability has two major flaws. First, it is based on the idea that each outcome is random and independent of the others. This leads to a normal distribution. Second, probability can't take into account more outcomes than what was already taken into account. Yes, that is what it means to be "caught off guard," isn't it? People have been "caught off guard" more times than we want to admit.
Since new information and new results can't be predicted, studies that rely on past results and events aren't useful when new information comes out. Because of this, investment reports always say "past performance is no guarantee of future performance." Risk is mostly about not knowing what will happen. Treasury securities are so "risk-free" because they are very likely to do what they are supposed to do.
But risk isn't just the uncertainty of what will happen; it's also what will happen if something goes wrong.
Too long, people have defined risk based on how likely it is to happen, without taking the consequences into account. Risk is caused by uncertainty, and the end result of risk is a result. What is risky and what isn't is really determined by what could go wrong.
I think of risk as the chance of losing everything.
We always live in a risky environment and almost everything we do is risky, but we do it anyway because the chance of a huge loss is low or because a bad outcome can't be considered huge.
This brings us to the real nature of risk: different people have different ideas about it. Some people can handle a 20 percent loss in their portfolio, while for others, that same 20 percent loss is a disaster. When an investor knows what a "catastrophic loss" means for him or her, he or she will be able to use modern risk prevention tools to make investment portfolios that have no risks at all.
If even a 1% loss in a portfolio is a disaster for an investor, that investor should not put money into the stock market. If one sets a level of catastrophic risk, say 20 percent, they can use strategies like the Protective Put or the Married Put to make sure their stocks never drop below that level. In fact, a simple portfolio-wide stop loss policy can limit losses to the level that is considered a catastrophic loss. Would you still call your investment "Risky" if you knew you could never lose more than you wanted to?
Adding "convexity" to a portfolio means taking steps to limit the portfolio's potential losses. A convex portfolio has a limited chance of going down but an unlimited chance of going up. Modern risk management places a lot of importance on building convexity because it is impossible to know what might happen. All we can do is make sure that the worst thing that could happen doesn't fit into anyone's idea of what a catastrophic loss is. A long time ago, it was hard to get such a portfolio. However, now that great financial tools like stock options exist, convexity and risk-free investing are available to anyone who asks, "What would a catastrophic loss mean to me?"
