Question

The naïve investor hypothesis and the no effects hypothesis are two competing hypotheses to study accounting method changes. What do these two hypotheses say and which hypothesis is accepted by the research?

Answer 1

Naive investor hypothesis is best described as a rough and, more or less, instinctive common-sense division of a portfolio, without bothering with sophisticated mathematical models. At worst, say some experts, this approach can make portfolios highly risky. Then again, some recent research indicates that this kind of informed, but poorly logical division, is just as effective as those fancy, optimising formulae.

The null hypothesis is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups.
Testing (accepting, approving, rejecting, or disproving) the null hypothesis—and thus concluding that there are or are not grounds for believing that there is a relationship between two phenomena. The field of statistics gives precise criteria for rejecting a null hypothesis. The null hypothesis is generally assumed to be true until evidence indicates otherwise.

Each of us is potentially a naive investor. If we make this mistake, then we invest without a strong grasp of the return potential of the investment and the risks to the outcome. While obviously this can lead to poor specific investment outcomes, we also end up with poorly constructed portfolios because we aren’t aware of the risks we are trying to balance. It can even leave you open to fraud.