What is the Black Box Model?

A black box model describes the relationship between the inputs and outputs of a system. This model is used in different contexts and has different meanings. As it is often used in science, computing and engineering, a black box model is a device that describes the functional relationships between system inputs and outputs. In business, a black box model is a financial model where a computerized program is designed to change various investment data into strategies that are useful for investments. The black in the black box model refers to the lack of access to the internal workings or parameters of functions of the model. The white box model is the opposite of a black box model, in the sense that its inner components are accessible and can be inspected.

How Does the Black Box Model Work?

Before the black box model was widely adopted in the financial markets, it was peculiar to the science, computing and engineering fields where the relationships between system inputs and outputs are described. In the financial markets, the black box model is associated with the decision-making process of an investment. This model could be an algorithm, a transistor or even a human memory or brain. The use of the black box model in the financial markets has however raised questions on the systematic risks that this model contributes to the market, given the tendency of investors to hide the actual risk of investments under the use of computer programs and technology. The black box model is also used as a model consumer behavior theory to describe the stimulus-response pattern of consumers.

The Black Box Model Over the Years

The use of the black box model in the financial markets is largely dependent on the market conditions and the market cycle. During periods of high volatility in the market, black box models can cause more dangers and the ultimate destruction of the market. Examples of how black box strategies cause destruction are the flash crash of 2015, the portfolio insurance episode of 1987, the long-term capital management implosion of 1998, among others. Given that black box strategies carry inherent risks, a number of concerns have been raised against their use. However, technological advancement, machine learning, data science and other related fields have led to the sophistication of the black box models. Presently, institution investment managers and hedge funds still use these strategies when handling complicated investments.