Regression, Entropy and the Market Whales

Regression, Entropy and the Market Whales

Regression towards the mean is a statistical phenomenon in which extreme values tend to be followed by more moderate values, and vice versa. In financial markets, this principle can affect both low entropy energy sources (such as market whales) and high entropy waste (transaction noise).

1. Low Entropy Energy Sources: When market "whales" make large trades or hold significant positions in a particular security, they can cause the price to move significantly away from its historical average. However, due to regression towards the mean, it is likely that subsequent prices will revert back towards their long-term average as other traders adjust their expectations and trading strategies. This process may result in a temporary decrease in the value of low entropy energy (information) provided by whales, as their unique insights become less valuable when the market reverts to its historical average.

2. High Entropy Waste: Transaction noise generated by high-frequency traders or retail investors can also be affected by regression towards the mean. During periods of extreme price movements (caused, for example, by a major news event), transaction noise may temporarily increase as traders make rapid and uncoordinated adjustments to their positions. However, over time, these extreme price movements are likely to revert back towards the historical average due to regression towards the mean, reducing the level of transaction noise in the market.

In summary, both low entropy energy sources (market whales) and high entropy waste (transaction noise) can be affected by the principle of regression towards the mean in financial markets. This phenomenon may lead to temporary changes in the value of information provided by whales or the level of transaction noise in the market as prices revert back towards their long-term average trend.