Final answer:
Forecast accuracy tends to decrease with longer forecast horizons due to increased uncertainty and random variations. Examples from weather forecasting, political behavior predictions, and stock market analysis illustrate that while general trends can often be predicted, individual events or short-term outcomes remain unpredictable.
Step-by-step explanation:
The assertion that forecast accuracy generally increases as the forecast horizon increases is incorrect. In reality, forecast accuracy tends to decrease as the time horizon increases. This happens because shorter time horizons are less influenced by random variations and have more certain underlying patterns. For example, in the context of weather forecasting, short-term forecasts are usually more reliable due to the ability to capture immediate atmospheric conditions that are less prone to random events. Predicting political behavior on a general scale is achievable due to statistical averages and trends, but individual cases are inherently uncertain due to the element of human randomness.
Similarly, in the field of finance, the concept of a "random walk with a trend" explains stock price movements. Day-to-day prices may fluctuate unpredictably, but over time they generally follow an upward trend. With larger sample sizes, confidence intervals become narrower, enhancing the predictability of trends. However, individual events, such as stock movements on a single day, remain difficult to predict with complete accuracy due to unforeseen future news that may affect market expectations.