Exponential smoothing is a forecasting technique that assigns exponentially decreasing weights to past observations, giving more weight to the most recent data. The primary goal is to smooth out short-term fluctuations (noise) in time series data while keeping the underlying trend intact. By applying weighted averages, exponential smoothing effectively captures recent patterns and adjusts the forecast accordingly. This technique is widely used in scenarios where the data shows little to no trend or seasonality and is easy to implement for short-term forecasting. The other options are incorrect because: • Option 1 (Eliminating noise) is not the main goal. Exponential smoothing deals with smoothing data but not the complete elimination of noise. • Option 3 (Equal weight) is a characteristic of simple moving averages, not exponential smoothing, where weights decrease exponentially. • Option 4 (Decomposing the series) refers to decomposition techniques like classical decomposition or STL decomposition, not smoothing methods. • Option 5 (Higher-order differences) is a technique used for differencing in ARIMA models, not in exponential smoothing.
The maximum foreign direct investment (FDI) allowed in Indian insurance companies is:
New India Assurance Co Ltd is a type of ?
Which type of risks are not insurable ?
What is the ceiling of annual premium in a Micro Variable Insurance Product?
A policy that covers the loss of money in transit is:
As per the Consumer Protection Act, 1986, who cannot be classified as a consumer?
An independent professional person registered under the Insurance Act who represents the insurance buyer to purchase the insurers policy is known as?
In which year New India Assurance Co Ltd nationalized?
The Insurance Ombudsman was established to:
General Insurance Corporation of India (GIC) was established in: