Nadaraya-Watson Smoothers

The trading indicator under discussion leverages the Nadaraya-Watson estimator to smooth price data, utilizing the Gaussian kernel for weighting functions. This approach offers traders the option between non-repainting and repainting methods, adding flexibility to their trading strategy.

How Does the Flexible Smoothing Trading Indicator Work?

Non-Repainting Method

When the Repainting Smoothing option is turned off, the indicator functions like a standard causal moving average, often referred to as an "endpoint Nadaraya-Watson estimator." Unlike traditional moving averages, which derive their smoothness from calculation window length, this indicator’s smoothness is governed by the bandwidth setting. A higher bandwidth results in smoother data outputs.

For example, in the chart above, a bandwidth value of 50 is elected. An ascent in the smoother suggests an uptrend, whereas a descent indicates a downtrend.

Repainting Method

Typical non-causal smoothing methods are sometimes underutilized due to their tendency to repaint. However, they offer valuable insights into trend estimation and price deviation analysis. They also simplify pattern identification and uncover underlying price structures.

By increasing the bandwidth value, traders can gauge longer-term price trends.

Triangular labels denote points of directional shifts in the estimator, aiding in the identification of trend tops and bottoms in comparison with actual price movements.

Be aware that multiple labels may display in real-time as the estimator's direction shifts, with the latest label appearing first. While this can be beneficial for predictive applications, it’s not the sole recommended use.

Understanding the Nadaraya-Watson Estimator

The Nadaraya-Watson estimator employs weighted averages with a specially normalized kernel functioning as the weighting tool. At any given time t, the kernel's peak is at t, leading to maximum weights on values nearest to the time t price.

Smaller bandwidth values enhance the precise point price weighting, leading to less smoothing. If the kernel effectively becomes an impulse due to a minimal bandwidth, raw prices are returned.

Conversely, a larger bandwidth promotes a uniform price weighting, analogous to the price mean.

Significantly, due to the estimator’s inherent properties and weighting method, real-time results near the calculation window's center do not exhibit drastic deviations.

Key Settings for Optimal Performance

• Bandwidth: Adjusts the Gaussian kernel's bandwidth, with larger numbers providing smoother outcomes.
• Src: The input source for kernel regression.
• Repainting Smoothing: Decides whether the smoothing method should repaint. Disabled options yield the "endpoint Nadaraya-Watson estimator."

FAQ

What is the Nadaraya-Watson Estimator in Trading? The Nadaraya-Watson estimator is a type of weighted average using a Gaussian kernel, aiming to smooth out price data for better trend analysis.

How Can I Access the Flexible Smoothing Trading Indicator? You can get access on the LuxAlgo Library for charting platforms like TradingView, MetaTrader (MT4/MT5), and NinjaTrader for free.