Lagging Indicator Accuracy In ThinkOrSwim

[bobhobe]

Here is a moving average that identifies breakout points.
The accuracy of the breakout/breakdown points are not that good.
Any suggestions to improve accuracy would be appreciated.

declare lower;

input length = 15;
input multiplier = 2.0;

def price = close;

def average = MovingAverage(AverageType.SIMPLE, price, length);

def upperBand = average + multiplier * StDev(price, length);
def lowerBand = average - multiplier * StDev(price, length);

def isBullishBreakout = close > upperBand;
def isBearishBreakout = close < lowerBand;

plot MA = average;
plot BullishBreakoutPoints = if isBullishBreakout then close else Double.NaN;
plot BearishBreakoutPoints = if isBearishBreakout then close else Double.NaN;

BullishBreakoutPoints.SetPaintingStrategy(PaintingStrategy.POINTS);
BullishBreakoutPoints.SetLineWeight(2);
BullishBreakoutPoints.SetDefaultColor(Color.GREEN);

BearishBreakoutPoints.SetPaintingStrategy(PaintingStrategy.POINTS);
BearishBreakoutPoints.SetLineWeight(2);
BearishBreakoutPoints.SetDefaultColor(Color.RED);

MA.SetDefaultColor(Color.BLUE);

 

[MerryDay]

Moving averages make poor strategies for several reasons:

1. Lagging indicator: Moving averages are based on past price data, which means they are lagging indicators. They reflect historical price trends and do not accurately capture the current market conditions. By the time a moving average signal occurs, the price has already moved, resulting in suboptimal profits.
2. Whipsaw movement: Moving averages generate false signals during periods of volatility and / or market noise. In such cases, the price crosses above or below the moving average multiple times, leading to frequent buying or selling signals. This whipsaw effect combined with the lag results in multiple losses which eats into trader confidence.
3. Lack of adaptability: Moving averages use fixed lengths (e.g., 50-day or 200-day moving average) to calculate the average price. However, different securities and markets exhibit varying levels of volatility and trends. Fixed moving average periods are not suitable for all assets nor for all timeframes, leading to suboptimal results. Additionally, moving averages do not adjust dynamically to changing market conditions or emerging trends.
4. Insensitivity to market reversals: Moving averages tend to be slow in responding to market reversals. They are smoother indicators that provide a broader view of the price trend, which can cause delays in identifying trend reversals. As a result, traders using moving averages, enter or exit trades too late, missing out on potential profits or suffering larger losses.
5. Over-reliance on a single indicator: Relying solely on moving averages as a trading strategy is not recommended. The market is influenced by multiple factors, including fundamental news, economic data, geopolitical events, and investor sentiment. Ignoring these factors and relying solely on buy / sell signals overlooks critical information that significantly affects profits.

While moving averages can be useful as part of a broader trading strategy on the higher timeframes, use of lagging indicators on lower timeframes should be limited in scope.

@bobhobe