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Triple exponential smoothing for equity instruments - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When equity instruments prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in equity instruments price movement. However, neither of these exponential smoothing models address any seasonality of ###3###.
As with simple exponential smoothing, in triple exponential smoothing models past equity instruments observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older price observations.
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If you are a self-driven investor, you will appreciate our idea-generating investing themes. Our themes help you align your investments inspirations with your core values and are essential building blocks of your portfolios. A typical investing theme is an unweighted collection of up to 20 funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of equities with common characteristics such as industry and growth potential, volatility, or market segment. | Macroaxis Index Invested over 90 shares | |
 | SRI Sustainable Growth Invested over 90 shares | |
 | ESG Investing Sold few shares | |
 | Corona Opportunity Invested over 90 shares | |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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