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Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for equity instruments works best with periods where there are trends or seasonality.
When price 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 price trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent equity instruments observations are given relatively more weight in forecasting than the older observations.

Double Exponential Smoothing In A Nutshell

Smoothing is a term used when we are trying to turn the data into smoother trends. If you note on some indicators, they move in a wild manner and are choppy. The ideal indicator moves smoothly, giving use a potentially more accurate reading. If you saw an RSI that moved quickly, it may deter you from using that tool because you may not have the ability to form an opinion quick enough. However, if you are day trading, you may decide the quick movements are what you need.

If you have not done so or are new to exponential smoothing, check out simple exponential smoothing. It will give you a better understanding of double exponential smoothing and what the differences may be between the two. One of the main differences between the two is that simple exponential smoothing tends to lack when the market is trending.

Closer Look at Double Exponential Smoothing

You can smooth any amount of data into double, triple, and so on. The equation that goes into the double exponential smoothing can be difficult and off putting. However, it is important to understand the basic information that is taken into account as you want to understand what makes it move. It may not be necessary to understand the full equation however unless you are building a proprietary instrument. MacroAxis offers many different tools and researching aids that you can narrow in on exactly what fits your needs best. Throw in numbers and begin testing out certain aspects.

Generate Optimal Portfolios

The classical approach to portfolio optimization is known as Modern Portfolio Theory (MPT). It involves categorizing the investment universe based on risk (standard deviation) and return, and then choosing the mix of investments that achieves the desired risk-versus-return tradeoff. Portfolio optimization can also be thought of as a risk-management strategy as every type of equity has a distinct return and risk characteristics as well as different systemic risks, which describes how they respond to the market at large. Macroaxis enables investors to optimize portfolios that have a mix of equities (such as stocks, funds, or ETFs) and cryptocurrencies (such as Bitcoin, Ethereum or Monero)
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By capturing your risk tolerance and investment horizon Macroaxis technology of instant portfolio optimization will compute exactly how much risk is acceptable for your desired return expectations
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.

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