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在斐波纳契水平的策略

移動平均線(Moving Average)

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How to use Simple Moving average for N step forecast on unobserved data

I have a confusion about how to forecast future steps using MA. All the articles out there validate the model by only considering the historical data that were OBSERVED. However, once we validate an MA model has a good performance on our train data, we need to set up a pipeline for future forecats.

The problem is that for n-step ahead future forecast, all the data is observed 移動平均線(Moving Average) only for the first forecast. What happens to the other n-1 steps? Here is an example.

Lets say we have a dataset from Jan 2021 to June 2022 and based on our experiments, we noticed a moving average using the last 3 values leads to the best error for a 3-step ahead forecast horizon.

Now we want to forecast for July, August and September. For July, we already observed the prior 3 months values so we can get a mean of that and its the forecast. However, actual July data is missing for August forecast. What happens 移動平均線(Moving Average) here? Should we consider the forecasted value for July and the actuals for June and May to find the value for August?

I am sorry if my question is trivial but I am trying to code it myself in python so I want to make sure I am doing it the right way.

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Cabot (CBT) Recently Broke Out Above the 20-Day Moving Average

From 移動平均線(Moving Average) a technical perspective, Cabot (CBT) is looking like an interesting pick, as it just reached a key level of support. CBT recently overtook the 20-day moving average, and this suggests a short-term bullish trend.

The 20-day simple moving average is a popular investing tool. Traders like this SMA because it offers a look back at a stock's price over a shorter period and helps smooth out price fluctuations. The 20-day can also show more trend reversal signals than longer-term moving averages.

Similar to 移動平均線(Moving Average) other SMAs, if a stock's price moves above the 20-day, the trend is considered positive, while price falling below the moving average can signal a downward trend.

CBT has rallied 6.3% over the past four weeks, and the company is a Zacks Rank #3 (Hold) at the moment. This combination suggests CBT could be on the verge of another move higher.

The bullish case solidifies 移動平均線(Moving Average) once investors consider CBT's positive earnings estimate revisions. No estimate has gone lower in the past two months for the current fiscal year, compared to 1 higher, while the consensus estimate has increased too.

Investors may want to watch CBT for more gains in the near future given the company's key technical level and positive earnings estimate revisions.

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