## Data Aggregation

Whenever a selection is made in the ChartAgg App, we run an aggregation on the various data points associated with the selected period like price, close price, volume, RSI etc. If you are new to concept of data aggregation, please read a basic definition and example below. Google it if it isn't clear.

Data aggregation is the process where raw data is gathered and expressed in a summary form for statistical analysis.

For example, raw data can be aggregated over a given time period to provide statistics such as average, minimum, maximum, sum, and count. After the data is aggregated and written to a view or report, you can analyze the aggregated data to gain insights about particular resources or resource groups.

In the context of technical analysis, data aggregation can be over a period of time, which is what happens when a time period is selected in the ChartAgg app. A very simple example of aggregated data analysis can be maximum close price in the selected time period for a stock. So in a selection of 5 days for stock X, if the close price in those 5 days is [4,7,6,9,2], then the maximum close price over this time period (aggregation) is 9. # ​

To get a basic understanding of percentile, please watch this Khan Academy video on percentiles.

In the context of ChartAgg app, checkout the meaning of percentile distribution in the example below.

# What does (mean, 25%, 50%, 75%, min, max) indicate ?

You will notice (mean, 25%, 50%, 75%, min, max) being used in a lot of metrics generated by ChartAgg app. These indicate

mean: the mean of a given metric in the selected time period

25%: the 25th percentile of the a given metric in the selected time period

50%: the 50th percentile of the a given metric in the selected time period

75%: the 75th percentile of the a given metric in the selected time period

min: the minimum value of the a given metric in the selected time period

max: the maximum value of the a given metric in the selected time period

Considering the image above, notice the (mean, 25%, 50%, 75%, min, max) for volatility. In simple language this means, for all the days in the period, the mean volatility is x; 25% of days have volatility less than y (indicated by 25% percentile); 50% of days have volatility less than y (indicated by 50% percentile); 75% of days have volatility less than y (indicated by 75% percentile); the day with maximum volatility has a volatility of y; the day with minimum volatility has a volatility of y. Another way of looking at percentile is - considering the 75% value is 25% of days have volatility greater than y

# Total Periods

This indicates the total number of trading days in the selected period.

# Volatility

This metric is an aggregation of the 5 day rolling volatility of all trading days in the selected period. Volatility is calculated using Normalized Average True Range

Considering the metrics in image 1, the interpretation of this metric would be -  for all the days in the period, the mean volatility is 2.16; 25% of days have volatility less than 1.39; 50% of days have volatility less than 1.88; 75% of days have volatility less than 2.45; the day with maximum volatility has a volatility of 6.09; the day with minimum volatility has a volatility of 1.02.

# RSI (period 14)

This metric is an aggregation of the 14 day rolling Relative Strength Index (RSI) of all trading days in the selected period.

Considering the metrics in image 1, the interpretation of this metric would be -  for all the days in the period, the mean RSI (14) is 64.45; 25% of days have RSI(14) less than 58.44; 50% of days have RSI(14) less than 63.92; 75% of days have RSI(14) less than 72.41; the day with maximum RSI(14) has a RSI of 89.38; the day with minimum RSI(14) has a RSI(14)  of 34.48.

# Consecutive Close Higher

This metric is an aggregation of the length of all consecutive trading days, where the next day's close is higher than the previous day's close.

Considering the metrics in image 1, the interpretation of this metric would be - the mean length of consecutive close higher trading days is 1.65 days; 25% of them have length less than or equal to 0; 50% of them have length less than or equal to 1; 75% of them have length less than or equal to 3 trading days; maximum length of trading days with consecutive close higher days is 9, and minimum is 0 trading days (as there many days where the next day's closing price is lower than the previous)

# Red Candles Percent

This metric reflects the number of red candles (close price less than open price) as a percent of total periods.

Considering the metrics in image 1, there are 45.83 percent of red days in the selected period

# Green Candles Percent

This metric reflects the number of green candles (close price greater than open price) as a percent of total periods.

Considering the metrics in image 1, there are 54.17 percent of green days in the selected period # Drawdown

This metric is an aggregation of percentage drawdowns within the selected time period. A drawdown is the difference of  lowest price from the highest price yet as a percentage of that highest price.

Considering the metrics in image 2, the interpretation of this metric would be - the mean drawdown percentage for selected period is 3.04%; 25% of drawdowns are less than equal to 1.04%; 50% of drawdowns are less than or equal to 1.96%; 75% of drawdowns are less than or equal to 3.38%; maximum drawdown in the selected period is 15.36%, and minimum is 0.06%

# Time to new high

This metric is an aggregation of the days it takes to make a new high, in the selected period.

Considering the metrics in image 2, the interpretation of this metric would be - the mean days to make a new high is 8 days; the stock makes a new high on less than or equal to 25% of the days; the stock takes 3 days to make a new high on less than or equal to 50% of the daysthe stock takes 12 days to make a new high on less than or equal to 75% of the days; the maximum time for the stock to make a new high is 53 days; and the minimum time is 0 days (meaning stock makes a new high the next day)

# Rate of change percent

This metric is an aggregation of how fast the close price changes during the selected period. See formula

The higher the value, the faster the price is moving. Negative value indicates price moving lower. Higher negative value indicates faster price movement in the lower direction.

# Volume

This metric is an aggregation of the volume in the selected period.

# On balance volume

This metric is an aggregation of the on balance volume in the selected period.