GDP BreakdownProvides an easy way for viewing the sub sections that make up a country's total GDP. Not all countries provide data for each subsector (Agriculture, Construction, Manufacturing, Mining, Public Administration, Services, Utilities). Only countries that provide complete data are able to be selected in the settings. If I've missed any please let me know in the comment section so they can be added. This is much easier than having to individually selecting each ticker for each country when looking to compare how diversified an economy is.

# Diversification

Diversified Investment EMA Cross Strategy SimulatorThis simulating indicator proves that even if you use a simple strategy, you can reduce your risk by diversifying your investments.
The strategy itself is simple.(only long)
Buy when 50 days EMA crosses over 200 days EMA.
Sell when 50 days EMA crosses under 200 days EMA.
Or, stop loss when the asset falls by 2% (eg).
Using this simple strategy on an asset is just a test of your luck.
However, this capital change graph shows that risk can be reduced by diversifying investment into eight assets rather than one asset.
Options
Total Assets Capital Change represents the sum of capital changes for 8 assets. The gray line is the initial capital.
Each Asset Capital Change represents all eight asset capital changes. In this case, the gray line is displayed as the initial capital divided by 8.
The rest of the options show a graph of capital change for each asset, showing when buys and sells occurred.
And set the start date, initial capital, stop loss %, and commission.
And select the 8 assets you want to invest in and you are ready to go. To effectively reduce risk, uncoupled assets would be better if possible.
The table in the lower right shows the selected asset and color.
Please enjoy the simulation.

Coefficient of Variation - EMA and SMA StDevYet another way to try and measure volatility. An alternative to using ATR is Standard Deviation, it can be used to measure volatility or what is also known as risk. SD measures how dispersed or far away the data is from the mean. It's commonly seen in risk management formulas or portfolio diversification formulas. The problem however is that the numbers that ATR and SD give off from one equity might not be relative to others or its own past. For example, SPY can give a large number despite not being as volatile as other equities while others being compared to can have smaller volatility numbers and still be more volatile looking.
A solution I thought of is to use percentages that are relatable to different equities. I found out another name for this idea comes from statistics and is known as coefficient of variation, also known as relative standard deviation. This helps see the volatility as a percentage and not just a number that only relates to what is being seen at the moment. I put in a border line on the zero level to see where zero is at but also to edit in case there is such a thing as a percentage number that can be too high or too low for volatility to be looked at if needed. The average and standard deviation formulas can use either simple moving average or exponential moving average.