RATIOPLOTTER.EU

Our data is provided from a variety of sources: The Federal Reserve (FED-* tickers), The World Bank (WB-* tickers), The International Monetary Fund (IMF-* tickers), Tiingo (T-* tickers covering: stocks, ETFs, etc), Ourselves (MATH-* tickers). The ticker data sources vary according to ticker prefix as you can see. Our ticker selector allows browsing each ticker and their description and placing them on a basket for use.

For ratio plotting, the SEA(Ticker) function can only be used in the denominator argument and only for plotting TickerA over SEA(TickerA) like this: T-CRUD/SEA(T-CRUD). The SEA() ticker function works by calculating the median yearly seasonality as a new dataset (see the seasonality page for details and examples of this calculation). This one year seasonality dataset is then unfolded exactly the same for many years and directly inputted as a synthetic ticker into this plotting page arguments. Example: Ratio plot of Crude Oil by its seasonality: T-CRUD/SEA(T-CRUD). To write custom SEA() function synthetic tickers simply input your ticker of choice between the parentheses such as SEA(T-CRUD).

The RAT() ticker function works by calculating the ratio between two tickers as a new dataset. This dataset is then directly inputted as an synthetic ticker into the plotting page arguments. To write custom RAT() tickers simply input your two tickers of choice between the parentheses, separating them with a comma. Such as RAT(T-AAPL, T-MSFT). This can only be once, synthetic tickers like RAT(RAT(T-AAPL, T-MSFT), SEA(T-qtec)) are invalid for the time being. Example, how is Google outpacing Microsoft in terms of CAGR curve: RAT(T-GOOGL,T-MSFT)/MATH-CAGR_PCT-2

The LAG() ticker function is used to create a lagged version of an asset. This lags a dataset with an amount of days equal to the lag value in the ticker. To write custom LAG() tickers simply input your ticker of choice and lag value between the parenthesis, seperated by a comma. Such as LAG(T-AAPL, 10). Lag values can only be inputted into the denominator as positive whole numbers between 1 and 7000 days. Using the ratio plotter with LAG(), a ticker can be analyzed in its auto correlation, or correlation to a nother ticker with a gap of X days (e.g.ratio plot of TICKERA by LAG(TICKERB, 30)).

The MATH- tickers are custom mathematical tickers made by us (e.g. MATH-CAGR_PCT-2 for 2% exponential growth, MATH-CONST_VEC-1 for a constant value of 1 each day). To find the list of valid MATH tickers go to the Ticker Selector Page and search through the MATH category list. Important to mention is that when using the MATH tickers the last observed date for this MATH ticker will be far in te future.

The CURVE_FROM_VECTOR function allows transforming your own data vectors into plottable data. It is perhaps one of the most powerfull functions. As the name says, it creates a vector from user entered data points. This function is to be used when you cannot find the data you need in the ticker selector, or if your data is proprietary such as your own private company that you will plot against perhaps competitor's sales or a competitor's stock price. Learn using CURVE_FROM_VECTOR() here: price to x demo with CURVE_FROM_VECTOR() or on the details below. The price to x has an expression builder to require less typing from the user. Example usage: CURVE_FROM_VECTOR([198.27, 211.92, 245.12, 281.72, 318.27], '2026-06-30', 'last', '1y', 'linear', 'forward_fill') The first argument is the time ordered list of data points, separated by commas. The second argument ('2026-06-30') is the one data anchor we need to plot these values over time. The third argument ('last') tells the system to apply the anchor date to the last value, another value for this parameter is 'first'. The '1y' tells the values fall on the exact same date on each year (or closest if leap year). The '1y' could also be '1q' or '1m' for quarter or month. The same considerations made for year apply. The 'linear' parameter tells the system how to interpolate the values for days in between the value data points given, another possible value here is 'forward_fill'. The 'forward_fill' last parameter is about the extrapolation, its possible values are: 'none', 'forward_fill', 'linear'.

Let's take T-GOOGL as an example. When the projection variable is left blank, the ratio plotter will use the default projection variable which is -AdjClose (close price adjusted for both dividends and splits). This means that when you input T-GOOGL into the ratio plotter it will actually plot the Tiingo split and dividend adjusted close price of GOOGL (T-GOOGL-AdjClose by T-MSFT-AdjClose). If you want to plot the split (but not dividend) adjusted close price of GOOGL you can input T-GOOGL-SplitAdjClose. All projection columns are provided by Tiingo, with exception of the -SplitAdjClose column which is calculated by our system.

You can do this with the function: SIMUL_TICKER_DIV_REINVEST(T-MSFT,0.25,1,'2022-08-01')
This is a function available only for users with the advanced subscription. The first argument is the Ticker simulated, the second is your portfolio CAGR rate (in this case 0.25 = 25% yoy). We apply the daily equivalent rate though. The third argument is the initial investment in the currency of the stock ticker. The last argument is the start date. For a full example see our article on dividend reinvestment simulation.