quantmod
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joshuaulrich
Quantitative Financial Modelling Framework
### Description When specifying the from and to periods in getSymbols with source yahoo the expected results are often incorrect. I tested this on several markets (US, Europe, Argentina and...
### Description Chartseries adds (by default) a second volume chart, equivalent to "addVo ()" The volume chart scale is represented in a friendly way (x thousand, x one hundred thousand,...
### Description While chart_Series(symbol, name="title") works, but it is currently difficult to set the fontsize/fontcolor of that title. ### Expected behavior chart_theme() should be modified to allow for title customization....
### Description The x-axis has data labels on both the top and the bottom which looks a bit cluttered. ### Expected behavior It should be easy to customize the x-axis,...
`getSymbols.tiingo` currently only supports daily-monthly data sets. However tiingo does have an API sitting on top of IEX data that support intra-day granularity: https://api.tiingo.com/docs/iex/realtime#historicalPriceData It should be fairly straight forward...
### Description Hello, I am trying to use the quantmod function predictModel. However, it seems not to be found. ```r library(quantmod) > predictModel Error: object 'predictModel' not found # not...
### Description modelReturn does not include in its math the first day of returns. In modelReturn, the calculation of 'daily returns' is incorrect. ### Expected behavior modelReturn must include in...
### Description The function **getQuote** does not work when I don't request some specific metrics in the **what** argument. After taking a deeper look at the code and the JSON,...
### Description tradeModel calls quantmod:::modelReturn. Inside quantmod:::modelReturn, days.traded is calcualted by the following. ```r Browse[2]> n debug: days.traded tail(trade.signal) Next.OpCl.IBM signal.zoo 2018-10-12 -0.001913187 1 2018-10-15 0.005342641 1 2018-10-16 0.015322200 -1...
### Description modelReturn has the paramteter ret.type. tradeModel calls quantmod:::modelReturn. ```r args(tradeModel) # function (x, signal.threshold = c(0, 0), leverage = 1, return.model = TRUE, # plot.model = FALSE, trade.dates...