finance

Very new to QuantLib so guessing this is a rookie mistake. Enjoyed getting to know this powerful library so thank you to the authors and contributors! I'm able to generate amounts for cashflows for a FloatingRateBond without a pricer if there isn't a floor argument, so I don't understand why including a floor argument would necessitate a pricer. I would think the addition of the floor would just provide a min for each of the fixing values. Wanted to see if anyone has gotten the FloatingRateBond cashflows to work while using a floor. And, if so, if anyone can spot where I'm going astray. Thanks

I am looking for a Python plotting library that allows me to plot candlesticks (preferably the OHLC bars variant) with X zoom via mousewheel scrolling (or similar) and an automatically scaled Y axis when zooming. As an example of what I am looking for, tradingview.com does this perfectly. See https://uk.tradingview.com/chart/?symbol=NASDAQ:NDX . OHLC bars can be seen by clicking the candlestick icon near the top left and selecting 'Bars'. Plotly is almost able to do this. The Ohlc class in plotly.graph_objs give the OHLC bars, and the default rangeslider is a nice feature for X zoom

I'm using SQL Server 2008 R2 and need to create new tables grouped in Time intervals. The data is data from a stock market index. I have the data in 1 minute intervals, now i need them in 5,10,15,30,45,60...minute intervals. My primary key is the time stamp. My question is: how to query the 1 minute data table to return data that is grouped by a specific time interval for example 5 minute intervals. The query must return the Highest, Lowest, Last and First values in that particular group and most importantly also the last entry of the time-stamp in the group. I'm very new to the SQL language

I would like to generate a 1 min spaced time sequence to paste then to a xts object. Basically, I've got a tick-by-tick dateTime object like that : [1] "2010-02-02 08:00:03 CET" "2010-02-02 08:00:04 CET" "2010-02-02 08:00:04 CET" "2010-02-02 08:00:04 CET" "2010-02-02 08:00:04 CET" [6] "2010-02-02 08:00:04 CET" "2010-02-02 08:00:04 CET" "2010-02-02 08:00:05 CET" "2010-02-02 08:00:05 CET" "2010-02-02 08:00:05 CET" I'm aggregating my xts series (by previous tick) to get a 1 min (equally)-spaced time series using an RTAQ package function : price_1m<-aggregatets(price,FUN="previoustick",k=1,on=

Just wondering what kind of free finance API's are out there. I'm looking for something where I can specify the index and get a list of all the companies, by ticker symbol, that are included in that index. Currently I'm only interested in NYSE-listed company stocks. I'd really appreciate any suggestions on API's or methods. Other than doing the hard work, like downloading the symbols for the various exchanges from NASDAQ, then is a way to get Google Finance to display all of the stocks and/or companies listed on an exchange. Here is a sample url for obtaining the list of companies on NASDAQ:

Is it possible to optimize (make it much faster) this piece of code: out <- do.call(rbind, lapply(split(Cl(cumulativeBars), "days"), function(x) { previousFullBars <- barsEndptCl[as.Date(index(barsEndptCl), tz=indexTZ(barsEndptCl)) < as.Date(last(index(x)), tz=indexTZ(x)), ] if (NROW(previousFullBars) >= 4) { last(SMA(last(rbind(previousFullBars, x), n=6), n=5)) } else { xts(NA, order.by=index(x)) } })) Below you can find my original question with all the code example that runs but a bit to slow for my needs. ORIGINAL QUESTION: After I was able to transform xts to lower frequency in cumulative