do you mean by using QuickFIX ? (I can see QuickFIX in your tags) if that is the case, I don’t know. Generally it’s not difficult to write a simple parser for a FIX message. I found that the web tools on valid fix do the job.
I use tia (https://github.com/bpsmith/tia/blob/master/examples/datamgr.ipynb) It already downloads data as a panda dataframe from bloomberg. You can download history for multiple tickers in one single call and even download some bloombergs reference data (Central Bank date meetings, holidays for a certain country, etc) And you just install it with pip. This link is full of examples … Read more
This question is pretty broad; as it is, there is no mention of which instruments you’re interested in. For instance: Stocks Bonds Commodities Forex Derivatives (like Futures or Options) For the moment, I will assume you’re interested in stocks… if so, take a look at Ninja Trader, which offers these features for free. You can … Read more
I usually use a combination of Moving Average and Exponential Moving Average. It proved (empirically) to be well fitted for the task (enough for my needs, at least). The results are tuned with only two parameters. Here is a sample: Edit In case it is useful for somebody, here is my Mathematica code: f[sym_] := … Read more
Alpha Vantage have real-time intraday as well as historical daily time series in JSON format. Accessing the data requires an API key but it is free. Caveat: I have not yet used Alpha Vantage myself. The focus of my work requires long daily data series and for that Quandl (or, while it lasted, Yahoo) is … Read more
Firstly, 1 ms is an eternity in HFT. If you think it is not then it would be good to do a bit more reading about the domain. (It is like being 100 miles away from the exchange.) Throughput and latency are deeply intertwined as the formulae in any elementary queuing theory textbook will tell … Read more
It is important to note that there are various ways of defining the RSI. It is commonly defined in at least two ways: using a simple moving average (SMA) as above, or using an exponential moving average (EMA). Here’s a code snippet that calculates various definitions of RSI and plots them for comparison. I’m discarding … Read more
When you’re going to work with such time series in Python, pandas is indispensable. And here’s the good news: it comes with a historical data downloader for Yahoo: pandas.io.data.DataReader. from pandas.io.data import DataReader from datetime import datetime ibm = DataReader(‘IBM’, ‘yahoo’, datetime(2000, 1, 1), datetime(2012, 1, 1)) print(ibm[‘Adj Close’]) Here’s an example from the pandas … Read more
Floating point arithmetic will almost always be significantly faster because it is supported directly by the hardware. So far almost no widely used hardware supports decimal arithmetic (although this is changing, see comments). Financial applications should always use decimal numbers, the number of horror stories stemming from using floating point in financial applications is endless, … Read more