13

This question has been re-opened again after (rightly) being closed as too broad for the purpose of clearing some misconceptions regarding one of the answers here. The main idea that is to be stressed here is this: When it comes to high frequency trading, biggest or "as many as you can get" is rarely true. Not only is it false, it is impossible in terms of ...


10

Advent Geneva is a complex event processing platform, which employs the latest advancements in artificial intelligence and big data. It employs techniques derived from blockchain technology and cryptography to speed up trading strategies. Under the hood, it uses a fast in-memory database whose kernel sits on an FPGA, to meets its demands in Ultra (in caps) ...


9

FO is shrinking across the large investment banks. The market is not developing new products that will need new pricing formulas, if anything it is reverting to more vanilla structures. Nowdays FO quants typically hack existing models around the corners to manage new market conditions (change Sabr a bit to deal with negative rates, refine the treatment of ...


6

My favorite tool is Sornette's own Finanical Crisis Observatory: http://tasmania.ethz.ch/pubfco/fco.html If you are interested, I have developed my own tool in Java and JavaCL which can be found here: https://thebubbleindex.codeplex.com/ Update: Code moved to github: https://github.com/thebubbleindex/thebubbleindex


6

Check Noncommutative Geometry and Stochastic Calculus: Applications in Mathematical Finance


5

I can share my own experience working with the Deltix product suite. As a research and development platform it's very feature rich with support for every back-testing mode there is (BBO, Trade, Midprice, Bar, Level 2 Order Book) and advanced optimization modes (walk-forward, genetic, mean-variance, portfolio optimization, etc). I have built components and ...


5

http://lobster.wiwi.hu-berlin.de/forum/viewtopic.php?f=4&t=30 R code, pictures and discussion, it's easy to modify it


5

I think the most sophisticated solutions are to be found within the R universe. One package that comes to mind is the quantmod package. You can use it to download data from Yahoo and Google finance, plot charts and filter your stocks using all kinds of technical indicators (that come with the package). It can be found on CRAN: https://cran.r-project.org/...


4

Have you considered the HDF5 data model? Edit for Louis : Why using HDF5 ? As stated in the HFDF short description page : HDF5 is a unique technology suite that makes possible the management of extremely large and complex data collections. HDF5 is a suitable solution when dealing with very large datasets and you need performance. Again, as stated ...


4

There is one more solution available now to backtest option strategies: www.oscreener.com! This tool allows to screen and backtest bull put spreads, long calls, short puts, debit spreads etc and validate these strategies in seconds.


4

There is absolutely bright future being a pricing quant, so don't make it a reason for you not doing a degree in financial engineering. Being able to buy a relative cheap (still not that cheap, eg: Numerix charges like a million...) solution for quantitative pricing doesn't mean you don't need a quant. This is like saying we don't need a bus driver because ...


4

Being the question tagged as python and given I look for small challenges for my platform, backtrader, I took the chance to see how easy would be to do this with the platform. Documented at: http://www.backtrader.com/posts/2016-08-15-stock-screening/stock-screening/ The core code in this case is an analyzer which looks for assets which are above the 10-...


4

Zipline is a trading library that does exactly this.


4

Try Quantlib https://www.quantlib.org, it comes with everything you need.


3

You can also try Zipline, it's the library used in Quantopian platform. It is opensource and written in python, you can use your own .csv data or built-in yahoo finance data feed. You can of course use any python library you want with it.


3

Have you thought about using "Python for finance"? There is multiple Python librarys to help you getting up to speed, e.g. take a look at Python Algorithmic Trading Library


3

Look into OLF's Findur http://www.olf.com/software/financial-capital.html highly customizable trading platform, will not give you everything you mentioned out of the gate but has capability to get there with some development effort


3

So, I dont even know of comprehensive SW lists; one of the best ones probably being bobsguide directory (subdivided in specific topics). Another one is at Marketwiki. Lepus also offers a through comparison of software in some of the mentioned areas, and keeps lists with features. For HFT there's HFTReview's directory.


3

Unlike backtesting stocks or futures, backtesting multi-legged option spreads does have its unique challenges. One way to backtest your options strategies is to download historical option data (Market Data Express) and use a technical analysis Excel plugin (TA-Lib). You can then create an Excel spreadsheet to automatically enter / adjust your spread ...


3

There are two open source libraries that you should take a look at. Both feature a wide list of products and models. QuantLib. Written in C++ but usable in other languages such as Python. The library is developed for several years now. A feature that might come very handy is that there are toolboxes to implement derivative pricing libraries in Excel. Take a ...


2

There's nothing fundamentally different between options and cash instruments, so you really just need a backtesting platform that has good functionality for backtesting multiple instruments simultaneously with the same reference time frame. I'm assuming that you're looking for something halfway between in terms of level of sophistication and cost required ...


2

Stocks in the market can be twisted in braids and knots according to this paper http://arxiv.org/abs/1404.6637 Is a direct way to apply topology in finance.


2

There is a new Order Book visualization tool, called BookMap: http://www.youtube.com/watch?v=1c6HegAn-CA It allows to trade and simulate trading in real-time or replay mode. The replay mode is free to use. BookMap is the only tool, that visualizes the history (evolution) of the order book. (the first version will be soon in production)


2

Here is a quick example, you grab the total returns for each holding period, avg them out and compare the days for each level of return. You can change tmp1 for whatever is your preferred filtered data set. require(PerformanceAnalytics) require(sqldf) data(edhec) tmp1=edhec[,1] period_seq = 1:nrow(tmp1) combos=expand.grid(period_seq,period_seq) ###...


2

I wrote an R function to create those plots: library(quantmod) getSymbols("^GSPC", from = "1950-01-01") ## [1] "GSPC" inv_stat <- function(symbol, name, target = 0.05) { p <- coredata(Cl(symbol)) end <- length(p) days_n <- days_p <- integer(end) # go through all days and look when target is reached the first time from there for (...


2

My 3 points for you: Earlier checks like pre-compliance checks for orders are usually performed. Three different types of orders are correctly recognized - i.e. proposed orders but not routed, submitted orders and waiting for acknowledgement. When an order is added to the submitted queue, it should go through compliance checks and then be added orders which ...


2

I would recommend using Python because it can be downloaded for Windows or Mac and is available in almost all Linux repositories as standard. Once you have Python installed you can use any of the following links to see how to get your data https://www.quantstart.com/articles/Downloading-Historical-Intraday-US-Equities-From-DTN-IQFeed-with-Python https://...


2

I recommend taking a look at cufflinks and py-quantmod: https://github.com/santosjorge/cufflinks https://github.com/jackwluo/py-quantmod


2

From http://qr.ae/TbcrXL: Phil Newton's answer: Most modern charting packages can do this. Meta trader. Ninja trader. Multi Charts. Tradestation. Naoya Yamaguchi's answer: And Ninja trader is free. You can also program more indicators into it, using C#. This means a great collection of .NET assemblies, including Deep Learning ...


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