python/r交易
For those of you who are traders, how frequently do you use python/r in your job? I know that this question varies for someone who works at a market maker vs. someone who works at a trade house, but for those of you who do program can you give me a sense of how you use it on a day to day basis?
注释 (22)
撞
很多!虽然我不使用R太多。我会说75%Python 25%VBA(我讨厌VBA,但是我的PM(以及许多其他人在行业中持续了几十年)的工具都是2ManBetX登陆 。。。)。For what it's worth I'm on theHFside, but I did work at a market maker for a couple of years ~4 years ago and mostly used Python there as well.
话虽如此,很多人确实使用R,我只是喜欢Python。
不是要劫持线程,但是您会说什么编码语言是最好的回报?也就是说,如果您必须给出一个学习的比例贸易。就像我确定有轻松的知识是该死的无用的,这使您的生活变得更加轻松,但非常困难。您是否发现任何快乐的媒介?
It depends on the fund, role, and PM you work for, but in general for a trading role I would say VBA and Python is a good toolbox. C++ isn't really necessary unless you're working on pretty low latency strategies, and some people use R - you could argue R is easier to learn than Python, but I'm not really sure if that's true. Anyway, the industry is generally moving away from R towards Python.
对于一些角色你会只使用VBA,对于一些你孩子l only use Python, and for some you won't use either. Honestly I never really 'learned' VBA - I learned Python (and a couple of other basic languages, but Python is by far the most useful), and initially when I had to work on something in VBA, I struggled through but made it work just using Google and my experience with Python. At this point I feel pretty comfortable in VBA. I guess what I'm trying to say is that VBA is pretty easy to learn, but if you learn Python then VBA won't be that tough to figure out if/when you need to, but the other way around isn't necessarily true.
Python是最简单的流行语言,它使您可以使用行业标准统计,数据科学和深度/机器学习包。一旦您将其挑选到合理的熟练程度,我将进行比较,以比较熊猫/matplotlib vs Excel中的出现。
嘿,
我可能会问您,从道具店转移到对冲基金角色是否容易?我认为您是道具商店的交易员。
可能,但并不容易。我回到两者之间
I use it a couple of times per week for some personal projects.
VBA中有很多工具,但是我不知道VBA。
会尽其所能地说python可以做和拥有的大部分内容可以做面向对象的编程。我想说的是,SQL作为第二语言更有用,并且很容易获得基础知识(尽管我每天都使用Python)。
使用大量R,Python和10%的VBA(主要是旧的东西)。R非常适合统计模型,但是Python在过去几年中有了很大的改善,并且更容易与任何技术堆栈集成。如果您从零开始,如今我会选择python。
最重要的是不要迷失在愚蠢的X中比Y东西更好,是语言不可知论,并为每个任务选择最佳工具。如果您团队中的每个人都使用R,请使用R。如果您的经理想要一些花哨的Excel型号使用VBA。如果您需要5倍,并且您的代码质量很糟糕,则用特定语言编写代码是没有意义的。
过于简单的故障:
Python:多用途/多功能性。我可能有兴趣对我想到的广泛交易策略进行非常简单的模拟。我可能还感兴趣的是,使用Beautifuresoup,Selenium等的软件包直接从某些网站上刮擦数据,并使用Pandas进行一些初步数据分析。标准数据科学库。也许我想为某些阈值通过或我想进行的现场新闻事件构建一个简单的警报机器人。
R:如果您想对统计分析变得沉重,则非常有用。您的面包和黄油用于运行ML/AI的数据集分析。当然,您可以使用Python进行大量的定量深度,但是如果您想全力以赴,R将具有整体的“边缘”。不用说,它提供了出色的数据可视化选项,尽管我也不会打折Python
VBA:通常用于较小的密集型自动化过程。许多公司仍然依靠Excel,因此VBA是一座很棒的桥梁。使用电子表格,对于运营方面(例如EOD P&L回顾以及位置对帐)非常有用。当您开始担任交易角色时,通常需要监督和掌握桌面的操作方面。您当然可以使用Python,但在许多情况下也可能过度杀伤。
嘿,精算,
I don't really use python on a regular basis in my daily work, but it's something I am interested in learning. Specifically the data-analysis and website sentiment scraping. As someone looking to self teach do you have any recommendations as to the best place to start?
我最近在整个周末都花了整个周末,下载了Python,Sublime和一些图书馆,并通过Sentdex的“ Python介绍”课程,在那里他构建了Tic Tac Toe游戏。这很有趣,但我觉得我并没有真正“学习”太多,只是在挑选了一些事情。接下来,我去尝试了他的“金融”教程,但看来视频很老,他依靠不再有用的API,所以我放弃了。
I then learned about anaconda and that a lot of data-scientists prefer to use this vs traditional python and adding all the libraries they need as it comes "pre-loaded" out of the box with most everything you would want to use. Jupyter notebook also seems like the preferred way to teach/learn or am I off on this?
您是否知道通过Anaconda框架学习财务概念/manbetx3.0手机客户端数据分析的任何良好资源,最好是免费的,尽可能免费?
Thanks
Et fugiat est non et voluptatibus voluptatibus explicabo。非Quo锻炼AB。Nisi colduptas Ausem voluptas Quo。Quasi turema dolores官员。Veritatis cumque eos reiciendis atque doloremque est stit。
See All Comments - 100% Free
WSO depends on everyone being able to pitch in when they know something. Unlock with your email and get bonus:6财务建模课程免费($ 199的价值)
要么想要开锁通过签署您的社交帐户?
预览和下载评论作为图像
您可以使用浏览器的上下文菜单下载此屏幕截图或复制到剪贴板