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I have multiple variations of an automated strategy for trading certain investment vehicles. For each of these variations I have cross-validated backtests on historic data. I need to pick the best-performing test. There is significant variation between the tests in terms of trades per day, net position size, etc. This makes it difficult to compare one to another.
The nature of the test relies on the predictions of a multidimensional nearest-neighbor search.
Having been recently acquainted with R, I am looking for packages/functions/tests to help me analyze various elements of my strategies' performance. Particularly, I am interested in two things:
1. Packages/functions/metrics that gauge the efficacy of my predictor.
2. Packages/functions/metrics that gauge the relative "profitability" of one variation to another.
If you know something that I should take a look at, please do not hesitate to post it!
I would definitely take a look at these two R Task views:
Taskview Econometrics
Taskview Finance
They provide a broad overview of the kind of packages that are used in these fields. Googling for:
using R for financial analysis
also got me a lot of hits that are relevant for your situation. Good luck!
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this is more of an hypothetical question, but might have great consequences. Lot of us in Modelica community are dealing with large scale systems with expensive simulation times. This is usually not an obstacle for bugfixing and development, but speeding up the simulation might allow for better and faster optimizations.
Recently I came across Modia possibilities, claiming to have superb numerical solvers, achieving better simulation times than Dymola, a state-of-the-art Modelica compiler. The syntax seemed to cover all important bits. Recreating large scale component models in Modia is unfeasible, but what about automatically translating the flattenized Modelica to Modia? Is that realistic? Would that provide a speed up? Has anyone tried before? I have searched for some
This might also hopefully improve integration of Modelica models and postprocesssing / identificaiton tooling within one language, instead of using FMI or invoking a separate executable.
Thanks for any suggestions.
For those interested, we might as well start developing this.
We in the Modia team agrees that the modeling know how in Modelica libraries must be reused. So we are working on a translator (brief details given in https://ep.liu.se/ecp/157/060/ecp19157060.pdf) from Modelica to Modia. The plan is to initially provide translated versions of Modelica.Blocks, Modelica.Electrical.Analog and Modelica.Mechanics together with Modia.
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I just completed data science topic i want to fo a mini project in data science can anyone suggest me a project . I searched a lot in google but i not found any projects can anyonr suggest a project
The beauty of data science is that the project can be anything you're curious about. To figure out what kind of project you want to tackle, what kind of questions do you want to know the answers to?
At the top of my head, you could explore:
the various COVID related data try to find any insights or simply
the price differences of peaches around different areas of Atlanta,
GA
is there a particular skill you want to improve such as time series analysis, classification, or regression?
Find a question you want to answer or a project that will improve your skill in a certain area.
Try this project :
https://www.udemy.com/course/data-science-hands-on-1-hour-project-on-deep-learning/
The Hands on project is currently free on Udemy. It uses Image localization techniques to build, train and test deep learning model for autonomous vehicles. Try changing the data set and try something more innovative liks skin cancer detection or text detection. Try it once.
Try creating a project on no of accidents happened in your country or state, due to different conditions like natural calamities or human mistakes or due to animals and predict the no of cases for the next upcoming year.
Try creating a time series analysis project on covid - 19.
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My team estimate tasks with hours, which is related to the TFS SCRUM Template nomenclature, however I've heard recently that tasks should be estimated in some abstration unit and using of hours is evil, what is the recommended way?
You can estimate in hours provided your team velocity is also based on hours since that's how you decide how many backlog items are likely to be delivered in a sprint.
But it's not necessary to use hours and it can sometimes give a false sense of exactness.
If you use an abstract unit for both estimating and velocity, you (or, more correctly, stakeholders and others who don't understand Agile) won't be confused into thinking that hours is an exact measure.
The confusion will stem from the fact that velocity is work-units-per-sprint and "hours-per-sprint" will be unchanging if your sprints are always a fixed size (say, four weeks for example, which will always be expected to be four weeks by forty hours by some number of workers).
However, your velocity is actually expected to change over time as the team becomes more adept, or experienced people get replaced with those with less experience, or half the team takes a month off on holidays.
That's why the whole concept of story points exists. They provide such an abstract measure so as to avoid this confusion. You simply estimate your backlog items in story points and keep a record of how many points the team delivers each sprint (the velocity).
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I know R, I know SQL, I use Windows, I have a budget of $0, I have a terabyte of data, I have twelve processors, I have 96GB of RAM, I am motivated to learn new software if the speed gains will pay off in the long term.
I need to run descriptive statistics and regressions.
I have too many options. Where should I devote all of my energy? Thanks.
Well, that is a big topic.
We did write a survey paper of the state of the art of parallel processing with R which you could start with. While it is now three years old, large parts of the discussion still hold.
Otherwise, I would suggest starting small- to medium-size with something that actually matters to you and try to get that going faster. Over at the r-sig-HPC list (gmane link) list many folks are happy to help with specifics.
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The idea that one gives some of his credits to get an answer for a question seems simple enough but when applied to a whole network of millions of users each with varying reputations it seems like some rigorous checks and balances have to be applied. What is the math framework on which this stuff is based?
There's no math behind the bounty system. It's just rules that are described in the FAQ - https://stackoverflow.com/faq#bounty
The mathematical basis of this system would be simple addition and subtraction. Why the range was chosen is probably more because of economics rather than math. Supply and demand ... The demand is high and the supply has been found to be low, therefore the "price" will be relatively high. 50 to 500 reputation points is the reward set which may be construed as "relatively high" to enough consumers(answerers) to make it worth their time and effort to "purchase" the reputation points with a good answer. The bounty could also be construed as a marketing ploy to help market the product, thereby achieving the sale; which again is the sought after good answer. This bounty system is therefore a great example of market economics; and in the past, it was often noted that one's "reputations" is worth more than money.