Time-series R function design

Dibatalkan

We need R functions to help analyse historical financial time-series data. We're interested broadly in determining relationships between returns, and causal structures for forecasting. Data will be in CSV in a standardized format and will cover thousands of distinct time series in either x-minute resolution format or daily. This is NOT a school assignment! Functions will be tested on multiple data sets to ensure they work as designed.

Four functions are required:

1) Correlation coefficients for items in user-specified CSV folder, given user--defined subset date-range to define data points. Output as CSV symmetrical matrix. (Only daily data will be used here)

Example of function:

CorrFunc(FolderPath,FirstDate,LastDate,OutputLocation)

Example output:

A B

A 1 0.8

B 0.8 1

2) Johansen/E-G/ADF cointegration test for items in user-specified CSV folder, given user-defined subset date-rangeSome meaningful measure of "strength" such as significance. Ordering of strength per base item for cointegrated items. 2 CSV matrix outputs: First one dummy yes/no for unit root and a second matrix for other relevant information.

Example of function:

CointFunc(FolderPath,FirstDate,LastDate,Min-p-Val,OutputLocation)

Example output:

A B

A 1 1

B 1 1

A B

A 3.2 [url removed, login to view] 2.5 [url removed, login to view]

B 2.5 [url removed, login to view] 3.2 [url removed, login to view]

3) Linear regression for items in two user specified CSV folders (dependent and independent, for example folder 1 has 50 files, folder 2 has 2000 files, each has to be tested against the other) given user-defined subset time for returns and date-range. The time-series data has gaps for a variety of reasons which we need to account for by selecting only useful data, e.g. where we can measure returns from time-A to time-B on both dependent and independent. Time A can be on a preceding day to time B (e.g. 3pm preceding day to 10am). A smart way of doing this has to be implemented so we are comparing apples to apples and also not discarding data unnecessarily. We want to be able to define return minimum/maximum returns on both dependent and independent variables separately as an option.

Example of function:

LinRegFunc(FolderPathDep,FolderPathIndep,FirstDate,LastDate,Time1,Time2,DepMinR,DepMaxR,IndepMinR,IndepMaxR,OutputLocation)

Example output:

Independent Dependent Slope SDE window n

Z A 1.2 [url removed, login to view] [url removed, login to view]% 620

Z B 0.1 [url removed, login to view] 3.8% 580

4) Data test function that employs an output from the third function and utilizes dependent and independent items in their respective folders to find out a) if regression did/did not took place when we expected it, b) if that regression happened with a positive or negative independent variable, c) whether we were expecting regression to go "up" or "down", d) given the return (from the historical data) of the dependent variable at Time C how much regression took place as a % of what we expected and e) what minimum and maximum values for the return we observed during the period Time B-Time C. We define a minimum predictability as to not have to test every combination. Output as CSV.

Example of function:

LinRegTest(LinRegFile,FolderPathDep,FolderPathIndep,FirstDate,LastDate,Time3,MinSDE)

Example output:

Independent Dependent ExpectedReturn ObeservedReturn Obs/Exp IndepPosNeg UpOrDown, MinRetValArray, MaxRetValArray, DateOfObservation

There will be four milestones, one for items 1 and 2 together, one for item 3, one for item 4, and one for final project completion after user feedback and tinkering.

Keahlian Bahasa Pemrograman R

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ID Proyek: #11735485

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smartresearch1

I am an expert in data mining and predictive modeling. I have a PhD in Physics and I have extensive experience in machine learning applications, statistics and software development (web, mobile, desktop, SaaS). I work Lagi

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extinct

Hi, I am a professional statistician by training and boast longstanding experience in data analysis and presentation. I will be happy to assist in your project. I normally produce work high quality as evidenced in the Lagi

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11 freelancer menawar pada rata-rata €443 untuk pekerjaan ini

Joe156

Hi, I am familiar with time series analysis and R programming. I have done several projects related to correlation and regression analysis. I will be glad to work with you on this project. Please feel free to Lagi

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pywebr

I'm using Python for data processing and web development for a year, and was using R for two preceding years, with years of business/systems analysis in R&D in mostly manufacturing and insurance domains, in local, mult Lagi

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ashitjha7

20+ years industry work experience in the area of IT, Finance & Banking. Also, I have 4+ years of experience in Economics, Business Analytics and Advanced statistics projects using software such as Python, R, SPSS, Min Lagi

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vasilismtsakalos

Hello I can do that within a week if you don't mind since I have 3 really busy days. I can totally do that in R , but I would have better (more accurate results) if I would use python and a deep recurrent neural netw Lagi

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mohamedrdait

Hello sir I can achieve this project perfectly using R contact me for more details about this particular project best regards

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Programmer59

Hello Sir..! I read your description I can complete your project on time and within your budget I am fully confident about your project. I will receive your best wishes. I am waiting your response thanks you so much Lagi

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albertbarry99

Hi, I want to help with the placed request. Regards, Albert Cheruiyot

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AleenaIlyas

Hello I have read what you exactly need. However, I would like to ask you a few questions. I do work in a smart way and do not rest until I get the job done. Please feel free to ping me anytime so we can have a detaile Lagi

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