Develop program to identify strongest correlation between historic stock prices

Hello! I am a professional programmer with several years of Python programming experience. I have written trading software before, but more importantly I can code anything that I am provided the data for. This project involves comparing two sets of data with a defined set of rules, something I have coded many times in the past. I can also provide examples of code I have written; please contact me so that I may share files and so that we may speak further. Thank you for your consideration, and I hope to work with you soon.

Hi, This is Santhosh from India. I am a Business Management Graduate with Computer Science engineering background who is passionate about Data, Mathematics and Technology. I have worked in few data analytics projects involving SAS & R. Also I have worked on many projects involving Excel (Pivot Table, Macros) and VBA. I am relatively new to freelancing so I don't have many projects to showcase in this site. I believe I have enough expertise to complete this project as per your requirement. I am sure that you will be 100% satisfied with my work. Please get in touch. Looking forward to hear from you. Thanks & Regards, Santhosh Kanna

Hi I am a very experienced statistician with experience of several pHD level thesis projects involving advanced statistical analysis. I have worked with data from several companies and have done projects involving high level quantitative analysis and data interpretation skills to study the trends, time behaviour and compare the variables in the data. I can do advanced level analysis in SPSS, R, WEKA and excel tools like machine learning, hypothesis testing, forecasting, T-test, ANOVA etc. Please have a look at my profile. Looking forward to discussion, Best Regards, Suyash

I have done this kind of analysis for another client. I would suggest to take the data from quandl.com. I could deliver a web app for a reasonable price to filter the quandl database and visualize the results. No worries, if you need a higher than daily frequencies. We will find a solution, but I am sure that we can find a lot of valuable insight using daily data from quandl. For backtesting I would suggest quantopian.com. Looking forward to a job interview. I will be available from 9:00 to 17.00 on any weekday (I am located in Vienna, Austria). best regards, Joerg.

Hi, I'm experienced in Financial Analysis, Accounting and Economics, Project Management and Academic writing. Ready to complete your projects: 1) Writing Business Reports - Business Plan, Investment Memorandum, Financial Performance ... 2) Developing Financial model, Business valuation, Financial Projections 3) Designing and estimation of Econometric models 4) Essays writing in Finance, Economics, Accounting, Business, Management, International trade... According to the established formatting and referencing rules. Our team's qualification as well as experience and diversity in skills that we can offer makes us a dynamic source for meeting almost all your requirements.

I am adept at using machine learning algorithms like random forest, xgboost, ada boost and neural networks in R. You can send me your data set. I would be happy to help you with this.

I am a CAT (Certified Accounting Technician) and ACCA (Association of Chartered Certified Accountant) qualified, pursuing CFA (Chartered Financial Analyst). Hence, I have extensive knowledge of finance, accounts, audit, marketing, HR and business related matters. Though these subjects are my forte, being an academic writer, I have written reports, essays, dissertations & thesis on various other subjects as well.

I have previously developed code for similar assignments in R and SAS. I have 5 years of experience in coding and content writing along with 7 years experience of trading in stock market.

A proposal has not yet been provided

My day to day job duties include statistical analysis from basic to applied in R. I have done similar kind of analysis recently. I can include pretty figure/visualization for easy interpretation and sharing.

★★ Machine learning expert and software architect based in the United States - feel free to message me to discuss requirements prior to the project being awarded. ☞ How I Can Help You: I have actually worked on machine learning applications involving streaming market data before so I'm familiar with the data set characteristics. I think the most important thing to a project like yours is to make sure that the correlations you identify will hold up in the future. doing so requires looking at more than just the raw ticker data - and while it adds complexity, it also provides a greater level of confidence in future production. Shoot me a message so we can discuss your specific requirements and plan. Afterwards I will propose a set of milestones. ☞ About Me: My name is Tom Griffin, I'm based in the United States, and I have fifteen years of experience in a variety of technology and business roles. You may read more about me on LinkedIn if you search for "Tom Griffin IEEE." ║✭✭✭✭✭✭✭▅▅▅▅▅▅▅▅▅ Tom is based in the United States ║✭✭✭✭✭✭✭▅▅▅▅▅▅▅▅▅ and has worked with major organizations. ║✭✭✭✭✭✭✭▅▅▅▅▅▅▅▅▅ You can read more about him in his profile ║▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅ or by finding him on LinkedIn by searching for ║▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅ "Tom Griffin IEEE." ║▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅

Dear Sir. We claim to get it done perfectly for you EXACTLY in the way you want it - Kindly give we a chance and we will prove myself - Ready to prove our words, let's get it done right away and I mean RIGHT AWAY !! Looking forward to hear from you soon - GOD Bless You.

Hi I'm Diego Forteza and I have a degree in statistics from Universidad de la República del Uruguay. I've been using R almost every day for the last 7 years, calculation of correlations (linear or non linear) won't be a problem, I could do both calculations and give you both results. Cheers, Diego

Hello, I have 4 years of experience programming financial analysis tools. My portfolio contains only one item (a personal project) because all of my projects have been under an NDA. However, the one item is very relevant to this project (a correlation matrix built from historical forex data). You should hire someone that knows Python's limitations, how to optimize Python, and convert Python to C (if needed) and/or build C bindings for Python. That person is me. Why? Let's say you want to find the highest positive correlation between two stocks listed on the NYSE and you want to use the daily close price for the computations. Correlation has to be calculated for all permutations (e.g., correlation of A,B, correlation of A,C, correlation of A,D, and so on and then correlation of B,A; B,C; B,D etc.). That means, correlation has to be calculated 7,837,200 times. Let's say the data set contains 252 close prices for each symbol (1 year's worth of data). Consider how many calculations have to be done just to get one correlation value: covarianceX,Y / (stdevX * stdevY) (>3026 calculations for 252 prices). That is at least 23,715,367,200 calculations. Think about if you wanted to calculate this over 20 years of daily prices (~20*3026*7,837,200) ...

A proposal has not yet been provided

I have a degree in Statistics with advanced Maths and more than a decade of experience working with Time Series & Regression analysis. I have more than 10 years of exp with Python - with a good understanding of R. I also have very good experience working with Machine Learning algorithms and have been recently working with NLP and Self Learning ANN models using Restricted Boltzman machines. I also participate in Kaggle contests whenever I have some time.

I can bring to the table solid knowledge in the Financial Analysis and Research areas as well as access to historical securities data to test the algorithm. For this project the ideal language is R From the project description it seems that the work consists in creating the pairwise correlation matrix of a set of securities. In addition to the highest positive and negative correlation this will produce all of the correlations among every pair of securities that could be used for more complex trading algorithms.