We would like to search for an R programmer with good statistical knowledge, some modeling/modeling diagnostic experience, statistical research experience to develop the programs and consult on model for our academic statistical research on hedge funds. We would be analyzing the influencing factors that affect the performance, risk, and life cycle(hazard rate) of hedge funds using regression analysis (including multivariate regression, time series regression, Cox regression) and difference between mean test. Factors such as fund internal/external governance and regulations variables. The position’s responsibilities and qualifications are described below.
Work Period: Immediately to 2-5 weeks
Pay: Total project pay is determined by your availability and hourly rate. We would do flat rate only for the entire project (the budget amount would not be a good reference because it depends on the freelancer).
1. Programming/model implementation/data processing (main responsibility): programming in R to code our models and variables, data processing, and various other programming, data, statistics related tasks.
2. Modeling and model diagnostic: Consult on modeling design given what we are looking to do and the data, methodology or model diagnostic procedure that we should use to make sure our models/analysis are very robust and analyze what we should do, model parameters are specified to our analysis, and properly adjusted for factors that may affect our model/results - (such as to avoid multicollinearity, endogeneity, Heteroscedasticity, biase, distribution assumptions), and diagnose model and implement treatment accordingly.
3. Models implementation: Replicating or applying models and procedures from reference papers to our research
4. Description of procedures: Provide detailed and technical description of the methodology used models and implementation
1. Bachelor’s, Master’s or PhD’s degree in Statistics that used R significantly
2. Minimum 5 years of experience implementing programming using R (must), preferably statistical models
3. Knowledgeable and years of experiences in basic and advanced statistical modeling, including many of the below statistical analysis methods, models, procedures
• Regression analysis
o cross-sectional regression (t-statistic, chi square-statistic, F-statistic)
o logistics regression (regular and conditional logit model)
o Time series regression
o Multivariate regression
o Cox proportional hazard model (z-statistic) used for survival analysis
• Difference of the Mean Test(t-statistic) (a must)
• Portfolio sorting
4. Some experience in academic research would be preferred
5. Very good English communications skills in oral and writing
6. Have experience in applying statistical methodologies procedures to ensure robustness (such as to avoid multicollinearity, endogeneity, Heteroscedasticity, biases) (having experience in model diagnostic procedures such as Newey-West, VIF, White Test is a major plus)
7. Weekly availability to be at least 30 hours from now to 10/23, prefer 40-60 hours/weekly availability
Do you have a Barchelor’s, Master’s, or Statistics degree in Statistics, Applied Mathematics, or closely related field? (please send a CV or resume with your application)
Number of years for R experience? and approximately how often have you used R those years (such as 30 hours/w)? Could you describe your R usage? Please include a more detailed description for the statistical programming usage
Could you describe the extent of your statistical modeling experience? Please specify which models that you have had many years of working experience or academic research experience with
What is your weekly available hours that can dedicate to this work project up to 10/23?
Could you send us a sample of a R script that you have written to allow us to evaluate your skill level?