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VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, I COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM ON PROGRAMMING LANGUAGES; WHY MY DAD WENT FROM … In Data Science from Scratch, a book introducing data science using Python, Joel Grus said the following about R (pg. 302):. Although you can totally get away with not learning R, a lot of data scientists and data science projects use it, so it’s worth getting familiar withit.
REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course. Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studyingphilosophy
CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but IVIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, I COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM ON PROGRAMMING LANGUAGES; WHY MY DAD WENT FROM … In Data Science from Scratch, a book introducing data science using Python, Joel Grus said the following about R (pg. 302):. Although you can totally get away with not learning R, a lot of data scientists and data science projects use it, so it’s worth getting familiar withit.
REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course. Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studyingphilosophy
BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but IVIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are PYTHON - CURTIS MILLER'S PERSONAL WEBSITE A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, I GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible inGAME PROGRAMMING
One day I was looking around on GameJolt and saw a Fireside article by a developer called @jacklehamster, entitled: “That time I chose to leave my gamedev passion on the side of the road; A story about my love and hate relationship with game programming.” It’s about his romance with game programming: his sections are entitled, “It was love at first sight,” “The younger years THE END OF THE HONEYMOON: FALLING OUT OF LOVE WITH Introduction I spent good chunks of Friday, Saturday, and Sunday attempting to write another blog post on using R and the quantstrat package for backtesting, and all I have to show for my work is frustration. So I've started to fall out of love with quantstrat and am thinking of exploring Python backtesting libraries from UNPACKING NUMPY AND PANDAS Unpacking NumPy and Pandas. This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses setting up and using a Python data analysis environment with Anaconda, including the use of common tools likeJupyter Notebooks.
DATA ACQUISITION AND MANIPULATION WITH PYTHON Data Acquisition and Manipulation with Python. This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses how to use Python (Pandas in particular) for manipulating data, including getting data in R FUNCTION FOR SIMULATING GAUSSIAN PROCESSES This semester my studies all involve one key mathematical object: Gaussian processes.I’m taking a course on stochastic processes (which will talk about Wiener processes, a type of Gaussian process and arguably the most common) and mathematical finance, which involves stochastic differential equations (SDEs) used for derivative pricing, including in the Black-Scholes-Merton equation. ORDER TYPE AND PARAMETER OPTIMIZATION IN QUANTSTRAT One way to speed up the process is to parallellize it. quantstrat supports parallellization, and implementing it is as simple as loading the package doParallel and registering cores to be used in the parallelization; apply.paramset () already uses %dopar% and foreach () from the foreach package. CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I PYTHON - CURTIS MILLER'S PERSONAL WEBSITE Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and TRAINING YOUR SYSTEMS WITH PYTHON STATISTICAL MODELING This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses how to use Python for machine learning. The course covers Classical statistical methods (from both frequentist and Bayesian perspectives) Supervised learning methods, with models ranging from decision trees to neural networks Classification and regression ON PROGRAMMING LANGUAGES; WHY MY DAD WENT FROM … In Data Science from Scratch, a book introducing data science using Python, Joel Grus said the following about R (pg. 302):. Although you can totally get away with not learning R, a lot of data scientists and data science projects use it, so it’s worth getting familiar withit.
COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM PROBLEMS IN ESTIMATING GARCH PARAMETERS IN R UPDATE (11/2/17 3:00 PM MDT): I got the following e-mail from Brian Peterson, a well-known R finance contributor, over R’s finance mailing list: I would strongly suggest looking at rugarch or rmgarch.The primary maintainer of the RMetrics suite of packages, Diethelm Wuertz, was CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I PYTHON - CURTIS MILLER'S PERSONAL WEBSITE Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and TRAINING YOUR SYSTEMS WITH PYTHON STATISTICAL MODELING This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses how to use Python for machine learning. The course covers Classical statistical methods (from both frequentist and Bayesian perspectives) Supervised learning methods, with models ranging from decision trees to neural networks Classification and regression ON PROGRAMMING LANGUAGES; WHY MY DAD WENT FROM … In Data Science from Scratch, a book introducing data science using Python, Joel Grus said the following about R (pg. 302):. Although you can totally get away with not learning R, a lot of data scientists and data science projects use it, so it’s worth getting familiar withit.
COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM PROBLEMS IN ESTIMATING GARCH PARAMETERS IN R UPDATE (11/2/17 3:00 PM MDT): I got the following e-mail from Brian Peterson, a well-known R finance contributor, over R’s finance mailing list: I would strongly suggest looking at rugarch or rmgarch.The primary maintainer of the RMetrics suite of packages, Diethelm Wuertz, was BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. MOVING AVERAGE CROSSOVER STRATEGY Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. GRADES AREN’T NORMAL Figure 1 presents a histogram of the data in grades.When I see that distribution, it appears to be a left-skewed distribution. Most students are in the 60-100 range, some scored more than 100, and some scored much less than 60. 3 The median grade is 83, the first quartile 71.5, and the third quartile 92. Overall, not a bad distribution thatemerged naturally.
GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON I have created a video course published by Packt Publishing entitled Data Acqusition and Manipulation with Python, the second volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers more advanced Pandas topics such as reading in datasets in different formats and from databases, aggregation, and data wrangling. WALK FORWARD ANALYSIS DISCLAIMER: Any losses incurred based on the content of this post are the responsibility of the trader, not me. I, the author, neither take responsibility for theARKHAM HORROR LCG
(If you care, there may be spoilers in this post.) Introduction. I love Arkham Horror; The Card Game.I love it more than I really should; it’s ridiculously fun. It’s a cooperative card game where you build a deck representing a character in the Cthulhu mythos universe, and with that deck you play scenarios in a narrative campaign 1 where you grapple with the horrors of the mythos. REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course.Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studying philosophy in my debate class, and my experience in CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM TRAINING YOUR SYSTEMS WITH PYTHON STATISTICAL MODELING Training Your Systems with Python Statistical Modeling. This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses how to use Python for machine learning. The course covers. Classical statistical methods (from both frequentist and Bayesian perspectives) DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and ON PROGRAMMING LANGUAGES; WHY MY DAD WENT FROM … In Data Science from Scratch, a book introducing data science using Python, Joel Grus said the following about R (pg. 302):. Although you can totally get away with not learning R, a lot of data scientists and data science projects use it, so it’s worth getting familiar withit.
COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM PROBLEMS IN ESTIMATING GARCH PARAMETERS IN R Problems In Estimating GARCH Parameters in R. UPDATE (11/2/17 3:00 PM MDT): I got the following e-mail from Brian Peterson, a well-known R finance contributor, over R’s finance mailing list: I would strongly suggest looking at rugarch or rmgarch. The primary. maintainer of the RMetrics suite of packages, Diethelm Wuertz, was. CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM TRAINING YOUR SYSTEMS WITH PYTHON STATISTICAL MODELING Training Your Systems with Python Statistical Modeling. This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses how to use Python for machine learning. The course covers. Classical statistical methods (from both frequentist and Bayesian perspectives) DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and ON PROGRAMMING LANGUAGES; WHY MY DAD WENT FROM … In Data Science from Scratch, a book introducing data science using Python, Joel Grus said the following about R (pg. 302):. Although you can totally get away with not learning R, a lot of data scientists and data science projects use it, so it’s worth getting familiar withit.
COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM PROBLEMS IN ESTIMATING GARCH PARAMETERS IN R Problems In Estimating GARCH Parameters in R. UPDATE (11/2/17 3:00 PM MDT): I got the following e-mail from Brian Peterson, a well-known R finance contributor, over R’s finance mailing list: I would strongly suggest looking at rugarch or rmgarch. The primary. maintainer of the RMetrics suite of packages, Diethelm Wuertz, was. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. MOVING AVERAGE CROSSOVER STRATEGY In these posts, I discuss basics such as obtaining the data from Yahoo! Finance using pandas, visualizing stock data, moving averages, developing a moving-average crossover strategy, backtesting, and benchmarking. The final post will include practice problems. This post discusses moving average crossover strategies,backtesting, andbenchmarking.
WALK FORWARD ANALYSIS Introduction. Having figured out how to perform walk-forward analysis in Python with backtrader, I want to have a look at evaluating a strategy’s performance. So far, I have cared about only one metric: the final value of the account at the end of a backtest relative. This should not be the only metric considered. GRADES AREN’T NORMAL Figure 1 presents a histogram of the data in grades.When I see that distribution, it appears to be a left-skewed distribution. Most students are in the 60-100 range, some scored more than 100, and some scored much less than 60. 3 The median grade is 83, the first quartile 71.5, and the third quartile 92. Overall, not a bad distribution thatemerged naturally.
GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, IARKHAM HORROR LCG
(If you care, there may be spoilers in this post.) Introduction. I love Arkham Horror; The Card Game.I love it more than I really should; it’s ridiculously fun. It’s a cooperative card game where you build a deck representing a character in the Cthulhu mythos universe, and with that deck you play scenarios in a narrative campaign 1 where you grapple with the horrors of the mythos. REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course.Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studying philosophy in my debate class, and my experience in CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but IVIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM PROBLEMS IN ESTIMATING GARCH PARAMETERS IN R Problems In Estimating GARCH Parameters in R. UPDATE (11/2/17 3:00 PM MDT): I got the following e-mail from Brian Peterson, a well-known R finance contributor, over R’s finance mailing list: I would strongly suggest looking at rugarch or rmgarch. The primary. maintainer of the RMetrics suite of packages, Diethelm Wuertz, was. CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but IVIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COM COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COM PROBLEMS IN ESTIMATING GARCH PARAMETERS IN R Problems In Estimating GARCH Parameters in R. UPDATE (11/2/17 3:00 PM MDT): I got the following e-mail from Brian Peterson, a well-known R finance contributor, over R’s finance mailing list: I would strongly suggest looking at rugarch or rmgarch. The primary. maintainer of the RMetrics suite of packages, Diethelm Wuertz, was. BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch.VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PART This post is the first in a two-part series on stock data analysis using R, based on a lecture I gave on the subject for MATH 3900 (Data Science) at the University of Utah. In these posts, I will discuss basics such as obtaining the data from Yahoo! Finance using pandas, visualizing stock data, moving averages, developing a moving-averageGRADUATE EDUCATION
Graduate Studies MSTAT Studies I am pursuing a Master's in Statistics (MSTAT) at the University of Utah. Below are some of the classes I took, with links to pages providing more description and sample work Linear Models (MATH 6010) This course, taught by Prof. Lajos Horvath, discussed linear models and linear regression in statistics. R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. TRAINING SYSTEMS USING PYTHON STATISTICAL MODELLING Training Systems using Python Statistical Modelling. This book, published with Packt Publishing, is an introduction statistical inference and machine learning using Python. Topics covered in the book include statistical inference, supervised and unsupervised learning for both classification and regression, clustering, and dimensionality reduction. MOVING AVERAGE CROSSOVER STRATEGY In these posts, I discuss basics such as obtaining the data from Yahoo! Finance using pandas, visualizing stock data, moving averages, developing a moving-average crossover strategy, backtesting, and benchmarking. The final post will include practice problems. This post discusses moving average crossover strategies,backtesting, andbenchmarking.
DOWNLOADING S&P 500 STOCK DATA FROM GOOGLE/QUANDL WITH R I have created a video course that Packt Publishing will be publishing later this month, entitled Unpacking NumPy and Pandas, the first volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers the basics of setting up a Python environment for data analysis with Anaconda, using Jupyter notebooks, and using NumPy and GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, I CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch.VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COMFREE STOCK ANALYSISR STOCK ANALYSISSTOCK ANALYSIS TOOLSSTOCK ANALYSIS WEBSITESFREE TECHNICAL ANALYSIS OF STOCKS STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COMARKHAM HORROR CARD GAME CONTENTSARKHAM HORROR CARD GAME DIGITALARKHAM HORROR CARD GAME EXPANSIONSARKHAM HORROR CARD GAME ONLINEARKHAM HORROR CARD GAME WIKIARKHAM HORROR THE CARD GAME REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course. Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studyingphilosophy
CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch.VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COMFREE STOCK ANALYSISR STOCK ANALYSISSTOCK ANALYSIS TOOLSSTOCK ANALYSIS WEBSITESFREE TECHNICAL ANALYSIS OF STOCKS STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COMARKHAM HORROR CARD GAME CONTENTSARKHAM HORROR CARD GAME DIGITALARKHAM HORROR CARD GAME EXPANSIONSARKHAM HORROR CARD GAME ONLINEARKHAM HORROR CARD GAME WIKIARKHAM HORROR THE CARD GAME REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course. Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studyingphilosophy
VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in PYTHON - CURTIS MILLER'S PERSONAL WEBSITE A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, IBACKTESTING
Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of BACKTRADER | CURTIS MILLER'S PERSONAL WEBSITE A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, IARKHAM HORROR LCG
Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PART An Introduction to Stock Market Data Analysis with R (Part 2) Around September of 2016 I wrote two articles on using Python for accessing, visualizing, and evaluating trading strategies (see part 1 and part 2 ). These have been my most popular posts, up until I published my article on learning programming languages (featuring my dad’s story MOVING AVERAGE CROSSOVER STRATEGY In these posts, I discuss basics such as obtaining the data from Yahoo! Finance using pandas, visualizing stock data, moving averages, developing a moving-average crossover strategy, backtesting, and benchmarking. The final post will include practice problems. This post discusses moving average crossover strategies,backtesting, andbenchmarking.
GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON A few months ago I wrote a blog post about getting stock data from either Quandl or Google using R, and provided a command line R script to automate the task. In this post I repeat the task but with Python. If you’re interested in the motivation and logic of the procedure, IARKHAM HORROR LCG
(If you care, there may be spoilers in this post.) Introduction. I love Arkham Horror; The Card Game.I love it more than I really should; it’s ridiculously fun. It’s a cooperative card game where you build a deck representing a character in the Cthulhu mythos universe, and with that deck you play scenarios in a narrative campaign 1 where you grapple with the horrors of the mythos. CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch.VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COMFREE STOCK ANALYSISR STOCK ANALYSISSTOCK ANALYSIS TOOLSSTOCK ANALYSIS WEBSITESFREE TECHNICAL ANALYSIS OF STOCKS STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COMARKHAM HORROR CARD GAME CONTENTSARKHAM HORROR CARD GAME DIGITALARKHAM HORROR CARD GAME EXPANSIONSARKHAM HORROR CARD GAME ONLINEARKHAM HORROR CARD GAME WIKIARKHAM HORROR THE CARD GAME REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course. Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studyingphilosophy
CURTIS MILLER'S PERSONAL WEBSITE Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. BOOKS - CURTIS MILLER'S PERSONAL WEBSITE Below are books I have authored: Hands-On Data Analysis with NumPy and Pandas Training Systems using Python Statistical Modeling Prospective Publishers If you are a prospective publisher, I would love to hear from you! Contact me at my e-mail address: cgmil@msn.com I presently do not have time to commit to any additional projects, but I BLOG | CURTIS MILLER'S PERSONAL WEBSITE | CURTIS MILLER'S Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch.VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PARTSEE MORE ON NTGUARDIAN.WORDPRESS.COMFREE STOCK ANALYSISR STOCK ANALYSISSTOCK ANALYSIS TOOLSSTOCK ANALYSIS WEBSITESFREE TECHNICAL ANALYSIS OF STOCKS STOCK DATA ANALYSIS WITH PYTHON (SECOND EDITION) This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance. This is also an update to my earlier blog posts on the same topic (this one combining them together). I R | CURTIS MILLER'S PERSONAL WEBSITE Introduction. Now here is a blog post that has been sitting on the shelf far longer than it should have. Over a year ago I wrote an article about problems I was having when estimating the parameters of a GARCH(1,1) model in R. I documented the behavior of parameter estimates (with a focus on ) and perceived pathological behavior when those estimates are computed using fGarch. INTRODUCING RANK DATA ANALYSIS WITH ARKHAM HORROR DATA Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. COMPARING THE CLASSES OF ARKHAM HORROR; WHY SURVIVORS NEEDSEE MORE ON NTGUARDIAN.WORDPRESS.COMARKHAM HORROR CARD GAME CONTENTSARKHAM HORROR CARD GAME DIGITALARKHAM HORROR CARD GAME EXPANSIONSARKHAM HORROR CARD GAME ONLINEARKHAM HORROR CARD GAME WIKIARKHAM HORROR THE CARD GAME REFLECTION ON MEMORY The first readings of the course, selections from Francis Yates’ The Art of Memory, and Mary Caruthers’ The Book of Memory, were interesting reads and an unexpected kick-off to the course. Now, my exposure to the Middle Ages is fairly small, consisting of what I recall from sophomore world history, a couple semesters studyingphilosophy
VIDEO COURSES
Below are video courses I have authored: Unpacking NumPy and Pandas (Volume I in the series, Taming Data with Python; Excelling as a Data Analyst) Data Acquisition and Manipulation with Python (Volume II) Training Your Systems with Python Statistical Modeling (Volume III) Applications of Statistical Learning with Python (Volume IV) Prospective Publishers If you are PYTHON - CURTIS MILLER'S PERSONAL WEBSITE Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of GETTING STARTED WITH BACKTRADER A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible in AN INTRODUCTION TO STOCK MARKET DATA ANALYSIS WITH R (PART Around September of 2016 I wrote two articles on using Python for accessing, visualizing, and evaluating trading strategies (see part 1 and part 2).These have been my most popular posts, up until I published my article on learning programming languages (featuring my dad’s story as a programmer), and has been translated into both Russian (which used to be on backtest.ru at a link that nowBACKTESTING
Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of BACKTRADER | CURTIS MILLER'S PERSONAL WEBSITE A few weeks ago, I ranted about the R backtesting package quantstrat and its related packages. Specifically, I disliked that I would not be able to do a particular type of walk-forward analysis with quantstrat, or at least was not able to figure out how to do so.In general, I disliked how usable quantstrat seemed to be. The package’s interface seems flexible in some areas, inflexible inARKHAM HORROR LCG
Introduction. Last week I analyzed player rankings of the Arkham Horror LCG classes. This week I explain what I did in the data analysis. As I mentioned, this is the first time that I attempted inference with rank data, and I discovered how rich the subject is.A lot of the tools for the analysis I had to write myself, so you now have the code I didn’t have access to when I started. MOVING AVERAGE CROSSOVER STRATEGY Introduction. This is a lecture for MATH 4100/CS 5160: Introduction to Data Science, offered at the University of Utah, introducing time series data analysis applied to finance.This is also an update to my earlier blog posts on the same topic (this one combining them together). I strongly advise referring to this blog post instead of the previous ones (which I am not altering for the sake of GETTING S&P 500 STOCK DATA FROM QUANDL/GOOGLE WITH PYTHON I have created a video course published by Packt Publishing entitled Data Acqusition and Manipulation with Python, the second volume in a four-volume set of video courses entitled, Taming Data with Python; Excelling as a Data Analyst.This course covers more advanced Pandas topics such as reading in datasets in different formats and from databases, aggregation, and data wrangling.ARKHAM HORROR LCG
(If you care, there may be spoilers in this post.) Introduction. I love Arkham Horror; The Card Game.I love it more than I really should; it’s ridiculously fun. It’s a cooperative card game where you build a deck representing a character in the Cthulhu mythos universe, and with that deck you play scenarios in a narrative campaign 1 where you grapple with the horrors of the mythos. CURTIS MILLER'S PERSONAL WEBSITE CURTIS MILLER'S PERSONAL WEBSITE CURTIS MILLER'S PERSONAL WEBSITE, WITH RESUME, PORTFOLIO, BLOG, ETC.Skip to content
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Welcome to my website! Here you will find a portfolio that describes the work I have done professionally, during my college career while studying at Salt Lake Community College and the University of Utah, my personal blog, along with other work I have done outside the classroom that I feel is significant. Any material in this portfolio is considered my intellectual property. Should I discover that any material on this site is being used without my consent or without due credit being given to me, I WILL exercise my rights and pursue legal action to protect my intellectual property.THE QUICK LIST
The following is what I personally consider my best work: * Explaining Utah’s Gender Gap in Wages (Honor’s thesis; research paper) * Congressional Political Relationships (Website/visualization tool) * Money market fund reform(research paper)
* Identifying Gender of Authors; An application of Markov chains totextual analysis
(research paper)
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