Tuesday, January 22, 2019

First Marquette FMA Club meeting of the Winter/Spring 2019 Semester will be held on Thursday, January 24th



The Marquette University Financial Management Association (FMA) Club will meet this week

The first FMA meeting and guest presentation for the semester will be held on January 24th at 5:00 pm in DS 456 (Marquette College of Business).

Nichole Wearing
Nichole Wearing is a campus recruiter from Northwestern Mutual and she will be presenting on “Networking and Your Personal Brand.”

Dr. David Krause, AIM program director and FMA faculty advisor, said "Personal branding is a hot topic, but a lot of college students don’t understand what it really means. While this is covered in some of our business classes, join Ms. Wearing to learn more about the topic – students learn tips about how to market themselves properly."






For more information about the FMA, please contact E-Board Officer: Gino Piscopo (gino.piscopo@marquette.edu)



AIM Guest Speaker - Brian Nick, Chief Investment Strategist for Nuveen / TIAA Investments, Expects a Challenging 2019, but Not a U.S. Recession


The Marquette AIM Program Hosted Guest Speaker, Brian Nick, (Chief Investment Strategist of Nuveen / TIAA Investments


Brian Nick of Nuveen in the AIM Room
 A standing-room-only crowd of over 40 AIM and FMA students heard from Brian Nick, Chief Investment Strategist, and Bryan Brooks, Vice President at Nuveen Investments / TIAA.

Brian Nick and his colleagues at Nuveen / TIAA Investment have advised investors in 2019 to seek quality at a fair price in a slowing world. 

They believe that when the dust clears, the global economy in 2019 will probably not behave all that differently than it did in 2018, but they are hopeful for better investment returns across most public and private asset classes.


The economists at Nuveen believe that the world is slowing, but only gradually. 


Furthermore, they have stated recently that they believe a global recession and bear market are still at least a few years away, leaving room for portfolios with risk assets to benefit. Access the entire report at: https://www.tiaa.org/public/pdf/4648_AFFILIATED_GPE-GIC1QA-0119D_GIC_annual_outlook_2019_FINAL.pdf




Monday, January 21, 2019

Analyzing 'Key Trends and Topics Within FinTech' in Google Trends with R by David Krause, Marquette AIM Program Director


What are the key 'FinTech Topics' and how do they trend across time? by Dr. David Krause AIM Program Director, Marquette University

 

A previous article about global “FinTechTrends” and an example of the use of R code using Google Trends was published by Dr. David Krause, AIM Program Director, Marquette University. 

This article focuses on the key topic trends within FinTech. This research utilizing Google Trends and R code initially was done in 2018 to create the curriculum utilized in Krause’s FINA 4931: Topic in FinTech course that is being taught in the spring 2019 semester at Marquette University. The original research has been updated and is current as of 1/21/2019.

 

As displayed above, FinTech has taken the financial services industry by storm. According to a Google Trends analysis I recently undertook (shown above) as of 1/21/2019 - the current interest in FinTech continues to grow exponentially – not only in the United States, but globally.

What are the key FinTech Topics and how do they trend across time? The following charts display Interest over time (a Google metric based on search interest – which the reader can think of as an improved version of Google ‘hits’) for various key topics.




The overall current market environment is evaluated for five key FinTech topics (Artificial Intelligent (AI), big data, blockchain, cloud computing and cybersecurity). 

The charts above show the overall relative interest over time of Google trend searches for the five FinTech topics for the world since 2004. The recent explosion of interest in blockchain stands out; however, big data and AI are also displaying upward trends in global interest. The 5-year trends are also shown, and the results are similar to those observed of the entire period with recent interest in blockchain standing out.





The charts above show the overall relative interest over time Google trends for the five FinTech topics within the United States since 2004. The trends are nearly identical to the global FinTech topics trend results (shown above). The 5-year trends are also shown, and the results are similar to those observed of the entire period with blockchain interest showing the strong relative level of recent interest.

 


The results for the most recent 5-year Google Trends period for China are above – and are more challenging to analyze. The conclusion is similar, since the geometric smoothing shows that the relative interest in blockchain since early in 2018 was strong; however in 2019 it appears that the relative the level of interest is similar for all FinTech topics examined.



The chart above shows the overall relative interest over time Google trends for the blockchain FinTech topic search within the United States since 2014. The trend indicated very strong relative interest in early 2018 - near the time that bitcoin traded at its highest level.

(Blockchain technology continues to evolve with issues remaining concerning performance and privacy issues. While the potential is great within the financial services sector, the business model is not yet ready for large-scale consumer use. Blockchain is the digital currency represented by bitcoin; while the second generation of blockchain involves the smart contract platform – with the future likely to lead to advances in cryptography, consensus algorithms, performance optimization, and so on). 

 The chart above displays Google Trends interest over time since 2014 in the US for the search term: artificial intelligence or AI. The trend across time has nearly doubled since 2014 and continues to grow.

(Artificial Intelligence (AI) has begun to impact the wealth management and banking industry. Artificial intelligence applications include robo-advising, anti-fraud detection and credit evaluation - and utilizes tools such as big data analytics and facial and speech recognition. AI applications such as biometrics in mobile phones can assist with customer verification and improve transparency and service to the end-customers in investment and banking applications).



Cybersecurity as a Google search topic has also shown strong growth in interest over time. Since 2014, the relative interest in cybersecurity has more than doubled.

(Cybersecurity, which is also referred to as computer or information technology security (IT) security – it involves the protection of computer systems from theft or damage to the hardware and software. It importantly also contains the protection of internal and external digital data. The term also applies to the intentional disruption or misdirection of the services they provide. The field is growing in importance in the financial services industry due to increasing reliance on computer systems, the Internet, and mobile devices that are connected to wireless networks (including mobile phones, tablets and Internet of Things devices) connected via Bluetooth and Wi-Fi).  



The interest over time of the Google search phrase: big data has actually decreased on a relative basis since 2014.  

(Big data in financial services is quite widespread. Insurance companies, banks and wealth management firms have a major demand for the sharing and application of the internal and external data. Data mining and knowledge transfer plays a large role in analyzing trends and meeting customer needs).



Google search interest over time for cloud computing has shown a decline across the past five years, although not as pronounced as the decline in the search phrase for big data.

(Cloud Computing involves the use of the internet to access applications, data, or services that are stored or run on a remote server. Within financial services, cloud computing has been an important advancement because of the large amounts of data utilized within the industry).


The purpose of this research was to answer the question: What are the key FinTech Topics and how do they trend across time? The charts displayed Interest over time (a Google metric based on search interest – which the reader can think of as an improved version of Google ‘hits’) for various key topics.

Summary: The overall current market environment was evaluated for five key FinTech topics (Artificial Intelligent (AI), big data, blockchain, cloud computing and cybersecurity). The results showed the overall relative interest over time Google trends for the five FinTech topics for the world since 2004 and over the past five years.  The recent explosion of interest in blockchain stands out; however, big data and AI also displayed upward trends in global interest. The 5-year trends were also shown, and the results were similar to those observed of the entire period - the US and global trends were similar.

PS If you are interested in the R code utilized to produce this report, please reach out to Dr. David Krause.

















Analyzing 'FinTech' in Google Trends with R by David Krause, Marquette AIM Program Director


An article about “FinTech Trends” and an example of the use of R code using Google Trends by Dr. David Krause, AIM Program Director, Marquette University

 

FinTech has taken the financial services industry by storm. According to a Google Trends analysis I recently undertook as of 1/21/2019 - the current interest in FinTech continues to grow exponentially – not only in the United States, but globally.

As the following chart displays, Interest over time (a Google metric based on search interest – which the reader can think of as an improved version of Google ‘hits’) exploded about five years ago (2014).





Interestingly, as the following chart shows, Interest over time for both the United States (US) and Japan (JP) also increased about five years ago; however, the US rate of search interest in FinTech has grown by a greater rate recently than Japan.



The following chart indicates that both China (CN) and Great Britain (GB) have had increased FinTech Interest over time; however, both occurred later than the US and Japan – about 2016 for China. A significant development in Asian FinTech growth was the high-profile announcement of several major deals: in 2016 there the deal on Artificial Intelligence (AI) between ChinaAMC, a Chinese mutual fund and Microsoft - and in 2017 with a major agreement between the Bank of China and Tencent.




Using Google Trends and R it possible to look at more recent trends in FinTech Interest over time (the past five years) for the world, US, and China. 

 


The information presented above was obtained from a R code written by David Krause and compiled and viewed using R Studio. The code is contained below:

#Analyzing 'FinTech' in Google Trends with R by David Krause, Marquette AIM Program director

#load the following:
library(gtrendsR)
library(reshape2)
library(ggplot2)

## get web query activity for keyword = "FinTech" 
## Different go codes and time can be used.

#Here is a short-cut to run plots of Google Trends search data
plot(gtrendsR::gtrends(keyword = c("FinTech"), time = "all"))
plot(gtrendsR::gtrends(keyword = c("FinTech"), time = "today+5-y"))

#It is possible to look at search times by geography (i.e. United States - US, Japan - JP)
plot(gtrendsR::gtrends(keyword = c("FinTech"), geo = "US", time = "all")) 
plot(gtrendsR::gtrends(keyword = c("FinTech"), geo = "US", time = "today+5-y"))
plot(gtrendsR::gtrends(keyword = c("FinTech"), geo = "JP", time = "all"))
plot(gtrendsR::gtrends(keyword = c("FinTech"), geo = "JP", time = "today+5-y")) 

res0 = gtrends(c("FinTech"), gprop = "web", time = "all")
plot(res0)+geom_smooth()+geom_line(lwd = 1) 
res1 = gtrends(c("FinTech"), gprop = "web", time = "all", geo = c("US"))
plot(res1)+geom_smooth()+geom_line(lwd = 1) 
res1a = gtrends(c("FinTech"), gprop = "web", time = "all", geo = c("JP"))
plot(res1a)+geom_smooth()+geom_line(lwd = 1)
res1b = gtrends(c("FinTech"), gprop = "web", time = "all", geo = c("US","JP"))
plot(res1b)+geom_smooth()+geom_line(lwd = 1)
res1c = gtrends(c("FinTech"), gprop = "web", time = "all", geo = c("GB","CN"))
plot(res1c)+geom_smooth()+geom_line(lwd = 1)
res2 = gtrends(c("FinTech"), gprop = "web",time="today+5-y")
plot(res2)+geom_smooth()+geom_line(lwd = 1)
res3 <- c="" font="" geo="c(" gprop="web" gtrends="" intech="" time="today+5-y">
plot(res3)+geom_smooth()+geom_line(lwd = 1)
res3a <- c="" font="" geo="c(" gprop="web" gtrends="" intech="" time="today+5-y">
plot(res3a)+geom_smooth()+geom_line(lwd = 1)

# Get data from Google Trends 
#res2a = gtrends(
 # c("FinTech"),
  #geo = c("US","CN"), 
  #gprop = "web", 
  #time = "today+5-y") [[1]] 


#define the keywords to analyze from Google Trends
keywords=c("FinTech")
#set the geographic area: (i.e. US = United States, CN = China)
country=c("US","CN")
#set the time window
time=("today+5-y")
#set channels 
channel='web'

#access the data from Google Trends
trends = gtrends(keywords, gprop =channel,geo=country, time = time )
#select Google Trends Interest over Time (similar to hits) 
time_trend=trends$interest_over_time
#display the first several data items
head(time_trend)
#plot the data items
plot<-ggplot aes="" data="time_trend," x="date," y="hits,group=keyword,col=keyword))+</font">
  geom_line()+xlab('Time')+ylab('Relative Interest')+ theme_bw()+
  theme(legend.title = element_blank(),legend.position="bottom",legend.text=element_text(size=12))+ggtitle("Google Search Volume")
plot



Sunday, January 20, 2019

New FinTech course at Marquette has been developed by David Krause, Marquette’s Director of the Applied Investment Management (AIM) Program and is being offered this semester

Dr. Krause has created a new FinTech Topics course for Marquette students: Who says an old dog can’t teach new tricks?

David Krause, Marquette University's
Director of the Applied Investment
Management (AIM) Program
The global asset management and financial services  industry is growing and changing rapidly – and the Applied Investment Management (AIM) program at Marquette University is adapting… as it always has.

The Director of the AIM program, Dr. David Krause said recently, “The buy-side of the asset management industry is under considerable pressure to reduce their costs given the incredibly low fees being charged by index funds. They also need to demonstrate their value and to improve transparency given the emergence of the robo-advisor. We want to educate the next generation of asset managers (and bankers) who will be operating in an industry that must deal with the disruptions that will result from the new innovations in financial technology.”

While the industry is expected to continue to grow strongly (experts predict a sustained cumulative growth in assets exceeding 6% annually, resulting in a global Assets Under Management of over $110 trillion by 2020, and $145 trillion by 2025), asset management clients (institutional and retail) are becoming increasingly demanding, diverse and knowledgeable – and their expectations of investment outcomes is higher.

Krause said, "Millennials and Gen Zers will not tolerate poor customer service and today's newest investors expect to interact immediately with their investment advisors via digital mechanisms (including social media). Cybersecurity is also a major issue that will be discussed in the course. The demands that will be placed on the buy- and sell-side of the investment industry are huge and our graduates need to be prepared."

"The combination of strong growth, greater client expectations and massive cost pressures is changing the industry right before our eyes," he said. "And because the AIM program has always been on the leading edge of change within the academic investment industry, we are changing too."
Dr. Krause’s course on FinTech Topics (FINA 4931), which is currently being taught in the Spring 2019 semester at Marquette University, focuses on these issues. "This course and the topics covered should provide an opportunity for our students who understand the future changes that are taking place - and who can adapt. Even students graduating this May have an opportunity to become FinTech savvy."

There is a growing demand for graduates entering the industry who are stronger in their understand of the technology. Data analytics will be an important skill set for tomorrow's analysts to master. 

Krause commented, "Our graduates need to be able to add value within an industry where margins are under intense pressure  - while also understand the process of improving the quality of services delivered. Coding and programming are also likely to be required skills of the financial analyst." You can view other blogs about FinTech on this site - for instance: - AIM blog on "Here Come the Quants".

Dr. Krause's course will focus this semester on a range of new technologies and topics (including R coding, blockchain, cybersecurity, big data, and algorithmic and dark pool trading) that are emerging in order to meet this challenge. The application technologies highlighted include:

-         Robotics / Machine-Learning
-         Cybersecurity and Big Data Analytics
-         Blockchain (Distributed Ledger Technology)

Dr. Krause added, "The course is coming along nicely and I'm pleased with the students' enthusiasm concerning the content. I’m also working with a major FinTech software company on memorializing the course content, so that we might have an online version of this course and the new FinTech curriculum ready sometime in the summer of 2019 to offer beyond the classroom."



Saturday, January 19, 2019

An example of R coding "Analyzing Google Trends with R" by David Krause, Marquette AIM Program director

This is an example of an R coding data analytics assignment in FINA 4931: FinTech Topics taught by David Krause, Marquette University AIM Program Director




#Analyzing Google Trends with R by David Krause, Marquette AIM Program director

#load the following:
library(gtrendsR)
library(reshape2)
library(ggplot2)

#define the keywords to analyze from Google Trends

keywords=c("Amazon","Walmart","Target")
#set the geographic area: US = United States
country=c("US")
#set the time window
time=("2014-01-01 2018-12-31")
#set channels 
channel='web'

#access the data from Google Trends
trends = gtrends(keywords, gprop =channel,geo=country, time = time )
#select Google Trends Interest over Time (similar to hits) 
time_trend=trends$interest_over_time
#display the first several data items
head(time_trend)

     date         hits keyword geo gprop category
1 2014-01-05   50  Amazon  US   web        0
2 2014-01-12   48  Amazon  US   web        0
3 2014-01-19   48  Amazon  US   web        0
4 2014-01-26   45  Amazon  US   web        0
5 2014-02-02   43  Amazon  US   web        0

6 2014-02-09   45  Amazon  US   web        0


#plot the data items
plot<-ggplot aes="" data="time_trend," x="date, </font">




y=hits,group=keyword,col=keyword))+
  geom_line()+xlab('Time')+ylab('Relative Interest')+ theme_bw()+
  theme(legend.title = element_blank(),legend.position="bottom",legend.text=element_text(size=12))+ggtitle("Google Search Volume")
plot
#Outliers can distort the analysis and this is a way to remove outliers (hits greater than 80)
time_trend2=time_trend[time_trend$hits<80 font="">
plot<-ggplot aes="" data="time_trend2," x="date," y="hits,group=keyword,col=keyword))+</font">
  geom_line()+xlab('Time')+ylab('Relative Interest')+ theme_bw()+
  theme(legend.title = element_blank(),legend.position="bottom",legend.text=element_text(size=12))+ggtitle("Google Search Volume – Outliers Removed")
plot




#If there is seasonality, then geometric smoothing can assist with the analysis
plot<-ggplot aes="" data="time_trend2," x="date," y="hits,group=keyword,col=keyword))+</font">
  geom_smooth(span=0.5,se=FALSE)+xlab('Time')+ylab('Relative Interest')+
  theme_bw()+theme(legend.title = element_blank(),legend.position="bottom",
                   legend.text=element_text(size=12))+ggtitle("Google Search Volume")
plot





#Here is a short-cut to run plots of Google Trends search data
plot(gtrendsR::gtrends(keyword = c("Walmart","Amazon","Target"), geo = "US", time = "2014-01-01 2018-12-31"))



#It is possible to look at search times by geography (i.e. Wisconsin is US-WI)
plot(gtrendsR::gtrends(keyword = c("Walmart","Amazon","Target"), geo = "US-WI", time = "2014-01-01 2018-12-31")) 



Marquette AIM Class of 2020 Equity Funds Off to Strong Start in 2019

Thus far the equity returns of AIM Funds for the first three weeks of 2019 have been quite favorable for the AIM Class of 2020


The following tables show the performance of the AIM Equity Funds and the top 5 performing stocks for the first three weeks of 2019:


Dr. Krause’s New FinTech Topics Course at Marquette is Off-and-Running!


The new course offering at Marquette University (FIN 4931:  FinTech Topics) completed week 1 and students are already running R code to scrap real-time, unstructured big data from Google!


As almost everyone knows today, data science is exploding - especially in the financial industry.

Articles appear almost daily talking about the increased number of financial firms that are utilizing data science and machine learning systems to support their research and trading activities.

During the first week of FINA 4931, Dr. Krause’s students were introduced to R – an open-source programming language used by many in industry and the academic community. 

Dr. Krause said, “The libraries and tools available in R – and with the use of R Studio – we have been able to get up and running with big data analytics within the first few class meetings. R is not only ideal for statistical analysis, it also has strong supporting packaging that make the collection of data fast and easy.”

 “The goal is not to create coders, but to provide the students will the ability to access data and statistical tools quickly in order to complement the traditional fundamental financial analysis skills,” Krause added.


The course will spend considerable time on data analytics (utilizing real-time Google, Twitter and Facebook data), but it will also include modules on: Artificial Intelligence, Machine Learning, Blockchain, and Cybersecurity.

Krause stated, “This course will likely grow and become embedded within the classes I teach at Marquette in the AIM program. The advances within the FinTech industry are amazing and the trend will only continue. The financial services sectors, including investments, insurance and banking will change dramatically because of the huge among of digital data they employ and the need to better serve their clients (including digital natives, millennials, and Gen Z). These are very exciting times.”

“Within the next several weeks, it is our goal for the students to be able to apply R programming language and essential data science techniques to begin to understand how to solve complex finance problems,” Dr. Krause concluded. 

“The students will begin to see how the content within the course can be effectively applied in areas such as: sentiment analysis, advanced econometric and time series analysis, risk management and reporting, real-time access and analysis of financial and economic data, credit evaluation, and machine learning algorithms.”



Dan Tranchita and Andy O’Connell of Baird Advisors presented at Marquette University to the Fixed Income Securities class


Dan Tranchita and Andy O’Connell (Marquette Alumni) visited Dr. Krause’s class and discussed the current macro-economic climate and the fixed income market

The fixed income investment management business is a challenge one – and Milwaukee-based Baird Advisors is one of the top firms in the industry.


Dan Tranchita
Andy O'Connell


 
Marquette and the AIM program are proud of the success of Baird’s fixed income team – especially because of the large number of alumni involved at all levels of the organization. 

Dan Tranchita and Andy O’Connell again delivered a strong presentation to the students that included current news and strategies – as well as meaningful insights into the application of the concepts talk in Dr. Krause’s Fixed Income class.


Dr. David Krause, AIM program director and professor of finance at Marquette, said, “It is always great to have alumni return to campus; however, it is more than just a friendly visit. Dan and Andy are a great example of how we work investment professionals and other practitioners into the curriculum. Not only do they bring current insights, but they help to reinforce the material contained within the CFA curriculum – which we utilize within the AIM program at Marquette.”

Krause continued, “I always like to bring them into the Fixed Income class during the first week of the semester because we're able to draw on the material from their presentation throughout the semester. Thanks to Dan and Andy - and Baird Advisors for supporting our students at Marquette.”