A Brief Update

I survived the first week of the semester at Unknown University. This is my first time ever teaching three preps, and it's tougher than I expected. I'm about 1 1/2 weeks ahead in my classes, so I'm not running around playing catch up (another first, it seems). But, it's still no cake walk.

On a different note - I just got an email from a coauthor. It contained a graph with some absolutely kick-hiney (that's a technical term) results. Times like this remind me what I love about this job - finding out interesting new things. I've got great hopes for this project - not only that it'll place in a good journal but that it'll be the start of a new stream of research. Time will tell, but for now, I'm excited.

Ah well - time to give the Unknown Baby Boy his last bottle for the night, and then turn in.

updates the next day - even more good new results. Woo Hoo!

The Summer Winds Down

It's been a busy week here in Unknownville. Unknown University starts up next week (we start later than most), so we've had a rash (or is that a plague?) of meetings. I'm still juggling several papers (writing a lit review for one, doing data work for another, and some polishing/editing for a third) and sequentially disappointing my coauthors.

Ah well - them's the breaks. But I have to be nice, since coauthors on each paper read the blog. So fear not, coauthors - my parts will be done in good time.

Along those lines, I just received a bunch of results from one coauthor, some of which are pretty interesting. It's an area that I had an unsuccessful paper in several years ago, and she usues s new and difficult data set that allows us to revisit the topic in a very new way. WE've got a good story and good results, and it'll gp to the head of the pile, since we're sending the paper to an upcoming conference (the Eastern Finance Association annual meeting) for which the deadline is next week. I hope it gets accepted since the Unknown Wife and I plan on making it a little vacation (she's neve been to Miami). We're pretty confident - its a good idea,goood data, and believable results (And we know the program chair).

After all, that's potentially one of the perks of academia - you can sometimes have the university partially fund your vacations by choosing your conferences wisely.

Finally, I just got an email telling me I've won 12,841,340 Euros in an inernational lottery that I don't recall entering. I have to share it with 14,000 winners, but it'll give my students something to calculate when I cover foreign exchange rates.

UnknwonDaughter is now back in scnool and once agaion well ahead of her classmates.. And Unknown Baby boy continues t alternately make us laugh and make us gag as he exceeds manufacturers capacit on his diapers (or as we call them "Code Brown!). Ah well - the wages fo hchild rearing.

Peace

-UP

Data Analysis With Stata

The Unknown Family went to the Unknown Sister-in-Law's family's house in an adjacent state (their youngest daughter is going off to college, and Unknown Wife wanted to see her before she leaves for the Big Adventure). So, I got a couple of days to myself. Nothing very exciting - I've been grinding data during the day, and went on a couple of longish bike rides (I'm up to 25-30 miles at a time at what for me is a pretty good clip).

On the data analysis front, I finally took the plunge and started using Stata. It's a pretty amazing package of tools. I work with a lot of large and complicated data sets, and there's always a lot of data manipulation before I get to the point where I'm running statistical analyses. When it comes to moving data around (merging data, sub-setting, mean adjusting, etc...) SAS wins hands down. And I've put a lot of time getting my SAS chops, so I'd put off learning Stata for a long time.

But I now understand what so many of my friends have been telling me for so long - once you get to the point that your data is all nice and neat, Stata rocks. I was able to do many permutations of regression models (fixed effects, random effects, robust and/or clustered errors, etc...) in about a quarter of the time it would take in SAS. And while it's possible to work in batch mode by writing "do" files, you can do quick and dirty analyses with drop down menus.

I have seen the statistical light, and it reveals that I'll be doing a lot more with Stata in the future.

Journal Of Undergraduate Research In Finance

There's a new journal out geared towards undergraduate research. It's called (appropriately), The Journal of Undergraduate Research In Finance. Here's it's description:

The Journal of Undergraduate Research in Finance publishes original work written exclusively by undergraduates. Accepted articles are largely the result of the highest quality senior or honors theses. Articles come from all areas of Finance, case studies and pedagogy. All articles are subject to blind review by faculty.

The JURF exists to encourage exceptional undergraduate students to pursue high quality research in Finance, to provide these students with an outlet for their research, and to prepare these students for success in graduate school or industry. To maintain a focus on contributions made by the students, faculty involvement is limited to the guidance typically given during the writing of a senior thesis. Initial submissions must be made while the author is an undergraduate student.

The JURF is published annually.

So, if you have a student who has done some good research and who might be looking for an outlet, have them send it in - the submission deadline for this year's edition is May 15. As an added inducement, the top three articles for this year's issue will be invited to the FMA meeting in Denver to present their research, and will be considered for the annual Mark J. Bertus prize (in the amount of $1,000).

Undergraduate Thesis on CDOs and the Credit Meltdown

This Harvard undergrad's senior thesis on CDOs (Collateralized Debt Obligations) and their role in the credit crisis was recently mention in Deal Journal.

It the doesn't say anything new, but it does an impressive job of marshaling facts about the CDO markets - the author hand-collected a data set on over 700 CDO deals, and provides a wealth of information.

What's more, she did it within a semester's time.

HT: Marginal Revolution

Rankings of Finance Doctoral Programs

Because I'm one of the few bloggers who regularly write about the life of a finance professor, I get about a dozen questions a month from people considering a PhD in finance (Note: if you're interested, you can read about a finance professor's typical day here and here, and about what's involved in getting a PhD in finance here).

The emails are one of the more surprising and most enjoyable things about writing the blog, and at least a couple of the folks who've sent me questions are currently in PhD programs. I look forward to seeing how their careers progress, knowing I may have played some small part it them.

Some of the most frequent questions I get are along the lines of "How do I find out how well respected University X's finance doctoral program is?" or alternately, "Where can a get a list of rankings of finance doctoral programs?"

I should have done this some time ago, but I'm a bit slow at times. But, since Unknown Daughter and She Who Must Be Obeyed are out to a classmate's birthday party, and Unknown Son is entranced by a Harry Potter movie, this seems like a good time to spent a little time on the Almighty Google. Here are the results:

• Karolyis and Silvestrini have a piece on SSRN titled "Comparing the Research Productivity of Finance PhD Program Graduates" here
• Jean Heck has a similar piece titled "Establishing a Pecking Order for Finance Academics: Ranking of U.S. Finance Doctoral Programs here. Both it and the Karolyi/Silvestrini piece analyze productivity on the basis of the author's doctoral-granting program, but this one lists a few more doctoral programs than the other piece. So, it might yield some possibilities for those looking for less selective programs.
• Finally, Arizona State has a ranking of finance departments (which may or may not have doctoral programs) here, while EconPhD has a similar one covering several finance areas here.

Updated 3/18: A regular reader of the blog (thanks, Jeff) submitted a couple other rankings

• Chan, Lung and Wolfe have a ranking of finance departments based on "citations" (in case you're not familiar with the term, a citation occurs when one author references another in his work). So, citation counts are often used as a measure of the impact a person's work has in the larger academic community.
• The University of Texas-Dallas has a ranking of business schools (not finance departments) based on publications in a pretty wide number of journals across all business disciplines.
  

Hopefully, these will prove useful. If any of you are aware of any other rankings that are relatively recent (i.e. done in the last 4-5 years or so), let me know and I'll update the list.

Another Crop Almost In

At the risk of sounding like Chauncy Gardner, teaching at the university level is a lot like farming - there's a definite rhythm to the semester that mimics the farming calendar. In the off season, you prepare the soil (make changes to the syllabus, do some reading for new materials in your classes, etc...). During the semester, there's planting (the first week or so), pruning and weed pulling (usually done with exams and quizzes), and finally, at the end of semester there's the harvest.

I gave my last final exam yesterday. So, the crop's almost in. Now all I have left to do is grade them (and the remaining class projects) and I'm done with teaching-related stuff for the semester.

No cracks about vegetables, please (or at least, not too many...).

But as for research in the "off season", there's a lot to do:

• I just yesterday finished my part of the work on one revise and resubmit (I'll call it R&R-1), which involved a fair bit of empirical work, and SAS programming out the yazoo. Now I can turn everything over to my coauthors, who'll do the remaining writing, and deal with the rest of the referee's comments.
  
• Since my part of R&R-1 is done, I now get to work on another R&R (R&R-2) where I get to do most of the writing (both coauthors are not native speakers of English). Unfortunately, the referee was extremely picky, so there's much to do.
  
• There's a third R&R (R&R-3) for which a coauthor is doing the first draft on the revisions (it's all writing - no new empirical work is needed). Then, he'll pass it back to me for further editing (I'm the "senior" writer on this one - the coauthor was my student previously). With luck, I'll finish R&R-2 before this one comes back to me.
• Then, there's a piece with a former colleague and a former Ph.D. student. It was sent out and soundly rejected previously. So, we (actually, the former Ph.D. student) did a lot of additional empirical work. Then the former colleague did a rewrite, and I'll get to do the final buffing and shining. Hopefully, it'll come back to me after R&R-2 is done and before R&R-3 comes back to me).
  
• Somewhere in there, there's another piece that I'm trying to finish before the FMA submission deadline. It's with another former student - we'd previously done a pilot study with interesting results. Since then, we've expanded the data set to about 5x its original size, and then ran some additional tests. If the coauthor can finish his part of the data work (mostly the coding of governance data from about 500 proxies) soon, we can write up the new results and send it off.
  
• There are a few other pieces in various stages, but I'll save discussion of them until they move out of the "vaporware" category.
  

Luckily, I have almost five weeks before the next "planting". Looks like it'll be a busy time. But that's what makes it fun.

Memoir of Gene Fama

Here's a pretty good "brief" memoir Eugene Fama wrote for a journal. I say "brief" because it runs pretty long - but that's to be expected given all the work that Fama has done.

A Great Review of Analyst Forecast Research

As most academics know, a good survey article is worth its weight in gold. So, here's a good one on analyst forecast research (you can send money later)

Sundaresh Ramnath, Steve Rock and Philip Shane have a piece in the 2008 International Journal Of Forecasting entitled "The Financial Analyst Forecasting Literature: A Taxonomy with Suggestions for Further Research." In it, they catalog and organize about 250 research articles on various facets of the equity analysis process done since 1992 (it builds on earlier pieces by Schipper (991) and Brown (1993)). They arrange their review into the following topics:

• How do analysts make decisions (i.e. what information do they use, how does their environment affect them, etc...)
• What is the nature of analysts expertise (i.e. how do you measure it, is there herding, etc...)
• Information content (how informative are analysts forecasts, is there information in forecasts over an above other available information)
• Market efficiency (how much is extant information reflected in forecasts, do stock prices reflect the info in forecasts, etc...)
• What incentives or behavioral biases affect or are present in analyst forecasts
• How does the regulatory environment affect the forecasting process
• How statistically valid are analyst forecast studies?
  

All in all, it's a very thorough piece, and I suspect it'll end up being read and cited by quite academics. In particular, I'd recommend it to grad students who are trying to get up to speed on this very broad literature.

The IJF piece is for subscribers only, but there's an ungated version on SSRN here.

HT: CXO Advisory Group.

Yo Momma is a Data Miner

Having a lot of data makes research easier - we now have more data in easily readable formats than ever before, and an amazing amount of computing power on our desktops (I have far more horsepower on my desk than NASA had in total in the 1980s)..

Unfortunately, there's a flip side to that coin - we can easily find variables (or specifications) that seem to "predict" returns (or just about anything). In reality, we're often just overfitting the data.

Here's a pretty good piece on the topic titled "Yo Momma is a Data Miner", by David Leinwebber in which he fits a polynomial time-series regression to the S&P 500 with surprising (if you don;t follow what he's doing) good results - particularly since he's using things like the sheep population and Bangladesh Butter production as regressors.

Talking With Practitioners

Unknown University recently had a function where they brought back a number of prominent alumni to talk about various topics. At dinner after the function, I ended up at a table with an MD from a major investment bank who manages about 10Billion overall in both traditional funds and alternative investments in the market where I'm currently doing some research. It was not by chance - I offered to lead a session that he was the main speacker for, and asked to be put at his table afterward.

So, at dinner (in between him checking his Blackberry every few minutes (dan - that is distracting), I got a chance to see whether my story about what I saw in my data passed the "sniff test" from someone who works in that market on a daily basis. Luckily, it did. Having topped that bar, we started talking about what sorts of things his firm has done in terms of research on the particular topic. So, it looks like I made a connection that could result in my getting some pretty scarce data in exchange for doing some research for the guy. It's a win-win - he gets some relatively low-cost access to eggheads, and I and my coauthor get some scarce data and access to people who can tell us far more about the markets involved than we could learn from academic articles and textbooks.

So, the bottom line is - If you're an academic who works on related topics, talk to practitioners. It's good for you.

Arghhhh!

The deadline for submissions to the FMA (Financial Management Association, our national association) national conference is this Friday. I'm trying to get two papers done - one in which I do the data analysis and hand it off to my coauthor for the writeup and another where the reverse happens (she analyzes and hands off to me). Last week I thought I was in good shape.

Uh oh - I spoke too soon.

First, this weekend when no one is around, my office computer gets cut off from the Internet by the University IT department - they said I had a virus. So, for the weekend I used my laptop for interned access (some citations and work on WRDS), and kept running analysis on my desktop - it has two screens and a lot more power.

Come Monday morning my college's IT guy (who is fantastic, BTW) said he'd look at it. So, I backed up all the relevant stuff for the two papers to a portable hard drive and started working on my notebook. I figure he'd scan the hard drives and give it back to me in a day or so.

Next thing you know, my IT guy tells me that my boot drive has gone Tango Uniform (I have two hard drives in the system - one is the boot drive and the other has all my data on it). Luckily I'd backed up everything from the data drive before giving the machine to him.

It's a 4 year old system, so, it looks like I'll be getting a new system with more memory and a bigger hard drive. But in the meantime, I'm working on a laptop with a 12 inch screen.

Ah well, I'm just about done with my part of the first paper, and I just got a load of stuff from my coauthor on the second one. So it'll be a busy week until Saturday.

One of these days I'll run across this Murphy guy, and we're gonna have some words.

Happy New Year

Here's wishing all of you a safe, happy, and prosperous New Year.

I've taken a few days off from working (a little blogging and a little studying for CFA but that's all). But tomorrow it's back on the hamster wheel.

Two of my revise and resubmits are coming back to me from my coauthors- both require a bit of work on my part, but not much. I also have two papers I'd like to have ready to go for the FMA submission deadline. One is with a former student and was part of her dissertation. We've been working on it for the last 3 months. The other was a pilot study another student and I did a while back with a small data set - we've now expanded the data set significantly, with a lot more analysis.

So, I'll be busy the next few weeks. It's good to get back in the saddle.