“Smart Beta” Investing

“Smart beta” strategies are a class of investment strategies based on company fundamentals.  In the FTS "Smart Beta Investing"project, students:

• Learn what these strategies are
• Construct and manage their own “smart beta” portfolio
• Compare its performance to a market index.

For background information, we refer you to this general article by the originators of these strategies, Research Affiliates, and to this academic paper describing the methodology.

The project uses

• Valuation Tutor and/or the Financial Statement Analysis Module to select companies based on fundamentals and to construct portfolio weights.
• The FTS Real Time Client for managing the portfolio.  The built in Equity Portfolio Rebalancer allows the automatic implementation of a large portfolio, as well as the rebalancing of the portfolio.

Building Practical and Analytical Skills

Analytical skills are critical in today’s world, specially in areas like finance and accounting.  Trading simulations can be very effective in building these skills for a large base of students.  They have the inherent motivational advantage of being competitive, and the simulations can show students how analysis gives you an advantage and also what trading means in today's markets. 

 

Both our trading systems accomplish this goal:

• Interactive trading simulations with price discovery
• In this trading simulation, students trade securities with the each other; they experience market impact, liquidity, real-time reactions to the strategies of others, and so on.  But they can also prepare strategies to help them, as summarized in the following PDF file: Student Case Preparation Manual. 
• The manual shows students how to model securities,value them in Excel, and use them to guide trading decisions.  They can use Excel formulas as well as VBA macros.  They can even develop automated trading algorithms and see how they algorithm competes against others.
• Beyond that, they can build automated trading strategies in Excel and see how their strategy performs against others. 
• Virtual trading simulations of real world securities
• Here, students trade “against the tape,” i.e. they trade securities at prices that come from real world exchanges, but these are paper trades so they have no market impact.  Our approach is summarized in these projects.
• The projects take them from simple calculations (e.g. how to calculate performance measures) to intermediate calculations (how to use Solver in Excel to create a diversified portfolio) to this comprehensive value investing project that combines stock selection strategies with financial statement analysis, and valuation.
• With derivatives, the analytics come into their own.  I particularly like this option hedging project, where you have to hedge the risk of a broad equity portfolio using only index options and futures (since you want to hedge the portfolio, not individual securities).  The technique they use (described in the project) is to use beta-weighted delta’s to manage risk. 
• This is one place where FTS shines.  Without the real time analytics, managing portfolio risk becomes a very difficult task.  Imagine calculating all the implied volatilities, the option hedge parameters, and the basis risk manually in Excel every few seconds!
• The algorithmic trading capability here is also very powerful.  It lets students develop real-time trading algorithms.  This lets them implement strategies that are close to impossible otherwise, such as optimal trade execution, basket or portfolio trades, and any type of dynamic trading exercise that requires continuous monitoring of markets.
•  This is where FTS differs from other simulations.  Some offer more stocks that can be traded, but without tools that let you develop trading strategies, you are left with what you could do in the 1990's. 
• Our instructor support and student feedback is second to none
• Instructors have complete access to the entire history and performance of every student at any time
• Student reports include detailed profit and loss reports on every trade as well as the usual measures of portfolio performance

Students can use tools such as our financial statement analysis module to build analytical depth,   One feature of this module is that it lets students work from first principles: they learn to be a true analyst, not just a consumer of other peoples research, by working with raw company filings and learning how to analyze and compare companies.  The software makes it easy to study several companies.  One really useful feature is that you can compare your calculations from those of financial data providers; this teaches you what assumptions they make, how they aggregate fields, and what they miss. 

WWW.OSFTS.COM

Please  visit our new website, which contains information on all of the FTS products

WWW.OSFTS.COM

TURNING UP THE HEAT

The FTS Heat Maps are a powerful way to visualize the performance of stocks based on different criteria and over different time periods. They are accessed through the Heat Maps tab and are currently available for the US Equity cases (and will be extended to other countries soon):

This picture shows the performance of stocks, over the past month, sorted by beta. So TRIP has the highest beta among the stocks in the case, SHLD has the second, and so on. If you move your mouse over a box, you will see the full name of the company and its beta. So by scrolling, you can quickly see how high beta stocks are performing relative to low beta stocks.

You can also view this by deciles. In decile analysis, we divide the data into ten parts: the top 10%, the next 10%, and so on. So Decile 1 in the picture below shows you the average performance of the 10% of stocks that have the highest beta within the set of stocks in the case. You can see that over the last 3 months, higher beta stocks have performed better than lower beta stocks:

You can change the timer period using the drop down; during the day, when markets are open, you can see today’s performance as well.

The tree on the left shows you the different sorting capabilities. For example, you could sort by sector. Then, you would see how stocks in sector are performing; they would be shown within that sector:

You can see that AES belongs to the “Basic Industries” sector. You can also see that the next sector (“Capital Goods”) starts with the company whose ticker is A; holding your mouse over the box tells you the sector name.

You can also see how sectors have performed by selecting Sector averages:

We have provided specific dimensions along which you sort or categorize stocks, and these are based both on practice and on what the academic research literature has identified as being potentially important ways to understand stock returns, for example the book value. The sector industry maps, over time, help with sector rotation strategies. Sorting by your position can show you how your long positions are performing relative to your short positions if you are following a long-short strategy.

Creating Real Time Simulations With Your Data Feed

As you know, FTS runs a variety of real time cases based around our teaching guide.  You may not know that if you have a data feed, you can run your own trading simulations using our real time system.  I realized that we had not written much about this capability just the other day, when we were helping a school with Reuter’s data feeds implement their own simulation.

There are quite a few trading rooms that subscribe to real time data from a variety of exchanges.  Even if the data vendor provides a mock trading platform, they are not set up for instructors.  For example, it can be hard to monitor student portfolios and calculate relative performance for a class, and these tools typically don’t provide a structured series of exercise to guide student learning.

The FTS RT Server solves this problem.  All the cases we run use this server.  You have to create the simulation, and this is done in an Excel workbook.  You specify the trading names and passwords, what can be traded, who can trade what, and so on.  We have also greatly simplified the connection to the data feed: all you have to do is bring the real time data into the Excel workbook.  This serves as a generic interface, and can handle quite a large amount of data; every data feed we have encountered in a trading room has a utility that downloads quotes into Excel. 

Students use the FTS Real Time Client to connect to the server, and then it works just as with the simulations we run.  Instructors have the support required, described, for example, here. 

If you are interested in this solution, please contact us; we will be happy to show you and your trading room staff how to create real time simulations with your own real time data feed.

Online Courses, Virtual Trading Rooms

I just returned from a conference where there was a panel discussion on university trading rooms. One point of discussion concerned online and distance education: how can students who are not on campus benefit from a trading room? The question becomes even more important given the large increase in online courses; according to the 2010 Sloan Survey of Online Education, online enrollment increased by 21% while overall enrollment increased by only 2%.

 

A physical trading room is expensive to build and maintain. For example, a 2001 paper by Alexander, Heck, and McElreath (http://www2.stetson.edu/fsr/abstracts/vol_10_num1_p209.pdf) estimated the initial cost to be about $100k. A recent paper by Norton and Kim (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2048506) puts a lower bound of $100k, going up to $500k.  More recent estimates by Rise Vision puts the construction cost of a 30-seat trading room at around $500k and an annual budget of about $75k, and an additional $100k if you have a dedicated lab manager.

The answer to the question is not easy. It obviously depends on why you built the room in the first place and how it is used in the curriculum. 

 

1. If the trading room is like a library, just a repository of information and data, then the answer is simple: find a way for online students to have access, i.e. build a virtual trading room. Ironically, virtual access is the most difficult with some of the most costly resources in trading rooms, like Bloomberg terminals.

2. If it is integrated into a wide range of courses, then you have no choice but to create a virtual environment. By “integrated” I mean that professors regularly use the resources in their courses, for example to conduct trading simulations, assign projects utilizing the data resources, and so on. In this case, you also have to provide a way for students to learn to use the resources without necessarily having access to a person for help.

 

In our case, we have been working on creating usable technology for virtual trading rooms for almost two decades. When I was at CMU, we built a trading room in the early 1990’s, called the FAST Lab. It had live data feeds, data servers, etc. We had about 25 seats. We learned several things very quickly.

First, having the data, such as real time quotes, is not useful unless you developed educational tools to do something with it. This led to what is now the FTS Real Time System. Our goal here was, and remains, providing a set of tools so students can learn concepts, their practical application, and their usefulness. It is not “teach trading” or “stock picking.” Our teaching guide therefore contains a series of projects that students can conduct that help them understand risk and return, portfolio diversification, duration and bond immunization, how to use the option Greeks to hedge, how to apply valuation models, and so on. It provides a tight integration of theory and practice.

 

Second, we learned a lot about complexity. Putting a student into a trading room with all the “latest whatever” is like putting a drivers ed student into a formula 1 racing car and asking them to drive it at 200 mph. You have to step them up to that. Hence our effort on online textbooks, application guides, and so on. Our Financial Statement Analysis module is the latest in this series, and provides a structured, step-by-step way for students to learn financial statement analysis and conduct fundamental analysis. You can combine it with a trading exercise, but that is not necessary. As part of the module, we also provide quick and easy access to financial reports, so students don’t have to spend hours downloading data and copying and pasting; Excel skills are still needed, but for developing higher level skills, not the mechanics of data collection.

 

Third, we learned about access. Students tend not to work around a 9-5 schedule, and their needs depend critically on when something is due. So a room with 25 seats is totally inadequate if 300 students in core investments courses have a project that is due, and they all want to work on it at 1 am. So you have to provide distributed access. You also can’t do many other things with a limited number of seats. For example, the FTS Interactive Market is a trading simulation where students trade with each other. While the trading is organized around cases that reinforce conceptual understanding, students experience many things, such as market impact and liquidity, that are difficult to teach in a textbook and that cannot be experienced by simulations where they trade against the tape. If you want to use this in a class of 45 students, a 25 set room is limiting. So again, our application is accessible anywhere there is an Internet connection.

 

Anyway, we had a physical trading room for a few years, and then moved entirely to a virtual trading room. This also meant that when we expanded distance education and wanted to use these resources (for example, in the computational finance classroom in New York City), it was easy to expand. 

 

When writing this, I recalled an article published by the AACSB in 2003 that discussed may of the issues that we continue to discuss today. You can find a copy at http://gtf.mcmaster.ca/reports/p22-27.pdf    Many of the issues remain the same as what we discussed almost a decade ago.

Announcing the Financial Statement Analysis Module

We are excited to announce our new module: the FTS Financial Statement Analysis Module.    It is a unique hands-on and interactive way to teach/learn ratio analysis.  In this post, I’ll discuss why we developed this module, discuss some of the advantages of the approach we have taken, and how it complements Valuation Tutor.

In my mind, the main difficulty students have with financial statement analysis, and that instructors have with teaching it, is that there is a big gap between theory and practice.  Using a simplified “textbook” example abstracts away from all of the details you encounter with real-world financial statements.  Using the actual statements of only one or two companies is helpful, but the knowledge may not be easily transferable to other companies.  And the more you focus on actual statements, the more you focus on details and perhaps lose sight of the bigger picture.  And this can be boring.

So the challenge was to come up with something that keeps the focus on the conceptual framework and lets you see how the details you encounter in real world financial statements fit into this framework in an exciting way.  At the same time, we wanted a manageable way for students to gain experience and develop judgment by working with a large set of companies if they wanted to.

The FSA module achieves these goals.

First, there is emphasis on practice.  It uses only real world financial statements.  You can use the filings of any of the over 4000 companies we currently cover.  These are (mainly US) companies that file using the SEC’s interactive data format.   The filings are updated every night. Filings from other countries are not as easily accessible; we have a data project underway where we are manually converting statements of Australian, European, and Canadian companies into an accessible format.

Second, there is a conceptual framework through which you analyze companies. The topics here are fairly standard (profitability analysis, risk analysis, operations, earnings quality, and price ratios).  What is unique is that you literally drag the information from the statements and drop it into the conceptual framework.  This way, you see first hand what is needed for what analysis, how companies present information, what items you have to aggregate or disaggregate, and so on.

To help with this, we also provide a Self-Assessment data set.  In this data set, we have gone through the analysis for several companies.  The software then guides you step-by-step though the process of analyzing any company in the data set.  You can ask for detailed help or less detailed help, even no help.  You can practice this repeatedly.  For example, you can start with detailed help, and repeat the process with less help.  Or you can do the opposite: start with no help, and then turn it on if you get stuck.  The ability to practice really helps in bridging the gap between theory and practice.

For individuals, the FSA module provides an intuitive and interactive way to learn the theory and the practice.  The self-assessment data set guides you through the steps so you are not left guessing whether you are doing something correctly.  You can work at your own pace, repeating an exercise as many times as you like.  By saving your work, you can add to your knowledge over time without having to restart every time.

For instructors, we have additional tools, described under the “Instructors” section of this site.  You can assign you own practice data for the students for a company you choose.  You can also “grade” assignments by checking how student solutions compare to yours: you assign a problem and a company; the students work through the exercise and send you their answers; the software quickly compares your solution to those of all the students.

Two features we would like to highlight are:
--- the self-assessment mode, that lets students work though examples at their own pace
--- the instructor grading support, that provides an immediate evaluation of student submissions to your solution

We provide examples for students to work through, but these can easily be constructed and assigned by an instructor.  We also have a test bank dataset that you can use.

The motivation for creating this module came from Valuation Tutor (VT).  We received a lot of very positive feedback on Valuation Tutor and its ability to graphically compare companies along different dimensions.  But  VT assumes that students know how to construct ratios and other performance measures from financial statements, and so focuses on interpretation.

The feedback pointed out the need for a step-by-step way for students to learn how to construct ratios, essentially a pre-requisite for VT.  The FSA module fills exactly this gap.   Please look at the descriptions and videos at www.fsamodule.com and don’t hesitate to contact us for more information