Report to the Instructor

As we near the end of the semester, I thought I would describe some of the capability available to instructors for evaluating student activity and performance in our real time system.  As I have written elsewhere in this blog, our emphasis is not just on performance, it has much more to do with the practical implementation of principles of investments.  So the market value or the Sharpe ratio may only be a small part of what is needed for a full evaluation.

An instructor can obtain the complete history of every student at any time by selecting “Instructor Reports” from the Reports menu item:

 

 The resulting window gives you everything you could conceivably want (I have hidden the actual numbers in the next picture since these are real accounts):

 The “normal” reports include daily market values compared to the benchmark, as well as a variety of performance measures.  We also show the rank of each student along various dimensions as you can see.  Note the “Export to Excel” button: you can transfer any report into an Excel spreadsheet by clicking this button.

The “Download Trade Activity” button lets you see who traded on what date.  This is critical when you need a project to start on a given date and end on a given date; you can monitor whether students are implementing their positions or not.

Beyond that, you can download the entire trading history of any student (buttons on the right hand part of the image).  This allows you to check their project reports against their actual trades.  You can also generate reports for a specific student once you have downloaded their history:

A students history is, of course, also available to the student; the instructor can additionally access request this for every student.  You can see every trade, a detailed replay of the the history of any security, and, perhaps most useful, the P&L reports.  These come in two forms: a summary report and a detailed report per security.  The following pictures give you an idea:

The detailed report shows you exactly what happened and when by security.

Of course, students are always interested in overall performance.   Here is an example of that report:

Ease of Access: SEC XBRL Filings

The world of financial statement analysis has undergone a dramatic change with the SEC’s Interactive Data requirement.   Effective June 2011, essentially all publicly traded companies “will provide their financial statements to the Commission and on their corporate Web sites in interactive data format using the eXtensible Business Reporting Language (XBRL)."  The SEC's goal in adopting this requirement is "to provide financial statement information in a form that is intended to improve its usefulness to investors. In this format, financial statement information could be downloaded directly into spreadsheets, analyzed in a variety of ways using commercial off-the-shelf software, and used within investment models in other software formats." (Source: sec.gov, Final Rule: Interactive Data to Improve Financial Reporting.)

At FTS, we have been busy bringing the power of the interactive data to our users.  Valuation Tutor now gives you immediate access, with easy search capability, to any interactive filing for companies traded on the major exchanges.  As of the time of this writing, over 9000 10-K's, 10-Q's, and 20-F's were accessible, and we expect to add roughly 5000 filings every quarter.  We are also exploring ways to provide access to filings in other countries, since our system is used in over 20 countries.

Market Microstructure

There are several different methods by which orders are submitted, displayed, and matched on real world exchanges.  There are usually three phases in a trading day: the time period before the market opens, the trading day during which the market is open, and then the time after the market closes.  Sometimes, different methods are used in each of the phases.  For example, many exchanges have a pre-opening call auction but continuous trading when the market opens.   There are variations even within each type.  For example, some exchanges display orders in the pre-opening call auction, some don’t.  Some display the “virtual price” (the volume maximizing price given current orders) and some don’t.  Some even have a random closing time.

The FTS Interactive Markets handle a wide range of mechanisms.  For example, you can run a pre-opening call auction followed by a continuous double auction.  You can run order-driven and quote-driven markets.  You can have competing dealers, who can or cannot trade for their own account.  You can even have traders who have to trade out of a position before they can trade for their own account.  You can hide or display the limit order book.  You can run a pure specialist market.  You can also have an “upstairs market.”

All the variations are listed at the link Microstructure treatments (the second part shows how you modify our trading cases to run a variation).  We also have pre-set cases that run through the variations.  Over the years, we have developed many cases for specific instructors; let us know if you want to modify a case.

Fundamental Value

It has been a busy summer so far.  We have been working on taking Valuation Tutor (www.valuationtutor.com) to the next level.  We have now made it very easy to directly access all company filings that are in the SEC’s interactive data format.  Starting from now, most filings will be in this format, and Valuation Tutor now gives you a simple way to access all the filings (by ticker or company name).  It has a simple data collection utility that lets you extract the information you want; over time, we will be working toward making this even simpler, so stay tuned for further developments.  The data can then be used for financial statement analysis as well as (intrinsic) valuation.  The online textbook now has

Insider Trading Rings

Recent news stories about insider trading and the conviction of a hedge fund manager reminded me of a simulation we used to run that is just as relevant today.  This simulation is different from the ethics simulation I wrote about elsewhere in the blog. The ethics simulation focuses on the individual decision: when faced with the situation, will you make the ethical decision?  The insider trading simulation focuses on groupssharing insider information for mutual profit.

In the simulation, traders receive insider information about the prospects of a company.  Prior to trading, they are allowed to exchange messages; they can choose whom to communicate with, and if they receive a communication, they can choose to see it or not. They know who is sending them the communication.  After the communication, the stocks are traded in the FTS Interactive Markets; in these markets, the trader buy and sell the stocks from each other, and in the particular simulation, the trading mechanism was a double auction where everyone is a dealer, so they trade for their own account.  There were cash prizes for the best performers, and all the information they received from the system was correct (and so unambiguously useful). 

Meet Me On The Web

As the semester draws to a close at US universities, we receive many inquiries that require “interactive” meetings where we can either see someone else’s computer screen or where we can show them how to achieve some educational goal using our system.  We use GotoMeeting to conduct these meetings.  They tend to be of four types.  The first, and most common, is people who are thinking about adopting FTS in the future, and these meetings usually consist of an overview of the system and its application in different courses.  The second is from people using our system for experimental research.  The third, usually before the start of the semester, is from instructors asking how to integrate specific parts of the system in their upcoming course.  The fourth type is from existing users of the system asking “how can I do “ something related to the end of the semester, whether it is students asking how to create reports or instructors asking how to get particular information on student performance.

 

It struck me today, when a flurry of requests for meeting came in, that we actually do a lot of these and on a regular basis, specially at the beginning and end of each semester.  For example, I did a series of meetings in December and January for an instructor who wanted to design a specific type of market microstructure course; the course was taught this spring.  Other example is of meetings on experimental research

Greek Alphabet

No doubt about it, one area where a real-time simulation adds tremendous value is in the teaching of options.  Perhaps more than any other application of textbook finance, you really need analytics to make decisions and to appreciate the usefulness of the models.  

While there are many different exercises you can conduct, one of my favorites is one where students hedge the risk of a stock portfolio using index options, as described in our Hedging with Options real time project. We like using index options because we want to stress hedging on a portfolio-wide basis, not hedging individual securities by themselves (which would over-hedge the portfolio).

This introduces many concepts beyond basic option pricing and hedging: you have basis risk since you don’t have options on your portfolio, you need to understand correlations between the stocks (and whether these are stable), and of course you have to decide how to rebalance.  In this exercise, the equity positions don’t matter; the question is after you take the position, can you effectively hedge the price (and/or volatility) risk?  Variations of the project have options on smaller and larger equity indexes, and you really only need positions in one or two stocks to create an interesting problem.  As an extension, you could add index futures as well.  These types of projects also have the added advantage that to draw realistic conclusions on hedge performance, you only need a short period of time, say a week or two, so they fit in well into course timetables. 

 

In such a project, each student can use their own estimates of parameters (such as risk free rates and volatilities), though we provide default values.  All the analytics can also be calculated using implied volatilities.   In real time, you see both the individual and portfolio-level Greek parameters; aggregation is calculated using beta weightings, as done in practice and as explained in the project writeup.  There are three main analytic screens.  The first shows the Greeks at the portfolio level:

 

  

Caught Short

Short sales can be confusing for students in several ways.  First, they are unintuitive, perhaps because most of their experience in life consists of buying things or selling something they already have.   Second, the concept of a portfolio weight is not as clear as for long positions, and there are at least two ways to define them.  Third, the margin requirements of short sales can be counterintuitive: you are selling something but don’t get the money; in fact, you have to put up additional money.  If they don’t understand this third point, they can run out of money when trying to implement a strategy.

All this comes together in our Portfolio Diversification project where we explain the issues involved.  The project forces them to work through and understand the issues.  The real-time analytics they use to monitor their positions reinforce this, for example:

Report to the Instructor

As we near the end of the semester, I thought I would describe some of the capability available to instructors for evaluating student activity and performance in our real time system.  As I have written elsewhere in this blog, our emphasis is not just on performance, it has much more to do with the practical implementation of principles of investments.  So the market value or the Sharpe ratio may only be a small part of what is needed for a full evaluation.

An instructor can obtain the complete history of every student at any time by selecting “Instructor Reports” from the Reports menu item:

 

 The resulting window gives you everything you could conceivably want (I have hidden the actual numbers in the next picture since these are real accounts):

Ethical Dilemma

Can you “teach ethics?”  I don’t know.  But I do know that we can teach about the economic and social consequences of unethical behavior and challenge students to think through how they themselves would behave when faced with a dilemma.  At FTS, we have devised trading simulations that use experiential learning to focus on individual decisions involving unethical behavior, the relationship to social norms, and the impact of such behavior on social outcomes. 

 

We do this by letting students trade stocks in a specially designed market simulation.   The market setting provides a unique way for students to not only face ethical dilemmas but to go beyond that and evaluate the implications of unethical behavior by individuals and groups for society.  In the exercise, a subset of market participants is provided with early information on the earnings of a firm. They have the option of accepting the information or declining it. The information is always correct, and if they accept it, it can help them trade and potentially make far greater profits than if they declined it. It is known that the information was not supposed to be leaked; whether it is illegal to accept the information is left ambiguous, but it is fairly clear that accepting it would be considered unethical behavior by most.

Executive Session

One requirement that comes up frequently is the use of our real time system in executive education or other short-duration courses.  The problem is that the participants will only be there for a short while, perhaps only for a couple of hours, so a daily marking to market is not useful.   A second problem is that markets may be closed during the time of the course, say on a Saturday or in the evening.  So what do we do?

After Hours

Did you know that the NYSE conducts a pre-opening auction at 4 am?  And that on the four largest US exchanges (the third and fourth are BATS and DirectEdge) the trading day is basically 8 am to 8 pm?  The reason for bringing this up is that a student on our real time system executed a trade after hours at a price different from the 4 pm close, and asked about why this may be the case.  On FTS, you can trade outside “normal” market hours at whatever quotes are available at that time (unless an instructor requests otherwise). 

We believe allowing such trade has serious advantages.  These stem from two sources. 

Baskets of Eggs: Risk, Return and Diversification

Interactive tools can make really dry material, like portfolio theory, come alive. When I first started teaching, without such tools, I used to dread this part of the course. Now its fun, and here is what I do.

I start with historical stock data on a few stocks. If you don’t have access to current data, you can download it from financial web sites, like Yahoo finance. Step 1 is to show the students what recent returns have looked like, for stocks, for the index, and for some simple (e.g. equally weighted) portfolios using the Efficient Portfolio module. The following picture will give you an idea of what we discuss:

The example uses:

Mind the Gap

A quote attributed to Yogi Berra (and others) says:

"In theory there is no difference between theory and practice.

In practice there is."

The primary goal of interactive learning tools, like trading simulations, is to bridge this difference and let students learn not only what the concept is, but also to learn to apply it and then understand whether or not it  works in practice.

At FTS, we take a specific 3-step approach to this and provide the necessary tools.  The steps are:
1. THEORY: typically taught by the instructor and covered in textbooks
2. APPLICATION: simple calculations and application to historical or current data
3. PRACTICE: the application going forward in time and using the concept to make actual decisions.

The third step is where the gap is ultimately bridged: if you can understand how to use the tool then you have a real, practical understanding of the concept.  

As an example, take the concept of duration, taught in most introductory finance and investments courses.

Ticker, ticker on the wall

I was asked the other day whether a scrolling ticker was necessary for an educational trading room.  It got me thinking about how technology has changed, particularly how easy it is to get information (data and interpretations) compared to when tickers were first invented.  The first stock ticker was created in 1867; there is a web site www.stocktickercompany.com that describes the history of tickers.  According to the site, the last stock ticker was made in 1960.  In recent years, electronic tickers have replaced the old ticker tapes.  There are many companies in the electronic ticker business, just do Google search for “digital stock ticker” and you will see a range of (fairly similar) offerings

 

No question about it, tickers are attractive.  The question posed was: how important are they, specially since they tend to be one of the most expensive components of an educational trading room.   My response at the time was vague, I think mainly because I am not sure there is a right answer.  On the one hand, tickers help make the statement “we have a trading room” and if I had the budget, I would want one too.  On the other hand, they can only display a small amount of data at a time, and the data is usually delayed by 15 to 20 minutes.  You can get real time quotes for stocks on your cell phone, so delayed quotes on a digital ticker don’t really transmit useful information in today’s world.  In fact, showing delayed quotes contradicts one of the main selling points of a trading room, which is to give students access to the “same technology and resources” as real world trading floors.  No real world trading floor that I have been to has delayed data on their tickers.  In fact, many don’t have tickers at all; traders have access to real time data on their desktops and other devices.  You can check for yourself: point your browser to Google images and type in "Trading Floor" in the search box.  You will see lots of rooms with information displayed on mounted devices but surprisingly few scrolling tickers.  The same exercise on Bing images gives similar results.

 

So what’s the right answer?  I think it ultimately is a resource question.  What matters is the effective integration of trading room resources into a curriculum.  A ticker cannot be integrated, it has no direct pedagogical value.  It serves to attract attention to the trading room.  So if you are investing sufficiently in teaching resources and can afford a ticker, definitely get one.  And don't forget that like any other technology, they will need to be maintained and upgraded. Otherwise, you would get a lot more use from systems that provide real content, like additional Bloomberg terminals or a Morningstar subscription.

Using Trading Simulations: Practice What You Teach

What is the role of trading simulations in a finance curriculum?  We think the real value added comes from helping students undertstand how concepts and techniques are translated and applied in practice, particularly the application of analytical techniques in markets. 

Of course, there are easy solutions.  You can tell your students: go trade whatever you want and write a report.  I am not against these, I think they give students a chance to observe what is going on in real world financial markets.   But they do not supply the experience or knowledge that is needed in todays world and the world your students will face: the impact of technology and analytics in shaping financial markets.

Our view is that you must understand how analytical tools are applied in practice, otherwise you will simply be a stock picker.  FTS accomplishes this by having a series of exercises (we call them projects) that are reinforce the practical application of the theory of investments.  Our goal is to use the simulations give students a deeper understanding of this theory in a real world, dynamic context and to enhance their analytical and model building skills.

For example, our virtual portfolio management system (we call it the FTS Real Time System) has about 25 specific projects for this purpose.  The projects bring to life the concepts being taught in class.  The payoff can be very large.  An essential part of the exercises is to conduct an analysis and interpret the results, whether it is understanding how to construct a diversified portfolio or using portfolio-wide option hedge parameters to manage risk.   To help students bridge the gap between theory and practice, our real time trading system comes with built in information and analytics, consistent with what is taught.  The algorithmic trading capability is particularly exciting: it allows the implementation of trading strategies that require frequent monitoring of markets, so in fact any dynamic trading strategy.  This is where markets are today; such trading strategies would be close to impossible to implement in "manual" trading simulations.

The approach is similar in the FTS Interactive Markets, our simulation with price discover.  These are exciting trading simulations where students trade with each other and experience what it is like to be on a trading floor.  What they trade is controlled by a trading case; you can see the list of standard cases at this link.  The modeling and analytical development comes from preparing for the cases, as shown in the student manual: modeling cash flows, valuing securities, developing hedging strategies, and even developing automated trading algorithms if you want.  These simulations give them the experience of a live trading floor, where orders are submitted, prices are negotiated, activity is fast paced and competitive, and everyone (or their algorithms) react in real time to the actions of others.

The FTS Teaching Philosophy

I am often asked: what is the difference between FTS and other systems?  The essential difference is that we focus squarely on analytical and model building skills and their practical application.   We think that in today's world, with algorithms, data mining, high frequency trading, and so on, these skills are particularly important.  You can use other simulations, even some that let you trade many more securities, but without the analytics, they prepare you for the markets of 20 years ago, not today's or tomorrow's.

For example, consider a stock trading simulation where students manage a portfolio and trade at prices coming from real world exchanges.  The typical simulation out there lets you buy/sell any stock and you can see what happened to your portfolio.  This certainly provides a “practical” dimension.  But it does not go far enough in today's world.  In fact, in such systems, it is impossible to implement any strategy that requires either frequent monitoring of markets or rebalancing a large portfolio, and consequently, rules out any dynamic trading strategy or the use of analytics to guide investment and risk management decisions.  Any sophisticated investment strategy cannot be implemented.  Imagine the number of steps required to rebalance even a medium size equity portfolio, let alone any understanding of the cost of rebalancing.  Imagine hedging an equity portfolio with options without any analytical support. 
 
FTS provides that bridge.   We focus on bridging conceptual and analytical understanding to prepare students. for today's markets and the markets they will face  So we have a series of exercises and analytics built in to our virtual portfolio simulation (we call it the FTS Real Time System).  For example, students can learn how to apply mean variance efficiency and construct an efficient portfolio and learn about rebalancing in addition to reporting on what happened.  Our equity portfolio rebalancing analytics shows them the cash required to finance the trades and the transactions costs incurred, whether you trade 10 stocks or 1000.   They can even develop algorithmic trading strategies and see how they work (and at the same time build their modeling and Excel skills).  Besides reinforcing conceptual and practical knowledge, they also start to see how analytics and algorithms are such an integral, maybe even dominant, part of financial markets today.

The approach in the FTS Interactive Markets (markets with price discovery) is similar.  You can see the steps students follow in building their modeling and analytical skills in the student manual.  Here, the focus is on modeling cash flows, valuing securities, and, in a trading context, having a "plan B:" what to do if you cannot trade at the"theoretical" solution.  That's where students get a true understanding of how to effectively use their conceptual knowledge in a practical, experiential setting.  Going further, students can develop trading algorithms.  In fact, you can even have a trading  contest where student algorithms compete against each other.  This brings them closer to understanding financial markets today.  Perhaps even more importantly, they begin to appreciate how technology and analytics are shaping financial markets.

Note the difference between our two trading simulations: in the FTS Interactive Markets with price discovery, you trade with other students and all prices are endogenous.  So market impact is a key feature that is not a part of paper trading simulations.  We offer both because we believe it is just as important to experience real market dynamics, where everyone reacts to each other in real time, to paper trading simulations that are based on real world securities.  With FTS, you get both.

Another example is stock valuation: we like our students to perform a fundamental valuation from first principles, so they learn to be analysts as opposed to consumers of research reports. You can see an example of this approach in this Value Investing Project. This project also illustrates how students can dig deeper using the Financial Statement Analysis module. This module lets them learn how many of the aggregated reports (like those you would get from e.g. Morningstar or S&P) are created, including the assumptions these sources make. Again, they conduct an analysis from first principles, rather than simply reading calculated ratios and other quantities from a data source; reading other peoples analysis is a useful but easily replaceable skill.

To summarize, FTS focuses on three things: analysis, analysis, analysis, translated into analytics, and algorithms.  Students experience and begin to see how analytics and quantitative techniques are applied in portfolio management, and the role of quantitative trading, investment, portfolio and risk management, and high frequency trading in today's markets.  

Coming to the bottom line, there are three questions to ask

• Do you want a trading simulation with price discovery as well as a virtual portfolio system and supporting analytical modules for one low price?  If the answer is yes, FTS is your only choice
• Do you want students to learn how analytics and quantitative techniques are applied in portfolio management?  If the answer is yes, FTS is your only choice.
•  Do you want students to understand how algorithms and high frequency trading have completely changed the nature of financial markets?  If so, FTS is your only choice.

 

Trading Rooms Don’t Have to be White Elephants

In 1993, Carnegie Mellon University opened the first educational trading room.  It had live feeds and developed a curriculum called the FAST Program that integrated the resources of the trading room into the curriculum.  We estimate there are approximately 200 educational trading rooms today.  Some are enormously successful, and early examples are in this article from BizEd magazine: http://www.aacsb.edu/publications/archives/jan03/p22-27.pdf

If you have a trading room or finance lab, the question you have to ask is: how does your trading room prepare your students to succeed in financial markets today and in the future?  Today's financial markets are a far cry from 1993.  High frequency trading, program trading, and analytics based trading dominates markets (just Google these terms and you will see the statistics and trends).  If you are using a simulation system, ask yourself: does it have the analytical support and the algorithmic capabilities that help students understand today's markets?  Or the markets as they were in 1993? 

A second question concerns benefits of a trading room/finance lab.  It is unfortunately true that most trading rooms, despite their flashy tickers and high costs, end up being be fancy computer labs with minimal impact on student education or benefiting very limited numbers of students.  Further, as online courses, distance learning courses, and evening and weekend classes expand, relying on access to a centralized facility with limited access becomes problematic.  Even more, while they may have state-of-the-art data resources (Morningstar, Capital IQ, Bloomberg), they don't always have state-of-the-art trading simulations and analytical tools. 

Here are some examples of what you can do with FTS:

• You can create a live dealing room using the FTS Interactive Markets, where students trade with each other.  They experience what it is like to be in the middle of a live trading floor, where orders are submitted, prices are negotiated, activity is fast paced and competitive, and everyone reacts in real time to the actions of others.  They can learn to build simple (and complex!) support systems in Excel, and even learn how to build algorithmic trading strategies.  
• You can run a virtual portfolio simulation (the FTS Real Time System), where students manage a portfolio, and trades take place at prices that come from real world exchanges.   Unlike the interactive markets, here there is no market impact (the real world prices don't react to the student activity).   Unlike others, our system has projects and built in analytics so students can learn how they are applied.  One example is our option hedging project: you have to use index options to hedge the risk of an equity portfolio.  You can't use individual stock options (you shouldn't really hedge each stock separately anyway!).  Our system provides portfolio level analytics that make this exercise feasible.  It would be very cumbersome otherwise.   Beyond that, the algorithmic trading capability lets students develop dynamic trading strategies that are impossible in "manual" trading simulations. 
• Our modules provide ways for students to dig deeper.  The financial statement analysis module lets them understand how to study a company, and compare companies, from first principles.  They can do this at different levels: from the raw company filings or the simpler task of using aggregated statements provided by data vendors such as Morningstar and Compustat (to which many labs have a subscription).  The efficient portfolio module lets them explore statistical properties of portfolio returns as well as learn how mean-variance efficient portfolios are constructed.  Other modules deal with interest rate risk, options, and futures. 

Three questions to ask

o   Do you want a trading simulation with price discovery as well as a virtual portfolio system and supporting analytical modules for one low price?  If the answer is yes, FTS is your only choice.

o   Do you want students to learn how analytics and quantitative techniques are applied in portfolio management?  If the answer is yes, FTS is your only choice.

o   Do you want students to understand how algorithms and high frequency trading have completely changed the nature of financial markets?  If so, FTS is your only choice.