Financial Trading System

Experimental Research with FTS

2012-02-10T08:00:00.000-08:00

Experimental research is a big part of our history. In fact, the first version of the FTS Interactive Markets was developed in 1989 and 1990 for conducting experiments on information aggregation; the resulting paper came out in the Journal of Finance in 1991. I even have a picture of the old text-based interface, on an original PS2 computer:

Since then, the FTS Interactive Markets have been used in many other experiments by different researchers. Even today, we are helping several people with their new experiments; this includes setting up the trading parameters as well as software modifications to accommodate their needs.

Beyond market experiments, though, we also have a “generic” experimental platform for conducting all sorts of experiments easily; these include behavioral experiments, auctions, and so on. You can also use it to add non-market dimensions to a market; one example is adding a cheap-talk phase before a trading phase in a market, as inhttp://server1.tepper.cmu.edu/Seminars/docs/JobMarketPaper_0107_HongQu_CMU.pdf

The experimental system is fairly straightforward. I’ll use an auction as an example. You set up the experiment in an Excel workbook. One worksheet contains common information, such as instructions, sent to all subjects. Another worksheet contains information to be sent to individually, such as a private value or signal for the object being sold in an auction. This area also specifies what input is required from the subjects, such as a bid for the object being auctioned.

• You run the experimental server on your computer and connect it to your workbook.

• The subjects all connect to your computer using the client program.

• You send the common information

• You send the private information

• The subjects enter their responses (e.g. bids) during some period of time that you choose.

• When the time is up, you “grab” all their responses, calculate the outcomes in your

workbook (e.g. the price paid and who is allocated the object) and send this information

back to everyone.

The information flow described above can also be made continuous; in fact, you can mix and match

information that is updated constantly and that is updated manually. For example, if you are running a

sealed bid auction, you only need to retrieve bids at the end of each round. If you are running an

English auction, you may want to display the highest bid (or all bids) continuously.

The experimenter’s screen looks like this:

In the spreadsheet, you can set the colors of each cell, the text alignment, and you can see all the features in the screen shot. We have a standard template that you can modify to create a variety of different types of experiments quickly and without a lot of effort. If you have questions, please contact us, we love to talk about experimental research.

Portfolio Fundamentals

2012-01-09T19:34:00.000-08:00

An exciting new capability is the integration of the Real Time System with Valuation Tutor (VT in what follows). What it lets you do is conduct a fundamental analysis of your portfolio and also helps with stock selection. I will describe the latter capability in a more general posting about using VT for stock selection. Here, I will focus on the portfolio analysis.

Recall that in VT, you can analyze and compare companies along many dimensions. These include common size analysis, cost-volume profit analysis, efficiency ratios, as well as price ratios. Now, you can do the same for your stock portfolio. This lets you answer questions such as: what is the ROE of my portfolio? How does it compare to the stocks in my trading case? How does it compare to specific industries or sectors? And ROE is just one metric; you can compare your portfolio to any subset of stocks (in the VT dataset), sector and industry averages, and see exactly what are the fundamentals of your portfolio along any dimension covered by VT.

To use the capability, launch the FTS Real Time client and log in to one of our US Equity cases. I will use the simplest case, the 30 stock case to illustrate the connection. After you log in, click on the (new) Valuation Tutor tab:

When you transfer the data, VT creates an (artificial) stock called “RT Portfolio”
, abbreviated to RTPORT in the chart legends. It calculates and shows the weighted-average fundamentals of the portfolio. For example, the chart on the top right shows the sales of the stocks in the portfolio normalized by assets, and compares them to the stocks in which I have a position. If you put your mouse over a column, it will tell you the value. Right click on the chart area and you can see numeric values:

and then download the Current FTS Dataset:

Once you see the Valuation Tutor screen with the basic charts, go back to the Real Time Client and click “Send Data to VT”

Your portfolio will now be transferred to Valuation Tutor, and you will see a screen like this:

When you transfer the data, VT creates an (artificial) stock called “RT Portfolio”, abbreviated to RTPORT in the chart legends. It calculates and shows the weighted-average fundamentals of the portfolio. For example, the chart on the top right shows the sales of the stocks in the portfolio normalized by assets, and compares them to the stocks in which I have a position. If you put your mouse over a column, it will tell you the value. Right click on the chart area and you can see numeric values:

Going back to the beginning, lets look at the ROE of my portfolio (select DuPont Decomposition in Valuation Tutor):

You can see that the portfolio ROE is primarily due to the position in Boeing (BA). The chart at the bottom left shows that buying IBM would raise the ROE of my portfolio.

Beyond this, the full power of VT now applies to the portfolio: you can conduct financial statement analysis of your portfolio, compare it to any subset of stocks or sectors or industries, perform advanced comparisons, and so on, and assess the strengths and weaknesses of your position at a fundamental level.

Valuation Tutor

2012-01-07T18:42:00.000-08:00

We have had some exciting developments with Valuation Tutor. First, we have added a lot of visualization and comparison capabilities.

You can read about these on the Valuation Tutor blog:
Financial Statement Analysis- The Power of Visualization
Financial Statement Analysis- The Power to Compare
The capabilities are also described in the video at the top of this blog. Second, we have integrated Valuation Tutor with the FTS Real Time Client. I will soon post a description of this, together with an example of using Valuation Tutor for stock selection, so stay tuned!

Report to the Instructor

2011-10-28T06:17:00.000-07:00

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

2011-09-16T06:50:00.000-07:00

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.

Details of how you can access these filings is in the online textbook at www.valuationtutor.com. Chapter 2 shows not only how you can access numerical information, but also the complete filing with all the supplementary information. The data collector build into Valuation Tutor lets you collect data and paste it into a spreadsheet; you can collect data from different statements within a filing, across companies, across time, etc. and so create a custom dataset. The textbooks then goes on to discuss how you understand a companies business model and strategy, conduct financial statement analysis (business ratios and activity analysis), relative valuation, and also covers a variety of intrinsic value models (such as the dividend model, free cash flow to equity, residual income, abnormal earnings, and distressed firm valuation).

This is a new and exciting capability. Please let us know if you want to hold a web meeting so we can show you all the capabilities of Valuation Tutor.

Market Microstructure

2011-09-14T08:40:00.000-07:00

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

2011-07-12T09:28:00.000-07:00

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 a step-by-step reconciliation guide that shows you how business ratios are derived directly from the statements. Beyond that, we have a dataset where we have collected the relevant information for about 1500 companies so you and your students compare any subset of the companies along different dimensions, and also look for interesting patterns and anomalies. The textbook and software cover five valuation models, starting with the simple dividend model and moving on to the free cash flow to equity model, the residual income model, the abnormal earnings growth model, and also an option-based model for valuing distressed firms.

The Valuation Tutor extensions are in line with our teaching philosophy: learning practical skills in an experiential way and discovering the conceptual framework along the way. We have developed an extensive set of exercises (and solutions!) to simplify your use of Valuation Tutor.

We will be holding webinars on all the latest features, so stay tuned.

Insider Trading Rings

2011-05-16T20:41:00.000-07:00

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).

We wanted to explore two issues. The first was whether insider trading mattered: did the market behave significantly differently from one without insider trading? Second, how hard is it to detect such trading? To focus on the latter, we decided to give the tick-by-tick trading to "regulators" who did not participate in the simulation, and asked them to analyze the data. If they could "convict" a trader, the regulators would get the cash prize of the trader. We decided not to give the regulators the content of any message (so no “wiretaps”) but did tell them whether any two parties had communicated (so, for example, phone records).

Ironically, what actually happened illustrates the difference between theory and practice. In terms of our original focus, we found that the value of information was short lived, that information was reflected in prices much more quickly with insider trading, and that trying to detect patterns of insider trading purely from the data was difficult.

But there was a lot more. First, we found that there were various rings that formed; people could be part of multiple rings, and they were careful not to pass information from one ring to another. Second, false information was passed. Third, there was a lot more communication of information than we expected; we even found that some groups had created their own codes. Fourth, we found evidence of coordination in trading, for example, gradually bidding up a stock, even taking some initial losses. Finally, we were surprised by the amount of communication that took place; apparently the traders were pretty confident that the likelihood of getting caught was low!

Even more fascinating was the behavior of the regulators. They quickly discovered that discovering insider trading from the trading data only was difficult at best. So they adopted a different strategy. First, they went after the big winners. Second, the way they obtained convictions was by getting others to testify and using the data to provide documentary evidence of both the coordinated patterns of trade and the gain realized. What helped them was that even within a ring, some traders made a lot more money than others; matching the pattern of communication to the pattern of winnings turned out to be the key.

The simulation also laid the basis for putting in context a wealth of discussion about insider trading: the need for laws, market surveillance issues, relationship to market efficiency, and so on. If you want more information, please contact us; we will be happy to show you how to run a similar exercise.

Meet Me On The Web

2011-05-10T05:13:00.000-07:00

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 with our interactive markets and also with our (separate) experimental system; these meetings can be quite involved, and include going through details of experiment design and can require modifications of our system to accommodate the research needs. And of course there are ongoing periodic meetings with instructors as their courses progress.

Time zones have not really been a problem; the most difficult time zones are those 12 hours ahead of us, which makes late evening or early morning for one of the parties. And we enjoy the interaction. So if you have questions, please contact us; we will be happy to meet you on the web.

Greek Alphabet

2011-05-09T07:52:00.000-07:00

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 to understand the 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. 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 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. There are three main analytic screens. The first shows the Greeks at the portfolio level:

You can see the term “Implied” in parenthesis, this means that all the values are calculated using implied volatilities. You can also use user-defined volatilities:

You can enter you own estimates (and these are then stored by the system) by clicking on Parameters; entering the numbers is easy, you can enter them one by one or you can copy and paste en masse from an Excel spreadsheet.

You can also see everything for each individual option, and as shown, export everything into Excel:

A second analytic shows you the volatility exposure; here is a screen shot of the volatility exposure of the position, you can also see this for every option individually:

So you can see what happens if there is a “non-local” shift in volatility.

The third analytic is the Value at Risk, so you can discuss tail behavior. This is calculated using Monte Carlo simulation, and is shown at the portfolio level, by asset class, and by individual security. Here is an example with two stocks and one option:

What’s nice about these exercises is that it provides a very real way for students to see how the concepts and techniques are used. Its hard to do this any other way.

Caught Short

2011-05-05T06:23:00.000-07:00

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:

Of course, they also get to see much more; they get to compare their portfolio with two optimized portfolios as well as the naively diversified portfolio and the benchmark. Various performance measures are along the top (the Jensen measure is zero since I am using CAPM expected returns). All this is calculated in real time. Incidentally, every parameter (such as beta or volatility or the equity premium) can be changed by the student and the instructor.

Report to the Instructor

2011-05-02T08:14:00.000-07:00

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 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:

Ethical Dilemma

2011-04-27T11:20:00.000-07:00

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.

The key word above is “potentially.” The value of the information depends on several things. First, how useful the information itself is; this can range in the treatments from being very useful to being marginally useful. Second, it depends on how many people receive information and how many choose to accept it. What is interesting here is that an individual’s decision in each case depends on what they think others in the market are doing, and so in fact is affected by what they think the social norms are. For example, their behavior is typically different “if everyone is doing it” from when they think they may be the only person receiving the information. So the outcome will be endogenous to the group at hand, depending both on their own ethical propensities and their view of the propensity of others (in other words what they think the norm is). Third, there is the market itself: the group behavior can have a strong effect on the market itself. In the FTS Markets, all the trading activity is done by the market participants themselves. In the current context, several outcomes are possible all of which affect the profitability of information. On one extreme, it may be a very active market where you can take advantage of your information. Or it may be the case that the information gets priced into the market quickly, and you only have a brief advantage. On the other extreme, it may be the case that the market collapses: no one wants to trade because they think that the presence of insiders makes it unfair or stacked against them. The actual market outcome is clearly influenced by the ethical propensity of the group as well as their perception; it could be the case that no one engages in unethical behavior yet the market fails because everyone thinks that most people are unethical.

The exercise lets students experience a real life ethical situation which is otherwise very difficult to do in the classroom.

Most of the main points become clear to the participants fairly quickly. This is helped enormously by the fact that they are live participant s in the exercise, and are constantly evaluating both their own behavior and that of the group. The participants face a moral dilemma, and they have to make a decision. Because they make the decision, and the decision directly affects others, whatever decision they make, they will unquestionably think about why they made this decision, and become keenly aware of the consequences of the decision. But it is not an individual decision taken in the abstract; it is influenced by what others do and what you think they may do, and it has a direct consequence on the entire group. This

transforms the discussion of ethics from an abstract textbook world into a dynamic real life situation. Follow on cases allow participants to communicate information to each other, make true or misleading public disclosures and other features that introduce more gray areas and more ethical dilemmas into the case. Following the trading, the discussion can focus on a variety of issues beyond the specifics of what happened including both social and normative aspects. One that we think is important is the impact on social outcomes; in the market setting of this exercise, one outcome is the liquidity in the market. If there is very little trading, then this has the social consequences of undeveloped capital markets, inability of companies to raise capital, with corresponding impact on growth, the standard of living, and so on. There are noneconomic outcomes as well that relate easily to participants experience, such as their faith and trust in institutions.

If you are interested in incorporating this exercise, let us know; we will guide you on how to set up different treatments and tell you what we have experienced in running this exercise.

Executive Session

2011-04-25T08:37:00.000-07:00

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?

The FTS Real Time System allows for what we call “session trading.” The moderator of the session can start the session, specify the mark-to-market frequency, and monitor performance in two ways: in real time and also at every mark-to-market. A sample screen is shown below, and if you are interested in using this feature, please contact us and we can go through the (relatively simple) steps involved.

As for trading when markets are closed, we can either replay history or we can simulate prices based on a model. We have two or three models that we have used, and all produce fairly realistic price paths. For derivatives, we use different pricing models so that the underlying and the derivative prices are in sync. This has been fairly successful so far and helps create an active real-time trading environment to handle these special circumstances.

After Hours

2011-04-18T06:29:00.000-07:00

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.
First, as we all know, news frequently comes out after 4 pm and before 9:30 am. Economic indicators that are released at 8:30 am include the weekly jobless claims, the monthly GDP report, PPI and CPI, durable goods, retail sales, and so on. Earnings announcements are almost always made before or after normal trading hours. So having to wait until the next day to execute a trade, besides being unrealistic, can be a serious disadvantage. Second, it prevents reaction to news in other countries. For example, in out popular Global Equities trading case, you manage a portfolio of stocks in Asia, Europe, and the US. Of course, different markets are open at different times, but since we allow 24 hour trading, it allows you to reposition your portfolio without having to wait, whether you are reacting to company specific events or global events. Let us know what you think.

Baskets of Eggs: Risk, Return and Diversification

2011-04-06T08:31:00.000-07:00

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:
two years of weekly data on 30 large cap US stocks. You can type in or copy/paste portfolio weights. The histogram above is for the equally weighted portfolio. We discuss how returns are measured, that volatility is commonly used as a measure of risk, and talk about skewness and fat tails. The students use their own data and analyze stocks they want, I just explain the concepts. The green line is a normal distribution for comparison and the JB statistic is the Jarque-Bera test for normality. The fat tails discussion lets us talk about Value at Risk. The discussion is mainly conceptual; for advanced students, you can go into formulas. The problem sets on this part depend on the level at which you are teaching, ranging from graphical conclusions only to having students reproduce the calculations on their own in a spreadsheet. Even at the basic level, I require some Excel calculations for one or two stocks. More on this below.

The next step is diversification. The “Portfolios” button lets you calculate frontiers and lots of other things. I have circled the parts I commonly use.

The yellow “curve” is the efficient frontier with short sales permitted (you can turn off short sales). The black dot corresponds to the portfolio weights shown. If you click on the frontier, it calculates the corresponding weights. The “Plot Securities” button shows you where each stock lies, and it is easy to illustrate that the frontier does a lot better than any individual stocks. Again, you can require verification of the calculations for a subset of stocks.

The Backtest button tests historical performance; you can use a constant mix (i.e. the portfolio weights are always the same) or you can set the target return and recompute the weights every period. The covariance matrix is recalculated and the performance is measured one-period ahead, out of sample. An interesting comparison here is to look at constant mix portfolios, some that correspond to high returns and some that correspond to low returns. It provides intuition on the volatility of high risk and low risk portfolios.

Having illustrated the basic ideas and how they worked historically, Step 2 is to take the model for a test drive. This is done with a real time trading simulation. In this simulation (typically done with 30 stocks, to keep the problem manageable), the students have to calculate an optimal portfolio in Excel, using Solver. This has the additional advantage of teaching them a transferable skill. They have to decide what constraints to impose, and then decide how to rebalance. This is all going forward in time. The FTS Real Time System has a set of analytics designed exactly around this. You can find details in the Portfolio Diversification project, so I won’t go into the details here, except to show you the analytics available:

The first two calculate optimal portfolios based on the single index model, so students can see in real time how these perform relative to equally weighted portfolios as well as their own portfolio. They can set their own expected returns or use CAPM. The covariances and returns allows them to copy the covariance matrix; again, they can specify their own if they want. The portfolio tracking lets them see how far they are from a specified portfolio and calculates the required rebalancing. The backtesting capability is the same as described above.

At the end of all of this exercise, the report produced is not on how much m

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oney you made but on the decisions you made: the portfolio you selected, the constraints you imposed, the rebalancing decisions, and of course the performance. Some instructors have students manage two portfolios, a low risk and a high risk one. The exercise is typically run for about as month. The amount of work required by the students can be tailored; for example, if you ask them to buy and hold, there is very little work except at the beginning and end. If you require a daily rebalancing, that is more work. But about two weeks of class time with a month long exercise bring all this material to life in an intuitive, step-by-step fashion.

In future posts, I’ll describe similar exercises, one on options and one on equity valuation.

Mind the Gap

2011-04-05T11:07:00.000-07:00

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.
In step 1, you would cover the concepts (Macaulay duration, modified duration, dollar duration) and explain how these measure the sensitivity of a bond's value to its yield. These are described in our online textbook at www.bondtutor.com.

Our approach to step 2 is covered in our modules. These modules teach the use of duration (and convexity) in portfolio selection and interest rate risk management. One module is a visual and interactive presentation of the concepts. The concepts are explained and an interactive calculator lets you see the interest rate exposure as you change your position:

A second module does a historical backtest (for any so you can see how it would have performed; this picture shows you the tracking error for a specific strategy:

In step 3, you manage a bond portfolio going forward in time, so you do not know what will happen to interest rates. This is accomplished with our real time trading project. The built in analytics give you real time updates of the duration and convexity, what you have to decide is what duration exposure to take, how to rebalance, and so on. The analytics are shown below for a simple case with four US Treasuries:

Ticker, ticker on the wall

2011-03-29T19:57:00.000-07:00

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.

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. Otherwise, you would get a lot more use from systems that provide real content, like additional Bloomberg terminals.

Using Trading Simulations: Practice What You Teach

2011-03-15T13:22:00.000-07:00

Really integrating simulations into a finance curriculum, whether at the undergraduate or graduate level, requires quite a bit of effort. Of course, there are easy solutions. You can tell your students: go trade whatever you want and write a report. There are cheap, even free, solutions for that and they require minimal effort from the instructor. But there is no way to know if anyone actually learned anything. I am not against these, I think they give students a chance to think about what is going on in real world financial markets. Ironically, they do not address the basic issue: the integration of theory and practice because there is basically no link between what is taught and the trading exercise.

As with any endeavor, doing it right requires effort, in this case by instructors. There have to be measurable learning outcomes: whether the student mastered the concept being taught and its application. FTS accomplishes this by having a series of exercises (we call them projects) that are based on what is typically taught in courses. We are not "training traders" in the classroom and are don't really believe in a "trading room curriculum." We believe in the theory of investments and our goal is to use the simulations give students a deeper understanding of this theory in a real world, dynamic context. The teaching guide to our real time system has about 25 specific projects for this purpose. Students go through these exercises in lock-step as they do with everything else being taught in the course. and the projects bring to life the concepts being taught in class. As projects are completed, instructors can judge learning just as they do with assignments and exams. The amount of effort required on the part of instructors is actually much less than it initially appears; you only have to do the exercises yourself.

The FTS Teaching Philosophy

2011-03-03T07:52:00.000-08:00

I am often asked: what is the difference between FTS and other systems? I think the essential difference is that we focus squarely on the practical application of concepts that are taught, and this guides the development of our products as well. For example, consider a stock trading simulation where students manage a portfolio and trade at prices coming from exchanges. The typical simulation out there lets you buy/sell any stock and you can see what happened to your portfolio. In my view, this is a cheap way out for the professor; they provide a “practical” dimension to the course without being involved in the trading and also leave the student to figure out how what is taught in the curriculum applies in practice.

The FTS approach is quite different. I like to see the application of what is taught in the course. So we have a series of exercises and analytics built in to the system: for example, students can learn how to apply mean variance efficiency to create an efficient portfolio and learn about rebalancing in addition to reporting on what happened. This does put a bit more work on the professor since you have be able to do the practical part as well, but it also integrates what is commonly taught with the simulation. Another example is stock valuation: we like our students to perform a fundamental valuation so they know why they may want to buy or not buy a stock. Our teaching exercise and the built in analytical support system lets the students learn valuation techniques by working through financial statements, and also see the market consequences of their decisions. In this exercise, I prefer that everyone focus on a few stocks; otherwise there is no way for me to follow their analysis. In fact, combining valuation with the stock simulation is so popular that we developed Valuation Tutor, www.valuationtutor.com, which is a complete textbook, software, and dataset package that lets students work through financial statement analysis and valuation techniques and compare ratios and calculated values across a large set of companies.

The bottom line is that we focus on teaching the “how and why” of the investment decision, not simply the “what happened” part. The teaching guide to our real time simulation now has over 25 projects and exercises that link directly to concepts and techniques taught in investments, corporate finance, options and futures, risk management, and accounting valuation courses. You can see the contents at http://www.ftsmodules.com/public/modules/ftsrt/textbook/rt_contents_nolink.htm

Trading Rooms Don’t Have to be White Elephants

2011-03-03T07:49:00.000-08:00

In 1994, 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

But 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 limited numbers of students. I have seen really fancy trading rooms that are empty most of the time. Some are used solely to run a student investment fund which is enormously beneficial but involves an extremely small group of students. Others are used for special “trading courses,” with only one or two sections using the resources in a semester. In many cases, much more is spent on the look of the room than on resources to help anyone use it.

In our experience, there are three important factors that determine the success of a trading room. The first and foremost is teaching support. This requires instructional materials that can be used by professors and that integrate what they normally teach with trading room resources. The second is technology support provided by a lab manager and/or a set of well trained teaching assistants. Without these two most professors are at a loss on how to use the room. The third factor is faculty involvement. If I already teach a successful course and use “real world” cases, why do I need to change?

There are other factors as well. These include the traditional academic “turf wars” as well as a lack of incentives to develop an integrated curriculum. Further, as online courses, distance learning courses, and evening and weekend classes expand, access to a centralized facility becomes problematic.

Finally, if you are thinking about investing in a trading room, don’t let some vendor sell you a bill of goods. Talk to professors who have had success in teaching this way, make sure your faculty understands what is involved, and make sure you have a plan for large numbers of students to benefit. If you have an underutilized room, talk to those who have overcome some of the roadblocks. We have lots of examples of successful trading rooms, and can put you in touch with them.