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
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.
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