Monroe Community College Customer Experience & Moment of Truth Discussion

User Generated

qnivq29

Business Finance

Monroe Community College

Description

1. I need to write 1 page on:

Discussing a personal moment of truth. In your response, please not go into a lot of detail as to what a MOT is.....focus on your personal experience.

2. Please comment on the writing below in 300 words.

I recently had a customer experience including several moments of truth with IRS and the company Sprintax. Indeed, most of you already know Sprintax as Pace University's recommended partner to help students file their tax returns. So here's the little background: I filed my tax returns document with the help of Sprintax in Spring and mailed them to IRS way before the deadline. After a few months of seeing all my friends receiving their refunds, I got worried as I hadn't received anything yet.

MOT 1: I called IRS hoping to talk to a human advisor, but ended up talking to an IVR (interactive voice response) robot who tells me that the information I gave them on request (name, social security number, address, expected refund amount) are not enough to track my refunds. Ultimately, the AI concludes by advising me to visit a special page on IRS's website to track my refund, and terminates the call. After this first MOT I was a little disappointed that I wasn't given the opportunity to talk to a real person and my perception of IRS as being a high governmental institution falls down considerably, along with my admiration and respect for the American bureaucracy.

MOT 2: As advised, I visit IRS's website and try to track my refund. However, after providing, once again, my name, SSN, address, and expected refund amount, the website shows me an error message saying that my refund cannot be tracked, and that this refund probably doesn't even exist! After this second MOT, I panicked, knowing that I expected an important amount of $ and that I followed Sprintax procedures properly when filing and mailing my tax returns. Needless to say that my esteem of IRS dropped even lower after this second moment of truth.

MOT 3: Panicked, I review my tax return documents and attach them to a desperate email for a Sprintax representative, hoping someone outside of IRS could help me. After only a few hours, Eva answered my email with some questions to help her find a way to track my refunds. She was very kind, quick, and professional. After a few emails, she was able to tell me that my New York State refund was being re-directed from my hold address to my new address and I received it just a few days later (thanks you Eva!). Regarding my Federal tax return, Eva was able to tell me that my documents were not in IRS system yet as they haven't finished to review all the returns they received and that it could take another month or so to receive it. Ever since that day, Eva emailed me once a week to ask me if I received my federal tax refund. I have not, but I really appreciate how committed she is to help me track my refunds! After this last MOT I can tell that I respect and trust Sprintax way more than IRS. Indeed, Sprintax provided a curated, personalized customer experience for me and helped me better, and in a more qualitative way than IRS ever did.

Unformatted Attachment Preview

Counterpoint: Groupon is not a success • by Erin Griffith (http://fortune.com/2015/03/20/groupon-success/) The company must overcome a bad business model. Earlier this year, my esteemed colleague Dan Primack argued that Groupon GRPN 1.31% , the daily deals company which is largely viewed as a failure, should not be viewed as such. It was a great contrarian argument, except that it was wrong. Dan’s argument boiled down to the following points, which I’ll address in order: 1.) Groupon is not a failure because it has a $4.9 billion market cap, which is more than it was worth as a private company. (Its market cap has risen to $5.3 billion since his story.) 2.) Groupon is not a failure because it has steadily grown since its IPO, with plenty of cash on hand and no debt, signals of a healthy company. 3.) Groupon was a victim of high expectations, and it’s not the company’s fault when it failed to live up to them. $5 billion company Indeed, Groupon is worth more than it was ever valued as a private company. But barely. Groupon’s last round of private funding valued it at $4.75 billion. That was in 2010. When Dan published his story, Groupon was worth $4.9 billion. A 3% increase is not much of a return for investors in five years, especially for a high-growth startup. What’s worse, Groupon could have been worth more. In 2010, Google GOOG 0.80% offered to acquire the company for $6 billion. After rejecting that deal, then-CEO Andrew Mason declared, “Like, okay, we’re the best company in the world.” Today it’s clear that not many people believe Groupon is the best company in the world, or that it’s worth $6 billion. But the real reason a $5 billion valuation does not make Groupon a success is because anyone who bought into Groupon’s growth story at IPO got burned. Groupon went public at a valuation of $13 billion, trading up to $19.5 billion on its first day. Shortly after, the stock price cratered, and it has been worth half of its IPO valuation (or less) ever since. Even insiders got burned, since Groupon’s shares collapsed before the 90-day lock-up period was over, meaning they couldn’t sell while their stock lost more than half of its value. Any employee that exercised shares in the IPO likely owed more in taxes than their stock was worth. Anyone who bought low has yet to see much growth either. Over the last three years, Groupon’s stock has ended up relatively flat. It’s hard to call that a success. Growth I’m as surprised as Dan that people still spend $7.6 billion a year with Groupon. (That’s gross sales—the company’s annual revenue was $3.2 billion last year.) Groupon is growing: It grew revenue by 24% last year. Revenue is expected to grow 11% this year. But Groupon has reported a net income loss for each year it’s been public, including last year, when it lost $73 million. That’s not likely to change, because Groupon is a company that has to overcome a bad business model. By now we know the daily deals business model is a novelty. Even Andrew Mason (who was ousted in 2013) admits the model stinks. Last month he told the Associated Press that Groupon was a “stupid, boring idea that just happened to resonate.” Groupon’s revenue from daily deals has been relatively flat since 2011. To diversify, Groupon launched “Groupon Goods,” where it sells things like iPhones and jelly beans at a discount. This business has grown to represent the majority of Groupon’s income, but the margins are significantly smaller: 88% for daily deals versus 20% for goods. The problem with both of Groupon’s businesses are the barriers to entry, or lack thereof. With daily deals, anyone could buy a “build your own Groupon” software package (from a company called Groupon Clone, no less) and start selling coupons with cute emails. In the height of Groupon-mania, many did just that, driving Groupon’s customer acquisition costs sky-high and forcing Groupon on an aggressive acquisition spree to take out regional competitors. At the height of the boom there were hundreds of daily deals startups. Groupon bought more than 30 of them. Now Amazon is moving in with its “Amazon Local” competitor. And Groupon Goods is already competing with Amazon AMZN 0.58% , and every other online discounter. To recap: flat growth in Groupon’s core business and some growth in Groupon’s low-margin business. This is why Groupon’s stock has been uninspired for the past three years. Today, 14 analysts rate Groupon as a “Hold,” and only nine rate it “Buy” or “Strong Buy.” High Expectations Dan believes Groupon was a victim of media hype. I disagree. While no company can fully control the media’s frenzied hype machine, Groupon poured fuel onto the fire. For example, the aforementioned “greatest company in the world” line. Others examples include appearing on the cover of Forbes with the headline “The fastest growing company ever” and a talk Mason gave on how to “get super rich.” Mason did not tamp down expectations after a report that its IPO would be worth $30 billion. Rather, he wrote detailed memo full of hype and promise about Groupon’s future during the company’s quiet period, which was leaked (some believe on purpose) and got him in trouble with the SEC. Groupon was on such a crazy train ride that it didn’t have enough time to prove its model actually worked before going public. This is why it ran into accounting issues like not anticipating a high refund rate on big-ticket travel bookings, which caused it to restate its earnings and sent its shares into a downward spiral. Some reports note that many of Groupon’s investors and managers though it was too early for Groupon to go public. After talk of a $30 billion IPO, Groupon’s brand is tainted so badly that it will be very difficult to recover. It doesn’t matter that Groupon is growing (modestly) or able to do $3.2 billion in annual revenue. Is Groupon a company that talented people want to work for? Is Groupon a company exciting startups want to sell themselves to? I would argue no to each. The hype factor, which again, was fueled by the company and its investors just as much as the press, is the reason I must address Dan’s headline, which implores: guys, come on, let’s all stop laughing at Groupon. I see no reason not to think of Groupon when I need a good chuckle, if only for the following seven reasons: 1.) Mason’s cheeky resignation letter (“I was fired today. If you’re wondering why… you haven’t been paying attention”). Actually, laugh at any of Mason’s goofball antics. 2.) Mason’s business rock album, “Hardly Working,” which is funny on purpose. 3.) This memo, which trashes the financial press for being critical of Groupon’s numerous accounting errors and challenges. 4.) This time Groupon attacked a critical reporter for her “nastygram.” 5.) This time Groupon thought the Earth was 400 years old. 6.) I’m even able to laugh at the fact that, in order to access Groupon’s investor relations page, I had to sign up for its daily deals blasts again, and the first deal I got was for a yoga studio I frequent. I had no choice but to buy the coupon (it was a good deal!), thus indirectly supporting my opponent’s argument. Dan had this to say: 7.) Lastly, after a few more weeks of irrelevant deals in my inbox, I got an offer for discount PajamaJeans, which are always hilarious. Counterpoint: Groupon is not a success • by Erin Griffith (http://fortune.com/2015/03/20/groupon-success/) The company must overcome a bad business model. Earlier this year, my esteemed colleague Dan Primack argued that Groupon GRPN 1.31% , the daily deals company which is largely viewed as a failure, should not be viewed as such. It was a great contrarian argument, except that it was wrong. Dan’s argument boiled down to the following points, which I’ll address in order: 1.) Groupon is not a failure because it has a $4.9 billion market cap, which is more than it was worth as a private company. (Its market cap has risen to $5.3 billion since his story.) 2.) Groupon is not a failure because it has steadily grown since its IPO, with plenty of cash on hand and no debt, signals of a healthy company. 3.) Groupon was a victim of high expectations, and it’s not the company’s fault when it failed to live up to them. $5 billion company Indeed, Groupon is worth more than it was ever valued as a private company. But barely. Groupon’s last round of private funding valued it at $4.75 billion. That was in 2010. When Dan published his story, Groupon was worth $4.9 billion. A 3% increase is not much of a return for investors in five years, especially for a high-growth startup. What’s worse, Groupon could have been worth more. In 2010, Google GOOG 0.80% offered to acquire the company for $6 billion. After rejecting that deal, then-CEO Andrew Mason declared, “Like, okay, we’re the best company in the world.” Today it’s clear that not many people believe Groupon is the best company in the world, or that it’s worth $6 billion. But the real reason a $5 billion valuation does not make Groupon a success is because anyone who bought into Groupon’s growth story at IPO got burned. Groupon went public at a valuation of $13 billion, trading up to $19.5 billion on its first day. Shortly after, the stock price cratered, and it has been worth half of its IPO valuation (or less) ever since. Even insiders got burned, since Groupon’s shares collapsed before the 90-day lock-up period was over, meaning they couldn’t sell while their stock lost more than half of its value. Any employee that exercised shares in the IPO likely owed more in taxes than their stock was worth. Anyone who bought low has yet to see much growth either. Over the last three years, Groupon’s stock has ended up relatively flat. It’s hard to call that a success. Growth I’m as surprised as Dan that people still spend $7.6 billion a year with Groupon. (That’s gross sales—the company’s annual revenue was $3.2 billion last year.) Groupon is growing: It grew revenue by 24% last year. Revenue is expected to grow 11% this year. But Groupon has reported a net income loss for each year it’s been public, including last year, when it lost $73 million. That’s not likely to change, because Groupon is a company that has to overcome a bad business model. By now we know the daily deals business model is a novelty. Even Andrew Mason (who was ousted in 2013) admits the model stinks. Last month he told the Associated Press that Groupon was a “stupid, boring idea that just happened to resonate.” Groupon’s revenue from daily deals has been relatively flat since 2011. To diversify, Groupon launched “Groupon Goods,” where it sells things like iPhones and jelly beans at a discount. This business has grown to represent the majority of Groupon’s income, but the margins are significantly smaller: 88% for daily deals versus 20% for goods. The problem with both of Groupon’s businesses are the barriers to entry, or lack thereof. With daily deals, anyone could buy a “build your own Groupon” software package (from a company called Groupon Clone, no less) and start selling coupons with cute emails. In the height of Groupon-mania, many did just that, driving Groupon’s customer acquisition costs sky-high and forcing Groupon on an aggressive acquisition spree to take out regional competitors. At the height of the boom there were hundreds of daily deals startups. Groupon bought more than 30 of them. Now Amazon is moving in with its “Amazon Local” competitor. And Groupon Goods is already competing with Amazon AMZN 0.58% , and every other online discounter. To recap: flat growth in Groupon’s core business and some growth in Groupon’s low-margin business. This is why Groupon’s stock has been uninspired for the past three years. Today, 14 analysts rate Groupon as a “Hold,” and only nine rate it “Buy” or “Strong Buy.” High Expectations Dan believes Groupon was a victim of media hype. I disagree. While no company can fully control the media’s frenzied hype machine, Groupon poured fuel onto the fire. For example, the aforementioned “greatest company in the world” line. Others examples include appearing on the cover of Forbes with the headline “The fastest growing company ever” and a talk Mason gave on how to “get super rich.” Mason did not tamp down expectations after a report that its IPO would be worth $30 billion. Rather, he wrote detailed memo full of hype and promise about Groupon’s future during the company’s quiet period, which was leaked (some believe on purpose) and got him in trouble with the SEC. Groupon was on such a crazy train ride that it didn’t have enough time to prove its model actually worked before going public. This is why it ran into accounting issues like not anticipating a high refund rate on big-ticket travel bookings, which caused it to restate its earnings and sent its shares into a downward spiral. Some reports note that many of Groupon’s investors and managers though it was too early for Groupon to go public. After talk of a $30 billion IPO, Groupon’s brand is tainted so badly that it will be very difficult to recover. It doesn’t matter that Groupon is growing (modestly) or able to do $3.2 billion in annual revenue. Is Groupon a company that talented people want to work for? Is Groupon a company exciting startups want to sell themselves to? I would argue no to each. The hype factor, which again, was fueled by the company and its investors just as much as the press, is the reason I must address Dan’s headline, which implores: guys, come on, let’s all stop laughing at Groupon. I see no reason not to think of Groupon when I need a good chuckle, if only for the following seven reasons: 1.) Mason’s cheeky resignation letter (“I was fired today. If you’re wondering why… you haven’t been paying attention”). Actually, laugh at any of Mason’s goofball antics. 2.) Mason’s business rock album, “Hardly Working,” which is funny on purpose. 3.) This memo, which trashes the financial press for being critical of Groupon’s numerous accounting errors and challenges. 4.) This time Groupon attacked a critical reporter for her “nastygram.” 5.) This time Groupon thought the Earth was 400 years old. 6.) I’m even able to laugh at the fact that, in order to access Groupon’s investor relations page, I had to sign up for its daily deals blasts again, and the first deal I got was for a yoga studio I frequent. I had no choice but to buy the coupon (it was a good deal!), thus indirectly supporting my opponent’s argument. Dan had this to say: 7.) Lastly, after a few more weeks of irrelevant deals in my inbox, I got an offer for discount PajamaJeans, which are always hilarious. This estimate is even lower, but the range is even greater (with fewer observations), but again a big overlap with the other beta estimate ranges. So the conclusion from the historical regression estimates is that the beta (for the past) is around 1 to 1.5, with a fair degree of stability. However, we'd still have to figure out if the future is likely to be similar to the past. If we believe the Groupon business is going to remain "techy" in the future, we'd stick with this "high" beta estimate. On the other hand, if we believe the Groupon coupon business is likely to be countercyclical in the future, we would go with a lower beta estimate. Ultimately, we see that the final estimate still depends on our evaluation of Groupon's business. Data helps us come up with estimates, but in the final analysis, we have to apply economic analysis and our own common sense.I could simply have computed the ratio of the Covariance between the returns on Groupon and the S&P to the variance of S&P returns and I would have got the same answer much more easily. But if I did that, I would not know how much reliance to place on my computed estimate. With a regression, I can say (assuming that the returns are normally distributed), that the true underlying beta is between 1.018 and 2.063 with a probability of 95%. This gives me quite a bit of certainty that the true beta is greater than one! Now I went ahead and regressed weekly Groupon returns on S&P weekly returns from Nov. 7, 2011 to April 18, 2016 and found the following: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Return Multiple R 0.363181 0.131901 R Square Adjusted R Square Standard Error 0.128143 Observations 0.089594 233 df Regression Statistics SS MS F 1 0.281739 0.281739 35.0986 1.854255 0.008027 2.135994 231 232 This suggests a higher beta; on the other hand, this is for the period Nov. 4, 2011 to April 18, 2016. Perhaps the beta has been decreasing over time, so that a beta computed using only the last year would have a lower beta. So I repeated the regression using the same time period as the daily regression (of course now I would have much fewer data observations). My results were as follows: Standard Coefficients Error t Stat P-value Lower 95% -0.00734 0.005921 -1.23929 0.216495 1.935643 -0.019 0.326724 5.924407 1.13E-08 1.291904 0.406737 0.165435 0.149071 Significance F 1.13E-08 0.087252 53 Upper 95% 0.004328 2.579382ANOVA Regression Residual Total Intercept X Variable 1 Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df Not surprisingly, the range for the 95% confidence interval is much larger (since we have fewer observations), but the center of the range is more or less the same. What we do note, though, is that the ranges in all three regressions overlap quite a bit. Hence it is difficult to say that the beta has been drifting. Regression Residual Total It is also common for betas measured using daily data to be lower (particularly for less liquid stocks) because the closing price for the stock may be from a time a few minutes before the actual close, at which time the S&P would probably be trading and for which time we'd be measuring the S&P close. So this introduces a bit of noise. Using monthly data, I got for the period 4th November 2011 to 4th January 2016: Regression Statistics Intercept SP_Ret SS MS F 1 0.076964 0.076964 10.10971 51 0.388259 0.007613 52 0.465224 Coefficients Standard Error t Stat P-value 0.011985 -0.70049 0.486802 1.830913 0.575835 3.179576 0.002508 -0.0084 0.161516 0.026087 0.006991 Significance F 0.002508 0.195379 53 df Upper 95% -0.03246 0.015666 0.674875 2.986951 Lower 95% Significance F SS MS F 1 0.052148 0.052148 1.3661 0.247917 51 1.946812 0.038173 52 1.99896 Standard Upper 95% Coefficients Error t Stat P-value Lower 95% -0.0173 0.028323 -0.61074 0.544082 -0.07416 0.039563 1.019712 0.872441 1.168803 0.247917 -0.73179 2.77121The Groupon company is discussed in the NY Times of Nov. 23, 2010. (http://boss.blogs.nytimes.com/2010/11/23/doing-the-math-on-a-groupon-deal/? ref=business). You can also read up on Groupon's history on Wikipedia. The About Tech website has a readable description of Groupon's business model. Groupon financial information can be found on finance.yahoo.com. We know that a stock's beta measures its sensitivity to market movements. We also know that the stock beta is related to the nature of the product sold by a company, especially its price elasticity. What is your best estimate of the beta of Groupon? You can use published estimates, as long as you can explain how those published estimates have been computed. Keep in mind, as well, that the beta is a forward-looking number. Beta estimates using historical information are backward-looking and may or may not be the best estimate of the underlying beta, which measures the future tendency of an asset to move with the market. (As mutual funds note, "Past performance is no indication of future results.") Before you answer the question, read the Fortune article about Groupon's business model given below. Once you have read the article, think about Groupon's beta in two different ways: 1. A beta measures an asset's comovement with the market. If so, we need to ask whether Groupon's profits and market value would move together with the market or against it? Would it move in the same direction as the market, but more than the market? Or perhaps less than the market? Think carefully about the implications of Groupon's business model for your structural estimate of Groupon's beta. 2. If Groupon's future business model is likely to be similar to its past business model, then we can use regression using historical stock returns to estimate Groupon's beta. Download stock returns for Groupon and the S&P and estimate a regression beta for Groupon. Based on your answers to these questions, what is your considered estimate of Groupon's beta. Remember that you can have not ony a point estimate, but also a likely range within which you believe the true beta is likely to lie.Recall that the beta estimates the tendency of a stock to move with the market. Hence we have to ask ourselves what we think the nature of Groupon's business is - is it cyclical or countercyclical? When would a company want to avail itself of Groupon's services? Would it be when the economy is doing well or when it's doing badly? My guess is that it would be when the economy is doing badly. If that is correct, then Groupon's sales would be high when the market is doing badly and low when the market is doing well. This suggests a low beta or maybe even a negative beta. As far as Groupon's costs are concerned (office costs, internet costs, personnel costs), they are probably going to move in sync with the economy. Hence that will reinforce the low beta. Although Groupon may be a "tech" firm, does it make sense to classify it with tech firms like Google or Microsoft? Are the products that all the tech firms sell the same? Here's what one of the students in a previous term, Philipp Zahn, said -- right on the ball, it seems to me: "The article (the 2010 NY Times article referenced above) states that many believe, that only "desperate" businesses cooperate with Groupon. If this is really the case, Groupon might be able to find more partners in a bad economic situation." In bad economic times, consumers are more motivated to look for goods and services that can be purchased below market price. Therefore, more customers might be willing to purchase coupons at Groupon. Groupon would profit from a general bad economy, and return on assets would change in opposition to the companies of the benchmark. This would also cause the beta to be negative. However, consumers spend less in bad economic times. It is uncertain, if this decrease in spending has a stronger effect on Groupon, than the fact, that consumers are more interested in low price goods and services in bad economic times. All of this is from a purely theoretical point of view. However, since that article was published, Groupon has gone public. Hence there is now data on Groupon returns. It is, therefore, possible to see which effect is stronger. According to Yahoo, Groupon's beta is 0.72 (http://finance.yahoo.com/q/ks?s=GRPN+Key+Statistics) However, according to Nasdaq (May 2, 2014), Groupon's beta is 1.76 (http://www.nasdaq.com/symbol/grpn); Google declines to provide a beta. Unfortunately, therefore, we need to run a regression, ourselves, to see what the actual measured beta is. It is possible that the measured beta is not stable, especially since Groupon has only been trading for about 2.5 years. I regressed daily Groupon returns (capital gains plus dividends, 16th March 2015 to 15th March 2016) on daily S&P 500 returns (again capital gains plus dividends) and found the following. Note that in order to compute returns taking into account dividends, there is a shortcut provided by Yahoo. The Yahoo site computes an adjusted closing price which includes the impact of dividends and stock splits. Hence, in order to compute the return including dividends and stock splits, all you need to do is to simply look at the percent change in the adjusted closing price: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept SP_Ret 0.343974 0.118318 0.114806 4.443285 253 df SS MS F 1 665.0005 665.0005 33.68322 251 4955.438 19.74278 252 5620.439 Significance F 1.95E-08 Standard Upper 95% Coefficients Error t Stat P-value Lower 95% -0.15815 0.279347 -0.56614 0.571802 -0.70831 0.392013 1.540367 0.26541 5.803725 1.95E-08 1.017652 2.063082ANOVA Regression Residual Total Intercept X Variable 1 Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df Not surprisingly, the range for the 95% confidence interval is much larger (since we have fewer observations), but the center of the range is more or less the same. What we do note, though, is that the ranges in all three regressions overlap quite a bit. Hence it is difficult to say that the beta has been drifting. Regression Residual Total It is also common for betas measured using daily data to be lower (particularly for less liquid stocks) because the closing price for the stock may be from a time a few minutes before the actual close, at which time the S&P would probably be trading and for which time we'd be measuring the S&P close. So this introduces a bit of noise. Using monthly data, I got for the period 4th November 2011 to 4th January 2016: Regression Statistics Intercept SP_Ret SS MS F 1 0.076964 0.076964 10.10971 51 0.388259 0.007613 52 0.465224 Coefficients Standard Error t Stat P-value 0.011985 -0.70049 0.486802 1.830913 0.575835 3.179576 0.002508 -0.0084 0.161516 0.026087 0.006991 Significance F 0.002508 0.195379 53 df Upper 95% -0.03246 0.015666 0.674875 2.986951 Lower 95% Significance F SS MS F 1 0.052148 0.052148 1.3661 0.247917 51 1.946812 0.038173 52 1.99896 Standard Upper 95% Coefficients Error t Stat P-value Lower 95% -0.0173 0.028323 -0.61074 0.544082 -0.07416 0.039563 1.019712 0.872441 1.168803 0.247917 -0.73179 2.77121This estimate is even lower, but the range is even greater (with fewer observations), but again a big overlap with the other beta estimate ranges. So the conclusion from the historical regression estimates is that the beta (for the past) is around 1 to 1.5, with a fair degree of stability. However, we'd still have to figure out if the future is likely to be similar to the past. If we believe the Groupon business is going to remain "techy" in the future, we'd stick with this "high" beta estimate. On the other hand, if we believe the Groupon coupon business is likely to be countercyclical in the future, we would go with a lower beta estimate. Ultimately, we see that the final estimate still depends on our evaluation of Groupon's business. Data helps us come up with estimates, but in the final analysis, we have to apply economic analysis and our own common sense.The Groupon company is discussed in the NY Times of Nov. 23, 2010. (http://boss.blogs.nytimes.com/2010/11/23/doing-the-math-on-a-groupon-deal/? ref=business). You can also read up on Groupon's history on Wikipedia. The About Tech website has a readable description of Groupon's business model. Groupon financial information can be found on finance.yahoo.com. We know that a stock's beta measures its sensitivity to market movements. We also know that the stock beta is related to the nature of the product sold by a company, especially its price elasticity. What is your best estimate of the beta of Groupon? You can use published estimates, as long as you can explain how those published estimates have been computed. Keep in mind, as well, that the beta is a forward-looking number. Beta estimates using historical information are backward-looking and may or may not be the best estimate of the underlying beta, which measures the future tendency of an asset to move with the market. (As mutual funds note, "Past performance is no indication of future results.") Before you answer the question, read the Fortune article about Groupon's business model given below. Once you have read the article, think about Groupon's beta in two different ways: 1. A beta measures an asset's comovement with the market. If so, we need to ask whether Groupon's profits and market value would move together with the market or against it? Would it move in the same direction as the market, but more than the market? Or perhaps less than the market? Think carefully about the implications of Groupon's business model for your structural estimate of Groupon's beta. 2. If Groupon's future business model is likely to be similar to its past business model, then we can use regression using historical stock returns to estimate Groupon's beta. Download stock returns for Groupon and the S&P and estimate a regression beta for Groupon. Based on your answers to these questions, what is your considered estimate of Groupon's beta. Remember that you can have not ony a point estimate, but also a likely range within which you believe the true beta is likely to lie.Recall that the beta estimates the tendency of a stock to move with the market. Hence we have to ask ourselves what we think the nature of Groupon's business is - is it cyclical or countercyclical? When would a company want to avail itself of Groupon's services? Would it be when the economy is doing well or when it's doing badly? My guess is that it would be when the economy is doing badly. If that is correct, then Groupon's sales would be high when the market is doing badly and low when the market is doing well. This suggests a low beta or maybe even a negative beta. As far as Groupon's costs are concerned (office costs, internet costs, personnel costs), they are probably going to move in sync with the economy. Hence that will reinforce the low beta. Although Groupon may be a "tech" firm, does it make sense to classify it with tech firms like Google or Microsoft? Are the products that all the tech firms sell the same? Here's what one of the students in a previous term, Philipp Zahn, said -- right on the ball, it seems to me: "The article (the 2010 NY Times article referenced above) states that many believe, that only "desperate" businesses cooperate with Groupon. If this is really the case, Groupon might be able to find more partners in a bad economic situation." In bad economic times, consumers are more motivated to look for goods and services that can be purchased below market price. Therefore, more customers might be willing to purchase coupons at Groupon. Groupon would profit from a general bad economy, and return on assets would change in opposition to the companies of the benchmark. This would also cause the beta to be negative. However, consumers spend less in bad economic times. It is uncertain, if this decrease in spending has a stronger effect on Groupon, than the fact, that consumers are more interested in low price goods and services in bad economic times. All of this is from a purely theoretical point of view. However, since that article was published, Groupon has gone public. Hence there is now data on Groupon returns. It is, therefore, possible to see which effect is stronger. According to Yahoo, Groupon's beta is 0.72 (http://finance.yahoo.com/q/ks?s=GRPN+Key+Statistics) However, according to Nasdaq (May 2, 2014), Groupon's beta is 1.76 (http://www.nasdaq.com/symbol/grpn); Google declines to provide a beta. Unfortunately, therefore, we need to run a regression, ourselves, to see what the actual measured beta is. It is possible that the measured beta is not stable, especially since Groupon has only been trading for about 2.5 years. I regressed daily Groupon returns (capital gains plus dividends, 16th March 2015 to 15th March 2016) on daily S&P 500 returns (again capital gains plus dividends) and found the following. Note that in order to compute returns taking into account dividends, there is a shortcut provided by Yahoo. The Yahoo site computes an adjusted closing price which includes the impact of dividends and stock splits. Hence, in order to compute the return including dividends and stock splits, all you need to do is to simply look at the percent change in the adjusted closing price: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept SP_Ret 0.343974 0.118318 0.114806 4.443285 253 df SS MS F 1 665.0005 665.0005 33.68322 251 4955.438 19.74278 252 5620.439 Significance F 1.95E-08 Standard Upper 95% Coefficients Error t Stat P-value Lower 95% -0.15815 0.279347 -0.56614 0.571802 -0.70831 0.392013 1.540367 0.26541 5.803725 1.95E-08 1.017652 2.063082I could simply have computed the ratio of the Covariance between the returns on Groupon and the S&P to the variance of S&P returns and I would have got the same answer much more easily. But if I did that, I would not know how much reliance to place on my computed estimate. With a regression, I can say (assuming that the returns are normally distributed), that the true underlying beta is between 1.018 and 2.063 with a probability of 95%. This gives me quite a bit of certainty that the true beta is greater than one! Now I went ahead and regressed weekly Groupon returns on S&P weekly returns from Nov. 7, 2011 to April 18, 2016 and found the following: Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Return Multiple R 0.363181 0.131901 R Square Adjusted R Square Standard Error 0.128143 Observations 0.089594 233 df Regression Statistics SS MS F 1 0.281739 0.281739 35.0986 1.854255 0.008027 2.135994 231 232 This suggests a higher beta; on the other hand, this is for the period Nov. 4, 2011 to April 18, 2016. Perhaps the beta has been decreasing over time, so that a beta computed using only the last year would have a lower beta. So I repeated the regression using the same time period as the daily regression (of course now I would have much fewer data observations). My results were as follows: Standard Coefficients Error t Stat P-value Lower 95% -0.00734 0.005921 -1.23929 0.216495 1.935643 -0.019 0.326724 5.924407 1.13E-08 1.291904 0.406737 0.165435 0.149071 Significance F 1.13E-08 0.087252 53 Upper 95% 0.004328 2.579382The CPI Card Group Inc. made an IPO filing on August 7, 2015 for $100m. Here is a description of the company from Bloomberg Business: CPI Card Group, Inc. engages in designing, producing, personalizing, packaging, and tracking of smart cards. It focuses on providing financial, commercial, and identification card production and related services. The company offers contactless smart card using RFID, RFID stickers, physical access cards, and FOBS, EMV cards, and MicroSD; financial, commercial, and blank cards; microprocessor cards; and memory cards that are used for pre-paid telephone, library, access control, parking, and loyalty programs applications. It also provides packaging customization options that include silver foil, iridescent glitter, canvas, hot foil stamp, dimensional FX, metallic flake, and pearl. In addition, the company offers personalization services, such as daily processing for secure and non-secure card programs; bulk DOD ink-jet printing for card programs; and B2B and B2C card issuance, distribution, and smart card and EMV personalization and fulfillment services. Further, the company provides mailing and fulfillment solutions, such as envelope with card and carriers, greeting card with card and greeting card envelope, self mailers, iron cross mailers, and custom designed mailers; printing of corresponding mailing materials, manufacturing and perso of the cards, inline match verification, NCOA data processing, and custom programming; and daily fulfillment, weekly fulfillment, Web based ordering and fulfillment for B2B and B2C, and large direct mail. It serves banking, gift and retail, prepaid, government and security, gaming and entertainment, and loyalty and membership industries in the United States and internationally. The company was incorporated in 1982 and is based in Littleton, Colorado. It has locations in the United States, United Kingdom, and Canada. We know that a stock's beta measures its sensitivity to market movements. We also know that the stock beta is related to the nature of the product sold by a company, especially its price elasticity. Keep in mind, furthermore, that a beta is not just a computed quantity, it's a characteristic of a financial asset, which can be estimated in many ways -- the estimate using stock prices and regression being only one of them. Otherwise, the CAPM could only be used for traded securities, which would make it a lot less useful! What is your best estimate of the beta of CPI Card Group? You can use published estimates, as long as you can explain how those published estimates have been computed. Keep in mind, as well, that the beta is a forward-looking number. Beta estimates using historical information are backward-looking and may or may not be the best estimate of the underlying beta, which measures the future tendency of an asset to move with the market. (As mutual funds note, "Past performance is no indication of future results.") Write up your answer in a Word file using no more than two pages and email it to me by the due date. Make sure to send an Excel file; however, the Word file should be self-explanatory. I should only need to look at the Excel file for clarification of your computations. The rubric that I will be using for evaluation is as follows: Rubric Understanding of what beta is Conceptual determination of beta by looking at product Regression beta computation Discussion of t-statistic/confidence interval Use of competitors to determine CPI Card beta Conceptual determination of beta by looking at strategy Additional discussion/ bonus points Total Pts Assigned Max Points 2 2 2 7 2 2 2 1
Purchase answer to see full attachment
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Attached.

1

THE MOMENT OF TRUTH

Name
Institution
Course
Date

THE MOMENT OF TRUTH

2

Jan Carlzon introduced the concept of Moment of truth in the 1980s (Hyken, 2016).
Carlzon defined the Moment of truth as the impression that a consumer comes into contact with
any business even if the business is located far away. This essay aims to narrate a personal
moment of truth that I encountered.
Apple products have always left an impression on me, mainly the iPhones. Ever since
Steve Jobs launched the first-generation iPhone in 2007 back when I was just a kid, I have
always been a fan of Apple products. However, the first real Moment of truth occurred when I
was old enough to get a smartphone, and I window-shopped the product online and in-display
stores. The first i...


Anonymous
I was stuck on this subject and a friend recommended Studypool. I'm so glad I checked it out!

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Similar Content

Related Tags