vania-janet/multiturn-rag-retrieval-data huggingface dataset:
[ACN maser brothers](http://old.post-gazette.com/world/20020524ecstasy4.asp) or they use a mlm to launder money and promise big bucks. That the owners have from dealing drugs not selling personal services. Mlm are a joke, who in their right mind would pay to work for someone that is so counter intuitive that it's not even funny
Yea I meant 2-2.5 effectively. The high amex is going to be offset by regulated debit to get you a nice sweet spot in the middle :) I'm in NYC so while some places opt out of amex for the most part people are going to take it. Since OptBlue came out it's helped mitigate amex costs too which definitely helped
Sometimes invested capital is expected to earn interest, I've seen this be a stipulation in LLC operating agreements and Corporate bylaws. I thought this arrangement looks a little less than fair. BTW I'm a college freshman, though I do the finances for my parents' regulatory compliance and governance consulting company. Anyhow, that's just my two cents.
Just looking at the numbers, something appears off. Cost of equity of ~4% seems very low and should not be below cost of debt. Also a risk free rate of 1.66% seems VERY low. Sometimes it's worth taking a step back and seeing if the numbers even make sense.  If you're serious about using your own analysis for investing, the assumptions are extremely important and incorrect ones can throw everything off.
Generally, speaking the (Rm-Rf) is around around 7% and the Rf tends to be around 6-7%. 1.66% for Rf is wayyyyy too low.  If you used a beta of 0.5, an Rf of 6%, and an (Rm-Rf) of 7%, that would give you an Re (cost of equity) of 9.5%  The cost of equity should not be less than the cost of debt. If it is, you know you need to revisit your assumptions.
You are missing a few variables from your calculation, particularly implied volatility.  Even so it does not look like it would be too great a predictor even if incorporated.  You should focus on calculating the option price at a different point in time (with a different underlying price) instead of using a total position value as that can be done afterwards. I programmed and use the standard Black-Scholes model to calculate expected returns.   There are many tools online to help you without doing the programming or calculations yourself.
I don't think the method falls short, it's the premise that is wrong. If the dividend stream really did grow faster than the cost of capital indefinitely, eventually the company behind the share would become larger than the entire economy. Logically, at some point, the growth must slow down.
The 3.7% annual increase is probably a little high. Current averages are about 2.8-3%. This leads to the final numbers being a bit inflated, but it still gets the point across. I know too many people my age that aren't invested, yet have not insignificant savings.
This would be 48x wrong, no need to sensationalize it any more than it already has been. Their 10 year estimate of actual solar production (an emerging market) was off by a factor of 4, which is pretty good.
"How accurate is Implied Volatility in predicting future moves? How would you measure this?  If the implied volatility says that there's a 1% chance that a stock will double, and it doubles, was it ""right""?  You could also say that it says there's a 99% change that it doesn't double, so was it ""wrong""?   What you could measure is the variance of daily returns over a time period, and see how well that compares to implied volatility, but there's no way to compare IV with the absolute price movement.  If a stock goes up 0.01 each day, then the variance is 0 (the daily returns are the same each day), but over 250 the stock would go up $2.50."
I also prefer to crunch the numbers myself. Here are some resources:
I don't understand the logic of converting a cost of funds of 4% to a monthly % and then subtracting that number from an annual one (the 1.5%).  Unfortunately without seeing the case I really can't help you...there was likely much you have left out from above.
You've flipped the numerator and denominator around, and need to multiply by 100 to get percentage rather than 10: I like to use a simple example to assess reasonableness of an approach, if you had invested $100 and after 1 year had $150, your approach would yield: But since $50 is half of $100, we know the rate of return should be 50%, so we know that approach is off. But, flipping the numerator and denominator and multiplying by 100 gets us the 50% we expected: Edit: Good catch by @DJohnM you've called it 9 years, but it's actually 11, so you'd want to adjust accordingly.
There is no right way but changing your methodology to suit your situation is   a problem. They were happy to use a 4 years period during the crazy times to lower the VAR and then switch to 1 year afterwards to do the same. It is picking and choosing your measures to suit the situation and that is statistical heresy. While there may not be a right way to measure VAR choosing the measure that is suits your situation is bad methodology.    And of course there is such a thing as bad statistical methodology, you see it everyday.   I also pointed out above that it vairies from bank to bank what confidence interval you use.
Happy to help.   I always recommend you try and solve these types of problems by hand over financial calculators so that you can get a feel for how terms in the equation relate to one another. That's important while you're studying/learning.  But for work--by all means you should use the fastest method, which is probably excel.
This is only a rule of thumb. Peter Lynch popularized it; the ratio PE/growth is often called the Lynch Ratio. At best it's a very rough guideline. I could fill up this page with other caveats. I'm not saying that it's wrong, only that it's grossly incomplete. For a 10 second eyeball valuation of growth stocks, it's fine. But that's the extent of its usefulness.
James Roth provides a partial solution good for stock picking but let's speed up process a bit, already calculated historical standard deviations: Ibbotson, very good collection of research papers here, examples below Books
Even without analyzing the math or doing a complete risk assesment, consider the following:
"Greatowl's response is pretty cynical. I'm not a wall street analyst but I do read some of the research and there is a lot of respectable analysis out there. There are many smart analysts who consistently get poached from the equity research departments to join the buy side. I'd also contend that level of accuracy is an incomplete measure of performance. It doesnt matter if you're right or wrong, what matters is how much you make when you are right and how much you lose when you are wrong. Soros is purported to have a 30% ""batting average"" but the guy makes a killing when he's right (source: Inside the House of Money)."
Convert operating leases into debt. Don't take MCD's word for cost of debt, calculate it on your own based on the credit rating they should have.  Check your numerator as well on your DCF, make sure you're considering reinvestment, etc.
It's really not. You have to realize that current rates are an outlier. The average on the 10yr since 1960 is 6.7%. Even on the 1yr it's still 5.7%. The average on the 30Yr from '77-present is 7.6%. You can use your own discretion about the length of time to consider for the average, but you don't just take the current rate as the risk free rate.
Dude honestly your comment is still pissing me off. Your comment history is literally just you going around berating and trying to shit on people with esoteric one or two sentence responses. Literally nothing you write up is ever technical, is focused on modelling, or any pitchdeck/CIM insight that bankers actually do. Like there's no way you're in banking.. you're just a sad kid going around on reddit trying to one up people (literally telling some nice dude they sounded deluded and just left it at that)
I agree. I think that is a good point, and that is also why I wanted to post and ask. If I could do this in a bear market I bet I could be Warren Buffett by the time my heart stops.  I use my benchmark as a mix of S&amp;P, Nasdaq, and Russell 3000. I got a near flat market for 2015 (only 0.23%). I thought that was decent but yes the rest of the years have been quite bullish
"If someone is guaranteeing X%, then clearly you can borrow money for less than X% (otherwise his claim wouldn't be remotely impressive).  So why not do that if his 4% is guaranteed? :) Anyway, my answer would be that beating the market as a whole is a ""decent"" rate of return.  I've always used the S&P 500 as a benchmark but you can use other indices or funds."
Whoops, an obvious one there. So much for audit! We were doing a Basel liquidity report at a bank. One set of numbers in Oracle always balanced with SAP. We were told to use their corrections to apply to the rest. It turns out that they ignored the transactions in Oracle and had loaded the balance sheet data from SAP in Oracle. Of course the data will match!
Quick and dirty paper but pretty interesting.. I'm not in Portfolio Management but I probably would have ended up at the modal number as well.   I don't know the subject deeply enough to answer my own question, but is the bias always toward underestimation of variance? Or is that a complex of the way the problem was set up?   Another question I have for those in investment management; Would this impact asset allocation?
Even with scenario and stress testing, VaR is still rather useless.  Im sure your VaR simulator was a great piece of work but at the end of the day when things go crazy VaR as a model fails when you need it the most. Risk management in the larger banks is reporting while at funds is more active.
There are entire 5-person teams dedicated to forecasting *individual products* at major companies that roll up to product class teams, which then roll up to balance sheet forecasting. Since all of those companies have major capital markets operations, these things get huge. The real forecasters are spending 10-14 hours a day, year-round using massive models to come up with competent forecasts. I did this for a few years, it's leaps and bounds more than applying multiples.   I hope you get a lot of participation, but you have to see the flaw in this dataset. I think this would be better done by honing your focus in on what forecasting you're talking about. It's a very, very broad field.
"&gt; A DCF works with whatever cash flows you are willing to forecast. If you have extreme skepticism about those &gt; forecasts then you can either adjust them, run sensitivity analyses, or use a significantly higher discount rate &gt; (or all three). All of those approaches will help you establish upper and lower bounds for a valuation.  The amount of uncertainty you have makes the upper and lower bounds insanely wide. Even choosing an appropriate discount rate is non-trivial.  &gt; So what you're saying is that Facebook can forecast that by acquiring Snapchat they're able to ""keep X users &gt; for Y period of time"" but they then can't make the next logical leap to figure out how to apply a profit/revenue &gt; factor to those user numbers in order to create a suitable DCF?  Why would they waste their time with a DCF? Sure, you can calculate incremental value saved or a hundred different metrics but at the end of the day this is a bet that you only get to make once, it would be very tough to gamble with any degree of statistical confidence here.  If they got to buy 100 whatapps' they might be able to do something but in this context it's a clear bet on strategy and it's that.  Forecasting future cashflows is notoriously difficult even with stable firms, trying this with a new firm that's practically a venture bet would be a waste of everyone's time.  Zuckerberg made a $20bn bet that this company would allow them to stay in peoples lives online and that can be sold to advertisers."
"Accretive means additive. When someone says ""accretive to EPS"" it means that it should theoretically add to EPS. The problem is that the models they're using to determine pro forma EPS are filled with bullshit assumptions that may or may not reflect reality. I remember working on merger models as a young analyst and having my MD tell me on multiple occasions ""those accretion numbers aren't good enough, play with the assumptions"""
Annualize quarterly returns:      AR = (1+QR)^4  Where *QR* is a decimal return, e.g. 0.05.  Standard deviations are similar:      Annual SD = SD * sqrt(T)  If you have quarterly deviations, *T=4*, if you have daily, *T=252*, etc.  As an aside, for work with money riding on it, it is *not* okay to aggregate standard deviations if there's autocorrelation amongst observations at a smaller time scale. Volatility is often quoted this way and that's fine, but it is dangerous to do any sort of risk management with this and you'll require more due diligence. It's a good enough approximation for napkin math, though.
Interesting thing is not all of this analysis is typically done by the person you are speaking with re: your mortgage.  Likely there is an economic team (at some institution or another, as many many loans are sold/distributed in some fashion), finance team, and all of them are looking at various rates etc.  Typically what is offered is matching an offsetting liability somewhere else.  So there may be cases where the spread someone is looking to pick up might be tighter or looser within institutions or types of institutions vs others, even though the overall market is at one place.  (e.g. banks vs. insurance companies).    So you may have negotiating room at a certain term, but not another, or the reverse at another firm.  One firm might have lots of 10 year money, while another might be limited, so will be picky in what they choose.  Either more conservative loan terms/ltv, or a higher spread, for example.  So many things go into the ultimate rate someone can get, but in theory the blog did a decent job.
That seems a little high in my experience.  I've used a home equity line of credit instead, as the rates are much lower (~3.5%).
"&gt;""Those measures all reflect a new way of measuring VaR though, one that switches the model from a four-year look to just one year, removing the rocky years of 2008 and 2009 from the current measure""   .............. seriously i dont even know what to say."
The real test of AAA's analysis is whether other insurers follow suite. Setting insurance rates is a balancing act between being high enough to make money given the expected payouts, and being low enough to not get undercut by competitors. If other insurers follow AAA's lead, then their analysis is probably right. If other insurers stay low than AAA probably made a mistake. When you price insurance on a given car it's not uncommon to have an outlier that overpriced that car.
This depends on the loan calculation methodology. If it is on reducing balance then yes. Else not much difference
Sorry... I'm a software engineer not an academic.  My assumption is that you can measure things like average throughput on a checkout line, or number of widgets assembled on an assembly line (and possibly the defect rate of those widgets), or pounds of fries dumped in the trash because they got cold before being served relative to fries served. Is this not the case?  In my field we measure things like the change in average time to launch, or the revenue impact of features, or the change in performance metrics, etc. They're all proxy measurements though. Poor performers are generally much easier to spot than high performers. Mediocre performers can generally get through things, but may not earn promotions etc.
Two measurements, one at the beginning of the term one at the end. Fixed effects regression.  Reward teachers based on how much they improved weak students and kept strong students smart. Bam.  Of course it's not nearly that easy, but it isn't as big a problem as you're making it seem.
"derivatives!  learn about how they are priced, traded, and used within a portfolio for hedging and speculating.  there are calculators for ""net present value calculations,"" and you are never going to walk into an interview and say, ""Hey! I can look at a formula and price something."""
The Sharpe ratio is, perhaps, the method you are looking for.  That said, not really sure beta is a meaningful metric, as there are plenty of safe bets to be made on volatile stocks (and, conversely, unsafe bets to be made on non-volatile ones).
It's a big dance. Share price will go up or down based on a number of factors, many that have nothing to do with the company operations. If a CEO fixates on quarterly returns, that will cause long-term investors to want that CEO replaced, or to sell their shares. Unless a CEO is weak and can't explain the business to shareholders he shouldn't need to focus on quarterlies. If he does then shareholders short and long will take advantage of the bump in price to exit, thus depressing the valuation. Then new money comes in after CEO is replaced.
"Remember that ""earned"" means ""earned in profit."" A company like LinkedIn may not be trying to earn any profit, because they believe that they are at the stage in their development where the best thing to do with excess cash is to reinvest it in growing the business. Therefore, profit may not be the best metric at this stage in the company's life cycle."
Some products will only have a technology shelf life, some will actually go bad or out of fashion, and even selling Superman bikes you want to get those to the store because the product is so big. So ignoring making a profit can a company sell off inventory at or around cost. If they can't, even if they made a profit, their risk factor goes up. So let's get back to Superman Bikes. This is the only product company ABC has. They had expected holiday sales at 100 million and profits at 40 million. They ended up at 120 million and 44 million. Let's say their stock was $20 before any information was gathered by the public (remember for most companies info is gathered daily now so this is rather simplistic). So you might expect that the stock would rise to maybe $24 - to which if you were an investor is a great profit. However this company has a cult consumer following who are waiting for the Captain America Bike (shoots discs) and the Hulk Bike (turns green when you go fast). Let's say consumer sentiment and projections base off that put next holiday sales at $250 million. So maybe the company is worth $40 a share now. But consumer sentiment is funny because not only does it effect future projections but it also effects perceived present value of company - which may have the stock trading at $60 a share (think earnings and companies like Google). Having a company people feel proud owning or thinking is cool is also a indicator or share worth. I gave you a really good example of a very successful company selling Superman Bikes... There are just as many companies that have the opposite happening. Imagine missing sales goals by a few million with bad consumer feedback and all of a sudden your company goes from $20 to $5 a share."
The only recommendation I have is to try the stock screener from Google Finance : https://www.google.com/finance?ei=oJz9VenXD8OxmAHR263YBg#stockscreener
I'll check it out. We'll need it to be a reference that's easy to understand for those that will ask us these questions--not for those of us with master's degrees in business.       (*I* don't need it to be easy to understand--I need something that saves me the trouble of explaining over and over...)
"This is the best tl;dr I could make, [original](https://www.ineteconomics.org/perspectives/blog/how-economists-turned-corporations-into-predators) reduced by 95%. (I'm a bot) ***** &gt; LP: What have these academic theorists missed about how companies really operate and perform? How have their views impacted our economy and society?  &gt; These are aggressive corporate predators who buy shares of a company on the stock market and then use the power bestowed upon them by the ill-conceived U.S. proxy voting system, endorsed by the Securities and Exchange Commission, to demand that the corporation inflate profits by cutting costs.  &gt; LP: So if shareholders and executives are too often just looting companies to enrich themselves - &amp;quot;Value extraction,&amp;quot; as you put it - and not caring about long-term success, who is in a better position to decide how to run them, where to allocate resources and so on?   ***** [**Extended Summary**](http://np.reddit.com/r/autotldr/comments/74pl6s/how_economists_turned_corporations_into_predators/) | [FAQ](http://np.reddit.com/r/autotldr/comments/31b9fm/faq_autotldr_bot/ ""Version 1.65, ~223416 tl;drs so far."") | [Feedback](http://np.reddit.com/message/compose?to=%23autotldr ""PM's and comments are monitored, constructive feedback is welcome."") | *Top* *keywords*: **company**^#1 **value**^#2 **share**^#3 **corporate**^#4 **stock**^#5"
Pretty much. There is an executive trying decide between a trader who has made the firm millions in the past few years and a quant who costs him a 6 figure salary but doesn't pull in any revenue. Then on top of it the quant is talking mathematics which the executive doesn't even know in the first place. Who is executive going to side with?
Also, how much did Microsoft pay out in dividends during that time? (Another theoretical consideration would be how much other capital they issued, but I don't think they have)  Edit: if you guys are talking about share price during Ballmer's tenure as a metric of performance then you have to consider total return to shareholders. Failure to do so is simply a wrong approach
The economy is not zero sum. Just because one group is experiencing exponential growth, doesn't mean they're exploiting others to achieve it.   To figure out whether or not those people deserve their wealth we have to examine exactly how it was accomplished. Did they lobby to shut out competitors? Did they take advantage of IP laws? Did they receive subsidies? Did they benefit from tax credits? Did they use eminent domain? And for each of these questions, follow up with the question of how much these actions affected their bottom line profitability.  Anything less than this level of examination is lazy analysis, and should be regarded as such.
This isn't true always. And it's about timing scenario more than a hard line goal.   Companies are supposed to be greedy. They need reserves.  But citizens must also recognize it's the the job of a Company to pay them. Their job is to create value.
Well, you're business/accounting acumen is nothing to brag about and your character is still out for judgment, though your insistence on trying to make this point despite being wrong is sort of working against you. Other than that, I don't know anything else about you to make that kind of assessment.  Though you are tenacious, I'll give you that. You keep arguing with me despite saying you were done with this. So that could possibly be a positive character trait.
You can't. If there was a reliable way to identify an undervalued stock, then people would immediately buy it, its price would rise and it wouldn't be undervalued any more.
If you have a mortgage, making part of it a mortgage-backed overdraft (ANZ call theirs a Flexi loan) is worth looking at. I'm in a similar situation, consulting since 2010. I pay GST and provisional tax every six months. If I've budgeted right, the balance on the mortgage-backed overdraft loan goes to zero right before I send the massive payment to the tax department in May and October.  One problem is that some banks don't like to give these accounts to sole traders. Using a mortgage broker may help get around that restriction.