vania-janet/multiturn-rag-retrieval-data huggingface dataset:
This doesn't have anything to do with safety. It's about understanding what goes into something. You reference using every part of the buffalo, but they know what they're getting and what they're using. If BPI wants to label it and sell directly to consumers, they can feel free.  Additionally, it's entirely likely they *didn't* use the parts that were used to create pink slime, as it can only be extracted mechanically.
In theory, GS has a Chinese Wall between the department which issued the advice and any departments which may profit from such advice. This would take away some of your distrust, except for the fact that GS did violate these rules in the past (see the answer from user10665). You're wondering about the timing, prior to the release of figures by Tesla itself. This is quite normal. Predicting the past is not that useful ;) The price range indeed is wide, but that too is a meaningful opinion. It says that GS thinks Tesla's share price strongly depends on factors which are hard to predict. In comparison, Coca Cola's targets will be in a much smaller range because its costs and sales are very stable.
Well yeah, that's why they put the disclaimer on the article, so people could know and judge accordingly. That's evidence of good journalism, not bad.  That conflict also doesn't negate Wapo's good track record, and the fact that that track record is one of its best selling points. I don't think Amazon would sacrifice that cheaply; definitely not as a cheapshot on some objectively bad pitch videos.
In this case, it looks like the interest is simply the nominal daily interest rate times number of days in the period. From that you can use a spreadsheet to calculate the total payment by trial and error. With the different number of days in each period, any formula would be very complicated. In the more usual case where the interest charge for each period is the same, the formula is: m=P*r^n*(r-1)/(r^n-1) where * is multiplication ^ is exponentiation / is division (Sorry, don't know if there's a way to show formulas cleanly on here) P=original principle r=growth factor per payment period, i.e. interest rate + 100% divided by 100, e.g. 1% -> 1.01 n=number of payments Note the growth factor above is per period, so if you have monthly payments, it's the rate per month. The last payment may be different because of rounding errors, unequal number of days per period, or other technicalities. Using that formula here won't give the right answer because of the unequal periods, but it should be close. Let's see: r=0.7% times an average of 28.8 days per period gives 20.16% + 1 = 1.2016. n=5 P=500 m=500*1.2016^5*(1.2016-1)/(1.2016^5-1) =167.78 Further off than I expected, but ballpark.
"Yes, and the math that tells you when is called the Kelly Criterion. The Kelly Criterion is on its face about how much you should bet on a positive-sum game. Imagine you have a game where you flip a coin, and if heads you are given 3 times your bet, and if tails you lose your bet. Naively you'd think ""great, I should play, and bet every dollar I have!"" -- after all, it has a 50% average return on investment. You get back on average 1.5$ for every dollar you bet, so every dollar you don't bet is a 0.5$ loss. But if you do this and you play every day for 10 years, you'll almost always end up bankrupt. Funny that. On the other hand, if you bet nothing, you are losing out on a great investment. So under certain assumptions, you neither want to bet everything, nor do you want to bet nothing (assuming you can repeat the bet almost indefinitely). The question then becomes, what percentage of your bankroll should you bet? Kelly Criterion answers this question. The typical Kelly Criterion case is where we are making a bet with positive returns, not an insurance against loss; but with a bit of mathematical trickery, we can use it to determine how much you should spend on insuring against loss. An ""easy"" way to undertand the Kelly Criterion is that you want to maximize the logarithm of your worth in a given period. Such a maximization results in the largest long-term value in some sense. Let us give it a try in an insurance case. Suppose you have a 1 million dollar asset. It has a 1% chance per year of being destroyed by some random event (flood, fire, taxes, pitchforks). You can buy insurance against this for 2% of its value per year. It even covers pitchforks. On its face this looks like a bad deal. Your expected loss is only 1%, but the cost to hide the loss is 2%? If this is your only asset, then the loss makes your net worth 0. The log of zero is negative infinity.
Thank you for your reply. I have the same questions as OP.  And have scheduled for next year to dive in the CFA lecture, out of curiosity. Question does the literature change every year or is last year's or even before also a good basis to learn?
"No, it's not fair usage at all. Maybe meets a legal definition of fair usage, but it's not what we'd consider a ""straight faced"" claim. Any amount of chicken added to a recipe is ""100%"" chicken. A molecule of chicken in a recipe qualifies it to include ""100% chicken."" It's tautological. It's designed to make you believe the product is more wholesome or free of additives than it actually is. It's a psychological scam, like pretty much all packaging and marketing."
"The June 2014 issue of Barclays Wealth's Compass magazine had a very nice succinct article on this topic: ""Value investing – does a rules-based approach work?"".  It examines the performance of value and growth styles of investment in the MSCI World and S&P500 arenas for a few decades back, and reveals a surprisingly complicated picture, depending on sector, region and time-period. Their summary is basically: A closer look however shows that the overall success of value   strategies derives mainly from the 1970s and 1980s. ... in the US, value has underperformed growth for over 25 years   since peaking in July 1988. Globally, value experienced a 30% setback   in the late 1990s so that there are now periods with a length of   nearly 13 years over which growth has outperformed. So the answer to ""does it beat the market?"" is  ""it depends..."". Update in response to comment below: the question of risk adjusted returns is interesting.  To quote another couple of fragments from the piece: Since December 1974, [MSCI world] value has outperformed growth by   2.6% annually, with lower risk. This outperformance on a risk-adjusted   basis is the so-called value premium that Eugene Fama and Kenneth   French first identified in 1992... and That outperformance has, however, come with more risk. Historical   volatility of the pure style indices has been 21-22% compared to 16%   for the market. ... From a maximum drawdown perspective, the 69% drop   of pure value during the financial crisis exceeded the 51% drop of the   overall market."
From my 15 years of experience, no technical indicator actually ever works. Those teaching technical indicators are either mostly brokers or broker promoted so called technical analysts. And what you really lose in disciplined trading over longer period is the taxes and brokerages. That is why you will see that teachers involved in this field are mostly technical analysts because they can never make money in real markets and believe that they did not adhere to rules or it was an exception case and they are not ready to accept facts. The graph given above for coin flip is really very interesting and proves that every trade you enter has 50% probability of win and lose. Now when you remove the brokerage and taxes from win side of your game, you will always lose. That is why the Warren Buffets of the world are never technical analysts. In fact, they buy when all technical analysts fails. Holding a stock may give pain over longer period but still that is only way to really earn. Diversification is a good friend of all bulls. Another friend of bull is the fact that you can lose 100% but gain any much as 1000%. So if one can work in his limits and keep investing, he can surely make money. So, if you have to invest 100 grand in 10 stocks, but 10 grand in each and then one of the stocks will multiply 10 times in long term to take out cost and others will give profit too... 1-2 stocks will fail totally, 2-3 will remain there where they were, 2-3 will double and 2-3 will multiply 3-4 times. Investor can get approx 15% CAGR earning from stock markets... Cheers !!!
DS is a tool that should be pulled out for the masses, the radio audience that The David (Dave Ramsey, radio show host) appeals to. They may comprise the majority of those with high credit card debt, and have greatest success using this method. But, you exhibit none of their symptoms, and are best served by the math. By bringing up the topic here, you've found yourself in the same situation as the guy who happens to order a white wine at a wedding, and finds his Mormon cousin offering to take him to an AA meeting the next day. In past articles on this decision, I've referenced a spreadsheet one can download. It offers an easy way to see your choice without writing your own excel doc. For the situation described here, the low balance total interest is $546 vs $192 for the higher interest. Not quite the $500 difference I estimated. The $350 difference is low due to the small rate difference and relatively short payoffs. In my opinion, knowledge is power, and you can decide either way. What's important is that if you pay off the zero interest first, you can say ""I knew it was a $350 difference, but I'd rather have just one outstanding loan for the remain time."" My issue with DS is when it's preached like a religion, and followers are told to not even run the numbers. I wrote an article, Thinking about Dave Ramsey a number of years back, but the topic never gets old."
"As Michael McGowan says, just because gold has gone up lots recently does not mean it will continue to go up by the same amount. This plot:  shows that if your father had bought $20,000 in gold 30 years ago, then 10 years ago he would have slightly less than $20,000 to show for it. Compare that with the bubble in real estate in the US:  Update: I was curious about JoeTaxpayer's question: how do US house prices track against US taxpayer's ability to borrow?  To try to answer this, I used the house price data from here, the 30 year fixed mortgages here and the US salary information from here. To calculate the ""ability to borrow"" I took the US hourly salary information, multiplied by 2000/12 to get a monthly salary. I (completely arbitrarily) assumed that 25 per cent of the monthly salary would be used on mortgage payments.  I then used Excel's ""PV"" (Present Value) function to calculate the present value of the thirty year fixed rate mortgage. The resulting graph is below.  The correlation coefficient between the two plots is 0.93.  There are so many caveats on what I've done in ~15 minutes, I don't want to list them... but it certainly ""gives one furiously to think"" !! Update 2:  OK, so even just salary information correlates very well with the house price increases.  And looking at the differences, we can see that perhaps there was a spike or bubble in house prices over and above what might be expected from salary-only or ability-to-borrow."
I agree with @Turukawa that the x-axes need to be the same to make a direct comparison.  However, the graphs you linked make me think of introductory calculus:  If you time averaged plots, speculative investments (gold, housing) seem to have many large concave up time periods and the dow jones has many concave down sections.  Using the concavity test: If the first derivative tells you about the rate of change, the second derivative tells you about the rate of change of rate of change.  Remember back to Physics 101:  1st derivative is velocity & second derivative is acceleration.   It would be interesting to have the same time scales for your plots & compare these accelerations between the two.  I suspect the more volatile investments would have larger (in magnitude) accelerations during boom/bust cycles than less speculative investments.
"No one can claim markets are perfectly efficient. The Grossman-Stiglitz paradox explains one reason why it is impossible for the market to be perfectly effecient, and there are plenty of investors that show it is practically possible to consistently beat the market (e.g. ""The Superinvestors of Graham-and-Doddsville"" or RenTec's Medallion Fund).  However, even if you accept as true that prices behave strangely around round numbers, that isn't a refutation of the efficient market hypothesis. The efficient market hypothesis says that price reflect all available information, so the expected price tomorrow is just the price today (not taking into account the time value of money).  The efficient market hypothesis says nothing about how prices are distributed. Historically, a random walk has been used, but that is neither a consequence of the EMH nor a required assumption.  You could say that prices are more volatile the nearer they are to a round number or new high, but that doesn't necessarily give you an edge in making money off the stock."
We've had a number of question like this, and this isn't really a rare occurrence. Never assume people selling you things are necessarily accurate or honest - always verify. C) The loan company just doesn't report the loan at all to a credit agency, or does so incorrectly. They are under no obligation to report to credit agencies, it's strictly up to them. If you don't pay then they can report it as something ""in collections"". This isn't the typical way of doing business for most places, but some businesses still operate this way, including some places that advertise how doing business with them (paying them grossly inflated interest rates) will ""help build your credit"". Most advertising fraud goes unpunished. Note: Under all of the above scenarios, the loan can only effect the credit rating attached to the bureau it is reported to. If the loan is reported to Equifax, it will not help you with a TransUnion or Experian rating at all. Some loans report to multiple credit bureaus, but many don't bother, and credit bureaus don't automatically copy each other. It's important to remember that there isn't so much a thing as a singular ""consumer credit rating"", as there are ""consumer credit ratings"" - 3 of them, for most purposes, and they can vary widely depending on your reported histories. Also, if it is only a short-term loan of 3-6 months then it is unlikely to have a powerful impact on anyone's credit rating. Credit scores are formulas calibrated to care about long-term behavior, where 3 years of perfect credit history is still considered a short period of time and you will be deemed to have a significant risk of default without more data. So don't expect to qualify for a prime-rate mortgage because of a car loan that was paid off in a few months; it might be enough to give you a score if you don't have one, but don't expect much more. As always, please remember that taking out a loan just to improve credit is almost always a terrible idea.
I would honestly find it difficult to believe that the high rate of failure are due to opioids (they break down way too fast and many have some kind of scrip even if the legitimacy is questionable). Admittedly we have an epidemic in our country however I would suspect that the author is looking at general failure rates and then mentioning opioids in the same breath as I don't think I have ever seen public data on what drugs people are being failed for.   Also while the article mentions opioids it also mentions an upcoming medicinal law in Ohio that is expected to be a problem for employers heavily drug testing. This leads me to further believe that any testing stats mentioned are aggregates.   EDIT: And lets be honest, opioids are eyeball grabbers in discussion these days. When you have ghost white parents passed out in public places, children overheating in the back of a minivan that is going to grab your attention. I don't think anyone has been horrified like that watching someone stoned eating an entire large pizza on their own.
"Why does the article, which refers to the 2006-2008 boom as a gilded age use the same time period as a basis for labor participation calculation? Should they not use a more wise approach and make the basis around 2005 or 2004 and then calculate the amount of labor participating in order to account for the ""false high"" of 2007? Maybe I missed something in my education but if a specific time counts as an anomaly, then it should not be the base calculation when deriving a hypothesis about that time period. For example wage growth between 2005 and 2007 increased x% but between 2007 and 2009 decreased 3x% so we are really in for it now. It should be the base period of 2005 shows a growth of x% to 2007 and from 2005 to 2009 shows a growth of only one tenth x%.   Of course this would make for much less sensationalist journalism and may not sell as many news stories as a sensationalist story would."
Oh my, i remember going through the Series 66... when i was at Morgan Stanley they provided learning material from Securities Training Corporation, or STC. I personally thought the STC material was okay in terms of preparing me for the Series 66...However, i heard a lot of good reviews/feedback around the office for Pass Perfect. https://www.passperfect.com/Series/66/Product/38  Hope this helps and good luck on the 66!! ;)
You missed the catch, there is always a catch, and in this case it is not well publicized.   First, some background. Congress (both parties) in 98 passed Graham-Leach-Bliley. It allowed commercial banks to invest, securitize, and insure securities. It also had privacy provisions, which prevented a securitizer of a mortgage from providing ANY personal information about the mortgage. That means that as Chase wrote these mortgage backed securities, they were forbidden, BY LAW, from telling the potential purchasers the addresses of the houses or SS#'s of the purchasers.   OF COURSE Chase did not choose to insure these MBS's themselves. Instead, they chose a third party like AIG because AIG could not know personal information about the mortgages, and was thus blinded to risk. AIG chose a middle of the road risk rating (something like 2% risk of default).   Chase FRAUDULENTLY represented the quality of the mortgages to the people writing the credit default swaps to insure them, and to the potential buyers. Chase KNEW the mortgages were crap.   Fraud is fraud and is illegal in security sales even after Graham-Leach-Bliley. However, to be clear, in this case there does not need to be any faking of paperwork. The loans can be passed along BLINDLY with insurance, as they were. If it could be documented that Chase misrepresented the quality of these AAA MBS's, they would be on the hook. But the catch is that Graham-Leach-Bliley offered them a cop-out.  AIG were the real dummies in all this. Who writes insurance without having a good idea of the risk....
"In your example, you said if someone calls for a 75% decline in the market next year, and instead it happens in 3 years, it's still a good call in your book. This is what I, and I believe mjvcaj, disagree with.   Without a time frame, or an incorrect time frame, you're essentially just making a blanket statement and hoping for the best. Otherwise anyone can ""predict"" what's going to happen, as long as you're vague about the details."
"The hardest part seems to be knowing exactly when to sell the stock. Well yes, that's the problem with all stock investing. Reports come out all the time, sometimes even from very smart people with no motivation to lie, about expected earnings for this company, or for that industry. Whether those predictions come true is something you will only find out with time. What you are considering is using financial information available to you (and equally available to the public) to make investment choices. This is called 'fundamental analysis'; that is, the analysis of the fundamentals of a business and what it should be worth. It forms the basis of how many investment firms decide where to put their money. In a perfectly 'efficient' market, all information available to the public is immediately factored into the market price for that company's stock. ie: if a bank report states with absolute certainty (through leaked documents) that Coca-Cola is going to announce 10% revenue growth tomorrow, then everyone will immediately buy Coca-Cola stock today, and then tomorrow there would be no impact. Even if PwC is 100% accurate in its predictions, if the rest of the market agrees with them, then the price at the time of IPO would equal the future value of the cashflows, meaning there would be no gain unless results surpassed expectations. So what you are proposing is to take one sliver of the information available to the public (have you also read all publicly available reports on those businesses and their industries?), and using that to make a high risk investment. Are you going to do better than the investment firms that have teams of researchers and years of experience in the investment world? You can do quite well by picking individual stocks, but you can also lose a lot of money if you do it haphazardly. Be aware that there is risk in doing any type of investing. There is higher than average risk if you invest in equities ('the stock market'). There is higher risk still, if you pick individual stocks. There is yet even higher risk, if you pick small startup companies.
"From what I have read from O'Neil to Van Tharp, etc, etc, no one can pick winners more than 75% of the time regardless of the system they use and most traders consider themselves successful if 60% of the trades are winners and 40% are losers. So I am on the side that the chart is only a reflection of the past and cannot tell you reliably what will happen in the future. It is difficult to realize this but here is a simple way for you to realize it. If you look at a daily chart and let's say it is 9:30 am at the open and you ask a person to look at the technical indicators, look at the fundamentals and decide the direction of the market by drawing the graph, just for the next hour. He will realize in just a few seconds that he will say to him or her self ""How on earth do you expect me to be able to do that?"" He will realize very quickly that it is impossible to tell the direction of the market and he realizes it would be foolhardy to even try. Because Mickey Mantle hit over 250 every year of his career for the first 15 years it would be a prudent bet to bet that he could do it again over the span of a season, but you would be a fool to try to guess if the next pitch would be a ball or a strike. You would be correct about 50% of the time and wrong about 50% of the time. You can rely on LARGER PATTERNS OF BEHAVIOR OVER YEARS, but short hourly or even minute by minute prediction is foolish. That is why to be a trader you have to keep on trading and if you keep on trading and cut your losses to 1/2 of your wins you will eventually have a wonderful profit. But you have to limit your risk on any one trade to 1% of your portfolio. In that way you will be able to trade at least 100 times. do the math. trade a hundred times. lose 5% and the next bet gain 10%. Keep on doing it. You will have losses sometimes of 3 or 4 in a row and also wins sometimes of 3 or 4 in a row but overall if you keep on trading even the best traders are generally only ""right"" 60% of the time.