vania-janet/multiturn-rag-retrieval-data huggingface dataset:
"I mean, it's only a difference of an order of magnitude, really.  Until you consider the following:  1) Only a fraction of the $800B Muni bonds market is new issue.  2) True spreads on Muni bonds are hard enough to calculate as is because they're all OTC.   3)The author quotes that the particular bid was for an 87K/year return on a notional of $300M. That's a spread of a whopping 3 basis points that the bank took extra over ""true value"".  4) Intraday vol for almost any financial instrument is more than 3 basis points.  5) So that's what he's making this big deal over? THREE basis points? I don't even know the length of my penis to within three basis points, and I challenge you to find anyone who could name the yield on the 10Y Treasury within 3 basis points."
I've got a small position at Lending Club and it's doing really well. It's been easy to use, good (not excellent) interface, easy to track the loans you've made &amp; does a good job with notifications. Not much there for doing anything advanced with the portfolio math--I've used a separate spreadsheet to track things *as well as* use their reporting.    The one catch with them I find is that when you put an order in you have to wait longer than you might expect for the process to complete--that is, even after the loan is *funded*, it still has to be *reviewed*, so the lead time before your money begins earning interest might be 2 weeks + 1 week of review time.
Regardless of how long the mortgage has left, the return you get on prepayments is identical to the mortgage rate. (What happens on your tax return is a different matter.) It's easier to get a decent financial calculator (The TI BA-35 is my favorite) than to construct spreadsheets which may or may not contain equation errors. When I duplicate John's numbers, $100K mortgage, 4% rate, I get a 60 mo remaining balance of 90,447.51 and with $50 extra, $87132.56, a diff of $3314.95. $314.95 return on the $3000. $315 over 5yrs is $63/yr, over an average $1500 put in, 63/1500 = 4.2%.  Of course the simple math of just averaging the payment creates that .2% error. A 60 payment $50 returning $314.95 produces 4.000%. @Peter K - with all due respect, there's nothing for me about time value of money calculations that can be counter-intuitive. While I like playing with spreadsheets, the first thing I do is run a few scenarios and double check using the calculator. Your updated sheet is now at 3.76%? A time vaule of money calculation should not have rounding errors that larger. It's larger than my back of envelope calculation.  @Kaushik - if you don't need the money, and would buy a CD at the rate of your mortgage, then pay early. Nothing wrong with that.
"Can you show me evidence to support the claim that this website is ""checked by multiple sources"" and ""maintained by media reviewers""? Also how is ""it rings true"" anything other than saying it's true because it confirms what I already believe?  From the methodology section of his website:   &gt; **Disclaimer**: The methodology used by Media Bias Fact Check is our own.  It is not a tested scientific method.  It is meant as a simple guide for people to get an idea of a source’s bias.    &gt; MBFC News was founded by Dave Van Zandt in 2015.  Dave studied Communications in college and over the years has focused on personal research in media bias and the role of media in politics.  His expertise is that he studied communications in college.  Communications is a required course in most colleges, giving anyone who attended college for one semester the same level of expertise in that field as him, including me.  Let's see who his contributors are:  Dennis Kelly - Professor of Religious Studies  Dr. Michael Allen - Professor of systematic theology  Faith Locke Siewart - Photographer  Aaron O'Leary - middle school teacher  According to the website itself. None of the content creators on the website have any history or expertise in media, communications, media research or any relevant field. Also, they admit in the disclaimer that their methodology is not a tested scientific method, which means it isnt a methodology at all, and it isn't subject to peer-review or fact-checking like you claimed.   The only evidence for the legitimacy of this website, is that it confirms what people already believe.  You can't get mad about being called fake news when you're essentially using some dudes blog as a source."
"You don't ""prove a model incorrect"". That's not how this type of statistical modeling works. This isn't cognitive dissonance, it's understanding what statistics tells us.   If I look at a model that takes a bunch of inputs from two football teams and the inputs tell me the expected numbers of yards, touchdowns, etc over 1000 different simulations, and gives me that over those 1000 different simulations that 750 of them is in favor of team A. When team B wins this doesn't prove a model wrong in a one shot game, it proves that one of those 750 times out of 1000 didn't occur.   In this case it's especially interesting because, continuing with the analogy, the yardage was almost near correct (popular vote) just the areas of the field that yardage came from differed slightly. This election was, essentially, when one team out gains the other, but loses due to the exact wrong play in the wrong area of the field.   Again, you clearly don't understand how this works, or the definition of cognitive dissonance, for that matter."
I mean, it doesn't really apply to a lease/buy decision in a home.  The variability due to the variables I discussed makes it not worth the analysis when you're talking about return differences of maybe 1-2%.  Even if your house costs $1 million, that's only a difference of $10,000... MAYBE if there's no difference in the other variables, but there will be.  My point is that it's not worth doing.  DCF models are used for valuation of large projects, not simple home buying problems.  There are way better ways to evaluate such a simple problem.
"Let's start by saying that of all the things to solve in a mortgage equation, the rate is the toughest. It's the least friendly to solving with pencil and paper. While I never tire of expressing my love for my Texas Instruments BA-35 financial calculator, it's no longer in production, and most folk won't have access, but Excel is right there.  The financial function pops up for you with RATE as a choice for solving.   I filled in the cells to show the numbers. The -665.30 is a typical convention for money flows as it's a payment from you not a credit for interest you earn. Note, some mortgage calculators leave this entry as positive. It takes a second to see how one's calculation or spreadsheet does this.  Last, you can see the software wants a ""guess."" This is because the software has a loop, guessing and getting closer to the solution. I entered .005 to guess 6% per year. The correct solution is .006 or 7.2% per year.  Class dismissed."
"tl;dr: Your best course of action is probably to do a soft pull (check your own credit) and provide that to the lender for an unofficial pre-approval to get the ball rolling. The long of it: The loan officer is mostly correct, and I have recent personal evidence that corroborates that. A few months ago I looked into refinancing a mortgage on a rental property, and I allowed 3 different lenders to do a hard inquiry within 1 week of each other. I saw all 3 inquires appear on reports from each of the 3 credit bureaus (EQ/TU/EX), but it was only counted as a single inquiry in my score factors. But as you have suggested, this breaks down when you know that you won't be purchasing right away, because then you will have multiple hard inquiries at least a few months apart which could possibly have a (minor) negative impact on your score. However minor it is, you might as well try to avoid it if you can. I have played around with the simulator on myfico.com, and have found inquiries to have the following effect on your credit score using the FICO Score 8 model: With one inquiry, your scores will adjust as such: Two inquiries: Three inquiries: Here's a helpful quote from the simulator notes: ""Credit inquiries remain on your credit report for 2 years, but FICO Scores only consider credit inquiries from the past 12 months."" Of course, take that with a grain of salt, as myfico provides the following disclaimer: The Simulator is provided for informational purposes only and should not be expected to provide accurate predictions in all situations. Consequently, we make no promise or guarantee with regard to the Simulator. Having said all that, in your situation, if you know with certainty that you will not be purchasing right away, then I would recommend doing a soft pull to get your scores now (check your credit yourself), and see if the lender will use those numbers to estimate your pre-approval. One possible downside of this is the lender may not be able to give you an official pre-approval letter based on your soft pull.
"For 3X, it's about 114, and for 4X, 144, which naturally, is twice 72. These are close, back of napkin, results. With smart phone apps offering scientific calculators, you should get comfortable just taking the nth root of a number for a more precise answer. Update in response to Brick's comment. The rule of 72 says that (n)(y)=72 to double your money. It answers both questions, how much time do I need, given a rate, and how much return do I need, given a time? Logic tells me that if 72 is the number to double, 144 is the 4X. But I'm a math guy, and my logic might not be logical to OP. So - Let's take the 20th root of 4. This is the key to use. 4, (hit key) 20, equals. The result is 1.07177 or 7.177%. And this is the precise rate you'd need to quadruple your money in 20 years) Now (n)(y)= 20* 7.177 = 143.55 which rounds to 144. ""Rule of 144"" to quadruple your money. This now answers OP's question, ""How to derive a Rule of X"" for a return other than doubling. One more example? I want 10X my money. Of course I need the initial guess to enter one calculation. People like 8%, in general. It's a bit below the 10% long term S&P return, and a good round number. The Rule of 72 says 9 years to double, so, 18 years is 4X, and 36 years is 8X. For my initial calculation, I'll use 40 years. The 40th root of 10. I get 5.925% (Again the precise rate that gives 10 fold over 40 years) and multiplying this by 40, I get a ""Rule of 237"" which I'm tempted to round to 240.
Of fucking course you do. It's a model. Your trying to develop an equation that represents the distribution of data for a stochastic process.   I have a random source, assuming data samples are stationary how can I develop a model of the distribution of those samples?   One way is to take N samples from that process and fit it to a particular distribution, e.g. Poisson, Gaussian, etc.   Now I have a mechanism to predict further samples from my random process.   Next step, look at the next M samples. Do the N+M samples faithfully fit my model?  No, well then I have a problem with my model. It's not Gaussian, or poisson, or whatever.   This is undergrad stuff...   And the model was clearly wrong. He was off by many percentage points in key swing states.   The cognitive dissonance is trying to bend the world to fit your failed model. What they tried to do was cook the data with a purposely flawed model which used likely voter models from the first Obama election even in the face of continually mounting evidence that the methodology was flawed.
You cannot use continuous compounding for returns less than or equal to 100% because a natural logarithm can only be taken for a positive amount.  This answer includes the accurate way to ascertain r, for which many people use an approximation. For example, using -20% monthly return for 12 months:- -0.2 -0.223144 0.0687195 Checking: 0.0687195 True Now trying -100% monthly return:- -1. Indeterminate Why?  Because a natural logarithm can only be taken for a positive amount.  So the latter calculation can not be done using (logarithmic) continuous compounding. Of course, the calculation can still be done using regular compounding.  For -100% the results go to zero in the first month, but -150% produces a more interesting result: -1.5 -11920.9
Yes, it's a risk. To put it in perspective, If we look at the data for S&P returns since 1871, we get a CAGR of 10.72%. But, that comes with a SDev (Standard deviation) of 18.67%. This results in 53 of the 146 years returning less than 4%.  Now if we repeat the exercise over rolling 8 year periods, the CAGR drops to 9.22%, but the SDev drops to 5.74%. This results in just 31 of the 139 periods returning less than 4%. On the flip side, 26 periods had an 8 year return of over 15% CAGR.  From the anti-DS article you linked, I see that you like a good analogy. For me, the returns of the S&P over the long term are like going to Vegas, and finding that after you run the math of their craps (dice rolling game) you find the expected return is 10%. You can still lose on a given roll. But over a series of a larger number of rolls, you're far ahead.  To D Stanley - I agree that returns are not quite normal, but they are not so far off. Of the 139 rolling returns, we'd expect about 68% or 95 results to be 1 SDev away. We get 88 returns +/-1SDev. 2 SDevs? We'd expect only 5% to lie outside this range, and in fact, I only get one result on the low side and 4 on the high side, 5 results vs the 7 total we'd expect. The results are a bit better (more profitable) than the Normal Bell Curve fit would suggest.
I really like Value Investing by Bruce Greenwald. It's not a textbook so you can probably pick it up for about $20. While it is dense, I think with some patience you might be able to understand it at the undergrad level. The process outlined in the VI book is very different from the conventional corp finance way of valuing a company.  A typical corp finance model would probably have you model cash flows 5 or 10 years out and then assume some sort of terminal growth. The VI book argues that it's nearly impossible to predict things that far out accurately so build your valuation on what we know. Start with the balance sheet. Then look at this year's earnings. Is that sustainable?  This is a simplification of course but I describe it only so you can get the idea. I think it's definitely a worthwhile read.
For younger companies a multi-stage DCF can be employed, where you forecast fairly confident numbers for the next 3-5 years, then 3-5 years beyond that the forecast is less certain, but assumed to be slowing growth, and a generally maturing, stabilizing company. And then the steady-state stage is tacked on to the end. You'll want to check out Professor Aswath Damodaran's website: http://pages.stern.nyu.edu/~adamodar/ . He addresses all this and so much more, and has a big pile of spreadsheets freely downloadable to get you started. I also highly recommend his book ""Investment Valuation"". It's the bible on the topic."
Box plots can also be plotted on the ""interquartile range"" or ""middle fifty""; this throws away the very noisy outliers and constructs a much more regular plot from the inner part of the bell curve. You can reverse-engineer a best-fit line connecting the elements of each box, and the closer two lines are, the more likely the real future data will be around that area (because the quartile between those to lines is very dense; 25% of the values are in a very small range meaning many samples occurred there). Lastly, there are outside factors that are not included in simple percentage growth. Big news must be taken into account by introducing more subjective guesses about future data. If you see an active hurricane season coming (or a hurricane bearing down on Galveston/Houston) then it's reasonable to assume that the price of oil and/or refined oil products (like gas and jet fuel) will skyrocket. A cyclical growth model will not predict these events, but you can factor in the likelihood of a big change with a base onto which you add last year's numbers, and onto that you add regular growth. Conversely, when a huge spike happens due to a non-cyclical event like a natural disaster, you must smooth it out by reducing the readings to fit in the curve, otherwise your model for next year will expect the same anomaly at the same time and so it will be wrong. These adjustments are necessary, but the more of them you make, the less the graph reflects real history and the more it reflects what you think it should have been."
"&gt;If we adopt an all-together conservative approach and control FDP at \gamma γ= 1% (i.e., we accept one per cent of lucky discovery among all discoveries on average or in our sample), we reject all the two million strategies.  I'm impressed that they would release this, as people are often dissuaded from releasing a negative result (""we tested whether X was causing the decline in bee populations, we found it probably wasn't.""). Very important to know though."
It's telling how Taibbi uses numbers like $3.7 trillion (which is the size of the bond market) instead of the size of municipal bonds, which is where the fraud took place (even by Taibbi's own admission), a market totaling $800 billion over years 2007-2008.  He consistently chooses numbers to make his stories seem much more egregious than reality. Reading the actual case PDFs shows a much smaller, less well orchestrated fraud than Taibbi's pablum.
Here's the original academic backbone that it's based on and expanded upon.  https://en.m.wikipedia.org/wiki/Modigliani%E2%80%93Miller_theorem  I think thats it's overly conservative in this case (I fully accept academic theories only go so far in the real world) as Damodaran (NYU professor) has made a pretty solid case that cash on balance sheet at large cap tech companies is valued by the markets at less than its after tax $ value.
"Your questions In the world of technical analysis, is candlestick charting an effective trading tool in timing the markets? It depends on how you define effective. But as a standalone and systematic strategy, it tends not to be profitable. See for example Market Timing with Candlestick Technical Analysis: Using robust statistical techniques, we find that candlestick trading rules are not profitable when applied to DJIA component stocks over 1/1/1992 – 31/12/2002 period. Neither bullish or bearish candlestick single lines or patterns provide market timing signals that are any better than what would be expected by chance. Basing ones trading decisions solely on these techniques does not seem sensible but we cannot rule out the possibility that they compliment some other market timing techniques. There are many other papers that come to the same conclusion. If used correctly, how accurate can they be in picking turning points in the market? Technical analysts generally fall into two camps: (i) those that argue that TA can't be fully automated and that interpretation is part of the game; (ii) those that use TA as part of a systematic investment model (automatically executed by a machine) but generally use a combination of indicators to build a working model. Both groups would argue (for different reasons) that the conclusions of the paper I quoted above should be disregarded and that TA can be applied profitably with the proper framework. Psychological biases It is very easy to get impressed by technical analysis because we all suffer from ""confirmation bias"" whereby we tend to acknowledge things that confirm our beliefs more than those that contradict them. When looking at a chart, it is very easy to see all the occurences when a certain pattern worked and ""miss"" the occurences when it did not work (and not missing those is much harder than it sounds). Conclusions"
Nothing you posted addressed anything I wrote. We can't know the future warming without knowing climate sensitivity (the multiplier factor) We don't even know if that is positive or negative. Here is a direct quote from the last IPCC report:   Page 11:16 “No best estimate for equilibrium climate sensitivity can now be given because of a lack of agreement on values across assessed lines of evidence and studies.”  Does that sound like 97% consensus? Does that sound like settled science upon which we should act?
Nothing is guaranteed - candlesticks are not crystal balls nor is any part of technical analysis. Candlestick patterns used correctly and in combination with other western technical indicators can increase the probability of a trade going into the derived direction, but they are not a guarantee - which is why you should always use stop losses with your candlestick or any trading. In saying that, another candlestick pattern that can provide high probability trades is the Doji, or a combination of Dojis in a row at a market extreme. Note that both Engulfing patterns and Dojis work best at price extremes (highs and lows) and in combination with other technical indicators such as an overbought momentum indicator at a market high, or an oversold momentum indicator at a market low. EDIT - An Example Here is a sample trade I placed on the 17th October and am currently 15.6% in profit on. See the chart below as it shows taking the trade on the open of the following day after a bullish engulfing pattern appeared at the bottom of a downtrend on the 16th in combination with the Slow Stochastic crossing over in the oversold region (below 20%). I would consider this a high probability trade and have placed an initial stop loss at 10% below my open price in case the trade went against me. As the price moved up I moved the 10% stop loss up as a trailing stop loss. My profit target is set at 25% or $4.00.
The only issue I have is with 4).  *Caveat emptor* always applies, and even if you accept the notion that S&amp;P was *criminally* misrepresenting bond quality, Fannie/Freddie still must do their own due diligence, and so I don't think they are off the hook here.  At worst, the execs running Fannie/Freddie are also guilty of criminal collusion; at best, they are guilty of massive incompetence.
Chances of success are very good, actually.  They are not a religious organization, they're a business.  You simply can't do this.  Note that the EEOC is representing the guy directly.  That doesn't happen unless after an investigation of a complaint, the EEOC decides there's a clear problem.  That happens RARELY.  The EEOC will only pursue their best cases.
When I was in grad school (at an engineering school) my apartment-mates and I came up with this formula: Worked marvelously.
How can you correlate a company stock's performance with overall market performance. No you can't. There is no simple magic formulae that will result in profits. There are quite a few statistical algorithms that specialists have built, that work most of the times. But they are incorrect most of the times as well.
Let's base teacher performance off of student value added growth scores!  Surely nothing bad will happen when we create incentivize teachers to make sure that student performance continuously rises.   I mean, Campbell's law is just a load of horseshit, right?  It's not like these policies led to widespread test cheating in Atlanta and Washington, DC, and several other cities.   In all seriousness, look at what happened in Washington, DC.  Student performance was used as the metric by which the district meted out both the carrot and the stick: the $160k paycheck or dismissal.  103 schools out of 200 or so were found to have statistical indicators of cheating, in some schools nearly 100% of tested classrooms were found to have wrong-to-right erasures in statistically aberrant levels.  This wasn't found out until years after these test scores were used to evaluate a whole crop of teachers. Suppose you were the teacher whose children had previously been scored by cheating teachers or administrators.  The model used to evaluate you expects that these children will see test score growth of *x* percent each year. If you don't cheat, you will get fired.  If you do cheat, you become eligible to get a shitton of money.  All that aside, the debate shouldn't even be about using student performance to evaluate teachers.  The debate shouldn't be about who gets laid off.  The debate should be about how we prevent teachers from getting laid off.