Welcome to Investing for Beginners podcast, this is episode 73. Tonight Andrew and I are going to talk about Wall Street study pitfalls, this is based on a book that Andrew is a big fan of by James O’Shaughnessy and we’re going to talk a little bit about some of the potential pitfalls that you may run into.
We’re going to start off by talking about data mining and I think the easiest way that I could explain this was a metaphor that James used in the book and he talked about if you’re in Grand Central Station which is obviously a very large place with lots and lots of people around.
If you find a specific area that has let’s say you go into one too but where one of the trains is running and you see 75 percent of the people there are blonde then you would be potentially thinking that hey everybody in Grand Central Station is 75 percent blonde and that’s not actually the case.
It just happens to be at that particular time at that particular place that you find that and so the data mining is something that if you’re doing Studies on different Wall Street things you different factors of looking for let’s say you want to buy stocks on a Wednesday every 16th month well that’s not necessarily that’s data mining because you feel like you have to only buy stocks on a Wednesday on the 16th of the month.
And that’s it could lead to a lot of pitfalls and okay that means dude but I mean.
Andrew: that’s now uh that’s part of I think having tests that look at history you have to be very careful I think when it comes to studies in general and I’m sure you can extrapolate this to things outside of Wall Street and it’s very easy to take facts and weaponize them and make them sound like basically a way to advance your own agenda and you can manipulate statistics to do that.
And so as investors who are looking at studies we like to talk about all the time on this podcast about how let’s learn from history. History might not repeat it might look different every single time but we know that there are some core things are true history mostly rhymes.
We have bear markets who have bull markets we have prosperity we have times where things tighten up credit expands creditor contracts these are things that we’ve observed over time and it’s recorded in written history. and so we can kind of see that this is how markets tend to work this is how human behavior tends to work and we can come up with a lot of different lessons from how this stuff all kind of works and we can use it in our investing.
Something like data mining though is definitely a huge pitfall to be aware of. like you know I love that Grand Central Station metaphor if I were going let’s say I was a tourist to America and the first tourist thing I did was I went to an NBA game right and then if I just thought that the players on the court were a representative of the entire United States I would think everybody’s above six five.
And you can do that and see that through a lot of different studies when it comes to Wall Street and you have to be really careful and look with a watchful eye. That hey there’s going to be things that you’re going to find out and this is true whether it’s a Wall Street study whether it’s something you’re kind of embarking on your own. And it’s very easy we talked to him a previous episode about biases and how it’s very easy for certain things to kind of skew your understanding of how the market really works based on your own skewed perception.
We all view the world through our own unique lens and so it’s our own experiences and our own things and lessons we’ve learned that is tainting whatever conclusions were coming up with. It’s very important to have a skeptical eye with that and so on the one hand how we always talk about let’s look at history let’s learn about it. On the other hand I think we need to address some of the things that maybe can be a little bit of a too quick of a conclusion and data mining is part of that.
When you mentioned data mining they’ve had something come to mind it’s a really fantastic book and I haven’t read it in years so nobody don’t come up with pitchforks and start saying that I’m crazy or I’m wrong whatever but I generally remember Martin’s Zweig Winning on Wall Street.
I believe he had a chapter where he talked about some of the I think it was very similar to that phenomenon right about like assigning to a particular day in the week but I think it had something to do with a particular month and so there were people who really believe this that whether it was based on tax reasons I think I had something to do with like selling off at the end of the year like in December and buying up in in January.
That there was like a lot of years that kind of in parallel showed this trend where it seemed like particular month was a better time to buy or sell I think that’s a fantastic example of taking something like data mining and taking these occurrences that might just be coincidence and really trying the form of an investment strategy based off of that I don’t think is very prudent it and I think it’s very important to can stay there and make sure we’re not doing that like let’s look at the big picture and not look at something so limited like data mining.
I always I don’t know if this is like necessary the smartest approach in the world or not but I always like to come up with observations. But I also I always want logic behind it if that makes sense.
When I looked at the bankruptcies way back in the day and I was this was before I like completely formulated the value trap indicator. I was just really looking at a lot of different companies and a lot of different stocks a lot of different financial statements.
And when I chose to look at the bankruptcies I kind of when I approached it with a very open mind and I just wanted to see like are there any similarities right try to try to remove the bias as much as you can don’t come in with an agenda and instead come with a clean slate and then observe the data yourself and see if there’s something that stands out.
So when it came to the bankruptcy stuff I noticed that more than 50% and I ended up being really high but definitely more than 50% of these stocks had negative earnings in the year before bankruptcy. And so A I saw that and I was like okay well that’s obviously seems to be a pretty relevant data point but B I started to think about that logically like what would be the reasoning behind this.
Is it because Wednesday people are more happy or it’s hump day and so they’re happy does that make sense logically whereas with a stock that has negative earnings well you think about what what’s why are businesses in business why dumb investors buy stocks why do they become part owners of business and what’s the what’s the function of a business is to create profits is to create earnings and us to pay out dividends and how do you pay out dividends you do it from earnings.
And so once I understood that I was like okay that really makes a lot of sense to me and that’s where I can kind of see a relationship with the data making sense and being a practical application that I can use to make a conclusion that hey I mean I took it all the way right like I avoid any stock with negative earnings like the plague.
But you don’t have to take it to that extreme you can say hey I have this finding that I found from looking that data I found it to have some sort of significant implication on there’s some sort of relationship there. And so at least it’s going to make me take a closer look at the stock and understand that this is probably something that is in a way more correlated with bankruptcy so maybe I’m going to keep a more watchful eye on the stock.
And I think you can do that not only with just kind of the way I’ve done it but with all sorts of different ways that you try to look at the market I look at the history of stocks and when you’re looking at any sort of academic study or anything really that’s written in the book or on the blog post on the news article these are all things that I think we need to consider and really just think from a logic perspective and try to think it through.
I don’t think it needs to be necessarily super complicated a dealer either like with the data mining it’s pretty simple is it just seem to be like a random thing or maybe is there a possible reason behind it just keep that in mind.
Dave: excellent alright moving on to the next topic a limited time period Andrew want to go ahead and take a stab at that one
Andrew: yeah so when we think of limited time period with the stock market stocks investments it’s really hard because there’s a big disconnect between what happens with investments and our kind of every day to day life.
You think about pretty much anything else a lot of different things in life right like everything happens super-fast especially in this day and age you want to like you want to have some sort of say a piece of furniture in your house you go to the furniture store you can have it delivered to you the same day or you could order it online have it to you in the period of a couple days you want to decorate your house completely you want to have that like that’s a problem and you want to find solution you can you can do that very quickly.
You can do a lot of different things pick up a lot of different skills and you can do that almost instantaneously you can find the answer than anything instantaneously. Welcomes the stock market and it comes to the way that things have historically appreciated over time the way that returns have really been made by the market it’s really been a very long time period.
And when people think of long term investments they might define it as holding for a year and that can feel like an eternity especially you know especially when you’re starting out. Our podcast is really geared towards people who are beginners it’s very I can relate 100% because I was there it you want to buy stocks and you want to see them payout a hundred percent yield on cost you want to see that reinvest a dividend it’s appreciated seventeen percent in a year you want to see that now you learn about it and you want to implement it right away.
And then the reality of it is you learn some stuff you buy a couple stocks and you have to wait and in two months you saw the stocks that you thought were such great values go down in value and then you have to wait some more and then maybe in six months it’s kind of gotten even with where you bought it.
Within a year you’re kind of disappointed and maybe moving on and thinking about other things and then finally when you’ve forgotten about it two and a half years later you finally see the results and you can see this especially happening with value approaches where you’re buying stocks that are hated and they can take a long time to get back to their real intrinsic values.
Even two years three years five years ten years that in the investing world that’s really a small time period and you can see this if you look at different studies about the stock market in general.
I’m in the middle of a great book right now it’s called it’s called Bull I want to say there’s there has to be more than the side of the book is says it’s bull with exclamation point it’s by Maggie Maher and she really just kind of breaks down the history she comes at it from a journalistic approach which i think is it’s cool makes it fun to read.
But she goes through a lot of the history of the stock market a lot of the history of some of the bull markets we’ve seen and it has some data in there too which is really fun to follow. And I mean she kind of takes I feel like she doesn’t really concentrate enough on like reinvested dividends and how some of these returns might have been fine for investors who are really in the long term.
But it’s somewhat of a pessimistic kind of outlook for the book but it’s very interesting to see that there are very many time periods where returns were not what people wanted or expected or even you would argue maybe or even worthwhile.
You can look at the Japanese stock market they still haven’t recovered from the 80s right and so you can take different time periods within the United States history where a five or ten year period the stock market either broke even or the stock market lost money. And so you can understanding that you can take the same approach to any sort of study that’s looking at any metric or any kind of conclusion any business detail that they’re observing any anything really.
It’s just you know it’s something that the stock market and returns they take a very long time you have to look at things through averages and you have to understand that these average returns that people talk about I talked about right 10% year these things are over very long time periods and not there’s no guarantee that just because you’re looking at a five-year time period that that’s going to be something that ends up being what you’re looking for or the kind of result is guaranteed.
It’s important when you’re looking at these things to not have those sorts of expectations up front. again I’ll say don’t take that as something negative I think a lot of good can happen even in time periods where the market kind of goes flat or negative. When you’re reinvesting dividends when your dollar cost averaging a lot of that stuff doesn’t really matter and we talk about it a lot and I hope that doesn’t get lost.
However when you’re looking at a study that’s examining companies with certain growth rates or examining certain business characteristics or certain trends right like momentum kind of comes to mind trend following comes to mind any of these things can do really well maybe you’ll volatility index does really well for a certain number of years. Something based on the interest rate could do very well for five years a come on anything could do well for five years.
These a lot of things can do really well and that doesn’t necessarily represent a reliable long-term return for the average investor so again like be very skeptical be wary of something that’s looking at a very short time period.
As I always do right I guess something that you could say in ten seconds I said in five minutes but I hope that was helpful and something to keep in mind too when you look at these studies do not limit yourself to making some sort of conclusion just because it’s had success it really needs to be something more like the tourists in the hair where it’s consistent and long-term and not something that just happened to have a hot streak maybe happen to have a lucky kind of run or for whatever the political or the business climate was that strategy happens to do well.
It really needs to be something that’s its much more longer and substantial than that.
Dave: I agree and I think those are all great points and no you are not you are not going on too long I thought that that was really good and I guess one thing that I like to maybe tag off of what you were saying was when you’re looking at a limited time period I like to think of it as so you guys all know I’m a baseball fan. Andrew and I play fantasy baseball well one of the things that sometimes you can fall into with fantasy baseball is you can get wrapped up in a guy that’s having a hot streak and maybe he’s playing really well for a two-month period and you get wrapped up into this particular player.
And so you put him on your team expecting that to continue and if he doesn’t have a history of that let’s say the guy is played in the league for five or six years and this is the moment in time where he’s actually lived up to his potential for a couple months.
You have a choice of deciding at one point at some point whether that is actually going to continue and he’s made changes in his approach that allow him to be successful and allow his talent to shine through. Or if it’s just a matter of he just got hot for a little bit of time in his athletic town is just taking over and it’s not really an improvement.
And when you look at that you also have to look at underlying factors that maybe are causing this to happen like in baseball geek terms maybe he’s hitting a lot of balls and they’re all falling in for hits which is unusual. And that’s not normal for him maybe he strikes out a lot not right now he’s not striking out a lot there’s a lot of different factors that can go into that.
And so when you’re looking at us at a stock you also have to think about a company that you’re going to buy you have to try to look at like Andrew was talking about you have to look at a longer enough time period that you can establish a pattern and a history of what the company has been able to do with their performance and if you get caught up into a shorter time period because you’re going into it with a bias.
When you’re looking at six months a year a year and a half there may be other factors like Andrew was mentioning but the political factors the economic factors that are causing that company at this particular time to perform better than they maybe should have or normally would have.
Let’s say management has changed or not changed I mean these are all different factors you have to take into account when you’re looking at why something is happening and if you look at a longer time period it’s going to give you more of a consistency of why this is happening and you can take any company you want and there’s going to be ebbs and flows of course throughout the time period.
And let’s talk about real quickly let’s talk about Microsoft for example Microsoft has been around for a long time and when they first came out they were kind of the darling of a stock market they were kind of the leaders of the tech world and then for a while things shifted. and they were not they were boring and they were kind of a kind of and that a has-been that’s maybe not the right word for it but there may be forgotten a little bit and they were kind of ignored and they weren’t really looked upon as a leader in the industry.
And over the last few years they’ve you know had management changes and they’ve done some different things to try to invigorate the company again and they’ve seen success course the stock market has embraced everything they’re doing and it’s you know the prices quadrupled in the last four or five years.
Now does that mean that necessarily the company is worth that price those are all their consequences and considerations you have to take into account but if you look over the long history of the company they’ve been a good company they’ve done a good job is it worth the price it is now that’s for another discussion for another day.
But I think what I’m trying to get at is you need to look at a long period of time to understand you can’t just cherry-pick hey this stock is doing great for the last year and a half I’m going to buy it now.
And it may be doing great for a year and a half because of other reasons and that’s why you have to always make sure that you do your due diligence and check all the different factors that could be causing this to happen just like with a baseball player you got to pay attention to what’s causing that you know just because the guy had a great two months last year doesn’t mean these made changes that are going to continue in cloud to continue that for the rest of the year it happens all the time every year and it’s just it’s part of the fun of the sport and it’s also part of the challenge with investing with stocks.
Andrew: I love that he brought Microsoft to I mean I remember when I got in the stock was flat for years and people were worried about the iPhone and Apple completely taking over everything right and after the stock does well then people like well obviously Microsoft was going to be fine there and every business could be there.
It’s like when there’s constantly changing depending on how the stock did the year prior.
Dave: yeah exactly yeah exactly all right moving on to the next one we got micro-cap stocks allowed Andrew why don’t you touch on that?
Andrew: sure so there’ll be some studies and again these major points we’re getting from James O’Shaughnessy’s book sometimes you’ll see back tests or studies showing data and including super small stocks micro-cap stocks maybe stocks that people wouldn’t have normally considered and so if you can’t reasonably consider it then it shouldn’t really be made – it shouldn’t be used to make a conclusion.
There can be stocks with market caps are so small that whether you’re institutional investors have certain requirements on what size of a stock you can jump in into what size of sake game and by there can be liquidity issues we talked about and we’re back to the basic series how the core function of the stock market and the way that stock prices work is a series of buys and sells and if there’s no buyers on one side their sellers on the other side liquidity is really not there.
Then can make it very difficult to execute trades or you’ll get weird spreads a lot of different problems with that and a lot of you know I’ve liked a lot of institutional managers just based on the way that their funds are structured they just can’t buy into a lot of these micro-cap stocks.
It’s almost like the findings won’t apply to you if you can’t implement them right and you can say this similarly with the retail or the average investor if it’s if they’re including stocks that are like over-the-counter traded how many of us are really going to go and buy a stock that’s not on the NYSE or is not on the Nasdaq.
I think to use those results now all of a sudden you’ve kind of muddled the water may have made it all dirty and so it could skew the results because a micro-cap stock here there could really be driving a lot of the returns that you might see and so it might make a certain strategy look better than another just solely based off one or two outliers that are really carrying the results.
And I think just in general you can see a lot of volatility with micro-cap stocks. I personally try to stay away from micro-cap as much as I can I guess not even try all right like I’ll do it in the fun money account but when it comes to my IRAs my retirement my money that matters I don’t generally go over two billion in market I mean under two billion maybe I’ll dabble and like anything above a billion.
But definitely nothing below a billion dollars I’m definitely not getting into the micro-cap kind of capitalization space and for a lot of those reasons.
You have to think to when it comes to a market that’s so in its infancy and growth stage when these companies are so small that they’re their stocks are trading at such low market capitalizations that they’re not even above a billion dollars. A lot of these industries are just very just barely beginning and it’s going to be a couple it’s going to be maybe one of two things as the markets so young that any little thing can happen to make one person kind of come to the top and it’s going to be it’s going to be unpredictable and past financial results are not going to be as an in the indicate –iv of future results when things are so rapidly changing.
Or be the stock could be such a small fish in a big pond that they are so small and there’s such other big competitors that they could a competitor can sneeze and they can really wipe a stock out and so with a lot of volatility where you could see like a hundred bagger you can also see a lot of just wreckage that could happen with a lot of these micro-cap stocks.
A lot of different reasons and that’s something you’re going to have to be wary of right like what where is this data set coming from what stocks is this study looking at and are they excluding micro-cap stocks are they and O’Shaughnessy they do a lot of great research reports that they’ll publish especially lately.
And they have done their back tests and their studies to account for micro-cap considerations liquidity problems stuff like that but you want to keep that with a vigilant eye and even when you’re reading like a blog post or an article. they might cite some academic study but if you don’t go and actually click on the academic study and see what kind of data sets going in well you have garbage in garbage out if micro-cap stocks are skewing the results and it’s really making something that hits your bias but might be concluding something that could be not useful for the average investor.
Then it could be something that really leads you to making poor decisions in the future so it’s definitely just another thing to keep in mind.
Andrew: yeah I really like that that’s a great way to put that alright. so next one we get that survivorship bias Andrew once you go ahead and take a stab at that I know that’s one of your favorites well I’ll keep it short this time because we’ve definitely covered this before but when you look at a back test right just doesn’t make sense if you look at 2018 stocks and you look at stocks that were there in 1998 you can look at all the stocks that are there in 2018 they’re all alive right it’s obvious but if you don’t account for the stocks that went bankrupt your account for stocks that maybe got acquired then you’re not looking at what really happened.
So you want to make sure that when there’s any source study any sort of back tests that they’re accounting for survivorship bias and this is very easy to do.
All you got to do is pick a stock let’s say Apple cross the trillion dollars well that must be a great stock so let’s look at it in 1998 let’s see what it did and whatever it did in 1998 that’s what we should do right no wrong that would be a terrible way to go because of survivorship bias because there could have been five stocks back in 1998 that looked exactly like Apple. But Apple just happened to be the one stock that beat all the rest because I had such a game-changing product like the iPhone.
That’s something to definitely keep in mind make sure you’re looking at and you’re accounting for survivorship bias because there can be data sets right like we could do it right now just going on Google you can you can take all 500 stocks of the S&P; 500 today you can put them on the spreadsheet and then you can and.
I’ve done stuff like this before where I’ll take a group of stocks and then I will look at what their past was but you also have to consider that these are the stocks that are still alive there could have been other stocks back in let’s say 1998 that looked at this that looked the same but you won’t see them today because they’re now dead right and either they got acquired that there and their name changed or they just straight went bankrupt.
so you always want to be a common for survivorship bias make sure that any study that you are trying to draw conclusions from anything in the research you’re doing on your own it’s accounting for survivorship bias and you will make much better conclusions if you do that.
Dave: that was excellent and I really like the way you put that and one of the ways that I think about this is think about your own personal portfolio.
Let’s say that you have a company that’s doing very poorly and you decide to sell the company and then you look at your returns and all of a sudden they go from let’s say I’ll just pick a number 25 percent and now a sudden because you dumped the company that’s dragging you down. All of a sudden you’re a 38% and you’re like sweet I’m kickin but this is awesome.
But you can’t really take that into account because you had that other company that you invested money and that lost money that that was down from where you bought it so that really it has to be considered into the study when you’re looking at it.
Because when you’re looking at your own personal return you put your money in there you put a hundred dollars in there and it went down to 72 dollars well you lost 28 bucks you’re not getting that back even though your personal account may show that it’s higher now because as you remove that other company.
The same thing applies to these stock market studies that can be done if they do not account for such as such a company going bankrupt or being negative for a long time or being swallowed up by another company. Those all things can affect the overall return and can buy a make a bias for you about that study and so that’s important to consider those ideas when you’re thinking about this.
Andrew: yeah 100% I like that that parallel to like the practicality of how we might do it ourselves anybody might do that very easily even if you’re not like an academic looking at studies.
Dave: yep I agree so all right the next one we’re going to talk about is look-ahead bias.
Andrew: yeah and the last one too I think it’s going to be a great I think Jim just kind of put this perfectly so he said you can assume that fundamental information was available when it was not and that can be a big drawback.
For example if you have a study that’s looking at well I was going to buy companies that had certain earnings this year and then I was going to buy at the first of the year right if in reality so he says like assuming you had annual earnings data in January but in reality the data might not be available until March then that’s going to bias your results.
And that makes sense too right because if you can’t look at if the information wasn’t available but maybe whatever computer set or data set you’re looking at isn’t taking it into account when everybody’s annual reports are being released then that can you might be getting into a stock a year or a couple months early.
Every stock will report their earnings differently I keep a spreadsheet this house keep me organized when it comes to figuring out when I need to update my kind of views on where every stock I own is going. You’ll have stocks that will release their annual reports in January February March almost every year some of them might do might share years but share months I’m sorry.
But it’s all going to vary and it’s something to keep in mind and you want to make sure that you’re not making mistakes like that. for example when I looked at again back to the bankruptcy data I made sure to only look at what was available on SEC.gov to my knowledge and from what I’ve kind of what I’ve taken from what I’ve seen from people in other books and stuff they talked about having to either use like a Compustat or maybe a Bloomberg terminal or going and actually buying annual reports the sec.
Before sec.gov which is a website if you’re beginner and you’re not aware of this it’s a website where you can look at you can pull up any company’s financial information and 10k aka annual report pretty much all the way back to like 1994 1995.
But before that website was up and running you had to call a company you had to maybe pay five ten twenty I don’t know what the amount was. I wasn’t in the stock market back then but however much the money was you had to pay it in order to get access to these annual reports these ten K’s.
And so when I did my research on the bankruptcy data I made sure that it was all available in sec.gov because that would be something that is kind of uh would have been readily available for somebody who might have been either buying these stocks or getting out of them before they went bankrupt right.
You always want to make sure that whatever it’s happening in the future is not kind of affecting what your possibilities with a bin like it would not be fair for me to look at a stock that’s already bankrupt because they’ll file annual reports and 10k is even after bankruptcy because I mean I don’t really know what the reason is but I don’t know whether it’s because they’re settling debts of bondholders or whatever reason the government’s making them file 10k is even after the bankruptcy.
It wouldn’t be fair to me to say that I’m doing research or I am trying to figure out what’s happening with certain stocks that happened what kind of lessons going to make from the past and taking like annual reports that happened after the bankruptcy.
If I’m really being fair and honest and sincere with trying to keep all the data as accurate and as conclusion bearing as I can. Well then I would be looking at 10 KS that happens after the bankruptcies and not before and so that’s kind of what I did I made sure any 10 K I looked at was prior to the bankruptcy and after any bankruptcy filing had happened.
And so you can really try to get a sense of what investors were feeling at the time and you can’t replicate it perfectly I don’t think any study can really do that a hundred percent. but if you can try to do that as much as you can and if a studies not doing that it might be kind of hard to catch. But that’s definitely something to keep in mind.
I mean it only makes sense right like if the annual reports are available till September but you’re buying it in January because you have this study that’s buying a certain criteria every year they’re not accounting for that nine months that the stock could have appreciated because in reality investors are maybe they’re getting quarterly reports this is maybe more relevant today where we have information that’s just coming at us every second.
And quarterly reports are analyzed like they’re the holy grail of investing and Wall Street. But there could have been three months of quarterly reports that really showed that this would be a really strong year but if you’re an investor who only buys off annual reports and 10k is kind of like the way I am.
Then it wouldn’t be fair for me to back test a strategy where I’m buying before those nine months happened before those three annual or at least those three quarterly reports can kind of make their move you know I’m getting like a free kind of gain inside those nine months.
And that’s just not fair and that’s just not realistic and it’s not something that you can reliably replicate in the future. So you want to try to put yourself put yourself into the shoes of somebody who’s like in the past try to eliminate as many kind of deterrence I think that’s really the whole point of this episode.
Try to limit anything that can really cloud the decision making that you and make in the past really just put yourself in the shoes of somebody who with whatever data they had available in front of them at the time would look at that data and make a reasonable decision on what they would do with the stock in the future and when you’re looking at the past try to do that as much as possible and if you can like.
I’m becoming more of a history buff like the more I get into this investing stuff where I used to how about you but like in high school I would just sleep through history classes it was just so boring to me but like as an investor trying to get a gauge of how just the cultural kind of pulse was and what the temperature was like and how people really felt and what kind of influences were really affecting their decision making.
I think it makes for a really cool kind of deeper understanding of what it would be like to be an investor at that time and how much conviction you would need to really make the types of decisions that would lead to long-term success on the stock market because it’s so easy to plug in an algorithm and just assume that we can all act like robots and just invest on these one or two criteria or metrics.
It’s much harder to actually do what that what the right thing would be at the time. A lot of value investing is going against the grain going against the crowd being in a contrarian investor and buying low and selling high. And that’s a lot harder to do in reality then in theory and I think that’s something that when you’re taking lessons from the history of stocks in the stock market if you can account for that as much as you can.
Then you can really separate the wheat from the chaff and really clean out the most important and valuable lessons from history and use that and your best ability to really help your results moving forward.
Alright folks will that is going to wrap up our discussion too I hope you enjoyed our conversation about Wall Street study pitfalls. I thought Andrew had some fantastic points tonight and really kind of hit the nail on the head about all the different biases and different things that we need to take into consideration when we’re looking at studies and how they can affect our investment decisions.
This is something you really need to think about when you’re considering a company to buy.
So without any further ado I’m going to go ahead and sign us off you guys go out and invest with a margin of safety emphasis on the safety have a great week and we’ll talk to you next week.
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