How to make decisions like a poker player
fronterablog.com
fronterablog.com
In real life the best marksman can get wiped out on the first day of a war, the best business strategist can get done in by a once in a generation disaster, and a hapless idiot in business can get an early big break. And so on.
I feel like it feels much more natural and intuitive to us to play games that are a mix of skill and random chance.
In truth, managing randomness is actually one of the core skills of the game. Not just on the decision in front of you, but on future decisions as well. It's a hard skill to master. Moreover, the timelines to evaluate one's skill are long, sometimes hundreds or thousands of games, incorporating tens of thousands of decision points. It's not a wonder it's often misunderstood.
Except that Magic: The Gathering is particularly bad for locking into specific "meta" (metagame) which then persists until new cards come out/old cards rotate out. Hardly random and hardly difficult to master.
The best MTG players are really good at what I call the "game mechanics corner cases". The know all the weird ways to play and resolve the cards--this gives them a quite persistent couple percentage point advantage.
However, it won't give them enough advantage to beat the "meta".
The thinking like a poker player is mostly about being upfront about your risk tolerances and then having a culture supporting people who make the best risk adjusted decision, even if it doesn't work out.
Expected Value is complicated because a 50% chance for $100 is the same as a 10% chance at $1000. It's the variance, not the EV that makes a lot of decisions hard.
You (and businesses) need to decide what risk is acceptable, communicate that clearly. Reward people who manage risk in a way that's aligned with the business even when it doesn't work out. Get rid of people who are either take too big risks, and people who don't take risks.
Is it though?
1 in 2 for the first one will pay out. and 1 in 10 for the second one will pay out.
Variance is higher for second than for first.
"50% chance for $100 is the same as a 10% chance at $1000"
should be
"50% chance for $100 is the same as a 10% chance at $500"
But that is when the payoff is 1, of course!
When it's not, we're really looking at payoff² * p * (1-p) and indeed the second situation has much higher variance.
Again I ask, is it really?
Reminds me of: https://en.m.wikipedia.org/wiki/Chinese_word_for_%22crisis%2...
The alternative to getting rid of these people, is offering positions to them that better match their risk tolerances.
EDIT: I see someone else noticed this further down than I looked in comments, sorry for dupe.
They use expected returns in conjunction with size of current pot and size of current holdings.
What you say about variance is right on. It involves the payout and the odds and so on ...
They use something internally like the Kelly Criteria, probably tuned against their own model of what is the probability of each relevant outcome.
The odds of winning a hand with a future card in order to estimate the call's expected value.
Future cards have significant impact on odds and betting.
If you have not yet made your hand (e.g. only 4 spades) then you consider your drawing odds, which is the chance of making your hand.
But say there is a pair on the board. Then you need to consider the probability that your opponent has or will make a full house, which would beat your flush if you were to hit. Likewise the probability that someone will have a higher flush than you.
Analyzing this in aggregate is what gives you the expected value, which is what poker players consider.
If you are simply playing a cash game with unlimited buy-ins. Then assuming your overall bankroll is sufficient, you will always make plays with positive expected value, even with high variance, because it is a continuous game and you expect the total return to be positive over sufficient iterations.
If you are playing a tournament with a set number of places in the money, then you need to take into account the variance as well as the expected return because it is an episodic game and the types of plays you will make will depend on not just expected value of the single play but what place you are in currently and the number of players left.
Implied odds are interesting in that they can make very bad hands more playable because if you do hit, then the likelihood that your opponent believes that they are winning is higher (because the chances of such a bad hand being played rather than folded immediately should be low) and thus the probability that you can elicit more money from them is higher.
Small pairs and low suited connectors are good examples of these kinds of hands. Your pre-flop chance of winning with a pair of 2's on a full table is pretty low. But if the flop is 2-K-A, you will likely get a lot of action.
> ~15k hands last month.
Is that not roughly a full-time jobs' worth of poker? (15k hands > 12k minutes? > 200 hours > 6h/day)
I can play up to 12 at the same time, but my play suffers and I don't feel like I'm able to focus and get better.
The key to this idea, which I don't see covered in the blog post, for making future decisions is that you shouldn't let past bad luck affect your future decisions. If you lose a positive EV bet, it shouldn't shy you away from making the same bet again.
Some examples off the top of my head about decision-making traps people could make: - Continuing to bet at the roulette wheel to "regain" what you've lost - Not going to a well-rated restaurant again just because you had a random bad experience - Not investing in ETFs after being burned by past downturns - Playing MTG and not burning them out just because they had a counterspell last game
Helloooo Japan!
ETFs are great, it will never happen to the US economy :)
In other words, based on market behavior from multiple countries, it is definitely a possibility that ETFs won't return much in a period of 30 to 40 years.
However, the example is simply wrong (IMO) since it assumes that within a 30 year timeframe you'll have gained 8% on average (adjusted for inflation). If this would be true, thne yes it would be a decision-making trap. I think that's what morley is getting at.
I'm arguing it's a tough sell that the S&P 500 works like that. If one would agree that the S&P 500 might not continue to give 8% ROI on average over a 30 year time frame, then one might consider doing something else with their money. For example, maybe it's more fruitful to invest in yourself to upskill even more rather than putting your money into the markets. I don't know I haven't researched it, I myself try to beat the market, it's a fun endeavour. The jury is still out.
Such that, if the "burn rate" for my household today is $60k/yr, and I store $60k in investments, then when I withdraw at some future date $X will still be enough to support my household for a year.
Physical cash is terrible but to an investor, "cash" tends to mean something like t-bills, which over the past century have done slightly better than inflation. Gold is horrible if you have too much of it, but it tends to do well in equity crashes, so mixing in a little can be helpful. Bonds also sometimes do well when stocks go down, though I think that's more likely when you start at higher interest rates. Commodities can have 15-year bull markets independent of everything else. An investor in Japan would have done fine if they had a lot of foreign stocks. Etc.
https://www.google.com/finance/quote/GLD:NYSEARCA?comparison...
10 year Treasury outperformed NASDAQ https://www.google.com/finance/quote/GLD:NYSEARCA?window=YTD...
That's diversification, even if it just means losing less.
Had this happen at work recently and shapes why I was ok with the outcome even though it wasn't what we wanted.
I was building an integration and got it working and trying to push to Prod when I realized the integration with the 3rd party required a security audit... Given the information at the time, it was the right thing to build but didn't do deep enough research. Lesson learned.
A major one is how we tend estimate probability. We naturally do that by equating it with how easy it is to imagine or remember it happening. This worked well in a tribal situation where our world was very small...if Grog got attacked by a tiger, there's a good chance that tiger attacks are a serious danger that I should consider. But this breaks down in the face of a global society of billions of people and a media that profits from making people afraid. Rare events get magnified by media attention and feel, to us, like they're incredibly likely. Plane crashes are incredibly rare. Even in a plane as fundamentally broken as the 737 Max was, passengers were safer traveling that way than by car. But since every airplane crash is covered extensively on the news whereas car crashes rarely merit a mention, people's primitive cognitive quirks kick in and they're more afraid of flying. You see it with mass shootings too. Even if you get 1-2 per day in the US, that's still maybe a few hundred people per day who are directly affected. Over the course of a year, that's roughly 70k people out of 330 million, or %0.02 of the population. Which isn't to say that we shouldn't do everything we can to prevent it, but when you hear people saying that they don't feel safe, that's entirely on the media and how it's warping our perception of the danger rather than it being a real threat to our lives. We also saw it with the spate of Asian attacks that became a media favorite. There was a story of Asians in New York starting to contort their lives to avoid becoming victims. But when I looked up the actual statistics, there were 20 such attacks at the time in a city with 1.2 million Asians. Which, again, doesn't mean that we shouldn't be treating each of those attacks as terrible and be doing everything we can to stop them, but when you consider 20 victims out of 1.2 million, that's just not a risk that's worth going to considerable inconvenience to avoid.
There was an interesting TED talk many years ago from a guy who specialized in these kinds of cognitive quirks. And he discussed the findings of one particular study that always stuck with me. In it, participants were presented with one of two hypothetical situations. In the first, they were going to the theater to see a movie and they pre-purchased the ticket for $20, and also brought along a $20 bill. When they arrived at the theater, they found that the ticket had gone missing. Almost all participants in the study said they'd turn around and go home rather than using the other $20 to purchase another ticket. In the second case, they were going to the theater to see the same movie, but instead of having pre-purchased a ticket, they were intending to buy one when they got there. But they had, instead, brought two $20 bills with them and managed to lose one on their way to the theater. Almost all participants presented with this scenario chose to use their remaining $20 bill to buy a ticket. Despite the situation being basically identical, when you're presented with both scenarios, we have a cognitive quirk where we don't want to pay for something twice whereas we can rationalize the loss of money that we never spent. But what got to me about that study wasn't the results, but how intuitive both decisions felt to me. I could feel how unpleasant it would be to buy a second ticket and, yet, how easy a decision it would be to buy a ticket for the first time even after losing some of my money. The lesson, for me, was that while I've always thought of myself as a logical person and someone who would always let statistics or other scientific basis guide my thinking, it's still really hard to follow through with that.
Statistically, on any given day, the odds of being in an accident are quite low. However, if you drive for 30-60 minutes every day, you are exposing yourself to a low amount of risk consistently over time, which inevitably means that one day, your number will come up.
Most people don't have a background in probability or they haven't taken the time to look at driving, but for those who consider themselves normally "rational", they're often very surprised to see just how dangerous driving a car really is, but they just weren't aware of the amount of risk.
Analyzing the risk of driving every day is an exercise worth doing. That being said, I have a fairly high level of risk tolerance, so I drive to work every day because I live just a little too far to reasonably walk, and riding a bike would be a higher risk than driving because of lack of adequate road shoulders for much of the route between my workplace and home.
Is this an empirical statement or based on the same gut feeling that makes people feel safe in a car?
I'm asking because when you actually run the numbers, in most cases I've been involved in, you get to be very surprised to see just how safe cycling really is.
I don't know what the culture and road type is around your neck of the woods, but I would prefer a road without a proper shoulder most of the time -- simply because the existence of the shoulder provides very little actual safety, but it does give a sense of safety that makes drivers behave more dangerously near cyclists. Not to mention lower quality road surface, collected debris, etc.
In Ancient Greece, you were a hero for what you attempted to do and not for what you actually accomplished. This was because the Greeks considered the outcome to be primarily governed by the whim of the Fates. What you attempted to do was a function of your courage especially given that a big task could lead to a big failure outside of your control.
I think of this quote often anytime the "outcome vs process" discussion comes up.
Here is what I'm thinking: How about we go up a level, and accept that life is basically random and a lot is decided by luck (your gene is luck, your childhood education is also luck, these two pretty much decide a lot of things), as indicated in the article, but maintain a (meta) mindset that can manoeuvre around or even mitigate negative emotions?
For example:
- Realize that probability is useful in poker but not that useful in life, thus it is impossible to calculate mathematical expectation.
- Learn to harden one against impulsive emotional acts (impulsive purchase, suicidal thoughts, etc.).
- Learn to control one's material requirements and save some $$ for rainy days.
- Keep connections active so when really bad days come maybe someone can get you out.
It also helps to know some probabilistic identities to derive the same probability multiple ways and see if there's consistency in your assessment.
That's very backwards. Sure, "exact" expectation no. But you can add errors bars to all your estimates, that's the basis of statistics. Being able to correctly estimate things and adjust for uncertainty is incredibly useful in life. Unlike poker, you have time to actually punch things into a calculator and consider different scenarios if you want to be super diligent but most things can be intuited if you have a solid grasp of probability/statistics. To be super pragmatic, the whole thing with fake news and misinformation wouldn't exist if people just applied Bayes theorem. For instance, people will say something like P(vaccine is dangerous | bad pharma company) = 1 but then P(bad pharma) = 0 in the sense that Pfizer doesn't want to kill people.
Business and life decisions aren't as simple as calculating pot odds and outs. Anyone who has estimated a complex and unfamiliar programming task knows that the unknown-unknowns are the biggest part of any equation.
It's a useful framework for thinking in various situations, but it is almost never going to reduce to an equation that can tell you some objectively correct answer or decision.
After all, although we don't know which the unknown unknowns are, the possibility of them is known. And they do, in my experience, tend to increase the required effort by, say, 1--30 × depending on task complexity and familiarity.
So even in the most complex and unfamiliar of tasks, you can adjust the upper end of your estimate by 30× and there you go! Unknown unknowns accounted for in your effort estimation.
(Simpler or more familiar tasks require smaller adjustments to their upper end. Knowing how much adjustment is appropriate is a matter of deliberate practise.)
So what you need to work on is how you define "success" in life. Money is a high variance objective, whereas self-improvement is a low variance objective. I think finding a good balance of variance and tolerance to risk is a key to happiness.
Rejecting the role of luck in our outcomes is delusional, and people who support it have something to peddle (if only their own personal brand as thought leaders).
In the non-poker real world, most people maybe get to play one hand in life, and that’s it. One at-bat in a baseball game, to use a different analogy. You dump 20 years of savings into buying that laundromat, and that’s your only shot of making it. If we are really lucky we might get one or two more hands to play but that’s it for the vast majority of us.
The rich get as many hands/at-bats in life that they want to play, so they will eventually win one. They can just serially start business after business until one of them lucks out and succeeds, then do talks for the rest of their lives on how to be good at business.
Money buys you chances to make money.
Measuring your net worth against those born rich is a fools errand, but you can definitely make your children have a better shot against their children. True wealth is almost never built up in a single generation, despite the fairy tales about the "American Dream" that we tell our children.
- potential reward of the decision: checks out
- probability of getting it: 95% if you already have the offer in hand
- resources (time/effort/money) to bet to get the reward: not significant
Then there is 'imagining a bet' and 'analysing your past failures'. The first one might lead you to the 'what if the company goes bust?' question, but would that really help in the decision making or be a reason to not accept the better job? The unlucky event is a recession, not this particular company doing badly (i.e. no signals to see).
If a recession hits, there is no reason to believe the consumer goods co. would fare any better and her old job more secure. I'd really like to see the 'poker player' mindset at play but this just feels like a complete miss.
So, if you have a 95% chance of going 10x that's great, but the question is: can you handle a 5% chance of having being potentially ruined for at least a decade? If not, then you cannot take the bet despite the fact that EV is super high.
Put more extremely, if I offer you a 99% chance to take make one billion dollars (legally) and a 1% chance of being killed, would you take it? I definitely wouldn't.
How about the following? I offer you an unfair coin flip advantage of 51% versus 49%, we're going to flip 1 million times, each time the bet is 1 dollar. Would you take it? I would.
The heuristic that poker teaches is: take a lot of small bets with huge upside with little to no downside. It doesn't matter how slim the chance of winning is. Slightly more nuanced (still a heuristic): the chance should be about as big as your volume of chance-taking. Say, you take 10000 chances, then the slimmest chance you can take (on average) is 1/10000.
I would even if it offered 50+% of getting killed. The small chance you strike a billion is worth the risk.
What would make a difference would be my life situation - if it would be worse or totally shitty I could take even 25% for a billion.
That was kind of theme of "Squid Games".
At some point it goes from a life changing amount of money to just "meh" money.
Your sum risk might be reduced (e.g. your job pays health insurance), but many jobs increase your risk e.g. just driving to work is dangerous.
Of course your primary finite resource is usually time (years of life), and your object function usually relates to quality of life (not $) . . . Win $ for risk of death is a poor metric.
- Right now we spend 33% of our life working, nd the stress of work impacts another 33%.
- A billion is also way more than out life expected income, but there's a big marginal reduction of value to money. But you also get it now when you're younger rather than parsing it out.
- As a random 25 year old male, you would only have a 1 in 16 chance of surviving to retirement age at 60 on your own.
I personally would only take the deal for 2.5% chance of death though.
The only reason I can fathom desiring a billion dollars is the leverage it would give me to influence the world in what I think is a positive direction. But when it comes to money for my own sake, $10M is about the most I can imagine having use for.
In all the worlds where you get the money, your life is improved. In all the worlds where you don't, well, you're dead, so you don't really care.
Obviously, this doesn't take into account the impacts to everyone else in the worlds where you died.
Isn't that just baccarat without ties?
I'd take it in a heartbeat. I've done things that have a 1% chance of death just to have a good story to tell.
> "Probability of getting it — you cannot know the exact probability, but estimate it the best way you can (remember the bet with a friend)"
is the hard part. Jane's case was clear (good decision), but what about Mike? Is there a proportion of his savings he should have invested that would have turned his "bad decision" into a "good one"? We have no signal to tell us what the probability of any cryptocurrency going up or down is over, say, 6 months (they've all gone up and down completely arbitrarily). Basically, finding the probability of any particular "success" (or actually, a failure) will easily tell you how much you should risk.
And that's what it's like with the most of life decisions as well: we don't know the probability — not even the ballpark range. Likelihood that any one person you meet is going to be your life-long partner is basically nil: but we still invest in building relationships before fully committing to either decide they are not, or increase the probability that they will be. But we still do that relationship building investment based on very few signals (appearance, short chats and potentially what social circle someone is from if from a shared acquaintance).
So sure, there is your probability. Will you make money knowing it? That's the question you're alluding to.
(As a concrete example: there is no "true" probability of rain six days from now. Either it rains or it doesn't. But a skilled meteorologist can give you a probability that would probably make you a little money over the climate average.
Both the climate average and the meteorologist's assessments are correct probabilities. They just reflect different amounts of information.)
My point is that with the available information when making most life decisions, we usually have no idea at all of even the ballpark chances of something turning one way or another.
Basically, the advice from the article is to incorporate luck into your estimations (both good and bad), and to use that to determine if a decision is good or bad, and then only go with good decisions (like a poker player would). And don't stress over bad (or good) outcomes if they were mostly due to really bad luck (i.e. something improbable has happened).
But if you don't know if chances of something happening are 10% or 90%, how do you incorporate that into your decision making?
What I am saying is that in life, we implicitely work to reduce the range (eg for a romantic partner, get to know them much better), but we've already decided to invest that much time with very slim chances of them turning out to be our lifelong partners.
Hold 'em, at least, still ain't fully solved.
Well, yes, but the point is that a fully GTO non-exploitable strategy is not solved for Hold'em. At least not outside of limit (and kinda no-limit) heads up play.
https://arxiv.org/pdf/1805.08195.pdf
(There is also an argument that Libratus actually just approaches Nash equilibrium and isn't fully there, since there are 1e+160 decision points in a heads up no-limit game, but compared to human players the difference is probably meaningless. )
The closest we have seen for larger games is Pluribus - https://www.science.org/doi/10.1126/science.aay2400 - but the researchers there aren't even attempting to say they have solved 6max, just that they could be less exploitable than some of the best in the world. It is not particularly useful for online play because it does not try to counter variance or manage bankroll, and in further results it began to lose quite heavily as the pros adapted to it, losing 700BB over the 10k hands.
By no means am I saying GTO-based strategy is ineffective - I'd probably be wasting my DTO subscription if I did think so ;) - but we're only part of the way there and the missing bits mean that you can't play perfectly unexploitable poker.
People try this.
> …by increasing their bet size to a point where I can’t profitably call.
A good poker player will adjust your expected range based on your sizing and frequency of bets/raises, and they will adjust their calling/raising ranges accordingly.
Most poker games, especially big bet games are played against a range/distribution of hands, not a specific hand.
I'll also point out that constructing ranges and thinking in terms of ranges/ hand distributions is a relatively new development in poker. I mean, the very good players were subconsciously doing it all along, but it's only been written down and analyzed in the last 10 years or so.
I agree with you overall points.
For historical reference for folks who are interested in the poker boom of the 00s but were not there, it’s more like 20 years, if not more.
The book Let There Be Range was published in 2008.
High stakes players were discussing the issues covered in that book amongst ourselves (live and online) with quite a bit of sophistication for several years before that.
All that said, and supporting the point made above, advanced computational support for ranges (esp. via “solvers”) didn’t really start becoming a thing until the early 2010s.
Annie Duke has cashed 39 times at the WSOP and has won at least four million dollars at tournaments alone.
Any good poker player would understand that the example was simplified for a non-playing audience. It’s so obvious it didn’t need to be stated.
This statistic is almost certainly not counting tournament buy-ins. It doesn't represent net profit. If you want to evaluate somebody's performance as a poker player, you want to look at net profit (among other things). Literally every poker player will have some wins, so if you only count the wins without counting losses, it will sound impressive but not actually mean anything.
This is most certainly not true, because it doesn't subtract the cost of all the entry fees, to the tournaments she cashed and the dozens or hundreds she didn't.
"alone" implies she has won additional money in non-tournament play, when there is no evidence she is a winning cash player.
Finally, there is a LOT more to the Annie Duke story. Morally, ethically, business-wise. A winner? A little research goes a long way.
It is fairly standard in the poker world to discuss total winnings in tournaments rather than net winnings.
When discussing net winnings, it’s usually discussed using an ROI measure (e.g., 30% roi over their past 100 MTTs between $1000 and $5000) rather than just dollars, since the biggest winners in dollars are almost all winners of super high roller tourneys like the Big One for One Drop.
Furthermore, live MTT results in general are often skewed due to the unmatched (?) softness of the $10k wsop main event for a field that size.
With regards to Annie Duke in particular, I never considered her a “good” pro poker player. That said, she was pretty good at fleecing amateurs, and she was able to play a tight game when she was outclassed.
But this is an article aimed at the general public.
An additional comment that I copied from another reply:
With regards to Annie Duke in particular, I never considered her a “good” pro poker player. That said, she was pretty good at fleecing amateurs, and she was able to play a tight game when she was outclassed.
You'll also become predictable if you only overbet when bluffing. If you try to deal with that by making all your bets larger, then you lose out on value from your strong hands because I can now profitably fold some hands that I would have had to call you down with otherwise.
Put another way: you can't exploit someone who makes decisions based on pot odds just by changing your bet size, because changing your bet size changes the pot odds.
I noticed because I read what seems to be the exact article there, with the same illustrations and everything on fs a couple weeks ago. Maybe it was a link in the newsletter to this article.
Looking around there is a lot of overlap in content.
It does not matter what hand an opponent has as long as you can convince him you have a better hand.
Also, it is handy to recognize the situations when an opponent might bluff, so you can call.
Bluffing is about making non-optimal choices for the express purpose of making it more expensive for someone else to make optimal choices. If someone knows you're engaging in bluffing, that's fine, because by bluffing you're still forcing them onto non-optimal lines.
On the other hand, you would prefer people not to know that you're engaging in deception.
I've seen many people getting a 3 year contract without having a clue of what they had to do, just buzz words.
Public sector
The reality is, 95% of scenarios don’t require what is asked for, and stating your capabilities in the most generous way is the optimal decision. Just back it up with work.
Numbers made up and simplified but in the same ballpark:
Round-trip ticket across town: 10€
Monthly pass: 50€
Fine: 70€
The chance to be controlled is roughly 1 in 10 for a round-trip. So if one did 5 round-trips in a month, on average one would pay 70 x 5 x 0.1 = 35€. Which is a good price with acceptable variance fur such usage. When caught just pay without fuss.
At some point (between 7 and 8 round-trips) it's more cost effective to just buy the monthly pass, as the average cost of not buying approaches/goes over such threshold.
As much as "fake it till you make it" is a much hated approach, there's a grain of truth to it. Many people only got the chance to prove their merit by bluffing (faking?) it first. Sure, they had to ultimately deliver on the expectations, and perhaps there are more of those who faked it and then failed to deliver. It doesn't change the fact that often you don't even get the chance if you don't project an aura of confidence.
Generally speaking, being confident gets you to places. This really applies to every aspect of life.
If you act like you belong somewhere and that there can be no questions about you belonging there, people in general will not question your presence. If you seem lost, or confused people will be curious why.
Walk into a private event acting like you belong, and there are good chances nobody will realize you shouldn't be there. Walk around looking all confused and you are likely to be asked to validate your presence.
Naturally, this doesn't apply only to places, but also groups, communities, companies...
How do I get caught? If they say no I get up, pause then change my mind.
I've never suffered from being caught by a bluff, but I structure them sensibly.
It surprises and slightly delights me to see how often people who try to ‘game’ others, queue jumpers, and others who display selfish behaviour are then given special (negative) treatment from those who notice their behaviour.
Some seem to go around thinking that people are awful, but really people are just awful to _them_. People are generally kind and help each other.
Other life pro tips:
- Stealing is a way to get money
- Murder may be useful
- Fraud is profitable
A bluff, in this context, is claiming or insinuating you're in a better position that you really are.
Eventually, you really do believe the lies you tell and then your ability to see the world for what it is is diminished.
Additionally, when dealing with other people, we tend to fill in the blanks about the things we don’t know about them using information we have picked up from other people as a template. We know ourselves better than any other person, so we often use our own motivations as a stand in for the motivations of others. If we are liars ourselves, we assume other people are liars too, by default (and, due to confirmation bias, once we look for evidence of this, we find it everywhere).
This mindset means we end up trusting people less than is probably optimal, but we are unaware of this fact.
Say you're a physical coward and you're being picked on for a fight by someone. You can puff your chest up, put your shoulders back and put a sneer on your face, possibly scaring the bully off.
Yes you're misrepresenting yourself. You're lying. But how exactly is that corrosive to your character?
Just this morning I was reading Scott Adams's How to Fail at Almost Everything and Still Win Big, and he was talking about making bets in Life that don't cost any money (they only cost time) and if we do this there's ~100% certainty of winning. Of course he's more eloquent and elaborate. It's also another way to look at "we miss 100% of the shots that we don't take".
1)All other things being equal you should generally prefer a higher expectation decision to a lower-expectation one
2)But you have to avoid decisions which have outcome distribution properties you can't tolerate. Most obviously you should generally ensure that your risk of ruin is zero because even if the probability is very low, that outcome is close to impossible to recover from so must be avoided.
3)For two possible strategies with similar-ish expectations in real-life terms you may well want to choose the one with the lower standard deviation of payoffs. Like say you're choosing between an offer at medical school to train to be a dentist and pursuing your long-shot idea of going to Hollywood and trying to make it as an actor. Imagine that when you look at the outcomes you estimate that in acting you have an insanely low probability of making it but a huge payoff if you do and in dentistry most people do pretty well but no-one's partying on superyachts with Jay-Z and Beyonce. Well even if the expectation of acting works out slightly higher, if they are close enough you should probably pick dentistry because the variance of outcomes is just way lower. If you think about your future as a monte carlo simulation you want to end up "ok" on most of the paths in the simulation even if that means giving up on some "lights out" outcomes.
4)most people agonise the most about decisions where the expectation is really pretty similar so it just doesn't matter that much either way. So don't beat yourself up about whether you made the right decision - just try to learn from the decision and move forward
A huge mistake people make is to evaluate the quality of the decision based on the single possible outcome that crystalised into reality by actually happening rather than using the framework above. So resist that temptation and instead evaluate your decision based on whether you chose to maximise expectation while avoiding risk of ruin and excessive variance.
[1]In the sense of being the weighted average of all possible payoffs where the weights are the probabilities and the payoffs are the utility of each outcome (usually just in cash terms).
https://en.wikipedia.org/wiki/Expected_value#Expected_values...
Probability distributions are complicated. Even determining what kind of distribution you are look at is difficult in many cases. Such distributions are also skewed in real life by things like insider information (in poker, that would be cheating). Even so the list is rather intimidating, assuming fair play:
Bernoulli, Binomial, Poisson, Geometric, Uniform, Exponential, Normal, Standard Normal, Pareto, Cauchy
If financial institutions (and crypto players) are using these kind of approaches to make their bets, then isn't the individual investor hopelessly outgunned in the vast majority of cases? Plus, not having a big pool of capital to absorb temporary losses makes that situation even worse.
Investment capitalism, in other words, is just a casino for the uber-wealthy. Letting it rule the economy is a serious mistake.
So you're not even dealing with a somewhat countable list of distributions -- everything has its own unique distribution!
Fortunately, you don't need to model things exactly. A very rough approximation often gives me miles better results than plain gut feeling.
>If financial institutions (and crypto players) are using these kind of approaches to make their bets, then isn't the individual investor hopelessly outgunned in the vast majority of cases?
When its your job, you're better at it compared to someone for whom its a hobby. And also, larger firms are able to manipulate the market which tilts the balance in their favor.