Physically attractive women and men earn more than average-looking ones, and very plain people earn less. In the labour market as a whole (though not, for example, in astrophysics), looks have a bigger impact on earnings than education, though intelligence—mercifully enough— is valued more highly still.
Read the full article here.
What is it exactly that quants do?
This is the third post in a series of curated interviews from Reddit’s IAmA subreddit, a place where individuals of various professions and backgrounds can request the community to “ask me anything”. There has been a lot of new readers to the blog recently, so I strongly recommend new readers to first read my first post on investment bankers and my second post on algorithmic trading and high frequency trading.
I have selected some curated questions and responses from that, in my opinion, comprise some of the best quant/algorithmic trading/high frequency trading interviews on Reddit.
Early on, I was in nasty drawdown period and I was having trouble figuring out what was off. I made the same mistake virtually all traders make, I caved to the vast collection of trading psychology books. When the guy mentoring me found out what I was reading, he gave me the following gem: Only pikers worry about psychology, either you have an edge and you exploit it, or you don’t have one and you lose and chase every other excuse.
Trading and Exchanges
Options, Futures & Other Derivatives
Option Volatility & Pricing
Volatility Trading
Dynamic Hedging99% of finance books are garbage, but those are the ones I thought helped me in some way or another. There’s also plenty of interesting research papers if you’ve got access to some databases.
I don’t have just 1 strategy/model/whatever you want to call it. I have a portfolio of 6 strategies, the oldest being the one I initially started out with. I have had to retire several strategies. When a strategy falls below benchmark performance I evaluate and then either continue or retire it. My strategies range from high accuracy with 2:1 risk:reward ratios to low accuracy and low risk:reward ratios. When I develop a model, I attempt to exploit some fundamental behavior whether that be news, volume, trader driven. From there, I systematically formalize rules and test.
- I rarely look at bar/candlestick charts. I’ll peek at one after hours or when I pull up the S&Ps or something like that. I personally don’t put much weight into price patterns/indicators, so I tend to ignore those. That being said, I do visualize data to spot behavior, such as mean reversion. I have a whole suite of scripts in Matlab and more recently R to help me analyze timeseries. When I develop a strategy, I lay down what I’m trying to exploit. For example, if I notice that an instrument is poised to be range bound for some period of time, I’ll go with a mean reverting model and adjust as needed.
- I do use volume, but it’s become a diminishing factor.
- I use any information I can get my hands on. From tick data to fundamentals, news, relative strength to other equities, etc.
IAmA High-Frequency Trader. AMA.
Mainly, we create statistical models of a variety of products in order to have some type of predicted price. I was in Computer Science, making the discrete math and probability right up my alley.
My best estimate: about half a dozen people, six to twelve months, and about $5-10 million to get a workable (but simple and narrow) high frequency trading firm. The capital needed for trading isn’t very high, but the technological outlay is pretty big.
Impossible. The amount of money that must be spent on infrastructure to even think about putting together a simple HF trade is probably close to the $10 million mark. Plus, you have no reason to. Work on your trade at work, and, while you won’t get 100% of the profits, you’ll get a good enough chunk to make up for all the infrastructure you get.
Good question, because you’re right – I am neither writing code, nor manually trading all day. What it comes down to is really watching everything, and reacting. Not everything can be automated. This may sounds simple, but it takes a holistic understanding of both your products, your aims, your markets, your exchanges, to do it well. There are times when for 2 hours i will be doing nothing than doing mental math, checking that every trade the system does is good. This is in quiet times.
Then there are times, when for some reason an algo starts building up a huge position. And the limits we have on it need to be increased, because we see opportunity. I must manually change this, then think, wait, how will this affect our exposure in X industry. What is our interest rate and currency exposure. Which exposure do I want? Which exposure do fellow desks have? How big do we want to go? Who is the counterparty, if there is a way to know? How can I adjust the algo settings? Maybe be more, or less aggressive? Think about similar algos, how they trade similar ways, and we need to tweak them relatively?
These are a few of the concerns that I automatically consider as I see all my trades aggregating, and I start to make decisions based on all the news and information I have coming into me, be it from Bloomberg, from brokers, even CNBC if I’m too busy to be reading. I cant leave this up to the computer because there is always a human element. And like we all know, leaving it in control of machines can lead to unexpected black swan disasters due to glitches or random inferior machine logic.
We have databases full of old tick data that we backtest on, but most of them you are pretty certain will work and will just put into use. This is simply by experience and just knowing the markets – as a simple example, if we can have our computers read the ECB’s interest rate announcement first, and be the fastest to trade, we will clearly make money. Most are far more complex, but that’s the idea – most should work. If it loses for the first few days or hours, we retool it and can eventually dump it. But that’s rare – even if it makes only a bit, we keep it. Leverage is used for general company wide leverage, not specific per trade. Books – Hull is one of the basics. Trading ideas, you would probably learn more from reading all of Wikipedia’s finance tabs, Investopedia, and the various industry biographies – like FIASCO, Liar’s poker, Genius Failed, Den of Theives, etc. The more algo based strategies are almost all derivatives of basic trading ideas, just faster. Some elaborate stat stuff, but a lot of it is quite simple. And the elaborate stuff no one is going to share, sorry.
Get in around 7, having read some sort of financial publication on the way to work. Spend first half hour checking positions, reviewing current FX rates, how the Japan markets closed and how the Euro ones have opened, make sure nothing happened in the futures markets to move anything too much. Read general news. Next hour prepping systems, various manual checks and such, checking strategies, double and triple checks, never can be too sure. Then prep for market open.
During open hours, need at least 2 guys of 3 at my desk at any time, one to be eyeing and checking every trade that comes through, another to be doing accounting/admin/checking positions/pnl/random stuff with backoffice and risk. Of course, monitoring, retooling, reacting and pre-acting on various information that comes along.
Then by the close make sure all positions are as we want, otherwise we would have to act on them on the close – various ways to do this, or work with the japanese markets and australians as they start up – or futures – or fx – theres always a market to work on/in.
Then finish up mundane tasks of finishing the day and closing the books by 5 or so. Until 8 or whenever we feel like going home, working on new strats. Sometimes do this intraday depending on vola.
Totally depends on your risk profile, capital levels, and access to markets.
Go to the local library and read every book on the markets and trading they have. I’d say that would be around 100 books, if you know everything in them you’ll be set. The biggest mistake people make is not knowing enough before they start. Really only trade a few thousand to get a feel for trading, while you are reading and learning, and until you can objectively look at yourself and say, I am more knowledgeable than 80% of market participants. That may take a year of reading a few books a week until you seriously start trading, but it’s the only way to be truly successful.
I will be posting more interviews soon, so please follow Curated Alpha via Email, RSS, or Twitter.
Posted in Curated Content, Trading
Tagged algorithmic trading, high frequency trading, quants, reddit iama
Madoff: I’m a Victim, Too – Fox Business
“It is unfortunate, to say the least, that the financial services industry is so corrupt and stacked against the typical investor.”
The Justice Department is conducting a wide ranging probe that has snared traders at major hedge funds, but Madoff says the government is really late to the game and missing most of the big cases. Insider trading he says, “goes on at every major firm’s Prop Desk and at every level of the Industry in plain sight and is the easiest thing to spot with today’s order trails.”
End of history and the last woman – The Economist
In 83 countries and territories around the world, according to the United Nations, women will not have enough daughters to replace themselves, unless fertility rates rise. In Hong Kong, for example, a cohort of 1,000 women would be expected to give birth to just 547 daughters, at today’s fertility rates.
The Debt Crisis at American Colleges – The Atlantic
Why has tuition climbed to $41,304 at Carleton, $42,384 at Wesleyan, and $43,190 at Vassar, three times over inflation since 1982? The short answer is that colleges have embraced a host of extraneous activities – from obscure sports to overseas centers – and tacked most or all of their tabs onto students’ bills. Unlike businesses, which cut losing operations, colleges simply hike their tuitions. In our view, good higher education could be had at much lower costs. It belongs on the nation’s agenda, up there with preserving Social Security and Medicare.
Asia’s lonely hearts – The Economist
Women are rejecting marriage in Asia. The social implications are serious.
Graph of the Day: How Do the Unemployed Spend Their Spare Time? – The Atlantic
The largest slice of time goes to sleep. Overall, approximately 50 percent of the forgone labor hours goes to leisure, which includes sleeping, watching TV, and socializing with friends. Another 30 percent goes to “non-market work”–things like cleaning, cooking, and doing household repair work.
What You Don’t Get About the Job Search: The Unemployed Speak – The Atlantic
For those of us prone to depression, the job search can amount to a heroic effort.
Ray Dalio oversees Bridgewater Associates, one of the largest hedge funds in the world. Dalio writes about his most fundamental life and management principles in his text titled Principles which is required reading for all employees at Bridgewater. A major part of Bridgewater’s corporate culture is a relentless focus on the open discussion of mistakes and weaknesses.
I like to expose myself to motivational texts, videos, or self improvement books from time to time for my personal journey of constant advancement. Around 95% of all self improvement texts are crap, but every once in a while, I’ll come across some ways of thinking that are used by people that have actually achieved a significant level of success and aren’t focused on just selling books or some sort of program. Ray Dalio is one of these people.
Dalio writes about making mistakes and weaknesses, something that individuals generally try to suppress and cover up — even to themselves:
Unlike any other species, man is capable of reflecting on himself and the things around him to learn and adapt in order to improve. He has this capability because, in the evolution of species man’s brain developed a part that no other species has – the prefrontal cortex. It is the part of the human brain that gives us the ability to reflect and conduct other cognitive thinking. Because of this, people who can objectively reflect on themselves and others – most importantly on their weaknesses are – can figure out how to get around these weaknesses, can evolve fastest and come closer to realizing their potentials than those who can’t.
However, typically defensive, emotional reactions – i.e., ego barriers – stand way of this progress. these reactions take place in the part of the brain called the amygdala. As a result of them, most people don’t like reflecting on their weaknesses even though recognizing them is an essential step toward preventing them from causing them problems. Most people especially dislike others exploring their weaknesses because it makes them feel attacked, which produces fight or flight reactions; however, having others help one find one’s weaknesses is essential because it’s very difficult to identify one’s own. Most people don’t like helping others explore their weaknesses, even though they are willing to talk about behind their backs. For these reasons most people don’t do a good job of understanding themselves and adapting in order to get what they want most out of life. In my opinion, that is the biggest single problem of mankind because it, more than anything else, impedes people’s abilities to address all other problems and it is probably the greatest source of pain for most people.
Some people get over the ego barrier and others don’t. Which path they choose, more than anything else, determines how good their outcomes are. Aristotle defined tragedy as a bad outcome for a person because of a fatal flaw that he can’t get around. So it is tragic when people let ego barriers lead them to experience bad outcomes.
People who worry about looking good typically hide what they don’t know and hide their weaknesses, so they never learn how to properly deal with them and these weaknesses remain impediments in the future. These people typically try to prove that they have the answers, even when they really don’t. Why do they behave in this unproductive way? They typically believe the senseless but common view that great people are those who have the answers in their heads and don’t have weaknesses. Not only does this view not square with reality, but it also stands in the way of progress.
This explains why people who are interested in making the best possible decisions rarely are confident that they have the best possible answers. So they seek to learn more (often by exploring the thinking of other believable people — especially those who disagree with them) and they are eager to identify their weaknesses so that they don’t let these weaknesses stand in the way of them achieving their goals.
So, what are your biggest weaknesses? Think honestly about them because if you can identify them, you are on the first step toward accelerating your movement forward. So think about them, write them down, and look at them frequently.
Successful people understand that bad things come at everyone and that it is their responsibility to make their lives what they want them to be by successfully dealing with whatever challenges they face. Successful people know that nature is testing them, and that it is not sympathetic. How much do you let yourself off the hook rather than hold yourself accountable for your success?
In summary, I believe that you can probably get what you want out of life if you can suspend your ego and take a no-excuses approach to achieving your goals with open-mindedness, determination, and courage, especially if you rely on the help of people who are strong in areas that you are weak.
If I had to pick just one quality that those who make the right choices have, it is character. Character is the ability to get one’s self to do the difficult things that produce the desired results. In other words, I believe that for the most part, achieving success – whatever that is for you – is mostly a matter of personal choice and that, initially, making the right choices can be difficult. However, because of the law of nature that pushing your boundaries will make you stronger, which will lead to improved results that will motivate you, the more you operate in your “stretch zone,” the more you adapt and the less character it takes to operate at the higher level of performance. So, if you don’t let up on yourself, i.e., if you operate with the same level of “pain,” you will naturally evolve at an accelerating pace. Because I believe this, I believe that whether or not I achieve my goals is a test of what I am made of. It is a game that I play, but this game is for real.
Read the full text of Ray Dalio’s Principles here.
Are algorithms controlling us? Interesting TED talk on algorithmic trading and algorithms in general. Kevin Slavin suggests that interactions between algorithms that cause unforeseen consequences will increase in frequency. Human lives are being increasingly controlled by algorithms, causing us to change the world to further optimize algorithms. Algorithms have a bright future.
Excerpt from the talk:
So if you need to have some image of what’s happening in the stock market right now, what you can picture is a bunch of algorithms that are basically programmed to hide, and a bunch of algorithms that are programmed to go find them and act. And all of that’s great, and it’s fine. And that’s 70 percent of the United States stock market, 70 percent of the operating system formerly known as your pension, your mortgage.
And what could go wrong? What could go wrong is that a year ago, nine percent of the entire market just disappears in five minutes, and they called it the flash crash of 2:45. All of a sudden, nine percent just goes away, and nobody to this day can even agree on what happened, because nobody ordered it, nobody asked for it. Nobody had any control over what was actually happening. All they had was just a monitor in front of them that had the numbers on it and just a red button that said, “Stop.”
And that’s the thing, is that we’re writing things, we’re writing these things that we can no longer read. And we’ve rendered something illegible. And we’ve lost the sense of what’s actually happening in this world that we’ve made.
Ray Dalio oversees Bridgewater Associates, one of the largest hedge funds in the world. Dalio writes about his most fundamental life and management principles in his text titled Principles which is required reading for all employees at Bridgewater. It’s mainly a motivational and self-help text that serves to introduce new employees to the cult-like culture at Bridgewater, but Dalio also writes about his thoughts on money and success which I found extremely interesting.
Dalio, one of the richest persons in the entire world (Wikipedia says he was the 162nd richest in 2011), explains that having a lot of money isn’t as great as it would seem. Instead, the basic experiences that make someone happy like relationships, meaningful work, and good experiences aren’t “materially improved upon by having a lot of money.” Read the full passage here, which is a collection of passages that I curated from Principles:
Yes, I started Bridgewater from scratch, and now it’s a uniquely successful company and I am on the Forbes 400 list. But these results were never my goals – they were just residual outcomes – so my getting them can’t be indications of my success. And, quite frankly, I never found them very rewarding.
What I wanted was to have an interesting, diverse life filled with lots of learning – and especially meaningful work and meaningful relationships. I feel that I have gotten these in abundance and I am happy. And I feel that I got what I wanted by following the same basic approach I used as a 12-year-old caddie trying to beat the market, i.e., by 1) working for what I wanted, not for what others wanted me to do; 2) coming up with the best independent opinions I could muster to move toward my goals; 3) stress-testing my opinions by having the smartest people I could find challenge them so I could find out where I was wrong; 4) being wary about overconfidence, and good at not knowing; and 5) wrestling with reality, experiencing the results of my decisions, and reflecting on what I did to produce them so that I could improve. I believe that by following this approach I moved faster to my goals by learning a lot more than if I hadn’t followed it.
I have been very lucky because I have had the opportunity to see what it’s like to have little or no money and what it’s like to have a lot o fit. I’m lucky because people make such a big deal of it and, if I didn’t experience both, I wouldn’t be able to know how important it really is for me. I can’t comment on what having a lot of money means to others, but I do know that for me, having a lot more money isn’t a lot better than having enough to cover the basics. That’s because, for me, the best things in life – meaningful work, meaningful relationships, interesting experiences, good food, sleep, music, ideas, sex, and other basic needs and pleasures – are not, past a certain point, materially improved upon by having a lot of money. For me , money has always been very important to the point that I could have these basics covered and never very important beyond that. That doesn’t mean that I don’t think that having more is good – it’s just that I don’t think it’s a big deal. So, while I spend money on some very expensive things that cost multiple relative to the more fundamental things, these expensive things have never brought me much enjoyment relative to the much cheaper, more fundamental things. They were just like cherries on the cake. For my tastes, if I had to choose, I’d rather be a backpacker who is exploring the world with little money than a big income earner who is in a job I don’t enjoy. (Though being in a job that provides me with what I want is best of all, for me). Also, from having come from having next-to-nothing to having a lot, I have developed a strong believe that, all things being equal, offering equal opportunity is fundamental to being good, while handing out money to capable people that weakens their need to get stronger and contribute to society is bad.
Self-interest and society’s interests are generally symbiotic: more than anything else, it is pursuit of self-interest that motivates people to push themselves to do the difficult things that benefit them and that contribute to society. In return, society rewards those who give it what it wants. That is why how much money people have earned is a rough measure of how much they gave society what it wanted – not how much they desired to make money. Look at what caused people to make a lot of money and you will see that usually it is in proportion to their production of what the society wanted and largely unrelated to their desire to make money. There are many people who have made a lot of money who never made making a lot of money their primary goal. Instead, they simply engaged in the work that they were doing, produced what society wanted, and got rich doing it. And there are many people who really wanted to make a lot of money but never produced what the society wanted and they didn’t make a lot of money. In other words, there is an excellent correlation between giving society what it wants and making money, and almost no correlation between the desire to make money and how much money one makes. I know that this is true for me – i.e., I never worked to make a lot of money, and if I had I would have stopped ages ago because of the law of diminishing returns. I know that the same is true for all the successful, healthy (i.e., non-obsessed) people I know.
Read the full text of Ray Dalio’s Principles here.
What is it exactly that quants do?
This is the second post in a series of curated interviews from Reddit’s IAmA subreddit, a place where individuals of various professions and backgrounds can request the community to “ask me anything”. The first post I wrote about investment bankers was well received, and I received several requests for IAmAs on other positions in the financial services industry, so I have decided to write a series of posts on quants that work with algorithmic trading and high frequency trading.
I encourage new readers to read the first post to understand my motivation for curating these interviews, but it can basically be boiled down to this: Practitioners in the financial industry generally aren’t motivated to share information with others and the ones that do are sometimes at risk of being fired by their employers. This results in significantly less robust online financial discussion when compared to other online communities.
There is also an issue of signal to noise — 95% of financial-related websites are crap because their primary purpose is to try to sell you something (usually newsletter prescriptions). Reddit’s IAmA subreddit is a surprisingly good source for quality discussion around interesting topics precisely because there are no ulterior motives (aside from accumulating “karma”) and because its done anonymously, allowing practitioners to say and explain things without the limitations that hold back most practitioners in the financial industry.
I have selected some curated questions and responses from that, in my opinion, comprise some of the best quant/algorithmic trading/high frequency trading interviews on Reddit. There is some good content both for novices that are being introduced to algorithmic trading and HFT for the first time, as well as developers that may wish to attempt developing some basic automated trading systems during their spare time.
HFTs do variety of things, but since their profit margin is very small, they need to be very high probability trades. Arbitrage is a big area for HFTs. When you hear about co-location and receiving quotes faster than the rest of the market, this is arbitrage. Essentially, they look for times when say AAPL is 224.25 in one market and 224.29 in another market and simultaneously buy the lower and sell the higher. When I say one market vs another this could be different exchanges, instruments (such as options), derivatives such as AAPL portion in S&P500. The second big area of HFTs is market making. If a stock is quoting bid/ask = $40/$40.20, this means a buy will be executed at $40.20 and a sell will be executed at $40. The HFT may add bid/ask = $40.10/$40.11 to the market. Note the price has improved for both buyer and seller. This increases the chances of trades taking place and the HFT profits 0.01.
No, its very possible to profit, make a living or be a millionaire by retail trading but its very very hard, because everyone has picked bad habits during their early investing/trading days. Many of these are reinforced by TV and web media.
For example:
- buy and hold and everything will eventually be profitable.
- buy a winner all the way to the top
- buy (scale in) a loser till it becomes profitable.
- the bull/bear market will never end, keep buying
Paul Rotter makes about $60 million a year trading. Al Brooks makes a living trading the size of small institutions. Most of these are day traders. About 80% of traders will lose everything they have. 11% will be consistently be profitable. The rest will break even. You have to trade for a while to move to the top bracket, but it can be done. I trade for a living and know quite a few people who do.
IAmA Someone who worked for Investment Banks developing automated trading systems AMA
It’s a team effort, the same reason a game developer at Sony doesn’t go and make their own games.
If you are using E-trade, you are just day trading. Fees per trade will be about $8. Using strategies like the ones described above involve many smallish trades. A common strategy is finding a relationship between two stocks – lets say DELL historically has been worth 1.3 times more per share than MSFT. Your strategy will then to be to buy or sell MSFT (or DELL) when one diverges from that multiplier. You could do this on E-trade, but the price may have moved by the time you enter in your transaction, and its pretty exhausting to sit there and calculate the multiplier constantly, and then trade based on it. So you need automated tools. There are some guys out there like Brokertech that will help you get set up for far smaller fees, but even then, to implement any strategy, I would say you want at least several hundred thousand to play with. To really do this properly though, you need access to historical data, real time market data, often level 2 market data, direct connections to exchanges, development time, etc, and all of these things are expensive. I do know some guys that have done “bedroom trading,” none have really run too far with it. Sometimes they are one-trick ponies and they find a reasonably profitable strategy that doesn’t work after time, or they just don’t have the scale (IE money) to diversify their strategies and consistently make enough money to justify the risk.
Why does it seem like stealing ?
Let me give an example with FX. With a currency pair say EURUSD you have a spread, the difference between the buy and the sell price (a useful tip if you’re going on holiday: you can easily tell how good a price you’re getting at a currency exchange is by looking at how big the spread is). The tighter the spread, the better the prices.
Supply and demands for currency is for practical purpose changing continuously (at this very second there are thousands of people who want to buy/sell USD). But imagine currency exchanges only updated every 500ms.
Now if you’re a market maker who wants to offer a price for trading you know that supply and demand has changed since that last 500ms update, and based upon historical data you might estimate that the price is going to have moved by 10pips so you take the price you’re willing to trade at and add 10pips to the spread. Because if you don’t you might find that when the next exchange price update comes out that your price is off the market by 10pips and you’ll get slammed by people doing arbitrage trading (because your price is so off market people can buy cheaply elsewhere and sell to you at profit with no risk to themselves).Now imagine the exchange updated every 100ms, on average the price might only move 1pip every 100ms, so rather than adding 10pips to your spread the market-maker only needs to add 1pip to their spread, so now prices for currency trading are better for everyone!
By increasing the frequency of trading you reduce the risk taken on by the market-maker and thus allow them to offer better prices because they no-longer have to account for that risk. This isn’t just theoretical, as the update frequency of FX exchanges has increased over the last decade spreads have been been dropping steadily.
IAmA Algorithmic trading developer at a large Wall St bank. AMAA
The bid/ask spread. I can probably explain a bit more later, but when you hear IBM is trading at $82.50, you can neither buy nor sell it at 82.50 You can buy it for maybe 82.55 and sell it for 82.45, and a guy called the market maker keeps the spread. For this he has certain responsibilities, like making sure he will always buy your IBM shares, even when everyone is selling. Spreads used to be 10 or 20 cents wide, now they are about a penny wide. The massive volume has brought these spreads down, and out of market makers pockets. Other guys look for inefficiencies in pricing. Without getting too detailed, there are stocks out there that represent a group of 30 or 500 stocks. If you see that particular stock is not trading the price that the basket of stocks is supposed to be trading at, you buy one or sell the other, and have a theoretical profit, because they should always be the same price. Its a good and difficult question. there are so many participants in the market, who trade for very different reasons, its tough to say anyone wins or loses, but I think this is the most direct answer. For the record, I think Joe Schmoe, aka a retail trader benefits. Trading costs used to be very high.
It depends. For a programmer like myself, I would say 150-500k. A lot of it is very bonus based, where base salary is around 100k. I would say 90% of these firms are based in NY and Chicago, and in NY that doesn’t make you rich.
If you do something awesome for the firm though that makes them boatloads of money, there is nothing stopping you from getting wheelbarrows full of money at year end. For a quant, there is no limit really. Most quants make in the hundreds of thousands to tens of millions.
Posted in Curated Content, Trading
Tagged algorithmic trading, high frequency trading, quants, reddit iama
Can mathematical models predict financial markets? H. Eugene Stanley, statistical physicist at Boston University, says no.
Why do economists and “quants”—those who use quantitative analysis to make financial trades—have such faith in their mathematical models then?
If they’re just to reduce risk, then they’re very valuable. If you’re worried, for example, about the segment of the Chinese economy that deals with steel, you make a model of what that whole market is all about and then you see if we did this what would likely happen. They’re right some of the time. It’s better than nothing.
But when they have excessive faith in these models, it’s not justified. Math starts with assumptions; the real world does not work that way. Economics, which calls itself a science, too often doesn’t start with looking at empirical facts in any great detail. Fifteen years ago even the idea of looking at huge amounts of data did not exist. With a limited amount of data, the chance of a rare event is very low, which gave some economists a false sense of security that long-tail events did not exist.
Stanley has some interesting discussion regarding tail risk, but ultimately I think his responses are biased towards a reliance on efficient markets. This is something that I believe to be untrue based on my personal observations and research but is still largely accepted in the academic community. Read the full post here.
Grantham, a fund manager with a quarterly newsletter with a cult following, argues that the recent rise in commodity prices is not a bubble but rather “one of the giant inflection points in economic history.”
Grantham, who says that “this time it’s different are the four most dangerous words in the English language,” has become a connoisseur of bubbles. His historical study of more than 300 of them shows the same pattern occurring again and again. A bump in sales or some other impressive development causes people to get excited. When they do, the price of that asset class — South Sea company shares, dot-coms — goes up, and human nature and the financial industry conspire to push it higher. People want to hear good news; they tend to be bad with numbers and uncertainty, and to assume that present conditions will persist. In the financial industry, the imperative to minimize career risk produces herd behavior. As John Maynard Keynes, one of Grantham’s heroes, put it, “A sound banker, alas! is not one who foresees danger and avoids it, but one who, when he is ruined, is ruined in a conventional and orthodox way along with his fellows, so that no one can really blame him.” All these factors contribute to a surge of what Keynes called “animal spirits,” which encourages people to convince themselves that this time prices will just rise and rise.
So it’s news when Grantham, who has built his career on the conviction that peaks and troughs will even out as prices inevitably revert to their historical mean, says that this time it really is different, and not in a good way. In his April letter, “Time to Wake Up: Days of Abundant Resources and Falling Prices Are Over Forever,” he argued that “we are in the midst of one of the giant inflection points in economic history.” The market is “sending us the Mother of all price signals,” warning us that “if we maintain our desperate focus on growth, we will run out of everything and crash.”
The letter is 19 pages long and dense with figures, but here’s the short version: “The prices of all important commodities except oil declined for 100 years until 2002, by an average of 70 percent. From 2002 until now, this entire decline was erased by a bigger price surge than occurred during World War II. Statistically, most commodities are now so far away from their former downward trend that it makes it very probable that the old trend has changed — that there is in fact a Paradigm Shift — perhaps the most important economic event since the Industrial Revolution.”
Read the full article here. For further reading,I recommend reading more on the Simon-Ehrlich Wager.
Market Folly has a great post on highlighting the current contrarian signals in the marketplace. Some are conventional (like the VIX) and some are unconventional:
Retail Investors Freaking the F Out: You all probably have that one retail investor friend that doesn’t pay attention to markets all that often but still wants to make money. You are their “go-to” market guy. When they start calling you wondering what the f*ck is going on, that might be a contrarian signal. When they call you saying they sold everything, that’s usually a contrarian signal. Don’t know about you, but we received these phone calls yesterday.
ZeroHedge Crashes: The popular market website with a cult-like following crashed on Sunday night due to insane traffic as bears tried to congregate in victory and scared bulls looked for answers.
Read the full post here.
