Physics to Economics -- possible?

[asc3nd]

<p>I’ve had a background over the last 4 years in high school as a science student, doing internships and research.
The problem is that I have gained a strong interest in economics and was wondering if I apply as a physics student, would it be possible to switch over and take economics as a major?</p>

<p>I’ve noticed that top-ranked universities don’t allow this (because economics and physics are in different schools within the university). Am I wrong on this? And how viable is this?</p>

[nj_azn_premed]

<p>I’m not sure about transferring between majors (but, I would say that few schools would really limit you to such an extent). Also, in case you’re not aware, there is a strong correlation between certain physics-related principles and economics. For example, did you know Wall Street regularly hires physicists (and pays them millions) to apply the principles of Brownian Mechanics to the market? Essentially, physicists (and, of course, math majors)are often used in business to handle the raw mathematical concepts.</p>

[tlesc01]

<p>I can’t really speak for other schools, but I know that at Georgetown both physics and economics departments are in the Georgetown College, so this wouldn’t require switching schools.</p>

<p>If you’re worried about not getting into an economics program because you have a lot of science ECs, I would tell you not to worry so much about this. Your ECs show focus already, a quality that is looked kindly upon in admissions no matter what the focus was. Also, economics employs a good deal of science and math, so your hard work will not be lost if you go into economics. There is also not a lot of opportunity for economics-related ECs at the high school level, at least less-so than science. I think you will be fine applying as Econ if that’s really what you want to do. (I’m fairly sure I’m going to do International Economics in Georgetown SFS, if you have any questions about that).</p>

[atlonmyback711]

<p>yessssss!!! ive been planning to major in physics and then possibly go into econ… nowadays you dont need to necessarily match your undergrad major with your grad degree… as long as you do well in physics in college (which is not always easy) you will be able to go into econ </p>

<p>economics requires a solid understanding of mathematics, quick and logical thinking, strategic and innovative thinking etc etc… the best companies want sharp individuals, which a physics degree certainly shows (an economics major; however, is not as uncommon and shows interest in economics, and not much else) </p>

<p>read chp 2 of lairs poker to really understand what i am talking about, the guy majors in art history and beats out his princeton classmates for an investment banking job</p>

[hampster]

<p>more favorably upon by econ. grad. programs (at least this is what I’ve been told with regard to math majors).</p>

[sakky]

<p>

I’ve noticed that top-ranked universities don’t allow this (because economics and physics are in different schools within the university)

</p>

<p>Exactly which top-ranked universities don’t allow this?</p>

[sakky]

<p>

read chp 2 of lairs poker to really understand what i am talking about, the guy majors in art history and beats out his princeton classmates for an investment banking jo

</p>

<p>Well, not exactly. You left out some crucial details. After Princeton undergrad, he (Michael Lewis) had to get a master’s degree in economics at LSE, then he worked for an art deal, and only then did he finally get a job as a bond salesman at Salomon Brothers (now Citigroup).</p>

[sakky]

<p>

did you know Wall Street regularly hires physicists (and pays them millions) to apply the principles of Brownian Mechanics to the market?

</p>

<p>Unfortunately, these are the very same models that have annihilated the Wall Street banks such that us taxpayers have to come in and bail them out.</p>

[Lafalum84]

<p>If you go to a smaller LAC you shouldn’t have much problem changing majors; many of them don’t have the “school of X” and “School of y.” They just have one college for everything.</p>

<p>It is easier to start out in a science and switch to Econ than the other way around. Econ has a few basic pre-reqs, but most of the upper-level courses require the same few pre-reqs so it’s not terribly regimented (in other words there’s not as much of you must take a before b, b before c, c before d, etc, as there is in science and engineering).</p>

[happymomof1]

<p>Every university that I know of has some system for allowing students to transfer between colleges. It is really hard to imagine any college that won’t make it possible because, well, they do want your money. HOWEVER, if you want to do something that is rarely done at that university, you will have to be proactive. If the colleges themselves had significantly different admissions requirements, there is the chance that you may have to take some remedial work in the new college once you get there, or you may have to take an extra semester or so to fulfill graduation requirements.</p>

[Seiken]

<p>^^^ What are you talking about sakky? </p>

<p>Anyways, one of the recent nobel prizes in economics went to two of the 3 people behind the so-called Black-Scholes equation. It is a partial differential equation that deals with the values of options, a type of equity.</p>

<p>The kicker: The reason the equation is so powerful is because the inventors of the equation came up with a specific substitution that transforms the PDE into the famous heat equation studied by mathematicians and physicists for quite some time. </p>

<p>You can interpret that story however you wish, I am just pointing the potential usefulness of a scientific mind in economics.</p>

[nj_azn_premed]

<p>“Anyways, one of the recent nobel prizes in economics went to two of the 3 people behind the so-called Black-Scholes equation. It is a partial differential equation that deals with the values of options, a type of equity.”</p>

<p>Yes! I completely forgot about that, but that’s an excellent example. And Sakky, I would also appreciate an explanation.</p>

[Alexandre]

<p>I double majored in Economics and Physics. It is a great conbination if you ask me. I don’t see why any university would restrict a student from pursuing such a double major. I have known students who double majored in Engineering and Economics (which is even harder to manage than Physics and Economics) at Cornell, Michigan, Northwestern and Stanford.</p>

[sakky]

<p>

Anyways, one of the recent nobel prizes in economics went to two of the 3 people behind the so-called Black-Scholes equation. It is a partial differential equation that deals with the values of options, a type of equity.

</p>

<p>A minor objection - options are not a ‘type’ of equity. Not at all. They are actually a derivative security that allows you to speculate on the movements of certain financial data and derive their value from that data. </p>

<p>

The kicker: The reason the equation is so powerful is because the inventors of the equation came up with a specific substitution that transforms the PDE into the famous heat equation studied by mathematicians and physicists for quite some time.</p>

<p>You can interpret that story however you wish, I am just pointing the potential usefulness of a scientific mind in economics.

</p>

<p>You guys are clearly talking about Myron Scholes and Robert Cox Merton, the infamous architects of the LTCM hedge fund that, a decade ago, not only lost a ridiculous $4.6 billion, but also required a government-organized bailout. So, I guess you’re right; these models are indeed extremely powerful in that they can destroy huge amounts of wealth in a tiny amount of time, and hence truly are financial ‘weapons of mass destruction’. </p>

<p>[Long-Term</a> Capital Management - Wikipedia, the free encyclopedia](<a href=“http://en.wikipedia.org/wiki/Long-Term_Capital_Management]Long-Term”>Long-Term Capital Management - Wikipedia)</p>

<p>

Yes! I completely forgot about that, but that’s an excellent example. And Sakky, I would also appreciate an explanation.

</p>

<p>It is indeed an excellent example…of financial engineering models that resulted in the destruction of a catastrophic amount of wealth and placed the world’s economy at risk. The LTCM catastrophe was simply a preview to today’s troubles in the financial system when you rely too heavily on mathematical models.</p>

<p>Look guys, I don’t have any objection to financial mathematical models themselves. Obviously they have their uses. However, clearly, the banking sector has relied far too heavily on these models without understanding their limitations. If these models were truly perfect, we wouldn’t be seeing the entire world’s economy being placed in jeopardy, and we certainly wouldn’t need governments to be bailing out millionaire bankers. It is now widely recognized that financiers were relying on models that they didn’t fully understand. For example, when the ratings agencies were stamping AAA ratings on CDO’s and CDO-squareds that only later turned out to be dodgy, when Ibanks were gearing up by 30x in buying MBS’s under the historical assumption that it was “impossible” for housing prices nationwide to decline, when banks were relying on short-term (in some cases 6-hour rollover) funding under the assumption that markets will always be liquid, when the financial system interlocks itself with up to $100 trillion worth of opaque over-the-counter CDS’s supposedly as ‘financial insurance’ without properly accounting for counterparty risk, such that nobody even knows how total CDS’s are out there, who holds them, and what they’re worth (hence they’ve been likened to “dark matter”, we’ve clearly hit a world where financial models have hit their limits. </p>

<p>

It turns out that what Brown discovered — called Brownian motion — is useful in studying all sorts of random phenomena, including financial risk. It’s useful — but not foolproof.</p>

<p>Richard Lindsay is the author of How I Became a Quant, about financial engineers. He says financial models built on Brownian motion have done a great deal of good. These models have been so helpful in managing risk — at least some of the time — that they have made the world far richer. But that doesn’t mean they always work — they’re not perfect. But they’re “the best thing that we have,” Lindsay says.

</p>

<p>[Why</a> Risk Models Failed to Spot the Credit Crisis : NPR](<a href=“http://www.npr.org/templates/story/story.php?storyId=89507530]Why”>Why Risk Models Failed to Spot the Credit Crisis : NPR)</p>

<p>

…market-sensitive risk models used by thousands of market participants work on the assumption that each user is the only person using them. This was not a bad approximation in 1952, when the intellectual underpinnings of these models were being developed at the Rand Corporation by Harry Markovitz and George Dantzig. This was a time of capital controls between countries, the segmentation of domestic financial markets and to get the historical frame right, it was the time of the Morris Minor with its top speed of 59mph.</p>

<p>In today’s flat world, market participants from Argentina to New Zealand have the same data on the risk, returns and correlation of financial instruments and use standard optimization models, which throw up the same portfolios to be favoured and those not to be. Market participants don’t stare helplessly at these results. They move into the favoured markets and out of the unfavoured. Enormous cross-border capital flows are unleashed. But under the weight of the herd, favoured instruments cannot remain undervalued, uncorrelated and low risk. They are transformed into the precise opposite.</p>

<p>When a market participant’s risk model detects a rise in risk in his portfolio, perhaps because of some random rise in volatility, and he tries to reduce his exposure, many others are trying to do the same thing at the same time with the same assets. A vicious cycle ensues of vertical price falls prompting further selling. Liquidity vanishes down a black hole. The degree to which this occurs is less to do with the precise financial instruments, but more with the depth of diversity of investor behaviour. Paradoxically, the observation of areas of safety in risk models, creates risks and the observation of risk, creates safety.</p>

<p>Quantum physicists will note a parallel with Heisenberg’s uncertainty principle.</p>

<p>Policy makers cannot claim to be surprised by all of this. The observation that market-sensitive risk models, increasingly integrated into financial supervision in a prescriptive manner, was going to send the herd off the cliff edge was made soon after the last round of crises*. Many policy officials in charge today, responded then that these warnings were too extreme to be considered realistic.</p>

<p>This brings us to the philosophical problem of the reliance of supervisors on bank risk models. The reason we regulate markets over and above normal corporate law is that from time to time markets fail and these failings have devastating consequences. If the purpose of regulation is to avoid market failures, we cannot use as the instruments of financial regulation, risk-models that rely on market prices, or any other instrument derived from market prices such as mark-to-market accounting. Market prices cannot save us from market failures. Yet, this is the thrust of modern financial regulation, which calls for more transparency on prices, more price-sensitive risk models and more price-sensitive prudential controls. These tools are like seat belts that stop working whenever you press hard on the accelerator.

</p>

<p>[FT.com</a> | Willem Buiter’s Maverecon | Why Bank Risk Models Failed and the Implications for what Policy Makers Have to Do Now](<a href=“Financial Times”>Financial Times)</p>

<p>

The problem is that Wall Street and regulators relied on complex mathematical models that told financial institutions how much risk they were taking at any given time. Since the 1990s, risk management on Wall Street has been dominated by a model called “value at risk” (VaR). VaR attributes risk factors to every security and aggregates these factors across an entire portfolio, identifying those risks that cancel out. What’s left is “net” risk that is then considered in light of historical patterns. The model predicts with 99 percent probability that institutions cannot lose more than a certain amount of money. Institutions compare this “worst case” with their actual capital and, if the amount of capital is greater, sleep soundly at night. Regulators, knowing that the institutions used these models, also slept soundly. As long as capital was greater than the value at risk, institutions were considered sound – and there was no need for hands-on regulation.</p>

<p>Lurking behind the models, however, was a colossal conceptual error: the belief that risk is randomly distributed and that each event has no bearing on the next event in a sequence. This is typically explained with a coin-toss analogy. If you flip a coin and get “heads” and then do it again, the first heads has no bearing on whether the second toss will be heads or tails. It’s a common fallacy that if you get three heads in a row, there’s a better-than-even chance that the next toss will be tails. That’s simply not true. Each toss has a 50-50 chance of being heads or tails. Such systems are represented in the bell curve, which makes clear that events of the type we have witnessed lately are so statistically improbable as to be practically impossible. This is why markets are taken by surprise when they occur.</p>

<p>But what if markets are not like coin tosses? What if risk is not shaped like a bell curve? What if new events are profoundly affected by what went before?</p>

<p>Both natural and man-made systems are full of the kind of complexity in which minute changes at the start result in divergent and unpredictable outcomes. These systems are sometimes referred to as “chaotic,” but that’s a misnomer; chaos theory permits an understanding of dynamic processes. Chaotic systems can be steered toward more regular behavior by affecting a small number of variables. But beyond chaos lies complexity that truly is unpredictable and cannot be modeled with even the most powerful computers. Capital markets are an example of such complex dynamic systems…</p>

<p>The more enlightened among the value-at-risk practitioners understand that extreme events occur more frequently than their models predict. So they embellish their models with “fat tails” (upward bends on the wings of the bell curve) and model these tails on historical extremes such as the post-Sept. 11 market reaction. But complex systems are not confined to historical experience. Events of any size are possible, and limited only by the scale of the system itself. Since we have scaled the system to unprecedented size, we should expect catastrophes of unprecedented size as well. We’re in the middle of one such catastrophe, and complexity theory says it will get much worse.</p>

<p>Financial systems overall have emergent properties that are not conspicuous in their individual components and that traditional risk management does not account for. When it comes to the markets, the aggregate risk is far greater than the sum of the individual risks; this is something that Long-Term Capital Management did not understand in the 1990s and that Wall Street seems not to comprehend now. As long as Wall Street and regulators keep using the wrong paradigm, there’s no hope they will appreciate just how bad things can become. And the new paradigm of risk must be understood if we are to avoid lurching from one bank failure to the next.

</p>

<p>[washingtonpost.com</a> - nation, world, technology and Washington area news and headlines](<a href=“http://washingtonpost.com%5Dwashingtonpost.com”>http://washingtonpost.com)</p>

<p>I personally believe in the Black Swan principle, which holds that not only do supposedly ‘improbable’ events occur far more often than we might expect, but that these events often times have large impacts on the observed system and in ways that models cannot predict. </p>

<p>

In the breakdown of our current financial system, which many deemed impossible or at least highly improbable, I believe we have witnessed the appearance of a black swan. The term black swan comes from the ancient Western conception that 'all swans are white.’ In that context, a black swan was a metaphor for something that could not exist. (Source: [Wikipedia](<a href=“http://www.wikipedia.org%5DWikipedia%5B/url%5D”>http://www.wikipedia.org)</a>.)</p>

<p>In Nassim Taleb’s book The Black Swan: The Impact of the Highly Improbable, he discusses how randomness and uncertainty are much more common than investors would like to admit. In our financial markets, what people perceive to be rare and improbable events do occur. Some examples of these are the stock market crash of 1987, the terrorist attacks on September 11, 2001, and the recent meltdown of our financial system. Yet investors tend to fight the acceptance of this reality. As a result, investors tend to make decisions based on certain assumptions. When markets move outside the realm of these assumptions many are confused, scared and panicked. This is because the reality of investing is much more complicated and unpredictable than many are willing to accept. Opportunities and dangers appear when we least expect them.</p>

<p>Therefore we must know and expect that any portfolio, even those considered to be the safest, will at some point experience a series of very bad returns. More importantly, we must accept that this series of bad returns is unavoidable and not a mark of failure. So with that in mind, even if you hold a portfolio of the safest assets in the world (US Treasuries, ITE) you will at some point see a loss on paper of your investment. In the last 82 years, IA US Intermediate Treasury Index has dropped as much as 6.50% in one month.</p>

<p>Most investors construct portfolios with a set of rules that hopefully allow them to achieve their investment goals under normal circumstances. However, investors must understand, study and appreciate abnormal events. Under these abnormal circumstances even passive investors must change their strategy to actively identify, avoid and adjust to game-changing events. A game-changing event is an event that would permanently change the rules that we use to manage our portfolios. The market dropping 20% in one day is not a game-changing event. In contrast, a permanent ban on short selling would be an example of a game-changing event.</p>

<p>One recent game-changing event my firm encountered was the selling of BearLinx Alerian MLP Select Index ETN (BSR). Once we identified that Bear Stearns, which backed this exchange traded note “ETN”, was at risk of going under, we sold the ETN. On March 17th Bear Stearns was acquired. Once JP Morgan Chase (JPM) announced that it would honor Bear Stearns debts we were able to buy back the ETN and continue with our strategy. We bought it to track the Alerian MLP Index. While we were willing to accept the credit risk inherent in an ETN, we were not investing in BSR to take on the credit risk of a company that might go bankrupt. As soon as we identified that this game-changing risk was present, it was time to exit the investment. While we were able to identify and manage this event, this will not always be the case.</p>

<p>It is true that over long periods of time investors have fairly accurately managed risk and return through asset allocation. I personally believe that we can effectively manage many investment risks most of the time, but not all of the time. Unfortunately and unavoidably, the asset class assumptions that we find relevant to average market situations are less relevant to irregular situations. Does this mean investors should drastically change their long-term strategy when the irregular situations occur? I believe the answer is only if the situation is deemed to be game-changing.

</p>

<p>[System</a> down for maintenance](<a href=“http://seekingalpha.com/article/98669-current-financial-crisis-is-a-black-swan]System”>http://seekingalpha.com/article/98669-current-financial-crisis-is-a-black-swan)</p>

<p>

Last August, The Wall Street Journal published a statement by one Matthew Rothman, financial
economist, expressing his surprise that financial markets experienced a string of events that “would
happen once in 10,000 years”. A portrait of Mr Rothman accompanying the article reveals that he is
considerably younger than 10,000 years; it is therefore fair to assume he is not drawing his inference from
his own empirical experience but from some theoretical model that produces the risk of rare events, or
what he perceives to be rare events.</p>

<p>The theories Mr Rothman was using to produce his odds of these events were “Nobel-crowned” methods
of the so-called modern portfolio theory designed to compute the risks of financial portfolios. MPT is the
foundation of works in economics and finance that several times received the Sveriges Riksbank Prize in
Economic Sciences in Memory of Alfred Nobel. The prize was created (and funded) by the Swedish
central bank and has been progressively confused with the regular Nobel set up by Alfred Nobel; it is now
mislabelled the “Nobel Prize for economics”.</p>

<p>MPT produces measures such as “sigmas”, “betas”, “Sharpe ratios”, “correlation”, “value at risk”, “optimal
portfolios” and “capital asset pricing model” that are incompatible with the possibility of those
consequential rare events I call “black swans” (owing to their rarity, as most swans are white). So my
problem is that the prize is not just an insult to science; it has been putting the financial system at risk of
blow-ups.</p>

<p>I was a trader and risk manager for almost 20 years (before experiencing battle fatigue). There is no way
my and my colleagues’ accumulated knowledge of market risks can be passed on to the next generation.
Business schools block the transmission of our practical know-how and empirical tricks and the knowledge
dies with us. We learn from crisis to crisis that MPT has the empirical and scientific validity of astrology
(without the aesthetics), yet the lessons are ignored in what is taught to 150,000 business school students
worldwide.</p>

<p>Academic economists are no more self-serving than other professions. You should blame those in the real
world who give them the means to be taken seriously: those awarding that “Nobel” prize.
In 1990 William Sharpe and Harry Markowitz won the prize three years after the stock market crash of
1987, an event that, if anything, completely demolished the laureates’ ideas on portfolio construction.
Further, the crash of 1987 was no exception: the great mathematical scientist Benoît Mandelbrot showed
in the 1960s that these wild variations play a cumulative role in markets – they are “unexpected” only by
the fools of economic theories.</p>

<p>Then, in 1997, the Royal Swedish Academy of Sciences awarded the prize to Robert Merton and Myron
Scholes for their option pricing formula. I (and many traders) find the prize offensive: many, such as the
mathematician and trader Ed Thorp, used a more realistic approach to the formula years before. What Mr
Merton and Mr Scholes did was to make it compatible with financial economic theory, by “re-deriving” it
assuming “dynamic hedging”, a method of continuous adjustment of portfolios by buying and selling
securities in response to price variations.</p>

<p>Dynamic hedging assumes no jumps – it fails miserably in all markets and did so catastrophically in 1987
(failures textbooks do not like to mention).</p>

<p>Later, Robert Engle received the prize for “Arch”, a complicated method of prediction of volatility that does
not predict better than simple rules – it was “successful” academically, even though it underperformed
simple volatility forecasts that my colleagues and I used to make a living.</p>

<p>The environment in financial economics is reminiscent of medieval medicine, which refused to incorporate
the observations and experiences of the plebeian barbers and surgeons. Medicine used to kill more
patients than it saved – just as financial economics endangers the system by creating, not reducing, risk.</p>

<p>But how did financial economics take on the appearance of a science? Not by experiments (perhaps the
only true scientist who got the prize was Daniel Kahneman, who happens to be a psychologist, not an
economist). It did so by drowning us in mathematics with abstract “theorems”. Prof Merton’s book
Continuous Time Finance contains 339 mentions of the word “theorem” (or equivalent). An average
physics book of the same length has 25 such mentions. Yet while economic models, it has been shown,
work hardly better than random guesses or the intuition of cab drivers, physics can predict a wide range of
phenomena with a tenth decimal precision.</p>

<p>Every time I have questioned these methods I have been abruptly countered with: “they have the Nobel”,
which I have found impossible to argue with. There are even practitioner associations such as the
International Association of Financial Engineers partaking of the cover-up and promoting this pseudoscience
among financial institutions. The knowledge and risk awareness we are accumulating from the
current subprime crisis and its aftermath will most certainly not make it to business schools. The previous
dozen crises and experiences did not do so. It will be dying with us, unless we discredit that absurd
Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel commonly called the “Nobel
Prize”.

</p>

<p><a href=“http://www.fooledbyrandomness.com/FT-Nobel.pdf[/url]”>http://www.fooledbyrandomness.com/FT-Nobel.pdf&lt;/a&gt;&lt;/p&gt;

[Seiken]

<p>Meh, I was trying to be loose with my definitions so I wouldnt have to define what my words were. (ie what a derivative is).</p>

<p>And I personally believe that the LTC example is in no-way related to the current state of affairs; it is an unrelated event. sorry. I do however agree that the concept of modeling Wall Street is overall a dumb idea IF you are trying to make a profit. The first thing you are taught in financial economics 101 is that you CANNOT accurately predict the behavior of the market based on past trends.</p>

<p>Nevertheless, the Black Scholes equations, in my opinion, was a brilliant idea, and a good example of how powerful a scientific background can be in economics. Find a PDE that can be reduced to the Schrodinger equation and you might get the next Nobel in economics. </p>

<p>And to clarify, if it seemed like I were stating otherwise, studying economics in one way with a scientific mind is one thing, but trying to apply your results to the finance realm is likely to destroy millions. </p>

<p>If LTC is not enough for you, my financial markets and modeling professor likes to remind everyone that Isaac Newton died in a poor house because he got caught up in the stock market.</p>

[sakky]

<p>

And I personally believe that the LTC example is in no-way related to the current state of affairs; it is an unrelated event. sorry

</p>

<p>An unrelated event, is it? Hmmm, financial institutions that over-relied on dodgy models that lost billions of dollars and triggered a government bailout. Sounds pretty related to me. The problem is that nobody seemed to learn from LTCM. They thought they learned, but they obviously didn’t learn. </p>

<p>

The first thing you are taught in financial economics 101 is that you CANNOT accurately predict the behavior of the market based on past trends.

</p>

<p>Ha! Well, then, the 2nd (and 3rd and 4th, etc.) things you learn in financial economics are how to do just that! Or, at least, how they think they can do that. </p>

<p>

Nevertheless, the Black Scholes equations, in my opinion, was a brilliant idea, and a good example of how powerful a scientific background can be in economics. Find a PDE that can be reduced to the Schrodinger equation and you might get the next Nobel in economics.

</p>

<p>The (sad) truth is that economics is not a science. What makes the Schrodinger equation useful is that it has been used to predict experimental results to a very high degree - that the resulting quantum wavefunction does in fact predict the probabilities of locating quantum-scale particles to a highly accurate degree. One can engage in philosophical debates about what exactly that wavefunction really means (i.e. the question of “where” exactly was the particle before I decided to look for it vis-a-vis the Copenhagen interpretation vs. Many Worlds vs. ensemble vs. many minds, etc.), but there is no question that the Schrodinger equation has been continually verified by providing predictions that have been repeatedly experimentally confirmed. Furthermore, Schrodinger follows the key principle of falsifiability. All you would need is find one experimental result that does not conform to the Schrodinger predictions in order to throw the entire theory into question. </p>

<p>But has Black-Scholes done the same? That is to say, has it survived any true experimental tests of its validity? No. In other words, nobody really “knows” whether Black-Scholes is true. It’s certainly not scientific, in the sense that it relies on the scientific method. If we find a case of options pricing that does not conform to Black-Scholes, would that invalidate Black-Scholes? Sadly, it probably would not. In other words, Black-Scholes and other financial modeling equations are really axioms rather than actual scientific equations. The irony is that Black-Scholes is true only in the sense that we as a society believe it to be true, and hence arbitrage away any price discrepancies that do not conform to the equation, but we don’t know whether it’s actually true in any greater sense. Particles would behave according to the principles of quantum mechanics whether we chose to believe in those principles or not. But an options market that does not conform to Black-Scholes would probably just be seen as offering a profitable arbitrage opportunity. In other words, the “problem” would be with the market, not with the theory itself. </p>

<p>Look, the truth is, financial economics is basically just a sub-branch of mathematics leavened with philosophy, neither of which is a science, for neither is inherently falsifiable and neither is concerned with empirical, experimental results.</p>

<p>Hence, I would argue, if anything, you should study economics with a decidedly unscientific mind if you want to do well. To paraphrase Feynman, economists don’t make predictions, they make excuses. </p>

<p>

If LTC is not enough for you, my financial markets and modeling professor likes to remind everyone that Isaac Newton died in a poor house because he got caught up in the stock market.

</p>

<p>Well, your prof didn’t tell you the whole story. Yes, technically speaking, Newton died in debt. However, a few years prior to his death, he had bequethed a quite considerable fortune to his nieces and nephews. It’s actually a rather brilliant strategy: to die in debt because you had already legally bestowed all of your riches to your family, hence leaving your creditors with no way to collect after your death.</p>

<p>When Newton died in 1727, with almost three decades of his cut from the Mint’s prodution in hand, he left an estate — excluding the land inherited from his mother — worth 30,000 pounds. That’s between four and five million pounds in contemporary currency. Newton died rich…</p>

<p>[Friday</a> (Isaac) Newton blogging: Q: How did Newton get rich? (A: He mastered a mundane form of alchemy.) « The Inverse Square Blog](<a href=“http://inversesquare.■■■■■■■■■■■■■/2008/02/01/friday-isaac-newton-blogging-q-how-did-newton-get-rich-a-he-mastered-a-mundane-form-of-alchemy/]Friday”>Friday (Isaac) Newton blogging: Q: How did Newton get rich? (A: He mastered a mundane form of alchemy.) | The Inverse Square Blog)</p>

[dilksy]

<p>“If LTC is not enough for you, my financial markets and modeling professor likes to remind everyone that Isaac Newton died in a poor house because he got caught up in the stock market.”</p>

<p>There’s a reason he’s a financial markets and modeling professor, and not a historian.</p>

[Seiken]

<p>Regarding the issac newton thing; fine, I really dont think its that important. I could be misquoting him or he could be wrong. </p>

<p>More importantly:
*An unrelated event, is it? Hmmm, financial institutions that over-relied on dodgy models that lost billions of dollars and triggered a government bailout. Sounds pretty related to me. The problem is that nobody seemed to learn from LTCM. They thought they learned, but they obviously didn’t learn.
*
Its really stretching it to say that the current crisis is caused by “dodgy models.” In fact I cant really come up with even a BS thing correlating the two, other than in both cases people tried something stupid.</p>

<p>In any case, you seem to think that people only study economics for the sake of making money and have no real interest actually coming up with theories, which is just complete idiocy. Sure a lot of people get econ degrees expecting to work on wall street, but there are a handful of people out there who are more interested in trying to explain why things happen in the market the way they do. Of course there theories dont have to be 100%, and I would run for the hills if people ever invested money into a THEORY, but that doesnt mean such thinking shouldnt be done.</p>

[sakky]

<p>

Its really stretching it to say that the current crisis is caused by “dodgy models.”

</p>

<p>Uh, what? Go and re-read the links in my previous posts. All of them blame the crisis on dodgy financial models. After all, why did the banks pile into mortgage-backed-securities and derivatives that only later turned out to be sketchy? Because their models told them that these were supposedly good bets. It is now a general consensus that the financial industry relied on poor models, hence causing the crash. If their models had actually been accurate, we wouldn’t be in the situation we are in. </p>

<p>Here are a few more:</p>

<p>

Hundreds of hugely complex products based on hugely complex mathematic financial models were created and sold around the world—without first being tested out. There was little or no real-world iterative process. Commercial ankers, hedge fund managers and investment bankers didn’t know what would work or not work in a troubled economic environment, such as one where housing prices fell sharply. In fact, the complex financial instruments were supposed to spread and reduce risk. In the end, they did the opposite. In short, the innovation process was flawed. New inventions were not stress-tested in a real enviroment. </p>

<p>Second, the new financial products were flawed. They were opaque—not transparent. They were sold to investors who didn’t really know what they were buying. Instead, they relied on the rating agencies to tell them the value of the products—if they were AAA or BBB. But that didn’t work. The rating agenices had mathematical models that didn’t work in a period of sharply falling housing prices. In the end, no one really knew what the new products were worth. Worse, when trouble came, those who sold them didn’t know how to fix the products.

</p>

<p>[Did</a> Innovation Cause The Crisis on Wall Street? - BusinessWeek](<a href=“Businessweek - Bloomberg”>Businessweek - Bloomberg)</p>

<p>

To make matters worse, the financial models underpinning many of the most sophisticated new products were largely based on trading patterns from a more tranquil time, at least by historical standards.

</p>

<p><a href=“http://www.nytimes.com/2008/09/20/business/20crisis.html?ref=business[/url]”>http://www.nytimes.com/2008/09/20/business/20crisis.html?ref=business&lt;/a&gt;&lt;/p&gt;

<p>

Recent events have revealed that the methodology of Wall Street’s financial models used for valuing securitized assets is entirely broken. Furthermore, the credibility of rating companies on assigning ratings that assess ultimate payouts for mortgage-backed and asset-backed securities is also bankrupt.</p>

<p>Hence, in contrast to the potentially generous mark-to-model valuations that banks are currently using, it is anyone’s guess as to what the value of Level lll assets sitting on bank balance sheets are worth

</p>

<p>[Asia</a> Times Online :: Asian news and current affairs](<a href=“http://www.atimes.com/atimes/Global_Economy/JI25Dj02.html]Asia”>http://www.atimes.com/atimes/Global_Economy/JI25Dj02.html)</p>

<p>

Duration mis-matches are responsible for much of the failed financial models that led to the crisis

</p>

<p><a href=“http://www.mortgageintroducer.com/mortgages/231845/219/Yesterday’s_news/You_can’t_solve_problems_you_don’t_understand.htm[/url]”>http://www.mortgageintroducer.com/mortgages/231845/219/Yesterday&#37;27s_news/You_can’t_solve_problems_you_don’t_understand.htm&lt;/a&gt;&lt;/p&gt;

<p>

In any case, you seem to think that people only study economics for the sake of making money and have no real interest actually coming up with theories, which is just complete idiocy.

</p>

<p>I never said that people only study economics for the sake of making money. Of course there are some people that want to try to figure out what is going on without actually trying to make money. Don’t put words in my mouth. </p>

<p>On the other hand, what is clearly inevitable is that somebody will try to use your ideas to make money. Maybe you will not personally try to use your own ideas. But somebody will try. Regardless, whoever ends up trying, the point is that economic modeling holds tremendous potential to damage the world, as we are seeing now. </p>

<p>Which gets to my central objection to what you have said. You seem to think that economics is a science, when the truth is, it is not. To be a science is to first make careful observations about the real world, ideally through controlled experiments, and only then do you devise potential hypotheses which may eventually be turned into a true scientific theory. That theory then is probed for predictions that are either confirmed or falsified through more experimentation. </p>

<p>But economics, and especially financial economics, doesn’t really do that. Since you invoked Black-Scholes, let’s use that as an example. What experimental data did the authors use to devise Black-Scholes? The fact is, they used none. They derived the Black-Scholes equation from initial assumptions in a purely deductive style similar to a mathematics proof. But that’s not scientific, because pure mathematics is not a science. Furthermore, has anybody used Black-Scholes to generate predictions which are then experimentally tested on the data to attempt to confirm or falsify? Again, no. Any real-world options prices that are found not to conform with Black-Scholes would be interpreted as a problem with those prices rather than a problem with Black-Scholes itself. In other words, nobody really knows whether Black-Scholes is true, and nobody really seems to be interested in finding out through experimentation. Black-Scholes, like other financial models, is now taken to be an axiom, and that’s clearly not scientific.</p>

[atlonmyback711]

<p>lol nice catch sakky i was referring more to being able to get into grad school and major in economics while not having to major in it undergrad…</p>