These past 2 weeks we’ve periodically gotten a huge number of worldwide referrals from what appears to be a pornographic website, based on the verbage contained the referring URL. Running the link through a Whois search reveals it is in reality a Forex scam site. As is my custom I checked the wiki entries to see if the explaining could be made easy for me and sure enough the two wiki entries had a wealth of great information. (Those wondering about the Forex proper can click here.) For the balance of this post we’re going to concentrate on the scam I linked first and the implications therein so is there we now visit:
A forex (or foreign exchange) scam is any trading scheme used to defraud traders by convincing them that they can expect to gain a high profit by trading in the foreign exchange market. Currency trading “has become the fraud du jour” as of early 2008, according to Michael Dunn of the U.S. Commodity Futures Trading Commission. But “the market has long been plagued by swindlers preying on the gullible,” according to the New York Times. “The average individual foreign-exchange-trading victim loses about $15,000, according to CFTC records” according to The Wall Street Journal. The North American Securities Administrators Association says that “off-exchange forex trading by retail investors is at best extremely risky, and at worst, outright fraud.”
With the scam set let’s visit with the assertion it is possible to beat the Forex. I’ll note these same concepts apply to the stock markets too in varying degrees:
The forex market is a zero-sum game, meaning that whatever one trader gains, another loses, except that brokerage commissions and other transaction costs are subtracted from the results of all traders, technically making forex a “negative-sum” game.
…………..there are many experienced well-capitalized professional traders (e.g. working for banks) who can devote their attention full time to trading. An inexperienced retail trader will have a significant information disadvantage compared to these traders.
Retail traders are – almost by definition – undercapitalized. Thus they are subject to the problem of gambler’s ruin. In a “Fair Game” (one with no information advantages) between two players that continues until one trader goes bankrupt, the player with the lower amount of capital has a higher probability of going bankrupt first. Since the retail speculator is effectively playing against the market as a whole – which has nearly infinite capital – he will almost certainly go bankrupt. The retail trader always pays the bid/ask spread which makes his odds of winning less than those of a fair game. Additional costs may include margin interest, or if a spot position is kept open for more than one day the trade may be “resettled” each day, each time costing the full bid/ask spread.
Although it is possible for a few experts to successfully arbitrage the market for an unusually large return, this does not mean that a larger number could earn the same returns even given the same tools, techniques and data sources. This is because the arbitrages are essentially drawn from a pool of finite size; although information about how to capture arbitrages is a nonrival good, the arbitrages themselves are a rival good. (To draw an analogy, the total amount of buried treasure on an island is the same, regardless of how many treasure hunters have bought copies of the treasure map.)
So it is the middle men who always make the money. Often the middle men also are taking a trade position too so the game truly is rigged. I mention this because the entry properly mentions information advantages. Indeed in my closest circle of stock trading friends we often discuss price/volume movements in issues we own in terms of buyers/sellers “with superior knowledge” or “access to information” the retail investor simply does not have. Properly analyzed the data can confirm previous buys or signal that it’s time to sell. These concepts also underpin the business of insurance where “information advantages” has a more proper name: Information asymmetry.
I’ll stop at this point and mention the insurance industry loves to fund academic research in these areas. For instance, Travelers Insurance counts many grads of the University of Pennsylvania in its upper management ranks so it is only natural they would buy some research from the Wharton School as this very recent press release from U Penn illustrates. Let’s keep that in mind while we explore the wiki entry information asymmetry following this scribd embed.
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The inside joke for lack of a better word is that I met many of the players behind the press release last April at Senator Wicker’s insurance roundtable. Here is a snippet of the post I did last April on the topic:
I didn’t agree with much of what the U Penn people from the Wharton School had to say in that some of their statistics did not tell the entire story. I also think there are holes in some of the economic theory they cited in their presentation.
Its time to point out some areas where I think the research is slanted so lets visit with Wiki on Information Asymmetry, Adverse Selection and Moral Hazard (A topic which Slabbed wiped it a$$ with back in the day). Here is a blurb on Information Asymmetry:
In economics and contract theory, information asymmetry deals with the study of decisions in transactions where one party has more or better information than the other. This creates an imbalance of power in transactions which can sometimes cause the transactions to go awry. Examples of this problem are adverse selection and moral hazard. Most commonly, information asymmetries are studied in the context of principal-agent problems.
In 2001, the Nobel Prize in Economics was awarded to George Akerlof, Michael Spence, and Joseph E. Stiglitz “for their analyses of markets with asymmetric information.”
I noted Stiglitz did a stint at the World Bank so I hope James can give us further insights in the comments as appropriate. His work deals with the related concept of screening, which was recognized with a nobel prize. Wiki does a great job explaining the importance of the contribution:
Before the advent of models of imperfect and asymmetric information, the traditional neoclassical economics literature had assumed that markets are efficient except for some limited and well defined market failures. More recent work by Stiglitz and others reversed that presumption, to assert that it is only under exceptional circumstances that markets are efficient. Stiglitz has shown (together with Bruce Greenwald) that “whenever markets are incomplete and/or information is imperfect (which are true in virtually all economies), even competitive market allocation is not constrained Pareto efficient”. In other words, they addressed “the problem of determining when tax interventions are Pareto-improving. The approach indicates that such tax interventions almost always exist and that equilibria in situations of imperfect information are rarely constrained Pareto optima.” Although these conclusions and the pervasiveness of market failures do not necessarily warrant the state intervening broadly in the economy, it makes clear that the “optimal” range of government recommendable interventions is definitely much larger than the traditional “market failure” school recognizes. For Stiglitz there is no such thing as an “invisible hand”
Anyone not from the Ivory tower intuitively understands what Stiglet is saying. I’ll add that when the market is composed of inherently irrational participants further barriers to market efficiency are erected. You see this play out in the real estate market a good bit with sellers that do not have realistic expectations of value, instead basing a sales price on the amount it will take to accomplish a personal goal or make a miscalculated investment work. Such a condition is somewhat common among inexperienced sellers of real estate.
One would think that several hundred years into the modern era of economic theory such work is well past late in coming especially since very astute students of human nature have understood these factors most likely since human beings engaged in cooperative society. Stiglet’s work has applications in insurance because the terms “markets” and “information asymmetry” are thrown around a good bit by professional bullshit artists like Robert Hartwig of the Insurance (dis)Information Institute. We need only backtrack to those wiki entries on information asymmetry to see the influence of self serving bullshit on these concepts:
In adverse selection models, the ignorant party lacks information while negotiating an agreed understanding of or contract to the transaction, whereas in moral hazard the ignorant party lacks information about performance of the agreed-upon transaction or lacks the ability to retaliate for a breach of the agreement. An example of adverse selection is when people who are high risk are more likely to buy insurance, because the insurance company cannot effectively discriminate against them, usually due to lack of information about the particular individual’s risk but also sometimes by force of law or other constraints. An example of moral hazard is when people are more likely to behave recklessly after becoming insured, either because the insurer cannot observe this behavior or cannot effectively retaliate against it, for example by failing to renew the insurance.
Like most everything that comes from the trade groups there is a kernel of truth in the research. But did anyone bother to wonder if the reverse is true as well in an insurance transaction, such as the information an insurer has that an insured does not such as whether the insurer intends to fully pay its contractual obligations should a claim arise or whether there is a preordained proclivity to use boxing gloves on the customer/claimant in certain circumstances? Does anyone in their right mind think that Linda in Phoenix Arizona would have purchased a disability insurance policy from Unum Provident had she known they gave out the “Hungry Vulture” award to employees who screwed Unum’s own customers over the most come claim time?
And this brings us back to Moral Hazard where once again we see the concept applied in a self serving way:
According to contract theory, moral hazard results from a situation in which a hidden action occurs.
‘It has long been recognized that a problem of moral hazard may arise when individuals engage in risk sharing under conditions such that their privately taken actions affect the probability distribution of the outcome.’
The name ‘moral hazard’ comes originally from the insurance industry. Insurance companies worried that protecting their clients from risks (like fire, or car accidents) might encourage those clients to behave in riskier ways (like smoking in bed, or not wearing seat belts). This problem may inefficiently discourage those companies from protecting their clients as much as they would like to be protected.
Economists argue that this inefficiency inefficiency results from asymmetric information. If insurance companies could perfectly observe the actions of their clients, they could deny coverage to clients choosing risky actions (like smoking in bed, or not wearing seat belts), allowing them to provide thorough protection against risk (fire, accidents) without encouraging risky behavior. But since insurance companies cannot perfectly observe their clients’ actions, they are discouraged from providing the amount of protection that would be provided in a world with perfect information.
We noted the term Moral Hazard was used a good bit by the last two presidential economic teams as it related to the reckless behavior on Wall Street that imploded our economy. The reality is the claims practices of insurance companies are a perfect example of moral hazard, especially since common folks have been tort reformed and insurers are no longer afraid of the consequents of outrageous claims behavior. After all isn’t Unum’s HungryVulture and the infamous American Family Pink Pig also the height of arrogance and self service?
Maybe that is why we mocked the Ivory Tower crowd including Current Treasury Secretary Tim Geithner wiping our ass with moral hazard. That bunch is beyond clueless and as useless as teats on a boar hog.
Can anyone give me an example of the folks at Wharton chipping in with research on the topic of claims handling and information asymmetry, especially since an insured pays for the contract in advance of the performance of the other party? Follow the money folks and you’ll understand why the answer is probably not.
Finally this brings us to Russell Erxleben, the #36 all time draft bust as rated by ESPN:
Erxleben played five less-than-spectacular seasons with the Saints, and is perhaps best known for throwing an overtime interception (after a bad snap) that was returned for a TD in 1979 against the Falcons in his first NFL appearance.
Some die hard Saints fans would argue that Erxleben was a scam when the Saints drafted him with their first pick in the ’79 draft. It seems he had a fondness for running a Forex scam as Wiki explains:
After retiring from the NFL, he became a financial investor in foreign exchange trading, founding Austin Forex International in Austin, Texas. In 1999, following an investigation by the Texas State Securities Board and the Internal Revenue Service, Erxleben pleaded guilty to one count of conspiracy to commit securities fraud, mail fraud and money laundering, and a second count for securities fraud, in connection with misleading statements regarding the past performance of Austin Forex. On September 18, 2000, Erxleben was sentenced by United States District Court Judge James R. Nowlin to 84 months in prison, and ordered to pay a total of $28 million in restitution and a one million dollar fine. Erxleben’s lawyers, the law firm of Locke, Liddell & Sapp, settled a related lawsuit for $22m in 2000.
Next up in this series. Mike Chaney and Robert Hartwig bray in the media on Katrina plus 5 as Slabbed revists the topic of modeling.
Slabbed reports, you decide.