Joseph Heller and Kurt Vonnegut were at a party given by a billionaire when Vonnegut asked Heller how it felt to know that their host might have made more money in one day than Heller’s Catch-22 since it was written. Heller said he had something the rich man could never have. When a puzzled Vonnegut asked what that could be, Heller answered, “The knowledge that I’ve got enough.”
When Princeton Newport Partners closed, Vivian and I had money enough for the rest of our lives. Though the ending of PNP was traumatic for us all, and the future wealth destroyed was in the billions, it freed us to do more of what we enjoyed most: spend time with each other and the family and friends we loved, travel, and pursue our interests. Taking to heart the lyrics of the song “Enjoy Yourself (It’s Later than You Think),” Vivian and I would make the most of the one thing we could never have enough of—time together. Success on Wall Street was getting the most money. Success for us was having the best life.
It was by chance during this time that I discovered the greatest of all financial frauds. On the afternoon of Thursday, December 11, 2008, I got the news I had been expecting for more than seventeen years. Calling from New York, my son, Jeff, told me Bernie Madoff confessed to having defrauded investors of $50 billion in the greatest Ponzi scheme in history. “It’s what you predicted in…1991!” he said.
On a balmy Monday morning in the spring of ’91, I arrived at the New York office of a well-known international consulting company. The investment committee hired me as an independent adviser to review their hedge fund investments. I spent a few days examining performance histories, business structures, and backgrounds of managers, as well as making onsite visits. One manager was so paranoid when I interviewed him at his office that he wouldn’t tell me what kind of personal computers they used. When I went to the restroom he escorted me for fear that I might acquire some valuable crumb of information en route.
I approved the portfolio, with one exception. The story from Bernard Madoff Investment didn’t add up. My client had been getting regular monthly profits ranging from 1 percent to more than 2 percent for two years. Moreover, they knew other Madoff investors who had been winning every month for more than a decade.
Madoff claimed to use a split-strike price strategy: He would buy a stock, sell a call option at a higher price, and use the proceeds to pay for a put option at a lower price.
I explained that, according to financial theory, the long-run impact on portfolio returns from many properly priced options with zero net proceeds should also be zero. So we expect, over time, that the client’s portfolio return should be roughly the same as the return on equities. The returns Madoff reported were too large to be believed. Moreover, in months when stocks are down, the strategy should produce a loss—but Madoff wasn’t reporting any losses. After checking the client’s account statements I found that losing months for the strategy were magically converted to winners by short sales of S&P Index futures. In the same way, months that should have produced very large wins were “smoothed out.”
Suspecting fraud, I asked my client to arrange for me to visit the Madoff operation on the seventeenth floor of the famous Lipstick Building on Third Avenue in Manhattan. Bernie was in Europe that week, and as we now know, likely raising more money. His brother, Peter, head of compliance and of computer operations, said that I would not be allowed through the front door.
I asked my client who it was that did the accounting and annual audits for the Madoff fund. I was told it was handled by a one-man shop run by someone who had been a friend and neighbor of Bernie’s since the 1960s. Now on high alert for fraud, I asked when the client received confirmations of trades. The answer was that they came by mail in batches every week or two, well after the dates they supposedly occurred. At my suggestion, the client then hired my firm to conduct a detailed analysis of their individual transactions to prove or disprove my suspicion that they were fake. After analyzing about 160 individual options trades, we found that for half of them no trades occurred on the exchange where Madoff said that they supposedly took place. For many of the remaining half that did trade, the quantity reported by Madoff just for my client’s two accounts exceeded the entire volume reported for everyone. To check the minority of remaining trades, those that did not conflict with the prices and volumes reported by the exchanges, I asked an official at Bear Stearns to find out in confidence who all the buyers and sellers of the options were. We could not connect any of them to Madoff’s firm.
I told my client that the trades were fake and Madoff’s investment operation was a fraud. My client had a dilemma. If I was right and he closed his accounts with Madoff he would protect his money, save his reputation, and avoid a legal mess. He argued that if I were wrong, he would needlessly sacrifice his best investment. I answered that I could not be wrong: I had proven from public records that the trades never happened. He was being sent make-believe trade slips. I made the point that to ignore this could put his job at risk. That clinched it. He closed his accounts with Madoff and got his money back. Over the next eighteen years, he watched other Madoff investors seem to get rich. I wonder how often he regretted hiring me.
In my attempt, via “networking,” to find out how much other money was invested with Madoff I repeatedly heard that all his investors were told not to disclose their relationship, even to one another, on threat of being dropped. Even so, I asked around, located half a billion dollars, and concluded that the scheme had to be much larger. One investor’s track record showed gains every month back to 1979, annualizing at 20 percent, and I was told the record was similar stretching into the late 1960s. The scheme had already been operating for more than twenty years!
Having shown that Madoff was posting made-up trades to my client’s accounts, and that he was apparently doing so to several other investors with whom I spoke, I had the smoking gun that proved fraud. I warned people in my network, forecasting an ever-expanding Ponzi scheme that one day would end disastrously. Ponzi schemes take profits to investors. They use the money the investors put in but eventually need more, which they get by recruiting new investors. These new investors also have to be paid, leading the Ponzi operators to sign up still more. The longer it went undetected the bigger it would grow and the worse it would be when it collapsed.
At this time Madoff was a major figure in the securities industry, serving as chairman of NASDAQ, running one of the largest “third market” (off the exchanges) stock trading firms in the country, consulted by government, and routinely checked out by the SEC.
Would the establishment have believed charges of wrongdoing? The story of Harry Markopoulos gives the answer. Challenged by his boss in 1999 to explain why Madoff, with a supposedly similar strategy, could produce much better and steadier returns, Markopoulos concluded that it was impossible on the basis of quantitative financial reasoning, just as I had done before I began my investigation that proved fraud. Though he didn’t establish that the individual trades were faked, even without that smoking gun his arguments were overwhelmingly persuasive. For the next ten years Markopoulos attempted to get the SEC to investigate, but it brushed him aside repeatedly, cleared Madoff after superficial investigations, and quashed a request from the Boston office, prompted by Markopoulos, to investigate Madoff Investment as a possible Ponzi scheme.
In a remarkable 477-page document, “Investigation of Failure of the SEC to Uncover Bernard Madoff’s Ponzi Scheme—Public Version,” August 31, 2009, Report No. OIG-509, the SEC investigates and documents its own repeated failures, beginning in 1992 and continuing until Madoff confessed in 2008, to follow up on obvious clues, pointed complaints, and clear violations of securities laws. Yet the SEC continued to destroy documents through at least July 2010, relating not only to Madoff, but to major financial institutions like Goldman Sachs and Bank of America, as well as SAC Capital Advisors, during a continuing investigation of the latter. Charged with insider trading, SAC Capital agreed to a record $1.8 billion fine in late 2013 and closed itself to outside investors.
Ten years after I discovered the Madoff fraud, at a hedge fund investing conference sponsored by Barron’s, a weekly publication by The Wall Street Journal presenting financial data and in-depth stories, the headline article was about the investment manager who wasn’t there, the manager with the best record of all—Bernie Madoff. Better yet for investors, he didn’t charge the typical hedge fund fees of 1 percent of assets per year plus 20 percent of any new net gains. Supposedly he made his money from charging small fees on the huge trading volume that was flowing through his brokerage firm from the orders he placed on behalf of his investment clients.
Even with the well-publicized doubts expressed in the Barron’s story, and the suspicions of fraud now being voiced by many, the regulators slept on. So did Madoff’s thousands of investors and the fiduciaries they paid to protect them. How did the fraud end? When it became clear that there wouldn’t be enough money to keep paying investors, which is how all Ponzi schemes end, Bernie Madoff (pronounced MADE-off, as in “with your money”) turned himself in on December 11, 2008. Probably to protect his associates, he came up with the improbable story that he was the sole conspirator in the scheme. This man who was virtually ignorant about computer systems claimed to have single-handedly directed the whole secure seventeenth-floor computerized operation, along with some twenty or so employees generating—supposedly unknowingly—a daily torrent of billions of dollars of fake trades for thousands of accounts.
On August 11, 2009, exactly eight months later, Frank DiPascali, Jr., the man who supervised Madoff’s operations day-to-day, was charged by the SEC in the US District Court, Southern District of New York. At this point the SEC knew that Bernard Madoff Investment Securities (BMIS) “managed investor accounts as far back as the 1960s…” However, the SEC complaint said the split-strike price strategy dated from 1992, whereas I had reviewed client records showing that it was in place years earlier. Pleading guilty, Madoff told the judge that he began stealing money in the early 1990s. But his criminal empire was already big then and had started at least twenty years earlier. Madoff claimed his brother, Peter, and sons, Mark and Andrew, all principals in the firm, and the detail-oriented hands-on wife, Ruth, were totally innocent and unaware of any complicity in the massive forty-year fraud. In addition to supposedly running his swindle single-handedly, Madoff was vacationing at his various residences, traveling abroad to raise ever more money, shuffling massive funds internationally among banks, and paying large fees to “fiduciaries” who brought him investments, while the complex scheme somehow ran like clockwork during his many absences.
Bernie Madoff, in his allocution to the judge, said, contrary to fact, that he thought his swindle began about 1991, whereas I discovered then that the scheme had already been running for decades. The SEC’s complaint against Frank DiPascali—presumably using information from DiPascali—that the fraud was computerized and the split-strike price strategy had begun in 1992, was also contradicted by the client reports I had reviewed from 1989 through 1991. Peter Madoff, DiPascali, and several other employees later pled guilty and were sentenced to fines and jail.
Madoff gave the size of the scam at $50 billion, though based on the amount of fake equity investors believed they had in their accounts at the end it was later estimated at $65 billion. To equitably distribute any remaining money, the bankruptcy trustee has to determine how much money each victim put in, what was paid out, and to whom. Several “handlers,” who each collected billions from the investors for whom they claimed to have thoroughly verified the legitimacy of Madoff’s strategy, skimmed off hundreds of millions in fees. Powered by this cash flood, they rose among the politically and socially connected superrich. One individual reportedly withdrew over $5 billion more than he put in! The fact that Madoff was letting others collect huge sums in management fees, all the while settling for much less in trading commissions, should itself have been enough to alert investors, advisers, and regulators.
The government released a list of more than thirteen thousand past and present Madoff account holders, ranging from hundreds of not very rich Florida retirees to celebrities, billionaires, and nonprofits such as charities and universities. If these legions of investors were easily gulled, often for decades, what does this swindle (and others) say about the academic theory that markets are “efficient,” with its claims that investors quickly and rationally incorporate all publicly available information into their selections?
Among the thousands of Madoff investors on the list was a well-known financial adviser who had been present at the meetings in 1991 where I exposed the Madoff scam. At that time I had known Ned, as I’ll call him, for many years so I made sure he understood every detail. Although we lost touch in the mid-1990s, I was astonished in 2008 to find that he and his family were on the government’s list of Madoff’s investors. Moreover, a mutual acquaintance told me that Ned, who had made hundreds of millions advising clients, was still directing investors to Madoff the same week that the latter confessed.
Having once known Ned well, I thought back to get more insight into why he believed in Madoff. In my opinion Ned was not a crook. Instead, I think he suffered from so-called cognitive dissonance. That’s where you want to believe something enough that you simply reject any information to the contrary. Nicotine addicts will often deny that smoking endangers their health. Members of political parties react mildly to lies, crimes, and other immorality by their own but are out for blood when the same is done by politicians in the other party.
I also learned early that when I gave Ned my opinion on anything, no matter how careful or reasoned, it didn’t have much impact. Others had the same experience. To make a decision, Ned would simply poll everyone he knew for their opinion and then go with the majority view. Once I figured this out, I stopped wasting my time sharing my thoughts with him.
The Ned polling method works remarkably well in certain situations, like guessing the number of beans in a barrel, or the weight of a pumpkin. The average of all the guesses by the crowd is typically much better than most of the individual guesses. This phenomenon has been called the wisdom of crowds. But like most simplifications, this has a flip side, as in the Madoff case. Here there were just two answers, fraudster or investment genius. The crowd voted for investment genius and got it wrong. I call the flip side to the wisdom of crowds the lunacy of lemmings.
By 1991, I had simplified to a staff of four people. Steve Mizusawa was hedging Japanese warrants, with some assistance from me. I was also managing a portfolio of hedge funds for myself, with help from Judy McCoy. She was in charge of tax and financial reporting, helped Steve, and backed up our office manager.
Enjoying life and ambivalent about returning to the investment hubbub, I tried to find a time-efficient way to cash in on our statistical arbitrage knowledge. After discussions with Steve, who would be crucial in implementing any such venture, I went shopping for a partner to whom we could license our software for royalties.
I contacted Bruce Kovner, a successful commodities trader whom I knew from Princeton Newport days. Kovner started with the Commodities Corporation in the 1970s, then went on to run his own commodities hedge fund, eventually making billions for himself and his investors.
Along with Jerry Baesel, the finance professor from UCI who joined me at PNP, I spent an afternoon with Bruce in the 1980s in his Manhattan apartment discussing how he thought and how he got his edge in the markets. Kovner was and is a generalist, who sees connections before others do.
About this time he realized large oil tankers were in such oversupply that the older ones were selling for little more than scrap value. Kovner formed a partnership to buy one. I was one of the limited partners. Here was an interesting option. We were largely protected against loss because we could always sell the tanker for scrap, recovering most of our investment; but we had a substantial upside: Historically, the demand for tankers had fluctuated widely and so had their price. Within a few years, our refurbished 475,000-ton monster, the Empress Des Mers, was profitably plying the world’s sea-lanes stuffed with oil. I liked to think of my part ownership as a twenty-foot section just forward of the bridge. Later the partnership negotiated to purchase what was then the largest ship ever built, the 650,000-ton Seawise Giant. Unfortunately for the sellers, while we were in escrow their ship unwisely ventured near Kharg Island in the Persian Gulf, where it was bombed by Iraqi aircraft, caught fire, and sank. The Empress Des Mers operated profitably into the twenty-first century, when the saga finally ended. Having generated a return on investment of 30 percent annualized, she was sold for scrap in 2004, fetching almost $23 million, far more than her purchase price of $6 million.
Kovner referred me to a hedge fund in which he was a major investor, and I proposed to the manager of the fund that we would supply the software for a complete statistical arbitrage operating system and license it for 15 percent of his gross income from the use of the product. We would train their employees and provide continuing counsel. Our license fee would decline over time to adjust for improvements they might add, and for the obsolescence of the original system. However, every time we agreed on a deal, the GP insisted on making yet another change in his favor. After we had agreed to some of these, it became apparent that they were endless. I terminated negotiations.
Most of us who have dealt with used-car dealers or rug merchants, or who have bought and sold real estate, are familiar with a negotiation process perhaps best described as haggling. To illustrate, suppose a house you want is priced at $300,000. You offer $250,000. The seller counters at $290,000. You counter at $265,000, and so forth. Finally you agree to buy at $275,000. This stylized dance may involve cajolery, trickery, and deceit. Wouldn’t it be simpler and more satisfying for the seller to state his price and have the buyer take it or leave it? After all, that’s how it’s done in most stores in the United States. How could you shop if the prices you compare aren’t firm?
Yet in business deals haggling is common, just as it was with the fund manager who haggled with me. What’s going on here? In our house example, suppose the seller’s real lowest price is $260,000 and that the highest price the buyer is really willing to pay is $290,000. (The seller might find out, for instance, that the buyer will really pay $290,000 by reporting that he has another offer at $289,000, at which point the first buyer offers $290,000.) Thus any price between $260,000 and $290,000 is acceptable to both parties, even though neither party knows this at the time. So $30,000 is “up for grabs.” The objective of the haggle is to capture as much of this $30,000 as possible for one side or the other.
On the other hand, if instead the buyer is willing only to go to $270,000 and the seller’s (secret) lowest price is $280,000, there is no overlap, no price both will accept, and there will be no deal.
Where my family and I lived for over two decades was determined by just such a haggler. We had decided to build a new house and had located a lot with a spectacular view high on a hill in Newport Beach. In the depressed 1979 real estate market it was offered at $435,000. We started at $365,000; after a series of offers and counteroffers, we eventually came back with $400,000, which was countered at $410,000. We countered at $405,000, our absolute limit. Rejected. We walked. A few days later the seller relented and offered to meet our $405,000 price. But we didn’t accept. Why not?
At our absolute limit, we were almost indifferent as to whether we did the deal or not. Meanwhile the seller had now alienated us, and we preferred not to have any further dealings with him. Consequently his deal was less attractive, and our top price now dropped below $405,000. Meanwhile we considered alternatives. We soon bought a better lot, built a new house, and spent twenty-two happy years there. The haggler’s lot remained unsold for another decade.
Coincidentally, when we sold this house, we had another example of the losing haggle. After it had been on the market a year, we suddenly got two offers the same weekend. We were asking $5,495,000 and expected to get about $5,000,000. One offer was at $4.6 million, and the prospective buyer used his aggressive business partner to open negotiations. The partner’s in-your-face style and nitpicking criticism of the house was designed to beat down the price. He alienated us and our agent. The other offer was for $5 million from an agreeable family who loved the house “as is.” We accepted, upon which the other buyer begged us to reconsider, indicating he would meet or exceed the other price, and wouldn’t use Mr. in-your-face to close the deal. Too bad. Lesson: It doesn’t pay to push the other party to their absolute limit. A small extra gain is generally not worth the substantial risk the deal will break up.
Knowing when to haggle and when not to is valuable for traders. In the days of Princeton Newport our head trader used to crow about how, by regularly holding out for an extra eighth or quarter, he saved us large amounts of money. Here’s the idea. Suppose we want to buy 10,000 shares of Microsoft (MSFT), currently trading at, say, 71 bid for 50,000 shares, and 71¼ asked for 10,000 shares. We can pay 71¼ now and buy our 10,000 shares. Or, as our trader would do, we can offer to buy our 10,000 shares at 711⁄8 and see if we have any takers. If this works—and it does most of the time—we’ll save $1⁄8 × 10,000 or $1,250.
This sounds good. Is there any risk? Yes. By trying to save $1⁄8 per share we may miss a big winner if the stock always trades at 71¼ or higher for however long we’re trying to buy. Those stocks we miss, which run away to the upside, would have given us windfall profits. Put simply, you might scalp $1⁄8 twenty times but lose $10 once. Do you like that arithmetic? I don’t.
I asked our trader how he could tell whether his repeated scalping for an eighth of a point offset his losses from missed opportunities. He could not make a case for what he was doing. I asked other traders around the street the same question and didn’t find anyone who could clearly show that they gained more than they lost by doing this.
Markets are basic to modern economics, and trading is a fundamental activity. Modern financial theorists have, therefore, intensively analyzed how markets work, both by examining data and by developing theories to explain what they observe. They note that trades are initiated, sometimes by a buyer and other times by a seller, for a variety of reasons. Some participants have no edge—no special advantageous information—probably including most of the people who do think they have an edge. Examples of these so-called noise traders might include an index fund selling a company because it was dropped from the index, or buying a stock that was added to its index, or an estate liquidating to pay taxes, or a mutual fund buying or selling in response to cash additions and withdrawals. Of course, to the extent worthwhile information is used in these trades, such examples are imperfect.
The other type of trade is initiated by traders who do have an edge. Examples might be the illegal insider trades made famous by the prosecutions of Ivan Boesky and others in the 1980s—despite which such activities continue to this day; or the legal trades made by those who are the first to act on public information like an earnings announcement, a takeover, or an interest rate change.
Does all this really matter? What’s an eighth of a dollar a share? For our statistical arbitrage program that was trading one and a half billion shares a year, it would amount to almost $200 million annually. As Senator Everett Dirksen was once quoted as saying about congressional spending, a billion dollars here, a billion dollars there, and pretty soon you’re talking about some real money.
What the hagglers and the traders do reminds me of the behavioral psychology distinction between two extremes on a continuum of types: satisficers and maximizers. When a maximizer goes shopping, looks for a handyman, buys gas, or plans a trip, he searches for the best (maximum) possible deal. Time and effort don’t matter much. Missing the very best deal leads to regret and stress. On the other hand, the satisficer, so-called because he is satisfied with a result that is close to the best, factors in the costs of searching and decision making, as well as the risk of losing a near-optimal opportunity and perhaps never finding anything as good again.
This is reminiscent of the so-called secretary or marriage problem in mathematics. Assume that you will interview a series of people, from which you will choose one. Further, you must consider them one at a time, and having once rejected someone, you cannot reconsider. The optimal strategy is to wait until you have seen about 37 percent of the prospects, then choose the next one you see who is better than anybody among this first 37 percent that you passed over. If no one is better you are stuck with the last person on the list.
This idea rescued me back in my graduate student days at UCLA, shortly after I had changed from the PhD program in physics to that in mathematics. My thesis adviser, Angus Taylor, decided that I, like other doctoral candidates, should deliver a mathematical talk for students. With my then comparatively skimpy mathematical background, I was stumped for a topic that would interest the mathematically knowledgeable people who would attend and also attract new faces from outside the department. At the last minute I came up with the title “What Every Young Girl Should Know” and refused to tell anyone what I was going to say about it. The room was packed, with attendance beyond anything previously seen. Most agreeably, in addition to the usual mostly male audience, there were lots of pretty coeds. From their questions and their expressions afterward, my listeners weren’t disappointed. I had talked about the solution to the so-called marriage problem and had made the math behind it understandable.