"Financial instruments across the globe hinge on tiny movements in Libor. If something was wrong, the pool of potential victims would be vast. As it turned out, something wasn’t wrong with Libor: everything was."
2/ "Boiled down to their essence, derivatives were designed to help people or institutions protect themselves from future circumstances. And no matter what, one party in the transaction always came out ahead—that was the bank that, for a fee, engineered the derivative." (p. 31)
3/ "As always, the advantage went to the trader who found an edge—whether that edge was a gullible client, a superior product, a more sophisticated computer model, whatever. Sometimes the edge was simply pushing the envelope just a little bit further than anyone else." (p. 35)
4/ "One illustration of the industry’s culture was that brokers used the word broking to mean “tricking” or “misleading”—as in, I was broking him to believe something that wasn’t true." (p. 42)
5/ "For every $100 that a trader generated in commissions, the broker recycled $5 or $10 of that back in the form of “entertainment.” It was meant to cement the relationship and create a causal connection between the amount of business and the amount of all-expenses-paid fun.
6/ "If that sounds like a kickback, that’s basically what it was.
"Dinners at Michelin-starred restaurants and thousand-dollar bottles of champagne at clubs were just the tip of the iceberg. All-expenses-paid jaunts to Mediterranean resort destinations became the norm.
7/ "So were boozy ski trips to the Alps; the resort town of Chamonix became something resembling an off-site campus for ICAP & Tullett. Private jets and helicopters ferried traders to the MTV European music awards. Some brokers picked up $10,000 golf club membership fees." (p.51)
8/ "From the start, Libor was prone to problems, including the potential for banks to manipulate it.
"Virtually all it took for a bank to skew Libor was for it to skew its own submission. It was common knowledge that banks tweaked Libor to benefit their own trading positions.
9/ "Banks had multiple incentives to push or pull Libor. One was that, because each bank’s submission was made public, investors scoured the data for indicators about the bank’s financial health. A bank that reported a spike in its borrowing costs might be in trouble.
10/ "There was a possibility that the interest rates on everything from mortgages and credit card bills to enormous corporate loans could be based on flawed data." (p. 73)
11/ "The Foreign Exchange and Money Markets Committee's members would turn out to be more concerned with minimizing their time commitments and protecting their respective banks than they would be about trying to deal with Libor’s increasingly obvious problems." (p. 77)
12/ "Smith had no clue what he was doing. He didn’t know how to go about figuring out the bank’s borrowing costs, which were supposed to be the basis of the bank’s Libor data. He didn’t even know whom to talk to internally. So Smith did what his peers at other banks were doing.
13/ "Lacking relevant information, he would make up his submission based in part on what the brokers were predicting. It was simpler than trying to navigate UBS’s internal bureaucracy. And handling the bank’s Libor submissions was just one of Smith’s duties, not a top priority.
14/ "Sometimes the swaps traders would lob a request in his direction about where they wanted him to submit the bank’s Libor data that day. Even as a rookie on the desk, he understood what was going on. The traders had big positions whose values hinged in large part on Libor.
15/ "A lot of money was on the line. So Smith generally followed their requests when it came to what he entered into his spreadsheet. He didn’t see any reason not to." (p. 84)
16/ "The guys responsible for submitting the bank’s daily Tibor data were seated next to the traders, like Hayes, who were making wagers that depended largely on the movements of Tibor and Libor. In some cases, the Tibor submitters themselves were making those trades.
17/ "Long before Hayes arrived in Tokyo, the submitters and the traders had helped each other. It had been common practice at UBS for traders to ask their deskmates to nudge Tibor in helpful directions and to ring colleagues in other parts of the UBS empire for help moving Libor.
18/ "Those colleagues didn’t have to comply—they could have reported something resembling the bank’s actual borrowing costs—but who wanted to be the martyr, the goody two-shoes, who interfered with traders raking in profits for the bank?" (p. 93)
19/ "Employees at some banks—including Citigroup, J.P. Morgan, Royal Bank of Scotland, WestLB, & Lloyds—who were in charge of submitting Libor data sometimes appeared to copy ICAP’s data rather than go through the onerous process of coming up with their own hypothetical estimates
20/ "of what it would cost to borrow across different currencies and time periods. Relying on the run-throughs represented an enticing shortcut. And because of the inherent subjectivity of the Libor estimates, nobody was likely to notice.
21/ "Once, when Goodman’s run-through contained a typo, suggesting six-month Libor at 1.10 instead of 1.01, Read noticed that Citigroup and WestLB copied it, even though it represented a huge leap from the previous day’s level.
22/ "When Goodman corrected it the next day, the banks again followed suit. In other words, the laziness of a few bank employees—“sheep,” as Read sometimes called them—meant that ICAP’s run-throughs had a startling amount of real power." (p. 97)
23/ "There were limits to the extent that traders would tinker with Libor. You could move Libor within a certain plausible band to help yourself, but straying outside that range was at best unwise." (p. 102)
24/ "Every morning, Hayes and Pieri gathered with more than a dozen colleagues in a conference room. The participants discussed their plans to get Libor moved. It wasn’t a secret; when senior executives cycled through Tokyo for periodic visits, they usually sat in." (p. 114)
25/ "Brokers sometimes were approached about possible trades by pension funds or other long-term investors (dumb-money clients, or “muppets”) who weren’t sensitive to small price variations.
"Brokers had the distinct pleasure of finding predators to take the other side." (p.123)
26/ "Phone calls & e-mails were pouring in from bankers who said the rate was divorced from reality. As the financial crisis intensified, banks’ borrowing costs soared, yet Libor wasn’t moving.
"Ewan reassured participants that the BBA had rigorous quality control measures.
27/ "Reality was different. Ewan knew troubling things were afoot. Banks, terrified about the escalating crisis, were hardly lending to each other. Giving money to another bank, even a relatively safe one, seemed a reckless act of doubling down on a highly distressed industry.
28/ "The safer bet was just stashing money in accounts maintained at any number of central banks. That made the Libor estimates little more than guesswork.
"Banks had a powerful incentive to err on the side of understating their borrowing costs.
29/ "If it seemed like it wasn’t expensive for them to borrow, it might look to the outside world that they were more stable.
"A Gulf International Bank official received a phone call from a bank that was on a Libor-setting panel expressing interest in borrowing from Gulf.
30/ "Later that day, that same bank submitted Libor data that was ten basis points lower than what they’d been willing to pay Gulf to borrow. The bank had been citing a specific rate and hours later appeared to be understating its borrowing costs by a substantial margin.
31/ "Before he could divulge the name of the offending bank, Ewan asked him not to. Such knowledge might force him to act on the allegations.
"The wild, unpredictable swings in Libor made it much harder to make money by lending to individuals and small businesses." (p. 182)
32/ "in the mid-1990s, structured notes were among Wall Street’s hottest fads. A type of bond whose value was partly linked to derivatives, the notes were custom-made by investment banks on behalf of companies that were looking for new ways to entice investors to lend them money.
33/ "Peng soon realized that most of those investors didn’t understand what they were buying or what the products were actually worth. The investment banks were taking advantage of that ignorance, which was a big part of the reason the market was booming." (p. 185)
34/ "The Federal Reserve’s arsenal was doling out billions of dollars in loans to cash-strapped banks. The banks had to bid for the loans, and the prices they paid were made public.
35/ "Peng compared the data about the prices of the Fed loans with where the banks were reporting Libor. Sure enough, the figures diverged. The banks were paying high interest rates to borrow from the Fed, but Libor remained suspiciously flat." (p. 186)
36/ "Mollenkamp hadn’t found anyone willing to speak on the record about problems with Libor. Even though concerns were widely held, Libor was such an ingrained part of the system that publicly raising questions bordered on blasphemy. Peng’s report was a breakthrough." (p. 189)
37/ "Whitehouse built a massive Excel spreadsheet comparing banks’ CDS prices with their Libor data over a several-month period. Results showed that many banks’ Libor submissions had little resemblance to their CDS prices and, therefore, their apparent funding costs." (p. 197)
38/ "It was actually in the best interests of the banks’ new government owners for their wards to return to profitability, since that would enable the governments to sell their stakes in the banks at a profit, helping quiet public fury over the unpopular bailouts.
39/ "And the best way to get the banks back to their normal profitable ways, at least according to the bankers themselves, was to unleash the creative, aggressive, risk-taking genius of their traders and investment bankers." (p. 224)
40/ "As Hayes left, UBS shifted responsibility for handling Libor submissions away from traders and clarified that submissions should no longer be based on trading positions or brokers. Some at UBS doubted whether it made sense for the bank to even remain involved with Libor.
41/ "Recent public scrutiny “leads to higher regulatory and reputation risk; we believe it would be worth for senior management to consider the ongoing benefit of being a Libor contributor bank,” read an internal memo 2 weeks before Hayes left. The qualms went unheeded." (p. 240)
42/ "In retrospect, the manipulation was hard to miss. But to outsiders, it wasn’t obvious at the time. The organizations closest to Libor (the BBA and banks) had done everything in their power to hide its problems. Libor's daily moves were not so massive as to suggest tampering.
43/ "They also were not consistently in one direction. The definition of Libor, and the way that definition was interpreted, was fuzzy—not to mention the fact that banks didn’t have rules about how their employees should set the rate." (p. 244)
44/ "Submissions were clustered around the fringes of the highest & lowest categories. Because of the way Libor was calculated—with the highest/lowest submissions thrown out and the rest averaged—banks wanting to move the rate had to aim for high or low without being knocked out.
45/ "This wasn’t the behavior of banks trying to mask rising borrowing costs by submitting artificially low Libor data. It was the behavior of banks trying to push the benchmark in specific directions.
"The report was titled “Does the Libor reflect banks’ borrowing costs?”
46/ "They noted the consensus—held from the Journal to the CFTC—that Libor manipulation appeared to be motivated by lowballing. But their research suggested “that bank portfolio exposure to Libor gives them incentives to push the rate in a direction favorable to these positions.”
47/ "They submitted the paper to a bunch of academic journals. An editor at the Journal of Finance, the field’s foremost publication, was among those who shot it down. “This is ridiculous,” the editor huffed. “Even if it’s true, who would care?” Nobody would publish it." (p. 251)
48/ "The wrongdoing was institutional, from Tokyo to Singapore to London to Zurich, and involved traders, managers, their managers’ managers, and even some high-ranking executives who either knew what was going on or should have. It involved numerous banks & brokerages." (p. 316)
49/ "It looked like there was a network of collusive behavior. That meant the scandal was much bigger than a random, haphazard attempt at manipulation, and it demolished banks’ claims that this was the work of just a few bad apples." (p. 317)
50/ "UBS had done its homework, matching up internal communications and Hayes’s requests to brokers with actual movements in UBS’s Libor submissions and occasional fluctuations in the benchmark itself. They weren’t huge moves—only a couple of bps in one direction or another.
51/ "It wasn’t possible to prove causation; it was conceivable that UBS’s submissions might have moved without Hayes’s pressure. (Another drawback: It involved a Japanese, not an American, rate, which meant it had less impact on, and therefore less cachet with, the U.S. public.)
52/ " “He’s the one,” Park told colleagues. That was just as UBS wanted it. Witnesses provided by UBS would describe Hayes—slim and not quite six feet tall—as large, physically intimidating, and potentially violent. He was beginning to resemble a bogeyman." (p. 325)
53/ "If someone was going down, UBS had to make sure it was Tom Hayes. Everyone who had worked with him had to do whatever he could to make sure Hayes fell alone. Hayes had been central to much of the Libor-skewing effort. But no orchestra is made of a single musician." (p. 326)
54/ "Even the most vigorous prosecutor would have to admit these guys had nothing to do with the larger financial crisis. They weren’t issuing reckless mortgages, packing them into toxic securities, or borrowing the billions of dollars that would topple some of the biggest banks.
55/ "Meanwhile, the bank executives who had done all those things were sitting pretty. Sure, some of them had lost their jobs, but many had walked away with fortunes worth well into the tens of millions of dollars." (p. 405)
56/ "The contrast between Hayes’s fate and those of his peers was stark. Six of his former brokers were preparing to stand trial, but most of his other colleagues were free—and gainfully employed." (p. 444)
57/ "Hayes still didn’t grasp what had really happened. These friends who were not friends, these bosses who now claimed not to be bosses, together they had just engineered their greatest trade of all: Hayes for their own freedom.
58/ "He was the genius, the university man, the millionaire, the star. And he was the fool. Most of them had their money; his would be seized. They had their liberty; he was in prison." (p. 458)
59/ Epilogue:
"These days, banks weren’t borrowing much from each other, so there was no way for them to come up with reliable guesstimates. Meanwhile, involvement in the flawed Libor-setting process had become so radioactive that banks no longer wanted anything to do with it.
60/ "But regulators feared that if banks stopped participating, Libor would unravel, and that would cause big problems for all the trillions of dollars of financial contracts—mortgages, corporate loans, derivatives, and the like—with interest rates based on Libor.
61/ "So regulators more or less demanded that banks remain involved in the rate-setting process. Bailey, though, had concluded that it wasn’t healthy for Libor to keep limping along. It would be better to force everyone to figure out a replacement that had more basis in reality.
62/ "By 2021, he announced, regulators would stop forcing banks to be involved with Libor. What would replace it? What would happen to homeowners with ARMs whose rates fluctuated in tandem with Libor? What about the interest-rate swaps and other derivatives linked to Libor?
63/ "Nobody knew.
"One thing was clear. The world’s most important number—the linchpin of much of modern finance and the root of an epic scandal—was about to be relegated to history." (p. 462)
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2/ "We construct a correlation risk proxy based on the difference between the option-implied correlation of stock returns (obtained by combining index option prices with prices of options on all index constituents) and the realized correlation for different equity markets."
3/ "For the individual variance risk premiums and 30 day maturities, we find generally stronger evidence of economic and statistical significance than for the index variance risk premiums."
"Traditional business cycle indicators do not capture much of the cyclical variation in factor returns. Major turning points seem to be caused by changes in sentiment instead. We infer a Quant Cycle directly from factor returns."
2/ "Altogether, the 1/N mix of factors has virtually the same return during expansions and recessions.
"The simple 1/N mix is again remarkably stable with respect to inflationary and non-inflationary periods, with practically the same return in both regimes."
3/ "Factor returns appear to be solid regardless of the ISM business outlook.
"The investor sentiment index appears to be more effective. However, computing investor sentiment in real time is not easy, given the required inputs, and the resulting scores can be counterintuitive."
1/ Impact of Impact Investing (Berk, van Binsbergen)
"Current ESG divesture strategies have little impact on on the cost of capital of affected firms. Instead of divesting, socially-conscious investors should invest and exercise their rights of control."
2/ "Using the most optimistic estimates, we show that to effect a more than 1% change in the cost of capital, impact investors would need to make up more than 80% of all investable wealth. Given the low likelihood of this, our results question the effectiveness of disinvestment.
3/ "Given that the set of companies targeted comprise only 18% of the market, socially conscious investors could purchase stock & effect change through the proxy process or by gaining a majority stake and replacing upper management. This would require less than 50% participation.
1/ Robust Beauty of Improper Linear Models in Decision-Making (Dawes)
"Even improper linear models are superior to clinical intuition when predicting a numerical criterion from numerical predictors. In fact, unit (i.e., equal) weighting is quite robust."
2/ "In proper linear models, predictor variables are weighted such that the resulting linear composite optimally predicts some criterion of interest; examples of proper linear models are standard regression analysis, discriminant function analysis, and ridge regression analysis.
3/ "Research summarized in Paul Meehl's book on clinical vs. statistical prediction—and a plethora of research—indicate that when a numerical criterion (e.g., graduate GPA) is to be predicted from numerical predictor variables, proper linear models outperform clinical intuition.
A few real estate investors made a lot of money in 2009 and 2010, but they didn't do it because prices rebounded quickly from a low. (In the U.S., prices peaked in 2005 and went into a six-year downtrend.)
They did it by buying houses at large discounts of 30% to 50% + repairs.
There is momentum in real estate like in everything else: trends from last year tend to continue.
But even where we do see mean-reversion (one-month time frames in individual stocks), it takes a portfolio of hundreds of positions to capitalize on this statistically weak effect.
I don't know of any trading strategy that can generate reliable returns by trading a single, individual asset (one stock, one house, etc.) using its past price data.
Real estate investors get around the lack of diversification by getting huge discounts.
1/ US Inflation and Global Asset Returns (Dai, Medhat)
"While average real returns were lower in years with higher inflation for most assets, many of the differences are not statistically reliable, especially among non-bond assets & in more recent times." papers.ssrn.com/sol3/papers.cf…
2/ "Our conclusion that most asset classes have limited inflation-hedging abilities is consistent with the literature. Bodie (1976), Fama & Schwert (1977), & Fama (1981), among others, find that nominal stock returns are negatively related to expected & unexpected U.S. inflation.
3/ "Gultekin (1983) & Beckers (1991), among others, find similar evidence outside the US. Fama & Schwert (1977) also find (i) that nominal returns to government bonds and bills are only positively related to expected inflation and