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Showing posts with label Finance. Show all posts
Showing posts with label Finance. Show all posts

May 30, 2020

Free Sessions during March, April, and May (Quantitative Finance)

Recent large losses in standard stock/bond portfolios emphasize the need for greater diversification and risk control. At the same time, many students are quarantined at home without access to the educational resources they're accustomed to.

As a result, I'm offering an unlimited number of free weekly quant finance sessions for the months of March, April, and May. Please contact me using the form at the bottom of this page for more information.

Students who love math and have a deep-seated interest the stock market will want to check out the curriculum for my Quantitative Finance course, developed from thirteen years of experience reading finance research and four years working as a quant.

Take a look at what others in the finance community are saying about my work:
"Just noticed that @ReformedTrader is bizarrely under-followed. He's curated, quoted, pasted, summarized, analyzed, organized and synthesized well over a hundred papers and articles on academic finance. Honestly, wtf are y'all reading if you aren't following his threads?" Adam ButlerCIO at ReSolve Asset Management (here as well)

"@ReformedTrader has put together an awesome series of Twitter “moments” that highlight research on risk premia, style premia, seasonality, and craftsmanship. Dig in." Corey HoffsteinCIO at Newfound Research and a member of Investopedia's Top 100 in finance (here as well)

"Gotta hand it to @ReformedTrader for his consistency in posting quality quant finance research links. Everyone who is interested in quant finance should follow him. Hidden gem." Pravit Chintawongvanich, Wells Fargo equity derivatives strategist

"Wow, good stuff. I didn't even know the Moments could be used like this. Really great reference and shows the power of info sharing and knowledge building on Twitter." Justin Carbonneaumanaging partner at Validea Capital Management

"Read this thread and become an expert on the quality factor. Fantastic work by @ReformedTrader." Chris Cain, Quantitative Researcher at Connors Research and author of The Alpha Formula (here as well)

"Wow, Darren knows the paper way better than I do now." Cliff Asness, billionaire co-founder of AQR Capital Management, which makes hedge fund strategies available to investors at mutual-fund-level fees

The charts below, taken from a paper written by my friend Pim van Vliet, describe one of the strategies covered in the course.

Note the strong performance in each decade, including the dot-com bust (2000-2002) and 2008 crisis periods. The Conservative leg of the strategy owns low volatility, high momentum, and high buyback yield stocks, leading to more reliable returns than those of the market as a whole.


This chart is from The Conservative Formula: Quantitative Investing Made Easy, one of the papers covered in my Quant Finance course.

Please contact me about tutoring and mention the words "Finance Offer."

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January 31, 2020

Quantitative Finance Course

Update: I've added links to the papers Leverage Aversion and Risk ParityTwo Centuries of Trend Following, Understanding the Tax Efficiency of Relaxed-Constraint Equity Strategies, Investing with Style, Factor Performance 2010-2019: A Lost Decade?, Shorting Costs and Profitability of Long–Short Strategies, Fact and Fiction about Low-Risk Investing, Equity Factors: To Short Or Not To Short, That is the Question, The Rate of Return on Everything, and Exploiting Commodity Momentum Along the Futures Curves.

Here's the curriculum I've put together for Quantitative Finance students.

It starts at a fairly basic level (an introduction to diversification, trend following, and relative momentum) and culminates with advanced reading in academic papers.


  • A deep-seated interest in how financial markets work
  • An A grade in either precalculus or high school statistics (AP Calculus AB or AP Statistics preferred)
  • Ability to commit a minimum of six hours per week to finance homework

Introductory Books

The Ivy Portfolio (Meb Faber)

I've screened dozens of books and have chosen this one because of its readability and balanced introduction to a variety of topics.

Part I discusses how the well-known Yale and Harvard endowments invest and how individual investors can replicate those strategies using index funds.

Part II provides a brief introduction to private equity and hedge fund strategies.

Part III introduces a simple trend-following system that has historically increased risk-adjusted returns while cutting the size of large losses in half.

For example, adding a 10-month moving average filter to the S&P 500 increased its return from 9.3% to 10.6% and lowered its volatility from 15.6% to 11.9%, nearly doubling the risk-adjusted return. The maximum drawdown (largest peak-to-trough loss) was cut from 45% to 23%.

The book also discusses a 13F strategy that can be used to track the stocks that hedge funds buy, cloning their exposures without paying fees.

The Way of the Turtle (Curtis Faith)

Curtis Faith's book is the most accessible introduction to building trading strategies that I've seen.

Chapters 1 and 2 cover the trader's greatest enemy: himself and his own biases. We can reduce these effects by using objective trading strategies that have historically had consistent performance across asset classes, especially if the results survive small tweaks to the strategies' rules.

Chapters 3-8 introduces trend following trading, risk management, and basic statistical metrics that are used to evaluate strategies.

Chapters 9-10 discuss specific indicators that are used to build trend-following trading systems.

Chapters 11-14 go into some of the pitfalls of building systems, including overfitting, small sample sizes, and under-diversification.

The epilogue presents the full-fledged trend trading system that the author, one of the original Turtle traders, used when he was in his twenties working for Richard Dennis.

Strategy Research and Paper Trading

To practice screening for stocks, students initially sign up for StockRover's free plan.

When they're ready to start testing to start testing stock market strategies, they'll need to sign up for Portfolio123. Students that are serious about doing their own research will find the Ultimate plan to be most helpful, as it will allow them to use variable position sizing (as opposed to equally weighting all the stocks) when they run their tests.

Paper trading for stocks and options can be done for free through TD Ameritrade's ThinkorSwim platform. (It's the paperMoney feature.) Your broker probably also offers a paper-trading system, though it may not be as sophisticated as Thinkorswim's.

Students who are interested in futures trading should start with the free Web site FuturesBacktest.

Academic Research (organized by topic)

Within each topic, I've sorted the research so that the easiest material is at the top of the list.

Read These First

A friend asked me to summarize factor investing in a simple way. I didn't do a good job of it over lunch, so here's a (hopefully) better attempt.

Does Higher Risk Actually Lead to Higher Returns?
This is a thread for weird stuff that's hard to explain. In my opinion, there's a lot evidence against the random walk and Capital Asset Pricing Model interpretations of the Efficient Market Hypothesis. That suggests that finance has the same difficulties as other fields in finding a model that works both conceptually and empirically.

Passive Investing

The Rate of Return on Everything
Our new, comprehensive data set includes total returns for equity, housing, bonds, and bills in 16 advanced economies from 1870-2015, revealing new insights and puzzles.


AQR addresses criticisms of momentum by pointing to its strong premium, pervasive evidence (both through time and across markets), and negative correlation to value.

Adaptive Asset Allocation
Estimates of parameters for portfolio optimization based on long-term observed average values are inferior to estimates based on observations over much shorter time frames.
NOTE #1: You can play around with Portfolio Visualizer's mean-variance optimizer if you want to get a hands-on idea of what the paper is talking about.
NOTE #2: This is one of the papers featured in my $10,000 financial adviser offer.

Volatility-Adjusted Momentum
Incorporating volatility estimates in constructing stock momentum leads to a Sharpe ratio increase (0.34 to 1.14) and strongly reduced crash risk. Similar improvements are found in corporate bonds.

Alpha Momentum and Alpha Reversal in Country and Industry Equity Indexes
Past short-term (long-term) alphas positively (negatively) predict future returns, subsuming their return-based counterparts.

Trend Following

We show that the returns of Managed Futures funds and CTAs can be explained by time series momentum strategies and we discuss the economic intuition behind these strategies. Time series momentum strategies produce large correlations and high-R-squares with Managed Futures indices and individual manager returns, including the largest and most successful managers. While the largest Managed Futures managers have realized significant alphas to traditional long-only benchmarks, controlling for time series momentum strategies drives the alphas of most managers to zero. We consider a number of implementation issues relevant to time series momentum strategies, including risk management, risk allocation across asset classes and trend horizons, portfolio re-balancing frequency, transaction costs, and fees.

Time Series Momentum
A diversified portfolio of time series momentum strategies across asset classes delivers abnormal returns with little exposure to standard asset pricing factors & performs best during extreme markets.

Trends Everywhere
AQR examines out-of-sample evidence for trend following in factors and alternative assets. They find that it works, provides substantial diversification, and isn't explained by vol targeting.

Enduring Effect of Time-Series Momentum on Stock Returns Over Nearly 100 Years
Trend following works in individual U.S. (1927-2014) and international (1975-2014) stocks without January losses or momentum crashes.

Two Centuries of Trend Following
Trend following on commodities/currencies/stock indices/bonds is profitable using spot data going back as far as 1800 (both before and after accounting for upward drift).

Dual Momentum – A Craftsman’s Perspective
Our objectives were twofold:
1.Verify the strength and robustness of the Dual Momentum concept and specifically the Global Equity Momentum strategy
2.Describe how to use ensemble methods to preserve expected performance while minimizing the probability of adverse outcomes

You Can't Always Trend When You Want
Trend following has continued to profit from market moves and diversification. However, the average size of global market moves has been more muted than usual.

The convexity profile for a short-term trend following system is most significant when measured over weekly or monthly horizons. Long-term systems, on the other hand, exhibit negative or insignificant convexity profiles over these horizons.

Cross-Sectional and Time-Series Tests of Return Predictability: What Is the Difference?
The difference between the performances of TS and CS strategies is largely due to a time-varying net-long investment in risky assets.

Do Stocks Outperform Treasury Bills?
The best-performing 4% of listed companies explain the net gain for the entire U.S. stock market since 1926; other stocks collectively matched Treasury bills.


Fact, Fiction, and Value Investing
With characteristic wit, AQR corrects misconceptions. Topics include concentration, profitability, momentum, value in other asset classes, composite metrics, and large caps.

Equal-Weight Benchmarking: Raising the Monkey Bars
In the period from 1969 to 2011, if you had picked stocks at random, there is a 99.9% chance you would have beaten the market. It is certainly remarkable that, at a time when the vast majority of hypothetical monkeys flinging darts at the financial pages outperformed, less than half of active managers managed to do so.
NOTE: This is the paper featured in my Introduction to Quantitative Finance page.

Combination Metric Backtest and Comparison of Value Deciles (1951 to 2013)
Over the long run, and with some regularity, cheap stocks tend to outperform more expensive stocks. The PB, PE and PCF ratios are all very useful metrics for sorting cheap stocks from expensive stocks, but we can’t know which will be the better bet at any given point in time. The combo spreads the risk of underperformance relative to any single metric, and, in doing so, generates reliable investment performance over the full period without lagging far behind the front-runner at any point.

Do 'Dogs of the World' Bark or Bite? Evidence From Single-Country ETFs
Mean reversion in financial markets is commonly accepted as a powerful force. This paper examines the performance of a simple mean-reversion-based strategy -- Dogs of the World -- designed to take advantage of return reversals in national equity markets. Both a simulated application of the strategy using indexes since 1971 and application using single-country ETFs since 1997 produces higher compounded average returns than those of a comparable market index. Although the Dogs strategy also produces higher volatility than the index, the information ratio for the strategy suggests that the return more than compensates. An advantage of this strategy is that its implementation using single-country ETFs is straightforward and inexpensive. [NOTE: This paper is no longer available at the SSRN link provided.]

Industry Long-Term Return Reversal
Long-term reversals (3-10 year formations): all U.S. stocks are grouped into 48 industries, and the industries are ranked and traded L/S against each other.


We present a model with leverage and margin constraints that vary across investors and time. We find evidence consistent with each of the model’s five central predictions: (1) Since constrained investors bid up high-beta assets, high beta is associated with low alpha, as we find empirically for U.S. equities, 20 international equity markets, Treasury bonds, corporate bonds, and futures; (2) A betting-against-beta (BAB) factor, which is long leveraged low beta assets and short high-beta assets, produces significant positive risk-adjusted returns; (3) When funding constraints tighten, the return of the BAB factor is low; (4) Increased funding liquidity risk compresses betas toward one; (5) More constrained investors hold riskier assets.

Leverage Aversion and Risk Parity
Consuming the high risk-adjusted returns of safer assets requires leverage. Risk parity portfolios exploit this opportunity by equalizing the risk allocation across asset classes.

Fact and Fiction about Low-Risk Investing
This article presents five facts and dispels five fictions about low-risk investing within equities and across other asset classes.

Betting Against Correlation
What drives BAB - leverage constraints or behavioral effects? AQR digs in by dividing BAB into B.A.Correlation and B.A.Volatility factors.


Accounting for both quality and value yields dramatic performance improvements over traditional value strategies. Gross profitability is particularly powerful, especially for large cap stocks and long-only investors.

Higher-quality stocks have higher prices (P/B) on average, but not by a very large margin. A quality-minus-junk (QMJ) factor earns significant risk-adjusted returns in the U.S. and globally.


In the earliest days of empirical work in academic finance, the size effect was the first market anomaly to challenge the standard asset pricing model and prompt debates about market efficiency. The notion that small stocks have higher average returns than large stocks, even after risk-adjustment, was a pathbreaking discovery, one that for decades has been taken as an unwavering fact of financial markets. In practice, the discovery of the size effect fueled a crowd of small cap indices and active funds to a point where the investment landscape is now segmented into large and small stock universes. Despite its long and illustrious history in academia and its commonplace acceptance in practice, there is still confusion and debate about the size effect. We examine many claims about the size effect and aim to clarify some of the misunderstanding surrounding it by performing simple tests using publicly available data.

Short-Term Reversal

Only the component of short-term reversal which isolates reaction to recent “nonfundamental” price changes is significant and positive; it generates a risk-adjusted return 3x as large.


Halloween and turn-of-the month (TOM) are the strongest calendar effects, fully diminishing the other three (the January effect, weekend effect and holiday effect) to zero.

* Stocks, L/S factors, commodities, and country indices have seasonality
* Factor seasonalities are comparable in size to factors themselves
* Stock seasonality may originate from factor seasonality

Using a sample of 97 stock return anomalies, we find that returns are 6 times higher on earnings announcement days. Results are consistent with biased expectations being at least partially corrected.


The Short of It: Investor Sentiment and Anomalies
Following high levels of market-wide sentiment:
* Anomalies in individual stocks tend to be stronger
* The short leg becomes more profitable
* The long leg's returns are not affected

Why Do Short Interest Levels Predict Stock Returns?
Short sellers are sophisticated investors who have value relevant information about firms and position themselves in stocks with deteriorating fundamentals.

Want Smart Beta? Follow the Smart Money: Market and Factor Timing Using Relative Sentiment
We present a real-time, cross-asset, positions-based relative sentiment indicator derived from the COT report to predict the U.S. equity market.


A simple formula based on low vol, high net payout yield, and 12-1 momentum provides "full and efficient exposure to the most important factor premiums" worldwide.

Value and Momentum Everywhere
Value and momentum are more positively correlated across asset classes than the asset classes are themselves. However, value and momentum are negatively correlated both within and across asset classes.

Superstar Investors
Identify structural edges and commit to seeing them through inevitable periods of underperformance. As each of our superstars shows, “merely good” edges over time compound to great long-term performance.

Buffett's Alpha
AQR finds that Berkshire Hathaway's large 13% CAPM alpha and 0.79 Sharpe ratio become insignificant after controlling for BAB and QMJ. Warren Buffett may have been the first multifactor investor.
NOTE #1: Here's a thread about Berkshire Hathaway's factor loadings. You can also check them yourself at Portfolio Visualizer.
NOTE #2: This is one of the papers featured in my $10,000 financial adviser offer.

Death of Diversification Has Been Greatly Exaggerated
Factor diversification is the best answer for the many investors whose risk is dominated by stock market directionality and who will take the time to understand the approach.

Investing with Style
Value, Momentum, Carry and Defensive deliver positive returns with low correlation in out-of-sample tests across a multitude of asset classes and time periods using very liquid securities.

Strategic Allocation to Commodity Factor Premiums
Portfolios of commodity factor premiums exhibit significantly better risk-adj performance than the commodity market portfolio and add value to a stock/bond portfolio.

Two Centuries of Commodity Futures Premia: Momentum, Value and Basis
* Commodity factors work in hand-collected pre-sample data (back to 1877)
* Long commodities + factor tilts earn higher Sharpes and are still able to hedge inflation

Global Factor Premiums
New sample evidence reveals that the large majority of global factors are strongly present under conservative p-hacking perspectives, with limited out-of-sample decay.

Factor Performance 2010-2019: A Lost Decade?
There appears to be a clear dichotomy in recent factor performance: while generally accepted factors struggled, various factors that are considered to be inferior or redundant remained effective.

Exploiting Commodity Momentum Along the Futures Curves
Momentum strategies that invest in contracts on the futures curve with the largest expected roll-yield or the strongest momentum earn higher risk-adjusted returns.

Ignored Risks of Factor Investing
The risks of factor investing are usually understated (perhaps, severely so), and the diversification benefits tend to be overstated.

Factor Momentum and the Momentum Factor
Factors are positively autocorrelated [and time-series momentum strategies work on them]. Momentum is not a distinct risk factor; it aggregates the autocorrelations found in other factors.

Craftsmanship Alpha

Leveraged Trading (Robert Carver)
* Systematic > discretionary
* Be careful with leverage
* Execution costs and financing spreads matter
* Adjust signals for volatility
* Measure position sizes in dollar × standard deviation units
* Diversification works wonders: add markets and create ensembles

Seemingly inconsequential design decisions can actually matter a lot. The skillful targeting and capturing of style premia may constitute a form of alpha on its own.

Long-Only Style Investing: Don't Just Mix, Integrate
AQR compares "mixing" styles via stand-alone portfolios and "integrating" by combining signals during the stock selection process. Integrating is better b/c it minimizes the impact of constraints.

Role of Shorting, Firm Size, and Time on Market Anomalies
AQR dives into the sources of alpha for L/S size, value, and momentum and whether the alphas have weakened over time.

When Equity Factors Drop Their Shorts
* The alphas of equity factor short legs are subsumed by those of the long legs.
* Only the short (not long) legs of HML, low vol, and low beta are subsumed by FF5.

Shorting Costs and Profitability of Long–Short Strategies
Shorting costs amount to almost 40 percent of gross long–short returns. If other trade-related transaction costs were considered, long–short profits would be reduced further.

Equity Factors: To Short Or Not To Short, That is the Question
A long-short implementation leads to better risk-adjusted returns than its hedged long-only counterpart, at least when AUM are not too large.


Returns of commodity futures indexes have, on average, been positive over the long run. Commodities are a potentially attractive asset class in portfolios of stocks and bonds.

Commodity Futures Risk Premium: 1871–2018
* New database (newspaper data)
* Non-surviving contracts have a minor impact
* Unlike stocks, median commodity has a positive return
* Long-only, carry, and trend strategies work but have prolonged drawdowns


Carry predicts returns cross-sectionally and in time series for a host of different asset classes, including global equities, global bonds, commodities, US Treasuries, credit, and options.

Anatomy of Commodity Futures Risk Premia
A single factor, high-minus-low from basis sorts, explains the cross-section of spot premia. Two additional basis factors are needed to explain the term premia.

Tax Alpha

Tax-managed factor tilts (β=1) generated average tax alphas of 1.6%-1.9%/year. Alpha for tax-managed indexing was 2.3%/year. This can be attributed to loss harvesting and the tax rate differential.

Tax Benefits of Separating Alpha from Beta
The turnover of a strategy that separates α from β is concentrated on the long-short component and enables the deferral of capital gains on the passive market component.

The authors construct basic value and momentum strategies. The long-short portfolio has a tax BENEFIT of 0.3%, which can be increased to 6.1% through tax-aware stock selection and timing.

Relaxing the long-only constraint results in a large increase in their tax benefits in particular due to an increase in the character benefit.

Understanding the Tax Efficiency of Relaxed-Constraint Equity Strategies
* Tax benefits of relaxed-constraint (130/30) equity strategies (character and deferral components)
* Potential impact of the Tax Cuts & Jobs Act of 2017

Volatility Targeting

The authors look at a strategy that uses volatility to adjust the leverage of individual factors (SMB, HML, Mom, RMW, CMA, Carry) as well as country equity indices.

This paper looks at volatility targeting over equities, futures and bonds. Volatility is generally autocorrelated, BUT targeting works better for equity and credit than Treasuries and commodities.


Options as a Strategic Investment (Lawrence McMillan)

Selling a call against stock does NOT provide a reliable cushion against declines. The cushion comes from the call's negative delta and its exposure to the volatility risk premium, not from the premium that you initially collect.

Delta-hedged covered calls outperform unhedged covered calls. This is the case in equity indices throughout the world. The VRP appears to add more diversification than the equity component of the strategy.

Equity index covered calls have historically provided attractive risk-adjusted returns largely because they collect equity and volatility risk premia. However, they also embed exposure to an uncompensated risk, a naïve equity market reversal strategy.

(1) Long-short trend-following and (2) covered calls each have higher Sharpes than buy-and-hold but negative correlations to each other. [This paper is no longer available at the original SSRN download page.]

Collaring the Cube: Protection Options for a QQQ ETF Portfolio
Diagonal collars on QQQ, 3/1999-3/2008, generated higher returns, lower volatility, lower drawdowns, and lower kurtosis than QQQ itself. Purchases were made at ask and sales at bid.

Embedded Leverage
Many financial instruments are designed with embedded leverage such as options and leveraged exchange traded funds (ETFs). Embedded leverage alleviates investors' leverage constraints and, therefore, we hypothesize that embedded leverage lowers required returns. Consistent with this hypothesis, we find that asset classes with embedded leverage offer low risk-adjusted returns and, in the cross-section, higher embedded leverage is associated with lower returns. A portfolio which is long low-embedded-leverage securities and short high-embedded-leverage securities earns large abnormal returns, with t-statistics of 8.6 for equity options, 6.3 for index options, and 2.5 for ETFs. We provide extensive robustness tests and discuss the broader implications of embedded leverage for financial economics.

Portfolio Strategies for Volatility Investing
The degree of VIX futures contango has been shown to hold predictive power over volatility returns. This study proposes a conditional strategy which allocates to market and volatility risk.

Risk Premia and the VIX Term Structure
A single principal component, Slope, predicts the excess returns of S&P 500 variance swaps, VIX futures, and S&P 500 straddles for all maturities to the exclusion of the rest of the term structure.

Risk Parity is Not Short Volatility (Not That There's Anything Wrong with Short Volatility)
The two strategies’ similarities are overstated, and we find no empirical evidence to support the claimed hidden exposure.

Volatility Trading (Euan Sinclair)

Financial Advisors

Misguided Beliefs of Financial Advisors
Advisors trade frequently, chase returns, prefer expensive, actively managed funds, and underdiversify. Their net returns [alphas] of −3%/year are similar to their clients'.

More Strategies

I stay abreast of current research via the FinTwit community and maintain lists of the more interesting developments below (organized by topic):
  1. Benchmarks
  2. Value, Long-Term Reversal, Low Volatility, and Quality
  3. Trend-Following, Cross-Sectional Momentum, and Carry
  4. Volatility Risk Premium
  5. Calendar and Diagonal Spreads
  6. Real Estate, Commodities, and Bonds
  7. Seasonality, Sentiment, Macro, and Short-Term Mean Reversion
  8. Craftsmanship Alpha
  9. Tax Alpha
  10. Sarlacc Pits (things to avoid buying)
  11. Market Psychology and Bubbles
You'll also find a very useful collection of research summaries at CXO Advisory, though you'll have to pay for a membership if you want to access any material written after July 2017.

If you're interested in learning more, please use the form below to contact me. I look forward to meeting you!

Your Name :

Your Email: (required)

Why are you interested in quantitative finance, and what are your eventual goals? (required)

September 6, 2019

SAT/ACT Tutoring in Exchange for Multi-Factor Strategy

Update: I've added a link to Adaptive Asset Allocation and added an additional note for those selling insurance products.

Open Offer

I'll provide $10,000 of free SAT/ACT tutoring to the first East Bay financial adviser who offers as an investible option a strategy that has historically done better than the multi-factor one described in AQR's recent paper Buffett's Alpha (supporting documentation required).

Buffett's Alpha
This chart is from Buffett's Alpha, one of the papers covered in my Quant Finance course.

To be clear, such strategies exist, but they're not normally offered to retail investors like us. I'd like to know whom I can direct people to who will do a good job.

Since most managers don't have a history going back to 1976, funds with a transparent investing methodology that can be backtested back to 1976 or earlier would suffice. Funds with semi-transparent strategies, such as AQR's funds, may qualify if their Portfolio Visualizer factor loadings are large and consistent with the funds' stated goals. A reasonable case can be made for a fund if its factor loadings are greater than Berkshire Hathaway's.

There are publicly traded ETFs and mutual funds that qualify. The adviser would need to provide evidence, such as a Web link, that those funds are offered to clients on a regular basis.

If you sell insurance products that are intended to provide downside protection (floors), you're welcome to use the Sortino ratio, which should make your products look more favorable. (Managers should be using the Sortino ratio anyway as their default metric.)

Strategy Example

Here's another strategy that's historically worked and is relatively simple: Adaptive Asset Allocation. After trading costs and fees, it has a Sharpe ratio of 0.82, higher than Warren Buffett's 0.79. The historical annualized return has been 7.7% percent with 9.4% volatility (a smoother ride than the stock market itself), is positive in 84% of all years, and handled the 2000 and 2008 recessions very well.

Meb Faber tests a similar strategy back to 1973 in his mini-paper A Quantitative Approach to Tactical Asset Allocation. AQR has also done an extensive out-of-sample test of a related concept, trend following, in the paper Trends Everywhere and finds that it works in "normal" assets classes (U.S. and international stocks) as well as alternatives like VIX futures and long/short factors.

Needless to say, if you implement something like this for your clients, you qualify.

This chart is from Adaptive Asset Allocation, one of the papers covered in my Quant Finance course.
The offer is transferable to the relative of your choice. I have perfect scores, so it's not a run-of-the-mill offer. Please contact me if you're interested. Thanks!

(This page has been active since June 11, 2019. I've sent it to every financial adviser who has contacted me as well as those who have advertised their services on NextDoor. So far, no one has attempted to claim the prize. It's still available!)

November 7, 2018

Boomerang (Michael Lewis)

This week, we'll look at Boomerang by Michael Lewis. As usual, I've included representative quotes from the book along with finance-related lessons (in blue) that we can apply to markets today.

Lewis visits Europe to consider the aftermath of the 2008 financial crisis on Iceland, Greece, Ireland, and Germany.

Each of these countries took enormous financial risks it didn't understand. In each case, there were people who saw what was going on. Their voices were ignored until after the market began to collapse.

Iceland: The Carry Trade

For the past few years, some large number of Icelanders engaged in the same disastrous speculation. With local interest rates at 15.5 percent and the krona rising, they decided the smart thing to do, when they wanted to buy something they couldn't afford, was to borrow not kronur but yen and Swiss francs. They paid 3 percent interest on the yen and in the bargain made a bundle on the currency trade, as the krona kept rising. (p. 8)

Borrowing at a low interest rate and buying an asset that is expected to provide a higher return is known as the carry trade. It's a profitable strategy for traders who get in early. In this case, as other traders piled in - borrowing yen and buying the krona - the krona rose in value, providing those early traders with both positive carry (the difference between what they paid to borrow yen and what they made lending the krona) and the appreciation of the krona itself.

It must have seemed like a no-brainer: buy these ever more valuable houses and cars with money you are, in effect, paid to borrow. But, in October, after the krona collapsed, the yen and Swiss francs they must repay became many times more expensive. Now many Icelanders - especially young Iceladers - own $500,000 houses with $1.5 million mortgages, and $35,000 Range Rovers with $100,000 in loans against them. To the Range Rover problem there are two immediate solutions. One is to put it on a boat, ship it to Europe, and try to sell it for a currency that still has value. The other is to set it on fire and collect the insurance: Boom! (p. 9)

At some point, the carry trade runs too far, creating mispricings that will eventually be reversed. In this case, the krona became overvalued and the yen undervalued. Traders needed to exit their positions, buying yen and selling the assets they had bought, but some weren't able to because the assets they bought weren't liquid enough. If you borrow yen in the short term and buy long-term bonds to get a higher interest rate (or worse, buy houses and cars), you're counting on finding a willing buyer to eventually take that position off your hands.

That was the biggest American financial lesson the Icelanders took to heart: the importance of buying as many assets as possible with borrowed money, as asset prices only rose. By 2007, Icelanders owned roughly fifty times more foreign assets than they had in 2002. They bought private jets and third homes, in London and Copenhagen. They paid vast sums of money for services no one in Iceland had theretofore ever imagined wanting. "A guy had a birthday party, and he flew in Elton John for a million dollars to sing two songs," the head of the Left-Green Movement, Steingrimur Sigfusson, tells me with fresh incredulity. "And apparently not very well." They bought stakes in businesses they knew nothing about and told the people running them what to do - just like real American investment bankers! (p. 15)

Since the entire world's assets were rising - thanks in part to people like these Icelandic lunatics paying crazy prices for them - they appeared to be making money. Yet another hedge fund manager explained Icelandic banking to me this way: you have a dog, and I have a cat. We agree that each is worth a billion dollars. You sell me the dog for a billion, and I sell you the cat for a billion. Now we are no longer pet owners but Icelandic banks, with a billion dollars in new assets. "They created fake capital by trading assets amongst themselves at inflated values." (pp. 16-17)

The Danske Bank report alerted hedge funds in London to an opportunity: shorting Iceland. They investigated and found this incredible web of cronyism: bankers buying stuff from one another at inflated prices, borrowing tens of billions of dollars and relending it to the members of their little Icelandic tribe, who then used it to buy up a messy pile of foreign assets. "Like any new kid on the block," says Theo Phanos, of Trafalgar Asset Mangers, in London, "they were picked off by various people who sold them the lowest-quality assets - second-tier airlines, sub-scale retailers. They were in all the worst LBOs." (pp. 19-20)

You didn't need to be Icelandic to join the cult of the Icelandic banker. German banks put $21 billion into the Icelandic banks. The Netherlands gave them $305 million, and Sweden kicked in $400 million. UK investors, lured by the eye-popping 14 percent annual returns, forked over $30 billion - $28 billion from companies and individuals and the rest from pension funds, hospitals, universities, and other public institutions. Oxford University alone lost $50 million. (p. 23)

As a bull market ages, the deals that are done tend be less conservative, and the people participating in those deals tend to be less sophisticated.

Greece: A Subprime Government

In 2001, Greece entered the European Monetary Union, swapped the drachma for the euro, and acquired for its debt and implicit European (read German) guarantee. Greeks could now borrow long-term funds at roughly the same rate as Germans - not 18 percent but 5 percent. To remain the in euro zone, they were meant, in theory, to maintain budget deficits below 3 percent of GDP; in practice, all they had to do was cook the books to show that they were hitting the targets. Here, in 2001, entered Goldman Sachs, which engaged in a series of apparently legal but nonetheless repellent deals designed to hide the Greek government's true level of indebtedness. For these trades Goldman Sachs - which, in effect, handed Greece a $1 billion loan - carved out  reported $300 million in fees. The machine that enabled Greece to borrow and spend at will was analogous to the machine created to launder the credit of the American subprime borrower - and the role of the American investment banker in the machine was the same. The investment bankers also taught the Greek government how to securitize future receipts from the national lottery, highway tolls, airport landing fees, and even funds granted to the country by the European Union. Any future stream of income that could be identified was sold for cash up front and spent. As anyone with a brain must have known, the Greeks would be able to disguise their true financial state for only as long as (a) lenders assumed that a loan to Greece was as good as guaranteed by the European Union (read Germany), and (b) no one outside of Greece paid very much attention. Inside Greece there was no market for whistle-blowing, as basically everyone was in on the racket. (pp. 82-83)

Greece bundled up and sold off tomorrow's income in order to have cash today. That would have made sense if they had invested the money in assets that would have provided a higher return and allowed them to pay the money back. Instead, they spent the money - after having paid fat fees to do the borrowing.

Ireland: An Even Bigger Housing Bubble

Kelly saw house prices rising madly, and heard young men in Irish finance to whom he had recently taught economics try to explain why the boom didn't trouble them. And the sight and sound of them troubled him. "Around the middle of 2006 all these former students of ours started to appear on TV!" he says. "They were now all bank economists and they were nice guys and all that. And they all were saying the same thing: 'We're going to have a soft landing.' "

The statement struck him as absurd on the face of it: real estate bubbles never end with soft landings. A bubble is inflated by nothing firmer than people's expectations. The moment people cease to believe that house prices will rise forever, they will notice what a terrible long-term investment real estate has become, and flee the market, and the market will crash. It was in the nature of real estate booms to end in crashes - just as it was perhaps in Morgan Kelly's nature to assume that if his former students were cast on Irish TV playing the financial experts, something was amiss. "I just started Googling things," he says.

Googling things, Kelly learned that more than a fifth of the Irish workforce was now employed building houses. The Irish construction industry had swollen to become nearly a quarter of Irish GDP - compared to less than 10 percent or so in a normal economy - and Ireland was building half as many new houses a year as the United Kingdom, which had fifteen times as many people to house. He learned that since 1994 the average price for a Dublin home had risen more than 500 percent. In parts of Dublin rents had fallen to less than 1 percent of the purchase price; that is, tyou could rent a million-dollar home for less than $833 a month.The investment returns on Irish land were ridiculously low: it made no sense for capital to flow into Ireland to develop more of it. Irish home prices implied an economic growth rate that would leave Ireland, in twenty-five years, three times as rich as the United States. ("A price-earnings ratio above Google's," as Kelly put it.) Where would this growth come from? Since 2000, Irish exports had stalled and the economy had become consumed with building houses and offices and hotels. "Competitiveness didn't matter," says Kelly. "From now on we were going to get rich building houses for each other." (pp. 90-1)

Their real estate boom had the flavor of a family lie: it was sustainable so long as it went unquestioned and it went unquestioned so long as it appeared sustainable. After all, once the value of Irish real estate came untethered from rents, there was no value for it that couldn't be justified.... 

"There is an iron law of house prices... the more house prices rise relative to income and rents, they more they will subsequently fall." (pp. 91-2)

As it happened, Kelly had predicted the future, with uncanny accuracy, but to believe what he was saying you had to accept that Ireland was not some weird exception in human financial history. "it had no impact," Kelly says. "The response was general amusement. It was what will these crazy eggheads come up with next? sort of stuff." (p. 93)

Kelly wrote his second newspaper article, more or less predicting the collapse of the Irish banks. He pointed out that in the last decade the Irish banks and economy had fundamentally changed. In 1997 the Irish banks were funded entirely by Irish deposits. By 2005 they were getting most of their money from abroad. The small German savers who ultimately supplied the Irish banks with deposits to re-lend in Ireland could take their money back with the click of a computer mouse. Since 2000, lending to construction and real estate had risen from 8 percent of Irish bank lending (the European norm) to 28 percent. One hundred billion euros - or basically the sum total of all Irish bank deposits - had been handed over to Irish commercial property developers. By 2007, Irish banks were lending 40 percent more to property developers alone than they had to to the entire Irish population seven years earlier....

This time Kelly sent his piece of a newspaper with a far bigger circulation, the Irish Independent. The Independent's editor wrote back to say he found the article offensive and wouldn't publish it. Kelly next turned to the Sunday Business Post, but the editor just sat on the piece. The journalists were following the bankers' lead and conflating a positive outlook on real estate prices with a love for country and a commitment to Team Ireland. ("They'd all use the same phrase, 'You're either for us or against us,' " says a prominent Irish bank analyst in Dublin.) (pp. 94-5)

As a bubble inflates, there are always people who point out how irrational the market's behavior is, and they're almost always ignored. In practice, it's hard to tell if they're wrong or simply calling the end of the bubble too early. 

Objective quantitative approaches may help here: are valuations currently high relative to history, relative to other asset classes, and relative to other countries? Have trend-following indicators begun to suggest that the bubble may be popping?

A banking system is an act of faith: it survives only for as long as people believe it will. Two weeks earlier the collapse of Lehman Brothers had cast doubt on banks everywhere. Ireland's banks had not been managed to withstand doubt; they had been managed to exploit blind faith. Now the Irish people finally caught a glimpse of the guy meant to be guarding them: the crazy uncle had been sprung from the family cellar. Here he was, on their televisions, insisting that the Irish banks' problems had nothing whatsoever to do with the loans they'd made... when anyone with eyes could see, in the vacant skyscrapers and empty housing estates around them, evidence of bank loans that were not merely bad but insane. (p. 98)

It would have been difficult for Merrill Lynch's investment bankers not to know, on some level, that, in a reckless market, the Irish banks acted with a recklessness all their own. But in the six-page memo to Brian Lenihan - for which the Irish taxpayer forked over to Merrill Lynch 7 million euros - they kept whatever reservations they might have had to themselves. "All of the Irish banks are profitable and well-capitalized," wrote Merrill Lynch advisers. (p. 112)

"At the time they were all saying the same thing," an Irish bank analyst tells me. "We don't have any subprime." What they meant was that they had avoided lending to American subprime borrowers; what they neglected to mention was that, in the general frenzy, all of Ireland had become subprime. Otherwise sound Irish borrowers had been rendered unsound by the size of the loans they had taken out to buy inflated Irish property. That had been the strangest consequence of the Irish bubble: to throw a nation that had finally clawed its way out of centuries of indentured servitude back into indentured servitude. (p. 113)

Experts aren't always right. Do your own research, and turn off the financial news.

Germany: It's Risk-Free. Right?

The curious thing about the eruption of cheap and indiscriminate lending of money between 2002 and 2008 was the different effects it had from country to country. Every developed country was subjected to more or less the same temptation, but no two countries responded in precisely the same way. Much of Europe had borrowed money to buy stuff it couldn't honestly afford. In effect, lots of non-Germans had used Germany's credit rating to indulge their material desires. The Germans were they exception. Given the chance to take something for nothing, the German people simply ignored the offer. "There was no credit boom in Germany.... Real estate prices were completely flat. There was no borrowing for consumption. Because this behavior is totally unacceptable in Germany. This is deeply in German genes, It is perhaps a leftover of the collective memory of the Great Depression and the hyperinflation of the 1920s." The German government was equally prudent because, he went on, "there is a consensus among the different parties about this: if you're not adhering to fiscal responsibility you have no chance in elections, because the people are that way."

In the moment of temptation Germany became something like a mirror image to Iceland and Ireland and Greece - and the United States. Other countries used foreign money to fuel various forms of insanity. The Germans, through their bankers, used their own money to enable foreigners to behave insanely....

They lent money to American subprime borrowers, to Irish real estate barons, to Icelandic banking tycoons, to do things to German would ever do. The German losses are still being toted up, but at last count they stand at $21 billion in the Icelandic banks, $100 billion in Irish banks, $60 billion in various U.S. subprime-backed bonds, and some yet to be determined amount in Greek bonds. (pp. 145-6)

He'd created the bank when the market was paying higher returns to bondholders: Rhineland Funding was paid well for the risk it was taking. By the middle of 2005, with the financial markets refusing to see a cloud in the sky, the price of risk had collapsed: the returns on the bonds backed by American consumer loans had collapsed. Rothig says he went to his superiors and argued that, as they were being paid a lot less to take the risk of these bonds, IKB should look elsewhere for profits. "But they had a profit target and they wanted to meet it. To make the same profit with a lower risk spread they simply had to buy more," he says. The management, he adds, did not want to hear his message. "I showed them the market was turning," he says. "I was taking the candy away... instead of giving it. So I became the enemy." When he left, others left with him, and the investment staff was reduced, but the investment activity boomed. "One-half the number of people with one-third the experience made twice the number of investments," he says. "They were ordered to buy...."

As long as the bonds offered up by the Wall Street firms abided by the rules specified by IKB's experts, they got hoovered into the Rhineland Funding portfolio without further inspection. Yet the bonds were becoming radically more risky, because the loans that underpinned them were becoming crazier and crazier. After he left, Rothig explains, IKB had only five investment officers, each in his late twenties, with a couple of years' experience: these were the people on the other end of the bets being handcrafted by Goldman Sachs for its own proprietary trading book, and by other big Wall Street firms for extremely clever hedge funds that wanted to bet against the market for subprime bonds. The IKB portfolio went from $10 billion in 2005 to $20 billion in 2007, Rothig says, "and it would have gotten bigger if they had had more time to buy. They were still buying when the market crashed. They were on their way to thirty billion dollars."

By the middle of 2007 every Wall Street firm, not just Goldman Sachs, realized that the subprime market was collapsing, and tried frantically to get out of their positions. The last buyers in the entire world, several people on Wall Street have told me, were willfully oblivious Germans. That is, the only thing that stopped IKB from losing even more than $15 billion on U.S. subprime loans was that the market ceased to function. Nothing that happened - no fact, no piece of data - was going to alter their approach to investing money. 

On the surface IKB's German bond traders resembled the reckless traders who made similarly stupid bets for Citigroup and Merrill Lynch and Morgan Stanley. Beneath it they were playing an entirely different game. The American blond traders may have sunk their firms by turning a blind eye to the risks in the subprime bond market, but they made a fortune for themselves in the bargain, and have for the most part never been called to account. They were paid to put their firms in jeopardy, and so it is hard to know whether they did it intentionally or not. The German bond traders, on the other hand, had been paid roughly one hundred thousand dollars a year, with, at most, another fifty-thousand-dollar bonus. In general, German bankers were paid peanuts to run the risk that sank their banks, which strongly suggests that they really didn't know what they were doing. (pp. 160-2)

The Germans were blind to the possibility that the Americans were playing the game by something other than the official rules. The Germans took the rules at their face value: they looked into the history of triple-A-rated bonds and accepted the official story that triple-A-rated bonds were completely risk-free....

Perhaps because they were some enamored of the official rules of finance, the Germans proved especially vulnerable to a false idea the rules encouraged: that there is such a thing as a riskless asset. After all, a triple-A rating was supposed to mean "riskless asset." There is no such thing as a riskless asset. The reason an asset pays a return is that it carries risk. But the idea of the riskless asset, whcih peaked about late 2006, overran the investment world, and the Germans fell for it the hardest. I'd heard about this, too, from people on Wall Street who had dealt with German bond buyers. "You have to go back to the German mentality," one of them had told me. "They said, 'I've ticked all the boxes. There is no risk.' It was form over substance...." 

IKB had to be rescued by a state-owned bank on July 28, 2007. Against capital of roughly $4 billion it had lost more than $15 billion. As it collapsed, the German media wanted to know how many U.S. subprime bonds these German banks had gobbled up. IKB's CEO, Stefan Ortseifen, said publicly that IKB owned almost no subprime bonds at all - whcih is why he's now charged with misleading investors. "He was telling the truth," says Rothig. "He didn't think he owned any subprime. They weren't able to give any correct numbers of the amounts of subprime they had, because they didn't know. The IKB monitoring systems did not make a distinction between subprime and prime mortgages. And that's why it happened." Back in 2005, Rothig says, he proposed to build a system to track more precisely what loans were behind the complex bonds they were buying from Wall Street firms, but IKB's management didn't want to spend the money. "I told them you have a portfolio of twenty billion dollars, you are making two hundred million dollars a year and you are denying me six point five million. But they didn't want to do it." (pp. 163-5)

People can be spectacularly wrong. It's a particularly bad sign when they can't make well-thought-out arguments for their views and ignore contradictory evidence.

At some point, you'll be tempted to capitulate and change your views because it feels like you're the only one in the world who's willing to stand against the crowd. As we've seen, it's good to question your beliefs and consider new evidence, but that evidence is probably not going to come from experts who are all trading in the consensus direction. Do your own research whenever possible.

ISBN 978-0-393-08181-7
Lewis, Michael. Boomerang: Travels in the New Third World. Norton, 2011.

October 26, 2018

The Big Short (Michael Lewis)

After introducing a quantitative finance course of study, I've decided to offer some brief comments on the finance-related books I've been reading.

This week, we'll be looking at The Big Short by Michael Lewis, who has a gift for telling stories about financial crises from the point of the view of the people who participated in them - in this case, the traders who made money from the crisis of 2008 by shorting subprime mortgage bonds.

Below, I've laid out some representative quotes from the book, each of which is followed by some practical lessons we can apply to today's markets.

"The most difficult subjects can be explained to the most slow-witted man if he has not formed any idea of them already; but the simplest thing cannot be made clear to the most intelligent man if he is firmly persuaded that he knows already, without a shadow of a doubt, what is laid before him." - Leo Tolstoy

This is consistent with Lewis's message throughout the book: overconfidence in financial models can cause the people who use them (ratings agencies, traders at investment banks, and portfolio managers) to ignore the risks of events that those models say are impossible.

Nobody Wants to Take Smart Risks

Now, obviously, Meredith Whitney didn't sink Wall Street. She'd just expressed most clearly and most loudly a view that turned out to be far more seditious to the social order than, say, the many campaigns by various New York attorneys general against Wall Street corruption. If mere scandal could have destroyed the big Wall Street investment banks, they would have vanished long ago. This woman wasn't saying that Wall Street bankers were corrupt. She was saying that they were stupid. These people whose job it was to allocate capital apparently didn't even know how to manage their own. (p. xvii)

It was then late 2008. By then there was a long and growing list of pundits who claimed they predicted the catastrophe, but a far shorter list of people who actually did. Of those, even fewer had the nerve to bet on their vision. It's not easy to stand apart from mass hysteria - to believe that most of what's in the financial news is wrong, to believe that the most important financial people are either lying or deluded - without being insane. (p. xviii)

"Steve [Eisman]'s fun to take to any Wall Street meeting... because he'll say 'explain that to me' thirty different times. Or 'could you explain that more, in English?' Because once you do that, there's a few things you learn. For a start, you figure out if they even know what they're talking about. And a lot of times they don't!" (p. 23)

"That was a classic Mike Burry trade.... It goes up by ten times but first it goes down by half." This isn't the sort of ride most investors enjoy, but it was, Burry thought, the essence of value investing. His job was to disagree loudly with popular sentiment. (p. 46)

"If you're in a business where you can only do one thing and it doesn't work out, it's hard for your bosses to be mad at you." It was now possible to do more than one thing, but if he bet against subprime mortgage bonds and was proven wrong, his bosses would find it easy to be mad at him. (p. 81)

A smaller number of people - more than ten, fewer than twenty - made a straightforward bet against the entire multi-trillion-dollar subprime mortgage market and, by extension, the global financial system. In and of itself it was a remarkable fact: The catastrophe was foreseeable, yet only a handful noticed. (p. 105)

A guy from a rating agency on whom Charlie tested Cornwall's investment thesis looked at him strangely and asked, "Are you sure you guys know what you're doing?" The market insiders didn't agree with them, but they didn't offer any persuasive counter-arguments. Their main argument in defense of subprime CDOs, was that "the CDO buyer will never go away." Their man argument, in defense of the underlying loans, was that, in their short history, they had never defaulted in meaningful amounts....

"Usually, when you do a trade, you can find some smart people on the other side of it," said Ben. "In this instance we couldn't." (p. 147)

He went on about how the ratings agencies were whores. How the securities were worthless. How they all knew it. He gave words to the stuff we were just suspecting.... When he was finished there was complete silence. No one specifically attempted a defense. They just talked around him. It was like everyone pretended he hadn't said it. (p. 149)

"I do my best to have patience... but I can only be as patient as my investors.... The definition of an intelligent manager in the hedge fund world is someone who has the right idea, and sees his investors abandon him just before the idea pays off." When he was making huge sums of money, he had barely heard from them; the moment he started actually to lose a little, they peppered him with doubts and suspicions. (pp. 187-8)

"Nobody came back and said, 'Yeah, you were right....' It was very quiet." (p. 199)

The people in a position to resolve the financial crisis were, of course, the very same people who had failed to forsee it: Treasury Secretary Timothy Geithner, Fed Chairman Ben Bernanke, Goldman Sachs CEO Lloyd Blankfein, Morgan Stanley CEO John Mack, Citigroup CEO Vikram Pandit, and so on." (p. 260)

Paper qualifications - degrees and job titles - don't say much about whether someone is capable of avoiding dumb risks and taking smart ones.

Risk, as measured by option prices, bond yields, and stock valuations, can get extremely overpriced or underpriced if everyone shares the same opinions. Trading against the crowd can be a smart risk, but it's difficult to do because investors pull their money out of managers' strategies at the worst possible time.

The Little Guys Lose

An investor who went from the stock market to the bond market was like a small, furry creature raised on an island without predators removed to a pit full of pythons. It was possible to get ripped off by the big Wall Street firms in the stock market, but you really had to work at it. The entire market traded on screens, so you always had a clear view of the price of the stock of any given company. The stock market was not only transparent but heavily policed. You couldn't expect a Wall Street trader to share with you his every negative thought about public companies, but you could expect he wouldn't work very hard to sucker you with outright lies, or blatantly use inside information to trade against you, mainly because there was at least a chance he'd be caught if he did. The presence of millions of small investors had politicized the stock market. It had been legislated and regulated to at least seem fair. 

The bond market, because it consisted mainly of big institutional investors, experienced no similarly populist political pressure. Even as it came to dwarf the stock market, the bond market eluded serious regulation. Bond salesmen could say and do anything without fear that they'd be reported to some authority. Bond traders could exploit inside information without worrying that they would be caught. Bond technicians could dream up ever more complicated securities without worrying too much about government regulation - one reason why so many derivatives had been derived, one way or another, from bonds. The bigger, more liquid end of the bond market - the market for U.S. Treasury bonds, for example - traded on screens, but in many cases the only way to determine if the price some bond trader had given you was even close to fair was to call around and hope to find some other bond trader making a market in that particular obscure security. The opacity and complexity of the bond market was, for big Wall Street firms, a huge advantage. The bond market customer lived in perpetual fear of what he didn't know. If Wall Street bond departments were increasingly the source of Wall Street profits, it was in part because of this: In the bond market it was still possible to make huge sums of money from the fear, and the ignorance, of customers.
(pp. 61-2)

Goldman Sachs stood between Michael Burry and AIG. Michael Burry forked out 250 basis points (2.5 percent) to own credit default swaps on the very crappiest triple-B bonds, and AIG was paid a mere 12 basis points (0.12 percent) to sell credit default swaps on those very same bonds, filtered through a synthetic CDO, and pronounced triple-A rated.... Goldman Sachs had taken roughly 2 percent off the top, risk-free, and booked all the profit up front. (p. 77)

According to the Bear Stearns analyst, double-A CDOs were trading at 75 basis points above the risk-free rate - that is, Charlie should ahve been able to buy credit default swaps for 0.75 percent in premiums a year. The Bear Stearns traders, by contrast, weren't willing to sell them to him for five times that price.... "I asked him, 'Are desks actually buying and selling at that price?' And he says, 'Gotta go,' and hung up." (p. 164)

As an independent investor, you're at a disadvantage trying to trade over-the-counter securities with investment banks. If you can even get them to talk to you, they'll set the terms and quote the prices at which trades take place. You're also exposed to counterparty risk: if your trading partner goes under, you may never get paid.

It's easier and safer to trade liquid, transparent contracts (like listed options) whenever possible.

Don't Make Trades You Don't Understand

Stage Two, beginning at the end of 2004 was to replace the student loans and the auto loans and the rest with bigger piles consisting with nothing but U.S. subprime mortgage loans. "The problem," as one AIG FP trader put it, "is that something else came along that we thought was the same thing as what we'd been doing." The "consumer loan" piles that Wall Street firms, led by Goldman Sachs, asked AIG FP to insure went from being 2 percent subprime mortgages to 95 percent subprime mortgages. In a matter of months, AIG FP, in effect, bought $50 billion in triple-B-rated subprime mortgage bonds by insuring them against default. And yet no one said anything about it - not AIG CEO Martin Sullivan, not the head of AIG FP, Joe Cassano, not the guy in AIG FP's Connecticut office in charge of selling his firm's credit default swap services to the big Wall Street firms, Al Frost. The deals, by all accounts, were simply rubber-stamped inside AIG FP, and then again by AIG brass. Everyone concerned apparently assumed that they were being paid insurance premiums to take basically the same sort of risk they had been taking for nearly a decade. They weren't. They were now, in effect, the world's biggest holders of subprime mortgage bonds. (pp. 71-2)

There were huge sums of money to be made, if you could somehow get [triple-B bonds] re-rated as triple-A, thereby lowering their perceived risk, however dishonestly and artificially. This is what Goldman Sachs had cleverly done. Their - soon to be everyone's - nifty solution to the problem of selling the lower floors appears, in retrospect, almost magical. Having gathered 100 ground floors from different subprime mortgage buildings (100 different triple-B-rated bonds), they persuaded the rating agencies that these weren't, as they might appear, all exactly the same things. They were another diversified pool of assets! This was absurd. The 100 buildings occupied the same floodplain; in the event of a flood, the ground floors of all of them were equally exposed. But never mind: the rating agencies, who were paid fat fees by Goldman Sachs and other Wall Street firms for each deal they rated, pronounced 80 percent of the new tower of debt triple-A. 

The CDO was, in effect, a  credit laundering service for the residents of Lower Middle Class America. For Wall Street it was a machine that turned lead into gold. (p. 73)

Goldman would buy the triple-A tranche of some CDO, pair it off with the credit default swaps AIG sold Goldman than insured the tranche (at a cost well below the yield of the tranche), declare the entire package risk-free, and hold it off its balance sheet. Of course, the whole thing wasn't risk-free; If AIG went bust, the insurance was worthless, and Goldman could lose everything. Today Goldman Sachs is, to put it mildly, unhelpful when asked to explain exactly what it did. (p. 77)

These supposedly diversified piles of consumer loans now consisted almost entirely of U.S. subprime mortgages. Park conducted a private survey. He asked the people most directly involved in the decision to sell credit default swaps on consumer loans what percentage of those loans were subprime mortgages. He asked Gary Gorton, a Yale professor who had built the model Cassano used to price the credit default swaps: Gorton guessed that the piles were no more than 10 percent subprime. He asked a risk analyst in London, who guessed 20 percent. "None of them knew it was 95 percent," says one trader.... In retrospect, their ignorance seems incredible - but then, an entire financial system was premised on their not knowing, and paying them for this talent. (p. 88)

The big Wall Street firms - Bear Stearns, Lehman Brothers, Goldman Sachs, Citigroup, and others - had the same goal as any manufacturing business: to pay as little as possible for raw material (home loans) and charge as much as possible for their end product (mortgage bonds). The price of the end product was driven by the ratings assigned to it by the models used at Moody's and S&P. The inner workings of these models were, officially, a secret: Moody's and S&P claimed they were impossible to game. But everyone on Wall Street knew that the people who ran the models were ripe for exploitation. "Guys who can't get a job on Wall Street get a job at Moody's," as one Goldman Sachs trader-turned-hedge fund manager put it. Inside the ratings agency there was another hierarchy, even less flattering to the subprime mortgage bond raters. "At the ratings agencies the corporate credit people are the least bad," says a quant who engineered mortgage bonds for Morgan Stanley. "Next are the prime mortgage people. Then you have the asset-backed people, who are basically like brain-dead...." Moody's and S&P didn't actually evaluate the individual home loans, or so much as look at them. All they and their models saw, and evaluated, were the general characteristics of loan pools. (pp. 98-9)

"I called S&P and asked if they could tell me what was in a CDO... and they said, 'Oh yeah, we're working on that.' " Moody's and S&P were piling up these triple-B bonds, assuming they were diversified, and bestowing ratings on them 0 without ever knowing what was behind the bonds! There had been hundreds of CDO deals - 400 billion dollars' worth of the things had been created in just the past three years - and yet none, as far as they could tell, had been properly vetted. (pp. 130-1)

The CDO manager's job was to select the Wall Street firm to supply him with subprime bonds that served as the collateral for CDO investors, and then to vet the bonds themselves. The CDO manager was further charged with monitoring the hundreds or so individual subprime bonds inside each CDO, and replacing the bad ones, before they went bad, with better ones. That, however, was mere theory; in practice, the sorts of investors who... bought the triple-A-rated tranche of CDOs - German banks, Taiwanese insurance companies, Japanese farmers' unions, European pension funds, and, in general, entities more or less required to invest in triple-A-rated bonds - did so precisely because they were meant to be foolproof, impervious to losses, and unncessary to monitor or even think about very much. The CDO manager, in practice, didn't do much of anything, which is why all sorts of unlikely people suddenly hoped to become one. "Two guys and a Boomberg terminal in New Jersey" was Wall Street shorthand for a typical CDO manager. The less mentally alert the two guys, and the fewer the questions they asked about the triple-B-rated subprime bonds they were absorbing into their CDOs, the more likely they were to be patronized by Wall Street firms. The whole point of the CDO was to launder a lot of subprime mortgage market risk that the firms had been unable to place straightforwardly. The last thing you wanted was a CDO manager who asked lots of tough questions. (p. 141)

Chau explained to Eisman that he simply passed all the risk that the underlying home loans would default on to the big investors who had hired him to vet the bonds. His job was to be the CDO "expert," but he didn't spend a lot of time worrying about what was in the CDOs. His goal, he explained, was to maximize the dollars in his care.... Chau's real job was to serve was a new kind of front man for the Wall Street firms he "hired"; investors felt better buying a Merrill Lynch CDO if it didn't appear to be run by Merrill Lynch. (pp. 142-3)

"You know how when you walk into a post office you realize there is such a difference between a government employee and other people.... The ratings agencies were all like government employees." Collectively they had more power than anyone in the bond markets, but individually they were nobodies. "They're underpaid.... The smartest ones leave for Wall Street firms so they can help manipulate the companies they used to work for." (p. 156)

Highly paid, putatively savvy experts took enormous risks they didn't understand. AIG went under because (1) they didn't question the models they were using to price extremely complicated contracts, (2) they believed what the rating agencies told them, and (3) they allowed other traders to take advantage of their ignorance.

Long-Term Options are Underpriced

The model used to by Wall Street to price LEAPS, the Black-Scholes option pricing model, made some strange assumptions. For instance, it assumed a normal, bell-shaped distribution for future stock prices....

It instantly became a fantastically profitable strategy: Start with what appeared to be a cheap option to buy or sell some Korean stock, or pork belly, or third-world currency - really anything with a price that seemed poised for some dramatic change - and then work backward to the thing the option allowed you to buy and sell.... People, and by extension markets, were too certain about inherently uncertain things... had difficulty attaching the appropriate probabilities to highly improbably events. (pp. 113-4)

What struck them powerfully was how cheaply the models allowed a person to speculate on situations that were likely to end in one of two dramatic ways. If, in the next year, a stock was going to be worth nothing or $100 a share, it was silly for anyone to sell a year-long option to buy the stock at $50 a share for $3. Yet the market often did something just like that. The model used by Wall Street to price trillions of dollars' worth of derivatives thought of the financial world as an orderly, continuous process. But the world was not continuous; it changed discontinuously, and often by accident. (p. 116)

Financial options were systematically mispriced. The market often underestimated the likelihood of extreme moves in prices. The options market also tended to presuppose that the distant future would look more like the present than it usually did. Finally, the price of an option was a function of the volatility of the underlying stock or currency or commodity, and the options market tended to rely on the recent past to determine how volatile a stock or currency or commodity might be.... The longer-term the option, the sillier the results generated by the Black-Scholes option pricing model, and the greater the opportunity for people who didn't use it. (pp. 121-2)

They were consciously looking for long shots. They were combing the markets for bets whose true odds were 10:1, priced as if the odds were 100:1. "We were looking for nonrecourse leverage.... We were looking to get ourselves into a position where small changes in states of the world created huge changes in values." (pp. 128-9)

This is a pretty accurate description of the way long-term options are priced. A trading technique called delta-hedging can be used to remove most of the impact of trending stock prices from an option's return. One-year and two-year options that are delta-hedged provide returns that are comparable to those of short-term bonds. When the delta-hedging is removed, options have high returns when markets makes large moves. They can be used to speculate on the possibility of these moves or to protect a stock portfolio from market corrections.

The opposite is true of short-term, or front-month, options, which are overpriced. Unlike longer-dated options, delta-hedged front-month options tend to have negative returns. Front-month options are the most heavily traded, and traders who buy them tend to lose money.

Buying a longer-dated option and selling a front-month option against it is called a calendar spread and is generally a profitable way to trade.

ISBN 978-0-393-07223-5
Lewis, Michael. The Big Short: Inside the Doomsday Machine. Norton, 2011.