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

October 30, 2020

Quantitative Finance Course

Update: I've recently started trading a combination of strategies from the course, including risk parity, long/short futures factors, long/short equity factors, and long/short volatility. Here's the live performance (March 2019 through September 2020):  

Return (CAGR): 16.6%/year  
CAPM Alpha: 18.5%/year  
AQR alpha: 8.6%/year (controlling for SMB, HML-Dev, Mom Large, QMJ, and BAB)
Sharpe ratio: 1.00  
Sortino ratio: 3.13 = 2.21√2  
CAPM Information Ratio: 4.22

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.

Prerequisites

  • 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.

Correlations jump (revert) in recessions (stable periods). Industry correlations < country correlations; diversifying through emerging market industries reduces correlations more.

Momentum

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.

Short-Term Momentum (Almost) Everywhere
Contrary to stock-level evidence, we find a short-term momentum pattern in five major asset classes: the most recent month’s return positively predicts future performance.

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

Can Sustainable Withdrawal Rates Be Enhanced by Trend Following?
While diversification across asset classes leads to higher withdrawal rates than equity/bond portfolios, trend following itself is far more powerful.

TSMOM is similar in developed & emerging mkts (adjusting for currency exposure). International mutual funds are exposed to long-only TSMOM.

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.

We establish a relationship between time-series momentum strategies in futures markets and CTAs and also do not find evidence of significant capacity constraints.

Glitch
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.

We introduce risk-adjusted time series momentum based on averages of past futures returns normalized by volatility. It provides exposure to FF3 factors without trading the stock universe.
Efficient volatility estimation and trend detection reduce turnover. Adjusting for correlations produces outperformance.

Value

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.

Will Value Survive Its Long Winter?
Value and other premiums carry the risk of being negative for as long as a decade. Allocating to value, even when it is not providing a premium, reduces long-term portfolio risk.

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.

Valuation changes unnecessarily reduce the precision of our estimates of true long-term expected market and factor returns. The usual examination of long-run average returns is not all it’s cracked up to be.

Deep Value
Examining deep value (wide valuation spreads) across global individual equities, equity index futures, currencies, and global bonds provides new evidence on competing theories for the value premium.

Returns of equity & other asset classes generally underperform after banking crises. Investors do not fully anticipate the consequences of debt overhang, which results in lower long-run dividends.

Returns to value in equities, industries, commodities, currencies, bonds, and stock indexes are predictable by their respective value spreads.

Betting-Against-Beta

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.

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.

Quality

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.

Size

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

Limiting the universe to large cap stocks and applying more sophisticated portfolio construction to lower turnover reduces short-term reversal's trading costs.

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.

Seasonality

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.

Sentiment

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.

Stocks with high borrowing fees tend to underperform their peers over the short term, but persistence of high borrowing fees is fast-decaying and not systematically predictable.

Equity loan fees are the best predictor of cross-sectional returns. 28% is explained by the best-performing anomalies; 72% is from unique information.

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.

Multi-Factor

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.

When Diversification Fails
To fully appreciate extreme correlations, we take an in-depth look at stock-to-credit, stock-to–hedge fund, stock-to-private asset, stock-to-factor, and stock-to-bond correlations during tail events.

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.

Factor returns can experience downside shocks far larger than expected. In certain conditions, returns also become more correlated.

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

Best Strategies for Inflationary Times
Unexpected inflation is bad for bonds and equities, with local inflation mattering most, while commodities and futures trend following performance is strong.

Stocks, currencies, and commodity futures only hedge against energy inflation rather than core inflation. Hedging against core inflation is costly.

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.

Factor-Based Commodity Investing
A multi-factor portfolio combining the momentum, basis, basis-momentum, hedging pressure and value commodity factor portfolios outperforms widely used commodity benchmarks.


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.

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.

Style premia have less macro exposure than do asset classes. Additionally, a diversified portfolio (for asset classes and style premia) may rely less on a specific macroeconomic outcome.

Risk parity can outperform 60/40 in a moderately rising rate environment, even if the cumulative rate increase is large. Its modest edge can compound to a large advantage over time.

We gauge the potential of four strategies: cap weighting, 60/40, unlevered and levered risk parity. Costs can reverse the ranking, especially when leverage is employed.

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.

For low-to-moderate factor exposures, portfolio blending works better than signal blending due to interaction effects between factors.

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.

We examine the causal effect of limits to arbitrage using Regulation SHO, which relaxed short-sale constraints for a set of pilot stocks, as a natural experiment.

Live momentum portfolios are capable of capturing the momentum premium, even after expenses, trading costs, taxes, & other frictions associated with real-life portfolios.

This paper compares the efficacy of three common transaction cost mitigation techniques: limiting a strategy to cheap-to-trade securities, rebalancing less frequently, and “banding.”

To Trade or Not to Trade? Informed Trading With Short-Term Signals for Long-Term Investors
Strategic trade modification [timing] provides exposure to short-term signals without imposing additional transaction costs/capacity limits.

Commodities

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.

Conquering Misperceptions about Commodity Futures Investing
Three misperceptions:
(1) Commodities are a play on commodity prices
(2) Commodity prices provide an inflation hedge
(3) Commodity markets can absorb abundant capital

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

Commodity financialisation and price co-movement: Lessons from two centuries of evidence
Recent cross-commodity correlations are not unprecedented. Similar episodes have occurred multiple times throughout history.

Carry

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.

Challenges of Oil Investing: Contango and the Financialization of Commodities
Proxies for crowding (e.g. concentration of major oil investors, ΔAUM, oil ETP flows) are associated with contango and futures/spot return divergence.

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

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.

Options price changes are predictable at high frequency. Effective spreads of traders who time executions are less than 40% of the size given by conventional measures.

Retail investors using simple strategies lose to the rest of the market. Volatility trading earns the highest return, and risk-neutral strategies deliver the highest Sharpe ratio.

Term Structure of Short Selling Costs
Forward short selling costs (derived from put-call parity) predict future costs and stock returns. Short selling costs are higher over horizons when negative information is more likely to arrive.

Volatility Trading (Euan Sinclair)


Closed-End Funds

We estimate CEF expected returns as a function of the history of premiums and current premium. Previous studies understated the value of this information.

The average CEF's monthly return is 64% more volatile than its assets'. Although largely idiosyncratic, 15% of excess risk is explained by market risk, small-firm risk, and risk that affects other CEFs.

Bonds

Investors chase bond funds with higher yields, even controlling for past returns. The return spread is less than half of the yield spread and comes from higher risk.

Retail investors appear to select bonds by first screening on a credit rating level, then sorting by yield. They systematically trade in the opposite direction of accounting fundamentals.

Based on an extensive new data set (1866-2008 period), corporate bond market default events are only weakly correlated with business downturns.

Real Estate

Modeling private real estate is not straightforward. We consider theoretical arguments, historical average returns, and forward-looking yields.

High (low) price tier cities had higher capital gains (net rental yields). *Within* cities, lower-price-tier zip codes had higher total returns from both higher yields & higher appreciation.

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)


August 26, 2020

Free Sessions for September 2020 (Quantitative Finance)

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

As a result, I'm offering free weekly quant finance sessions for the month of September. 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.

I've recently started trading a combination of strategies from the course, including risk parity, long/short futures factors, long/short equity factors, and long/short volatility. Here's the live performance (March 2019 through September 2020):

Return (CAGR): 16.6%/year  
CAPM Alpha: 18.5%/year  
AQR alpha: 8.6%/year (controlling for SMB, HML-Dev, Mom Large, QMJ, and BAB)
Sharpe ratio: 1.00  
Sortino ratio: 3.13 = 2.21√2  
CAPM Information Ratio: 4.22

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) 
"I enjoy these long threads Darren does on some great financial books." Jim O'Shaughnessy, founder of O'Shaughnessy Asset Management and author of What Works on Wall Street

"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 
Some of my social media followers include

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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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 Icelanders - 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 an 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 a 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, you 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 to 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 the 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 totaled 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 bond 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, which 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 - which 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.