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Big Ideas

These blog entries offer some big ideas of lasting value relevant for investing and trading.

Tools to Tackle Non-normality?

A reader commented and asked: “I frequently read that stock prices are not normally distributed, and that by assuming they are, an investor will tend to underestimate market risk. One paper I read says their distribution is leptokurtic, a distribution that has a more acute peak around the mean (that is, a higher probability than a normally distributed variable of values near the mean) and fatter tails (that is, a higher probability than a normally distributed variable of extreme values). My question is, given this fact, is there a practical way for retail investors who are not statisticians and who don’t have access to sophisticated tools, to better estimate risks than using functions that assume a normal distribution?” Keep Reading

Reversion of Stock Markets to Value Over the Long Run

Can investors count on stock markets reverting to some valuation benchmark? In their March 2010 paper entitled “Mean Reversion in International Stock Markets: An Empirical Analysis of the 20th Century”, Laura Spierdijk, Jaap Bikker and Pieter van den Hoek analyze reversion of 17 developed country stock market indexes to a valuation benchmark based on a world stock market index . Using annual index data spanning 1900-2008 (109 years), they find that: Keep Reading

Underestimation of Wildness?

In the opening paragraphs of his April 2010 article entitled “Traditional vs. Behavioral Finance”, Robert Bloomfield handicaps his subject contest as follows:

“The traditional finance researcher sees financial settings populated not by the error-prone and emotional Homo sapiens, but by the awesome Homo economicus. The latter makes perfectly rational decisions, applies unlimited processing power to any available information, and holds preferences well-described by standard expected utility theory. Anyone with a spouse, child, boss, or modicum of self-insight knows that the assumption of Homo economicus is false.”

Might some other frame of reference relieve the asserted asymmetry in self-insight and more equally burden the contestants, rationalist and irrationalist? Keep Reading

Trading Frictions Over the Long Run

Careful assessment of the exploitability of premiums or anomalies derived from long-run series such as stock indexes requires consideration of contemporaneous trading frictions. How have frictions changed over time? In the May 2002 version of his paper entitled “A Century of Stock Market Liquidity and Trading Costs”, Charles Jones assembles annual long-run series of three components of aggregate liquidity: (1) proportional bid-ask spreads for large-capitalization NYSE stocks (1900-2000); (2) proportional commissions for NYSE stocks (1925-2000); and, (3) turnover for NYSE stocks (1900-2000). He applies these series to explore the relationship between stock market returns and aggregate liquidity over time. Using a range of sources to calculate bid-ask spreads for the Dow Jones/DJIA stocks and commission, volume and return data for a broader sample of NYSE stocks, he finds that: Keep Reading

Credit Ratings and Stock Return Anomalies

Does designated creditworthiness, closely related to riskiness, drive the performance of many widely acknowledged stock return anomalies? In the April 2010 revision of their paper entitled “Anomalies and Financial Distress”, Doron Avramov, Tarun Chordia, Gergana Jostova and Alexander Philipov use portfolio sorts and regressions to investigate the relationship between financial distress (low credit ratings and downgrades) and profitability for trading strategies based on: stock price momentum, earnings momentum, credit risk, analyst earnings forecast dispersion, idiosyncratic volatility, asset growth, capital investments, accruals and value. Using data for broad samples of U.S. stocks (limited by extensive information requirements) spanning October 1985 through December 2008, they conclude that: Keep Reading

In Search of Super-anomalies

Is there a common factor explaining multiple widely accepted stock return anomalies? In the March 2010 version of their paper entitled “Do Five Asset Pricing Anomalies Share a Common Mispricing Factor?Multifaceted Empirical Analyses of Failure Risk Proxies, External Financing, and Stock Returns” , Joseph Ogden and Julie Fitzpatrick investigate the ability of a single factor, involving operating profit and external financing, to explain five stock return  anomalies: (1) the failure-risk anomaly; (2) earnings momentum; (3) the external financing (stock buybacks/secondary offerings) anomaly; (4) the accruals anomaly; and, (5) the book-to-market anomaly.  Using monthly stock return and firm fundamentals data for a broad sample of U.S. stocks to form 205 portfolios over the period 1974-2008 (60,301 firm-year observations), they find that: Keep Reading

A Long Run Demographic Stock Market Outlook

Does demographic mix of a set of investors affect aggregate demand for yield, and thereby total returns, from equity investments? In the December 2009 version of their paper entitled “Demographic Trends, the Dividend/Price Ratio and the Predictability of Long-Run Stock Market Returns”, Carlo Favero and Arie Gozluklu investigate the relationship between the aggregate stock dividend yield and the ratio of middle-aged (40-49) to young (20-29) populations in the U.S. (M/Y). Using U.S. demographic and aggregate equity dividend and price data spanning 1900-2008, they conclude that: Keep Reading

Beat the Market with Hot-Anomaly Switching?

Can investors beat the market by iteratively finding and exploiting the current hot anomaly? In the September 2009 update of his paper entitled “Real-Time Profitability of Published Anomalies: An Out-of-Sample Test”, Zhijian Huang investigates whether a trader can realize excess returns by repeatedly picking the anomaly with the best return during a rolling historical window from an expanding universe of anomalies as published, with a specific objective of suppressing data snooping bias. The universe includes anomalies that: (1) have been published in at least one of five top-ranked finance journals; (2) relate to the calendar or to cross-sectional predictability; and, (3) can be re-evaluated annually. Using monthly return data associated with 11 anomalies published during 1972-2005 (Monday/weekend effect, January effect and cross-sectional effects related to size, book-to-market ratio, momentum, earnings-price ratio, cash flow-price ratio, dividend yield, debt-equity ratio, sales growth and trading volume/turnover) as available from 1926 through 2008, he concludes that: Keep Reading

Diversifying Across Equity Anomalies

Is diversification across equity anomalies beneficial? In his December 2009 preliminary paper entitled “Diversification Across Characteristics”, Erik Hjalmarsson combines long-short portfolios formed on seven stock anomalies:

  1. Short-term (one-month) reversal (ST-R)
  2. Medium-term (11 months plus skip-month) momentum (Mom)
  3. Long-term (four years plus skip-year) reversal (LT-R)
  4. Book-to-market value (B/M)
  5. Cash flow-to-price ratio (C/P)
  6. Earnings-to-price ratio (E/P)
  7. Market capitalization (Size)

The portfolio for each anomaly is long (short) on an equally weighted basis the tenth of stocks expected to generate the most positive (negative) returns, reformed each month. Using monthly firm characteristics and return data for all NYSE, AMEX and NASDAQ stocks over the period July 1951 through December 2008, he finds that: Keep Reading

Managing Investment Risk by Parsing Uncertainties

How scientific can economics and finance be? In the March 2010 draft of their paper entitled “WARNING: Physics Envy May Be Hazardous To Your Wealth!”, Andrew Lo and Mark Mueller present a framework to help investors, portfolio managers, regulators and policymakers understand the potential effectiveness and inherent limitations of economics and finance. Focusing on levels of uncertainty (fully reducible, partially reducible, and irreducible) to explain some of the key differences between finance and physics and on the role of quantitative models in theory and practice, they conclude that: Keep Reading

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