Big Ideas

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

The Vanishing Bid-Ask Spread and Market Efficiency

How has the dramatic increase in trading over the past decade materially affected the stock market environment? In their October 2010 paper entitled “Recent Trends in Trading Activity and Market Quality”, Tarun Chordia, Richard Roll and Avanidhar Subrahmanyam examine trends in trading activity and the impacts of these trends on market efficiency. Using trade and quote data for a broad sample of NYSE stocks over the period 1993 through 2008, they find that: Keep Reading

Effects of Creeping Indexation?

What are the implications for investors of a trend toward strategic and tactical allocation to index proxies (exchange-traded funds and derivatives) rather than individual securities? The July 2010 paper entitled “On the Economic Consequences of Index-Linked Investing” by Jeffrey Wurgler provides an overview of the effects of index-linked investing on stock prices, risk-return trade-offs, investor portfolio allocation decisions and fund manager skill assessments. The September 2010 paper entitled “Index Investment and Financialization of Commodities” by Ke Tang and Wei Xiong investigates the effects of increased investing during the last decade in commodity indexes. The October 2010 paper entitled “The Financialization of Commodity Futures Markets or: How I Learned to Stop Worrying and Love the Index Funds” by Scott Irwin and Dwight Sanders surveys research on the impact of commodity index fund growth on commodity price behavior. Using results of prior research and recent data on indexation investment levels, index returns and component asset returns, these papers find that: Keep Reading

Alternative Equity Index Strategy Horse Race

Market capitalization is the most frequently used metric for weighting the individual stock components of market indexes. Other approaches range from equal weighting to weighting on firm fundamentals to weighting generated by return-risk optimization. How do such alternative metrics work empirically? In the October 2010 draft of their paper entitled “A Survey of Alternative Equity Index Strategies”, Tzee-man Chow, Jason Hsu, Vitali Kalesnik and Bryce Little examine several popular passive index weighting alternatives to market capitalization. They impose common assumptions to backtest these alternatives on U.S. and global equity data over long periods with either annual or quarterly rebalancing. They also apply the Fama-French three-factor model to investigate sources of outperformance relative to capitalization-weighted benchmarks. Using stock/firm data for the 1,000 largest global firms spanning 1987-2009 and for the largest 1,000 U.S. firms spanning 1964-2009, they find that: Keep Reading

Volatility and Valuation with High-frequency Trading

Does high-frequency trading amplify noise and thereby reduce the signal-to-noise ratio in stock returns? In his August 2010 paper entitled “The Effect of High-Frequency Trading on Stock Volatility and Price Discovery”, Frank Zhang examines the effect of high-frequency trading on stock price volatility and on incorporation of fundamental news into price. He defines high-frequency trading as that driven by fully automated trading strategies with very high trading volume and extremely short holding periods ranging from milliseconds to minutes and possibly hours (typically not overnight). He estimates the volume of high-frequency trading as the residual after accounting for institutional and individual investor activities. Using price, trading and institutional holdings data for a broad sample of U.S. stocks from the first quarter of 1985 through the second quarter of 2009, he finds that: Keep Reading

An Era of Unstable Risk Premiums?

How stable are risk premiums? How should investors respond to instabilities? In his August 2010 paper entitled “A New ‘Risky’ World Order: Unstable Risk Premiums: Implications for Practice”, Aswath Damodaran presents approaches for estimating equity, bond and real asset risk premiums that are imprecise, unstable and linked across markets. He also explores the implications of dynamic, linked premiums for asset allocation, market timing and asset valuation. Using long-run data for all three asset classes, he concludes that: Keep Reading

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

Avoiding Investment Strategy Flame-outs eBook
Current Momentum Winners

ETF Momentum Signal
for July 2014 (Final)

Momentum ETF Winner

Second Place ETF

Third Place ETF

Gross Momentum Portfolio Gains
(Since August 2006)
Top 1 ETF Top 2 ETFs
209% 217%
Top 3 ETFs SPY
211% 77%
Strategy Overview
Recent Research
Popular Posts
Popular Subscriber-Only Posts