Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for October 2024 (Final)
Cash TLT LQD SPY

Momentum Investing Strategy (Strategy Overview)

Allocations for October 2024 (Final)
1st ETF 2nd ETF 3rd ETF

Technical Trading

Does technical trading work, or not? Rationalists dismiss it; behavioralists investigate it. Is there any verdict? These blog entries relate to technical trading.

Classic Research: Dow Theory Long Dead?

We have selected for retrospective review a few all-time “best selling” research papers of the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the March 1998 paper entitled “The Dow Theory: William Peter Hamilton’s Track Record Re-Considered” (download count nearly 5,900) by Stephen Brown, William Goetzmann and Alok Kumar. This research applies risk adjustment and out-of-sample testing to re-examine Alfred Cowles’ 1934 debunking of the Dow Theory (as defined by the 255 editorials of William Peter Hamilton in The Wall Street Journal during 1902-1929). They conclude that: Keep Reading

Technical Trading Thoroughly Tested

In their March 2005 paper entitled “Re-Examining the Profitability of Technical Analysis with White’s Reality Check and Hansen’s SPA Test”, Po-Hsuan Hsu and Chung-Ming Kuan examine the profitability of a very large universe of technical trading rules and strategies against the Dow Jones Industrial Average (DJIA), S&P 500, NASDAQ Composite and Russell 2000 stock indexes. Their approach and findings, using data from 1989-2002, are as follows: Keep Reading

Technically, It Pays to Think Small

In a March 2005 update of his paper entitled “Simple Technical Trading Strategies: Returns, Risk and Size”, Satyajit Chandrashekar investigates the effectiveness of simple moving average technical trading strategies across ten market capitalization size deciles for the period 1963-2002. He finds that: Keep Reading

Information-Based Trading

Anyone attempting or contemplating day-trading should take a look at “Information-based Trading, Price Impact of Trades, and Trade Autocorrelation” of May 2004 by Kee Chung, Mingsheng Li and Thomas McInish. The authors examine how the price impact of trades and the persistence of trading direction relate to the probability of information-based trading, as opposed to liquidity trading (for example, by market makers) or noise trading (by the uninformed). Here’s what they find: Keep Reading

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