Investing Research Articles

The evaluation of Jim Puplava’s stock market forecasts is based on his archive of regular written market commentaries, covering roughly early 2002 through early 2005, at which point he discontinued publishing them.

We evaluate here the market commentary of Jim Puplava at Financial Sense Online for February 2002 (the earliest available) through October 2005, at which point he stopped posting regular written commentaries archive. Jim Puplava is president of of Puplava Financial Services Inc., an investment advisory and money management firm, and Puplava Securities Inc., a broker-dealer…. Keep Reading

…statistical testing of their specific methods or conclusions is more appropriate than subjective grading of market commentaries (which they apparently do not issue anyway).

…the QQQQ Crash Trade Trigger has not worked very well since James Altucher began writing about it in 2003, perhaps due to data mining bias in the pre-publication analysis.

The information at Dohmen Capital Research appears to be mostly promotional copy and opinion rather than research.

…while the backtested performance of the Value Line Select ETF Index versus the broad U.S. equity market is promising, the index underperforms during a relatively short out-of-sample test.

…evidence from hedge fund due diligence reports indicates a substantial level of misrepresentation by fund managers and confirms return chasing by investors. Key indicators of fund manager truthfulness are uses of external asset pricing and a major auditing firm.

…there is not enough information on VectorVest’s public web site to do any detailed evaluation.

…Asian stock markets do to some degree follow the U.S. market, including its sharp drops. However, U.S. market plunges are rare and clustered, the Asian market responses to these plunges are noisy, and overnight/weekend gaps on Asian markets substantially absorb plunge contagion.

…evidence indicates that aggregate earnings alone are not a useful predictor of overall stock market behavior, but firm-level (highly segmented industry) earnings are useful for predicting returns of individual stocks (highly segmented industries).