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Entries for date "May 2017"

Famous Investor's Real Money Record vs. Buy and Hold

When deciding whether or not to invest in a particular fund, or to follow the advice of some advisory service, there is that concept that what you really need to do is take a look at the long-term record of its management and to give much greater consideration to the management with the longest record of good performance. Really good idea? Maybe not so much.

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Real Vs. Hypothetical

Before investing with some fund or using some advisory service that one way or another provides active portfolio management, we naturally want to first look at past performance. I'm going to discuss the different kinds of performance histories that can be made available, and argue that the kind that is generally considered to be the gold standard is not necessarily what it seems to be.

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So Retail Backtest's backtested program performance is labeled "hypothetical", by me, to match expectations in that regard. However, what Retail Backtest does is the same thing that you would be doing if you were to pick funds to invest in based on their past "real-money" performance. Yes, you would simply be competing with me, performing the same function.

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Trading at the Speed of Light

One of the things that we have to keep in mind when putting together algorithmic means for portfolio management, especially if there is to be a substantial amount of trading, are the other ways in which the trading world has been changing due to electronics. It's not just computation that has changed; it's communication too.

I won't pretend to be a qualified historian of the stock and commodities markets, or of electronics, but it's not too difficult for me to cite some milestones for you— going all the way back into the 19th century. This is all just for a nostalgic look back. And I'm sure that readers under 25 years of age or so will find the discussion of the landlines telephone system to be something like a trip to a museum of natural history.
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"Why Most Published Research Findings Are False"

Today's note is to point to an essay of that title by John P. A. Ioannidis, Professor of Medicine and of Health Research and Policy at Stanford University School of Medicine and Professor of Statistics at Stanford University School of Humanities and Sciences. By false findings he is referring to research that passed the usual test of statistical significance but was ultimately proven to be false, non-reproducible. The problem is that the number of false findings is much, much higher than would be predicted from the researchers' own assessments of statistical significance.

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I want to talk a little about how the circumstances are a bit different for findings by quantitative analysts who work for funds managing securities. Can you guess why? Come on... it's easy.

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