I’ve seen some work coming out of the quant-blogosphere recently related to “timing” a strategy using mean-reversion, or in other words, increasing exposure to a strategy after it performs poorly and reducing exposure after it performs well.

On paper this often tests out to be a good idea (especially in today’s very mean-reversion driven market) but I’m wary of it for two reasons: (a) evolving markets, and (b) changing the nature of the strategy. Allow me to pontificate…

The S&P 500 has traded 9 days in a row at an extreme RSI(2) reading over 90. Unfamiliar with RSI(2)? Read more here and here.

Echoing Rob Hanna at Quantifiable Edges, extended overbought readings like this were much more likely in the last century when the market was momentum-driven (i.e. up days tended to beget more up days), but are a rarity in today’s mean-reverting market (read more).

In my previous post I looked at the Russian stock market and showed that like India, but unlike the US, short-term price changes in Russia are momentum, not mean-reversion driven. That’s important for at least two reasons: (a) short-term indicators like RSI(2) will work opposite the way they do in the U.S., and (b) it completely changes the dynamic of whether we should let winners run or take profits quickly, and cut losses early or wait for trades to develop.

This post will be about two oddities in the Russian data that I know are important to the U.S. market, but I’m still wrapping my head around why.

It’s been a while since I’ve talked about the day-after options expiration, but this particular oddity might be a changin’.

-When is options expiration day?

This is the fourth contribution to the MarketSci Blog from Andrey S. of Russia (along with the trading nuggets here, here, and here).

In this post, Andrey shows that, like India, day-to-day changes in the Russian stock market behave opposite of the US: they are momentum, not contrarian driven. This has huge consequences for all short-term indicators, such as blogosphere fav RSI(2).

A lot of chatter about the stock market’s upcoming golden cross has focused on whether the Dow Jones Transportation Index (DJT) is confirming a bullish trend.

Unfamiliar with the golden cross? Read our take on the cross, about its two flavors (SMA and EMA) and crosses in up vs downtrending markets.

It may come as a surprise coming from someone who does what I do, but I am (intellectually) in love with John Bogle.

Unfamiliar with Bogle? Bogle is the founder of the Vanguard Group and the person most responsible for the shift away from expensive actively-managed mutual funds towards low-cost index funds. Side note: Bogle was named one of Fortune mag’s four investing giants of the last century.

There’s been a lot of talk this year about leveraged ETFs pushing the market to make more extreme moves near the close (likely in the same direction as the rest of the day). Click for a WSJ primer on the issue.

Now I don’t know if traders are seeing a surge in volume near the close (because I don’t trade intraday), I don’t know if leveraged ETFs are responsible for today’s higher levels of market volatility, and I don’t know if leveraged ETFs add potential systemic risk should the market make a really big move up or down (a la Oct. 1987).

A quick note for readers following our (free) State of the Market report daily updates.

I’ve added the small vs large-cap trend-following strategy that I talked about in my post Do the Troops Lead or Follow the Generals? to the report as a long-term indicator.

I’ve written a lot on this blog about the concept of follow-through (i.e. the likelihood of up days following up days, and vice-versa), how it has evolved over time, and how it is becoming stronger.

A quick primer for the uninitiated – the graph below shows the results of two strategies: one going long the S&P 500 index at today’s close if the index closed up today (green), and one if it closed down (red), from 1950. Geek note: these results are frictionless.

This post was inspired by reader Soham Das (author of the Jump Up blog) who asked us to confirm his findings that in the short-term, the Indian stock market behaves opposite of the US market: it is momentum, not contrarian, driven.

A simple illustration…

Kudos to CXO Advisory for showing empirically what anyone familiar with this industry knows intuitively: that being a good stock market forecaster is not the same as being a popular (or rich) stock market forecaster.

CXO compares the actual performance of 50 stock market “gurus” with how often those gurus are mentioned in a Google search (to measure their popularity) and finds absolutely zero relationship between the two.

I’m doing a little playing around with the short-term interaction between the price of gold and the stock market. Some semi-interesting observations…

This strategy is another example of the importance of the right data, and not confusing the intricacies of indices with the intricacies of ETFs (or futures, or options, or anything else).

All this banter and wild speculation about what to make of our current rally is starting to make my head hurt.

Is it just a bear market rally or is it the start of a new bull market?

Five random strategy-development thoughts swimming around in me noggin’ re: creating better risk-adjusted (i.e. smoother) returns…

Method #1: Trade Low/Negatively-Correlated Assets

We’re poking around the edges of the McClellan Oscillator this week – read the previous parts of the series here, here, here, and here.

I’ve been toying with a new approach to analyzing advancing/declining numbers that I haven’t seen elsewhere – I’ll call it the McClellan RSI(2).

This is a multi-part series poking around the edges of the McClellan Oscillator (MO), a breadth indicator using the number of advancing and declining issues to measure the degree of participation in market moves (read more).

In my previous post, I looked at rising/falling and high/low MO readings and showed that what they’ve said about the markets has evolved over time, much the same way that similar indicators based purely on price have.

This is a multi-part series poking around the edges of the McClellan Oscillator (MO), a breadth indicator measuring the degree of participation in market moves (read more).

This post isn’t about a trading strategy (yet). In this post I want to try to understand in general terms what the MO says about the market by looking at how the market has responded to (a) an increasing/decreasing MO and (b) a MO reading above/below zero. In a follow up post we’ll look at the MO at extremes.

I’m going to do a few posts looking at the McClellan Oscillator, and I wanted to take a moment to define just what it is and what it is not.

Like most formulas that get pared down to a single name (Sharpe Ratio, CCI, whatever) the McClellan Oscillator has taken on its own bit of “mystique”. I think all this indicator worship is just silliness.