From my scant experience, bear markets in equities are dangerous beasts. As many of the pundits are wont to say, "stocks take the stairs up but the elevator down."

Futures and FX however are a different matter. Both have considerable potential for profit as prices fall. So, applying that supposition in the trading of equities, commodity ETFs can simulate futures markets to some extent. If you're developing a bear market strategy you might try and focus on those as an initial starting point.

Additionally, the commodity ETFs can form the basis of hedges against sector trades. And most of those look to be shortable. For instance,

Uranium ETF: https://gdcdyn.interactivebrokers.com/en/?f=/en/trading/ViewShortableStocks.php?key=URA&cntry=usa&tag=United+States&ib_entity=hk&ln=&asset=

Hello Erick,

If you know it is a bear market before it is too late to profit from it, and when it will end, it is a piece of cake, right? The Holy Grail is to have a strategy that is truly arbitrage, so it doesn't matter which way the market is going. I think that there are some claims to this effect on https://www.quantopian.com/posts/earnings-drift-with-estimize.

If you're a long-term investor, adding some bonds to your portfolio will help a lot. You can see this by running a backtest of a traditional stock-bond portfolio starting in 2007, re-balancing monthly or quarterly, for example. One rule of thumb is 100% (or 110%) minus your age (%) in stocks, and the rest in bonds (not high yield/risky/agressive ones).

Grant

Grant,

I am already hedging with Bonds, However in bear markets also bonds might suffer. Maybe looking for losers might be a good idea as Market Tech points out.

EG

Well, I'm currently interested if the mean reversion algo termed "OLMAR" could be modified to go short rather than long. If I'm thinking about things correctly, in a bear market, stocks that don't fall fast enough would be shorted to a greater percentage than those that are tracking the mean, or falling too fast.

See https://www.quantopian.com/posts/olmar-implementation-fixed-bug for a link to the original paper and algos you can clone. If you figure out how to apply it in a bear market, please share your algo and insights.

One of the best features of Quantopian is this concept of a strategy group. And the fact that one can specify, through their use of a universe, parameters that define one's group is just a wicked capability I've found no where else. Sure you can set screeners up to produce a dynamically re-generated group but what a pain. That said, the use of a gestalt metric, as compiled across a large enough group, I have found, produces excellent trend signals. It's the same concept as the A/D or TRIN. But when using your particular group (even as it changes within the universe) and applying your favorite market metric, when said metric drops below a threshold, beware the bear!

Grant's use of reversion could be augmented by taking the composite of the scores produced for each leg and using that as a risk on / risk off type traffic-trading-light. During risk off periods, one might either up the weight of your hedge, and or use the composite metric to dynamically shift more weight into your short side. I think I did something like this in one of the strats I built many moons ago... (Actually, it's for another S&C article coming out in April...) But effectively it's like this:

        if (avgRsi > 50):  
            trendAdjuster = .05  
        else:  
            trendAdjuster = -.05  

Simple right? Take the average RSI of your group of securities, if it's up, then shift the whole group's weight bias UP. This would reduce the shorts and increase the longs. The opposite when the average RSI is below 50. Such a deceptively primitive mechanism (but composed of hundreds of data points), can easily add a couple of percent to your annual return.