Kicking off a new strategy
After much delay, I’m finally kicking off a new stock investment strategy. Before you ask, no, I won’t divulge the details of the strategy. Suffice it to say that it is a quantitative equity strategy which looks at valuation, momentum, and sentiment/risk. Though I won’t spell out the factors here (hey, a magician never gives away his secrets!), I will be tracking returns on a monthly basis and posting them on the Y-Factor (link to follow). Shortly I’ll also include simulated returns for the strategy for some period in the past.
Actually investing money in this strategy (as opposed to simulation and paper-trading) is pretty nerve-racking – there are real gains and losses to be had now. I’ve also come across a few challenges, which you may find of interest:
- Unlike at work, capital is much more constrained and transaction costs are much higher. Building a strategy for work is great because we choose our universe (let’s say the stocks in the S&P 500), apply our strategy and buy the top decile (50 names). If we were a hedge fund, we could also short the bottom decile. A couple of things make this easy: 1) when you have millions to invest, it’s very easy to put on your positions (i.e. if I only have $10,000 to invest and Google is to be 1% of my portfolio, or $100, I’m in trouble because the stock costs $450, meaning the smallest position I can take is 4.5%. However, if you have $100 million to invest, you can easily but $1 million worth of Google), and 2) transaction costs at work are a much smaller percentage of capital. Even though I use a very-low cost broker, I’ll still pay a minimum of $1/trade. If you buy the top decile and short the bottom decile, that’s a minimum of $100 in commission, or 1% of a $10,000 portfolio. Paying that every month (since the strategy will rebalance positions monthly) is very costly – 12% a year! To alleviate this problem, I’ll go long the top 25 names and short the bottom 25 names. This will reduce my diversification, but will also reduce transaction costs and allow me more money per name to put on the positions I want.
- The had intended the strategy to be a long-short strategy. However, as I think about this more, taking short positions is very risky. For example, over the last two weeks the long positions in my strategy would have returned 2.6% but the short positions would have cost me 10.5%! This is primarily due to some of the stocks the model shorts being financials, which have rallied over the past two weeks (AIG has doubled!!). To get away from the downside risk to shorting, I could buy put options, what is what I was considering. The problem here is that an equity option contract is 100 in size. That means that I have to buy options in multiples of 100. So, if I want to short 10 shares of a stock, I can’t – I have to take on an exposure similar to short 100. This in itself is not bad because if the stock tanks I’ll make 10 times the money. But, the cost of the option is the limiting factor – the cost of the options for my portfolio would be greater than the equity I have! If I had $100,000 or more to invest, this wouldn’t be an issue, but that, unfortunately, if not my case.
So, after considering these annoyances, I’ve made a few last minute adjustments. I’ll go long only (since I can’t afford the options and don’t want the risk of the shorts), and I’ll buy the top 25 names my model chooses rather than the top 50 (as mentioned earlier). If things work well and I find that I am willing to put more money into the strategy, then I can always try to capitalize on the shorts later.
That’s a lot to digest for now. Keep watching and I’ll put up the simulated returns (soon) and actual returns (at the end of each month). I’ll also write more on the actual model and considerations that went into that as we move forward…