Invest Without Emotions
Investing insight to make you a better investor.
Retail news outlets are once again gaga over phenomenal listing day returns of IPOs. Investors will do well to take a step back and take in the scene:
The code and data is on github.
A fund’s alpha – returns over a benchmark – is often quoted and widely misunderstood. The root of the misunderstanding comes from investors assuming that alpha is a constant – which it is not – and the funds using benchmarks that the investors cannot actually invest in. Even if an investor decides to go “passive,” there is still an active choice that needs to be made regarding the basket of ETFs he needs to invest in. Let’s answer the first question: What exactly is the active manager’s value add?
We select three ETFs, NIFTYBEES, JUNIORBEES and M100, since they are popular and span a fairly decent spectrum of traded stocks in the market. Then, we do a rolling (window of 200) linear regression of returns over 200 days of a few midcap funds (selected at random.) The intercept is the alpha of the fund vs. the ETFs. Here’s how the alpha varies over a period of time:
Two out of the three funds have negative alpha over the ETF basket right now. However, that doesn’t mean that they will stay there.
As an investor, you can use the betas obtained by the regression over the ETFs to “replicate” the fund at a point in time. For example, if you set the start date as the date at which each of the funds had peak alpha and just held onto the basket, here’s how the relative performances look:
In all cases the basket fixed at the peak performs at par or better than the fund. However, you never really know what the “peak” is when you are living through it. What if you fix the basket right at the beginning?
In two out of three cases, we see funds beat ETF baskets.
The conventional way of implementing momentum strategies rank either relative or absolute time series returns of a universe of stocks. If either market beta, value or the small-cap premium had a big hand in driving equity returns during the formation period, then the momentum portfolio will be overweight those factors. This leads to steep momentum crashes, or so the theory goes.
In their paper on Residual Momentum, Blitz, Huij and Martens propose ranking stocks based on the residuals obtained after fitting their return series to the Fama-French Three factor model. They argue that a portfolio created this way outperforms vanilla momentum strategies.
We have created an automated residual momentum strategy, Momo (Residual) v1.0, that implements the residual momentum strategy outlined in the paper.
Is there a relationship between inflation and stock returns in India? A recent study that looked at monthly data between 1994 and 2014 shows that there is no significant pro-cyclical inter-dependency between inflation and stock returns.
However, the paper does not present the results of any statistical significance tests. This leaves the reader at the mercy of trying to interpret pretty pictures of wavelet transforms.