Author: shyam

Fun with SPDR Sector ETFs

State Street Global Advisors (SSGA) is known for its monster S&P 500 SPY ETF. With roughly $390 billion in AUM, SPY is one of the largest ETFs out there. Apart from SPY, they are also known for their SPDR “Spider” sector ETFs.

SYMBOLFUNDLAUNCH_YEAR
XLBMaterials Select Sector SPDR Fund1998
XLEEnergy Select Sector SPDR Fund1998
XLVHealth Care Select Sector SPDR Fund1998
XLIIndustrial Select Sector SPDR Fund1998
XLYConsumer Discretionary Select Sector SPDR Fund1998
XLPConsumer Staples Select Sector SPDR Fund1998
XLFFinancial Select Sector SPDR Fund1998
XLUUtilities Select Sector SPDR Fund1998
XLKTechnology Select Sector SPDR Fund1998
XLREReal Estate Select Sector SPDR Fund2015
XLCCommunication Services Select Sector SPDR Fund2018
Sector ETFs

These ETFs allow investors to take a concentrated bet on a specific sector and are often used as a benchmark for professionals who specialize in those sectors.

Markets go through cycles where some sectors do well and some don’t. Some sectors are extremely volatile and some barely move.

Cross-correlations are all over the place.

Given unstable cross-correlations and volatility, a naïve use of optimizers is a bad idea. For example, if you use these as inputs to generate an “efficient” portfolio, the weights wary widely from year to year.

Consumer Staples (XLP) ends up gobbling up most of the allocation, followed by Utilities (XLU.) The performance of such a portfolio depends on what you are looking for.

The efficient portfolio, given its large exposure to staples and utilities, has experienced lower drawdowns than both equity-weighted and S&P 500. This shows up in their Sharpe Ratios.

SPY remains the King when it comes to returns.

High-to-Price (HTP) Momentum Backtest

Momentum investing strategies have historically produced high returns in Indian equities. The biggest problem with them has been deep drawdowns when the markets enter bear territory.

A number of risk management strategies like using moving averages, trailing stop-losses, and hedging have been discussed on this blog before. These strategies, either standalone or in combination with each other, have provided investors with significant protection against momentum crashes. These are “exogenous” techniques, i.e. they are not part of the strategy itself but is imposed by portfolio management infrastructure. The advantage of these techniques is that the default is to be always invested in the market. It is risk-management’s job to control exposure.

Alternatively, endogenous risk-management techniques are those that are baked into the investment strategy itself. Our All Star strategy is a prime example of a momentum strategy that reduces exposure to equities by design. If enough stocks are not hitting their all-time-highs, it simply sits in cash. When you combine this with one of the exogenous risk-management techniques, you end up with a high Sharpe portfolio.

The advantage of high Sharpe strategies is that you can use leverage to amplify returns. However, if you are a “cash-and-carry” investor then it might be too conservative. Is there a momentum strategy that sits between All Star and traditional momentum?

High-to-Price (HTP) Momentum

A new paper, Büsing, Pascal and Mohrschladt, Hannes and Siedhoff, Susanne, Decomposing Momentum: Eliminating its Crash Component (SSRN,) outlines a new way to slice the 52-week momentum strategy to avoid crash risk. It describes a ranking system based on High-to-Price (HTP) where HTP = ln(Phigh/P0) where Phigh is the stock’s 52-week high price and P0 is its price at the beginning of the period.

A monthly rebalanced HTP long-only portfolio looks promising. It sidestepped quite a few whipsaws and has a better drawdown profile than NIFTY 50.

There have been periods where the strategy couldn’t find 25 stocks to go long and it only had a handful of positions or was all cash. However, the degree of overlap between constituents in consequent months is quite high indicating that the portfolio is likely to experience very low churn. In this aspect, it is very similar to the All Stars strategy.

At a line-item level, there have been instances where some stocks have tanked more than 30% in the month. However, the skew is, by-and-large, positive.

Investing in HTP Momentum

The real world doesn’t line-up perfectly to match the end-of-the-month rebalancing activity outlined in our backtest. To make this strategy investible, it needs to have some risk-management strategy in place on a clearly defined universe of stocks and has to be dynamically rebalanced.

We present our High-to-Price (HTP) Momentum Theme that consists of a portfolio of 25 stocks selected from the top 300 stocks by market-cap that rank high on their HTP scores. A 10% trailing stop-loss ensures that errant positions don’t drag down the whole portfolio. It is ideal for investors who can accept a bit more risk than All Stars for potentially higher returns.

Factor Momentum Performance Update

Factor performance tends to be sticky. If Value, Momentum, Quality, etc. out-performed in the recent past, they continue to out-perform in the near-future.

AQR wrote a paper on it back in January 2019: Factor Momentum Everywhere. More recently, the folks at Research Affiliates extended the research in their Factor Momentum paper. Based on AQR’s research, we setup a portfolio that mimics this for both US and Indian stocks in December 2019. We called it Factor Momentum III and Model Momentum Theme.

The performance of the US portfolio has been gangbusters. It sidestepped the Corona Crash of 2020 and has been on a tear since then. The Indian experience, however, has been disappointing.

US Factor Momentum

The Indian portfolio suffered from its inability to go into cash/bonds during crashes. Being fully invested took a bite out of its overall performance.

India Factor Momentum

The Indian version comes up short even if you compare its stats with its component factor portfolios.

India Factor Momentum Statistics

The intuition behind the Radar Plot above is that the larger the area under the points, better the strategy. Model Momentum is in pink and it pales in comparison to most of its constituents. Surprisingly, the Financial Strength Value Theme (light green,) that is rebalanced annually, beat out everything else.

What explains the underperformance?

  • Not being able to go into cash/bonds meant a larger hill to climb during recoveries. However, cash is a double-edged sword. If you get the timing wrong, you might end up going into cash after the bottom and watch the market recover helplessly. Unless the trend formation period is really short, cash is not a viable option.
  • High transaction costs can also be playing a role here. The difference between Gross and Net returns is ~15%. Not as high as a pure momentum strategy but not trivial either. Also, US portfolios do not incur STT and brokerages are essentially zero.
  • Maybe 20-months is too short a window to judge such a slow-moving strategy. The research looks solid and maybe all we need is to give it some time?

Getting Started

We are often asked by our readers to help them chart out a path for their investment journey. While we strongly believe that each investor’s risk appetite, hopes and goals are unique, we also understand that there are a lot of choices in front of the investor and sometimes, it could get overwhelming.

Here’s the path of least resistance:

  1. Go through Zerodha Varsity
  2. Understand the need for diversification and that there are not easy answers. No risk, no return.
  3. The best way to get started managing your own portfolio is to just dive into it. Onboard yourself onto our broker and get started on one of our momentum strategies. Great for portfolios between Rs. 15-30 lakhs.
  4. As a broker, we do not charge any additional fees for access to our strategies (over 50+, at last count.) And, you don’t have to worry about execution – we’ll take care of that.
  5. For larger accounts, where portfolio sizes are more than Rs. 25 lakhs, we offer customized solutions that typically involve risk-barbells. Get in touch with us!

We will keep this page updated as we go along – check back often!

Ranking and Visualizing Model Performance Metrics

On StockViz, we have over 50 quantitative models that are available for investing. They all have different risk and return profiles. It is fairly simple to pull up, say, the Sharpe Ratio of a particular model by navigating to its home page. However, it doesn’t say how it compares to all the other models we have going.

Let’s say you are looking to invest in one of our “Rapid-fire” Momo strategies. Our oldest ones are Relative, Velocity and Acceleration. Their (gross) performance metrics are displayed in a table.

Relative
Velocity
Acceleration

If you add net performance metrics into the mix, you’ll end up with a combinatorial explosion. How do you pick the “best” one of them to invest in?

Enter Radar Charts.

These charts show you the relative rank of each of these models against all the other 50+ models we have going. Intuitively, larger the area under the yellow (net) lines, better the model.

The only caveat with these Radars is that you should compare them against models of similar vintage. For example, we went live with our All Star momentum model in May 2020. Since then, the market regime has been extremely favorable to momentum strategies. It should come as no surprise that its Radar looks like the Queen’s Crown.

With that caveat out of the way, Radars are a great way to visualize how models square up against each other.