Category: Investing Insight

Investing insight to make you a better investor.

Allocating a Three-Asset Portfolio, Optimized

Our previous post showed how various allocation decisions impact an equal-weighted three-asset portfolio. However, equal-weights are not the only way to go. Every time a rebalance occurs, we can use that opportunity to re-weight the assets to minimize expected risk while maximizing expected returns. In this post, we look at two ways in which risk and returns can be optimized.

Portfolio optimization and the efficient frontier

The intuition behind what we are going to do is quite simple: for a given set of assets, there is an ideal mix of them that perfectly balances risk with reward. Imagine a plot of risk and returns of each asset under consideration. Harry Markowitz showed back in the 1950’s that they form a parabola and at a particular tangent of the parabola lies the ideal mix. The goal of portfolio optimization is to find that point. Here are some links that explain this concept further:

For the purpose of this post, we will assume risk to either mean variance (var) or expected tail loss (ETL.) We will use portfolio optimization methods to minimize one of these risk metric and maximize expected mean returns below.

Optimized portfolios

Like before, to keep things simple, we will go with the MIDCAP 100 index (A1), the 0-5yr TRI (A2) and the QQQ ETF (prices converted to INR, A3) as the three assets that form our portfolio.

Here is how the optimized minimum-variance portfolio performs after-tax:
min-var 3-asset portfolio (NIFTY MIDCAP, 0-5yr bond, NASDAQ-100)

Asset weights after rebalance:
min-var 3-asset portfolio (NIFTY MIDCAP, 0-5yr bond, NASDAQ-100) asset weights

And here is how the optimized minimum-ETL portfolio performs after-tax:
min-etl 3-asset portfolio (NIFTY MIDCAP, 0-5yr bond, NASDAQ-100)

Asset weights after rebalance:
min-etl 3-asset portfolio (NIFTY MIDCAP, 0-5yr bond, NASDAQ-100) asset weights

Min-var portfolio returns

min-var 3-asset portfolio (NIFTY MIDCAP, 0-5yr bond, NASDAQ-100) returns

Min-ETL portfolio returns

min-var 3-asset portfolio (NIFTY MIDCAP, 0-5yr bond, NASDAQ-100) returns

Take-away

  1. All things equal, the optimized portfolios under-perform the equal-weight portfolio in terms of absolute returns.
  2. Optimized portfolios show lesser risk than the equal-weight portfolio. During the 2008 carnage, for example, equal-weight drew-down ~40% whereas optimized portfolios drew-down ~20%.
  3. Optimized portfolios over-weigh bonds. Hard limits were set on the maximum and minimum weights the assets can have in optimized portfolios. Toggling these will have a significant impact on portfolio risk and returns.

Code, charts and the complete result dataset are available on github.

Allocating a Three-Asset Portfolio, Equal Weighted

Our previous post showed how various allocation decisions impact a two-asset portfolio. We started with two assets – equities and bonds – because it forms the foundation on which most allocation plans are built. However, the true impact of diversification is felt when you have uncorrelated assets in the portfolio. Here, we expand on the post by adding a third asset.

Picking the Assets and Allocation

As much as we would like equities and bonds to be uncorrelated, it is not always true. Indian equities and bonds are buffeted by the same storms at about the same time. However, what has historically shown to be a true diversifier are international equities. If you run the pair-wise correlations between the S&P 500, Nasdaq 100, the USD adjusted MIDCAP 100 and 0-5yr TRI, you see this:
correlations between SPY, QQQ, Indian MIDCAP and bonds

Given how strongly the S&P 500 (the SPY ETF) and the Nasdaq 100 (the QQQ ETF) are correlated, there is no point in adding both. We’ll go with the QQQ because it has an Indian analogue in the N100 ETF. Also, note how the SPY and QQQ are uncorrelated to the dollar adjusted MIDCAP and 0-5yr TRI indices. And finally, observe the light correlation between the MIDCAP and 0-5yr TRI indices.

So, to keep things simple, we will go with the MIDCAP 100 index, the 0-5yr TRI and the QQQ ETF (prices converted to INR) as the three assets that form our portfolio. And to get things started, we’ll keep an equal weight on all these three assets in the portfolio. The toggles that remain are the rebalance thresholds and tax impact. Here, we will use the same iterations that we employed in our two-asset portfolio example.

The results

In the cumulative return and drawdown chart below, A1 is the MIDCAP index, A2 is the 0-5yr bond index and A3 is the QQQ. A tax drag of 10% and an STT of 0.1% is applied at every rebalance. The rebalance threshold is set at 20%. The blue line is the resulting equal weight 3-asset portfolio returns.
NIFTY MIDCAP 100, 0-5yr bond and NASDAQ 100 equal weight portfolio

Take-away

  1. Lower risk: The equal-weight portfolio draws-down less than the MIDCAP index.
  2. Lower returns: The MIDCAP index out-performs the equal-weight portfolio (but with far greater volatility.)
  3. Needs discipline: The difference in returns between the MIDCAP index and the equal-weight portfolio can often be very large. Keeping still is a virtue.
  4. Tax-impact: The equal-weight portfolio has a tax and transaction cost angle that a MIDCAP buy-and-hold strategy doesn’t. Capital gains on international equities, bonds and domestic equities are all treated differently.
  5. Asset allocation is about delivering better risk-adjusted returns through diversification.
equal weight portfolio returns
Side note: setting the rebalance threshold is a trade-off between holding onto trending assets (potentially more profits) vs. booking profits and buying a lower-return asset (FOMO and tax incidence.) There is a wide range of theories on this topic. For now, we will restrict ourselves to just running through different scenarios.

Code, charts and the complete result dataset are available on github.

Allocating a Two-Asset Portfolio

Asset allocation and diversification are considered to be the holy grail of investing. Adding non-correlated assets to one’s portfolio is supposed to reduce volatility and hence encourage the good behavior of staying invested through market cycles. Here, we look at a simple two asset portfolio and work through some simple scenarios.

Picking the Assets and Allocation

When one looks historical inflation adjusted returns (link,) an investor with a 10+ year horizon should be invested in midcaps. So we pick the NIFTY MIDCAP 100 index and the 0-5 year bond total return index as the assets for our simple allocation setup.

The most popular allocation for an equity/bond portfolio in literature is 60/40 in favor of equities. However, we will go through a range of scenarios where the equity allocation is stepped through from 40% to 90% in increments of 10%

After picking the assets and their allocation, we need to figure out what would trigger a rebalance. Should we rebalance whenever the weights go off by 5% or should we wait until they drift 20% from their initial allocation? We will step through this as well – from 5% to 100% in increments of 10%

And lastly, the question of capital gains and securities transaction tax. Tax incidence on these two asset classes have varied over time. So for simplicity, we will assume an STT of 0.1% and a capital gains tax of 10% applied whenever a rebalance occurs.

The results

As one would expect, higher the risk taken, higher the cumulative returns. What changes are the drawdowns. Here are the various allocations, assuming a 20% rebalance threshold and with/without the tax drag. Note the different drawdown profiles at the bottom of the chart.
Without taxes:
equity/bond with 5% rebalance threshold (no tax drag)
After tax:
equity/bond with 5% rebalance threshold (no tax drag)

And here are the historical returns of the 60/40 portfolio:

pre and post tax returns of a 60/40 equity/bond portfolio
As intuition would suggest, the more frequently you rebalance, the higher your tax incidence. But keeping the rebalance threshold too high would allow a single asset to balloon and make the portfolio too sensitive to it. As show in this table, historically, keeping a rebalance threshold at 20% has worked out well for a 60/40 equity/bond portfolio.

Code, charts and the complete result dataset are available on github.

Mutual Funds: A quick note on performance metrics

There is absolutely zero stability in metrics used to analyze mutual fund performance. Whether it is alpha, beta or information ratio, they all vary over time and across market environments. Using them to pick the next “winning” fund is pointless. They are, at best, a measure of what happened in the past.

We take a 200-week sliding window of midcap mutual fund returns and calculate its alpha, beta and information ratio. Here’s how these numbers stack up for the HDFC Mid-Cap Opportunities Fund.
HDFC Midcap fund

What is apparent here is that

  1. There is no case for dropping a fund because of declining alpha. Alpha keeps changing through time.
  2. You cannot escape negative beta.
  3. Managers seem to be able to outperform on the way up but not under-perform drastically on the way down. This is asymmetric risk/reward for those who can stick with investments through long periods of time.
  4. Some argue that recent SEBI regulations on mutual fund holdings will erode alpha. Only time will tell if that is true because of (1) and (2).
  5. Under-performance is not permanent. See ICICI’s fund below.

ICICI midcap mutual fund

What we see here is that at least in the midcap space, funds have been able to outperform the index in the past (both recent and distant.) However, that is no guide to the future.

Notes:

  • The total-return index doesn’t go back long enough to be used for this analysis.
  • The risk-free rate used was the 0-5 year YTM adjusted for the weekly time-series.

Code, charts and time-series alpha, beta and IR for about a dozen mutual funds that are over 10-years old are on github.

Daily vs. Monthly SIP

We recently ran some numbers against some typical “buy the dip” strategies and concluded that they do not result in any significant advantage over a daily SIP. The daily SIP base case was chosen because it is easy to compute. It was not a recommendation for investors to switch over their monthly SIPs to daily ones.

Barring a few outliers, over rolling 5-year windows, a daily SIP and a monthly SIP result in similar amounts of assets accumulated at the end.
daily vs. monthly sip

Related links:
Systematic Buy-the-Dip, an Update
Systematic Buy-the-Dip, SMA crosses
Trading Day of Month Returns

Code is on github.