Tag: mutual funds

Introducing the StockViz Mutual Fund MCP Server

There are many instances (corporate compliance, for one) where investors cannot maintain a direct equity portfolio. This was a tough hill to climb earlier. However, thanks to the flood of index funds that scratch every itch in the market over the last couple of years, it is now possible to port some of our low-frequency quant strategies in to the domain of mutual funds.

As a Mutual Fund Distributor, if you ask us to execute this, we will obviously put you on “regular” funds. However, if you are a little tech savvy, you can do it yourself for free.

Point your AI agent to https://mutual-fund-mcp.stockviz.workers.dev/mcp and start exploring this brave new world.

We have set up a live model portfolio that tracks Factor Momentum with Index Funds. This is going to be the first of many.

Once your AI agent gets the model portfolio, you can ask it to execute it for you using any API of your choice with any broker of your choice.

Here’s a brief intro video that walks you through how to setup the MCP in an agent. We’ve shown it using Goose, but it should work in Hermes, Claude, etc… We’ve also thrown in some questions that you can ask it about the strategy, historical index metrics, etc…

If you have any questions or suggests, please post them on this substack chat thread.

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Factor Momentum with Index Funds

Factor Momentum is an interesting concept – it posits that factor portfolios (value, quality, low-volatility, momentum, etc.) themselves exhibit momentum. If a certain factor worked in the past, it will continue working in the near-term. We had introduced this in Factor Momentum Everywhere and setup a couple of model portfolios – Model Momentum that uses our own factor models, and Factor Momentum that uses ETFs.

While discussing Factor MAX, we realized that there are now index funds that reference the basic factors that can be used instead of ETFs. ETF liquidity tends to be patchy and does not support large portfolios. Index funds are more convenient in that sense.

Here’s how factor momentum using just these basic factor indices looks like:

Like every investment/trading strategy, there will obviously be years where it under-performs.

However, it looks like this has held its own.

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Winning with Market-cap ETFs

The Parag Parikh stable of funds attract a lot of attention because they are good story-tellers. In their Flexi-cap Fund, they are simultaneously placing concentrated bets on US and Indian equities, hedging, arbitraging, selling cover-calls, making cash allocation calls, and so on. And they talk about it a lot.

All this activity should surely result in superior performance?

We had written a couple of notes around this back in 2015 and 2019. Our concern revolved around return-attribution. When you are doing so many things, how do we know if you are actually good at any one of them?

If you look at returns since the first note came out, they under-perform the MIDCAP 150 index.

Not that there weren’t years where they out-performed. However, given all that activity, is this all they could do?

In our second note, we had mentioned that you could, technically, replace the fund with a midcap and S&P 500 index ETF in a 65-35 ratio. So, from that point on, if you were to construct such a portfolio, it would beat the fund as well.

It is not that their stock picks are bad. If you analyze the Indian equity portion of their portfolio over time, their stock picks, on average, has delivered 2% over the midcap index during the holding period.

And while digging through this, we noticed that there is alpha in keeping track of stocks that they have exited.

There is a decent skew in favor of entries but not as much as exits.

It is often said that exiting a position is tougher than entering it. In that sense, the fund managers have displayed good skill.

Tracking the current portfolio may not yield much. For example, if you look at positions held for more than 12 months, excess returns are distributed across the spectrum.

Our suggestion is that you can treat the fund as a research project for your own edification, but when it comes to deploying your own capital, you can stick with market-cap ETFs and index funds.

Code and charts on github.

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Performance & Flows

Our previous post examined how index providers and asset managers launch “hot” thematic/sectoral indices and funds to capitalize on stories. Who can blame them? Money always flows in to assets with strong recent performance (this is the very basis of momentum strategies). Take gold, for example.

Fund flows have a near perfect correlation with performance.

Flows into gold funds is nothing compared to what happened in thematic funds.

If investors were rational, flows would be predictable. However, that is not nearly the case.

The problem with lumpy flows in to hot assets is that once the price action cools down, the funds are trapped. Investors tend to feel the emotional pain of a loss about twice as intensely as the joy of an equivalent gain. So, they wait for the next cycle to exit.

If you look the cumulative flows into Sectoral/Thematic funds, there’s a large reservoir of capital that will look for an exit when these funds come back up to par.

Flows follow performance. And if the asset is illiquid enough, performance will then overshoot flows to form a spiral.

Map the terrain. Understand the landscape before making your move.

Code and charts on github.

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Index and Funds

Index funds and ETFs proved most naysayers wrong and finally took off post-COVID. Now, we are dealing with a problem of plenty.

The number of indices and index funds have skyrocketed with the vast majority of AUM concentrated in large-cap market-weighted indices.

As everything in investing, it is always better to wait for things to settle down before committing capital. Index post-launch returns tend to disappoint.

And these numbers are worse for index funds.

While investors win by having low-cost access to a wide range of strategies and sectors, they can still lose by rushing in to “hot” launches. Patience pays.

Charts and code on github.

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