Part 4: A crypto risk budgeting strategy

Part 4: A crypto risk budgeting strategy


Dear readers

This is the last installment of the 4 part do-it-yourself portfolio series I started a few weeks ago.   As a recap, in the first article , we set the stage for building your own trading model in excel by showing you how to download and arrange data.  The second post showed you the results of that out of sample model.  The third article showed you how to model portfolio risk.

In this last post, I am proposing a risk-budgeting strategy for consideration based off of the popular Liability Driven Investing (LDI) framework used by many large institutional investors.  As always, this is not investment advice so please do your own research.  Before we get started though, why should we create a risk budget in the first place?  I would propose two reasons:

1)  Theoretically, I would argue each of us has a limited amount of risk that we can handle and that pain threshold will be different for everyone.   If we assume that we must take on some level of risk in order to earn a reward, and we are limited in how much risk we can stand, doesn't it make sense to create a budget for it so we can track how well we are being compensated for this scarce resource?

2)  Secondly, when people allocate capital, to some degree risk becomes a fate as we saw in the third article.   When you look under the hood of the portfolio to figure out how much risk you're taking and where it is coming from, like we did in the third article, you'll be more informed and less likely to be surprised. 

With this context, I would propose splitting a crypto allocation into 3 different buckets according to how each will be used (their utility).    This then allows us to allocate based on the needs that each bucket is funded for.   In the graphic below, you'll see an example illustrated.

 

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Using the same portfolio risk model I showed you how to build here, you can then divide your allocation to each bucket based on your personal risk and goal profile.  See below for a screenshot of the model adapted from article 3.   In this scenario, I'm allocating 30% of the total capital to a trading portfolio, 60% to a Hodl portfolio, and 10% to a speculative alt coin portfolio. 

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Translating this information of this hypothetical example to the risk budgeting graphic, we end up with this:

 

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One benefit of this approach is you can adjust the characteristics of each one of the buckets to meet your needs.  For example, if you're super sensitive to drawdowns, you could over-fund bucket two.  If you're highly sensitive to taxes, you might consider over-allocating to the Hodl bucket to take advantage of long-term capital gains.  If you really like to roll the dice and try to find the next big thing, you would over allocate to the top bucket.   Once you have it all figured out though, make sure to build your portfolio risk budget model to make sure you're aware of how much risk each bucket adds to your total portfolio.  Personally, I'm using this sell-off as an opportunity to add to my long-term hold portfolio. 

Once you have established goals for each bucket and funded them appropriately, a variety of performance alarms exist that can be calibrated for each to let you know if you're on track according to your expectations.

This concludes the 4 part series, which I hope you've found helpful.  If you have, please follow, like, and tip!

Cheers,

NZFX

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NZFX
NZFX

Pursuing interesting conversations that help lead to truth. Twitter: @NZFX6


From skeptic to hodlr to investor
From skeptic to hodlr to investor

In this article, I apply a quantitative tool used by institutional investors to to try to determine where fair value is for Bitcoin. My hope is that it will help people avoid the mistake of buying high and selling low.

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