allocations - 6X leverage, or not?

On https://www.quantopian.com/allocation , we have:

Allocation Sizes

We are preparing to start trading investor capital later this quarter (Q1 2017). We plan to start with relatively small allocations and increase them over time. By the end of 2017, we hope to be making allocations that average $5-10 million per algorithm, with a presumed minimum of$1 million and we hope as high as $50 million. Elsewhere, it was reported "In time it intends to ramp up the leverage to six times capital to enhance the returns." So, do the allocation sizes include the 6X leverage or not? In other words, would managers end up with 6X($5M-$10M) =$30M-$60M, assuming their algos could support it? Or do the figures on https://www.quantopian.com/allocation already include leverage, and so the typical allocations would be$5M-$10M? 6 responses Are you asking so you can calculate how much payment the author receives? For that answer, the key line is "Our target is to pay you 10% of the net profit on your algorithm's allocation." With that language, the leverage is essentially mooted - the author gets 10% of the net profit whether it's profit on a 1X leverage or a 6X leverage. In answer to your direct question, the allocation sizes do include the use of leverage. All of those numbers refer to the total allocation to algorithm, as-leveraged. When an algorithm is invited to the due diligence process one of the first things we do is ask the author to change the algorithm to use 1X leverage if it isn't already. During portfolio construction we tell the algorithm that it has a certain amount of capital, and the algorithm trades that amount at 1X. The underlying leverage has been abstracted away from the algorithm and instead is controlled at the global portfolio level. It is invisible to the algorithm (and irrelevant) if it's trading is cash, leverage, or mixed. Disclaimer The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. Will managers know how much leverage is being applied to their algos? And will they have any say in how much is applied? For example, what if someone doesn't want the risk of 6X leverage? Could they opt for less? Or does the algo licensing put the power over leverage exclusively in Q's domain? The short answer is, no, the author won't have any knowledge or control over the leverage of the capital being traded. I think when you step back and think about it, though, you'll realize that it doesn't matter. In a simplified, hypothetical example, imagine your algorithm is given a$100 allocation. It goes up $10 over a year. You get paid 10% of the net profit, which in our example is$1 (I neglected commissions and financing costs for the purpose of simplification).

In our example, does it matter to you where the $100 came from? It could be$100 cash, or it could be \$1 leveraged 100X. There's no significant difference in outcome for you.

Your question was "what if an author doesn't want the risk of 6X leverage?" Hopefully this example has shown you that the author doesn't carry the risk of the leverage. It's a moot point.

Dan,

Does the author know how much capital is allocated to his/her algorithm at any given moment? I guess you could do the math based on the royalty you get and the algorithm performance; but I didn't know if this information is directly communicated.

Hi Dan -

I don't really understand how leverage works, but I get the sense that higher levels can lead to "blow ups" in investments. So my thinking is that managers may not want this risk and would simply like to have a steady stream of income. I guess my thought is if Q over-extends a given algo, the manager could end up getting wiped out--you'd drop his algo. In this sense, it would matter where the capital comes from, right? Isn't there a general principal in finance that leverage leads to risk. For one thing, lenders tend to want their money back at the worst possible time.

A related question is how are you handling dynamic gross leverage driven by the black-box algo itself. I suppose minute-by-minute you can always normalize to 1.0 and then multiply times your leverage, but this seems kinda dicey, if you don't know what's going on under the hood.

Stephen - the author doesn't get updates on a minute-to-minute basis on their allocation and performance, but they will get frequent updates. Also, the calculation of the royalty payments will be certified by third-party auditor.

Grant - It's probably better to describe the person as the author, not the manager. Quantopian is the manager. Quantopian and Quantopian's clients are bearing the risks of the investment. In the business relationship, the author isn't taking on any financial risk. It's a mutually beneficent relationship where the author provides valuable intellectual property to Quantopian in exchange for a share in any resulting net profits.

It's fair to say that using leverage increases risk, but it's only one factor. If you have poor risk management you can blow up at 1X leverage. If you have good risk management you can take advantage of many different financial tools, and leverage is one of them. In this case, leverage can be used safely to potentially increase the returns for the investor and for the author.

As for managing leverage, part of the due-diligence process I've described earlier in this thread includes making sure the algorithm consistently runs at 1X leverage.