I thought this was an interesting finding... not suited for the competition, however. The algo seems to work well during a significant downturn, but can find itself in all the wrong trades when the market is not trending...
Basic idea is to calculate the zscore over 150 days and use that value to calculate allocation. I'm moving the zscore along the sin wave to scale from 2x leverage to 0.
Feel free to hack it up.
-Jamie
So this is pretty much a bollinger band but scaled entry with a sin wave? Whats the logic behind that? If we see a pi/2 (around 1.5) move below the average, we don't position anything into the stock but if its a HUGE move (~4 sd down) then we go long full leverage? Thats not momentum.
Is there research or economic rationale for this? It seems to me like the model assumes that large moves accompany momentum while medium moves accompany mean reversion, which isn't that bad, just interesting.
Here's an improved version using a pure momentum scaling through a logistic function (1/(1+e^(-1.2x)) -- Thanks for the idea! -- 1.2 was picked arbitrarily such that at 4 stdev, the weight in SPY is nearly 200% (levered) and vice versa. I've also included a treasury option such that the strategy is short treasuries when we lever and long treasuries when we don't scale in on SPY. See the auxiliary chart. Notice that the beta is much lower while still retaining a higher alpha. The only downside is a higher Max Drawdown and slightly increased volatility by 1%
@Calvin: I think the reasoning for using TLT (iShares 20+ Year Treasury Bond ETF) is that it is relatively stable in a bear market and a good investment when momentum signals a downturn in the market. Not super sure though, I'm new at this stuff.
@ Jamie & good trader: thanks for the idea, this looks interesting!
@Calvin the TLT is what to position into when you are risk averse and dont want any money in the market (i.e in a traditional utility maximization scenario, the investor allocates optimally towards both the market portfolio and risk-free asset -- TLT as a proxy of rf in this case). As for the equation, woops, gonna fix it now.
Banks,
Great improvement! My rationale was pretty naive to be honest. I was looking for a way to be at 1x leverage when the zscore was at 0 and lever up to 2x when z = 2 and 0x when z = -2 (and i didn't want to be perfectly linear either). As an added benefit, sin(z)+1 allowed me to bring down my leverage as the zscore moved beyond 2 and increase leverage when SPY was oversold (zscore < -2).
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.
