Hacker News new | past | comments | ask | show | jobs | submit login

I may have written about this before, so apologies if this is repetitive. In 2010ish, I had gotten fairly sick due to a metal poisoning. The biggest issue was that it was messing with my cognitive abilities and that made me fearful of not being able to work and earn an income at the standard of living I had become accustomed to.

I quickly recovered, but became obsessed with finding a way to live - indefinitely - off of the savings that I had accumulated in my 20 year software career at that point. I had chosen a path around increasing responsibilities of management as opposed to startup founder (though I am one now). And I had diligently saved money, but didn't have not-work-anymore money.

I looked for a way to generate 20% returns reliably on my money, requiring little effort, manageable risk, and - mostly - passive. The stock market proved to be an answer. I ended up developing a couple of theories about how markets behave, generated some derivative trading algorithms and have been investing 100% of my spare cash since. The mini hedge fund requires activity once / week (generally) towards the end of the week, and also has two nice benefits of mostly getting taxed at long term cap gain rates along with being in all cash (fully liquid) with more core funds every weekend.

For this year, the algorithms have produced a return of 14.11% YTD. Since beginning the algorithms, they have averaged a yearly return of 24% compounded. I have traded these algorithms in a normal trading account and in an IRA, though the IRA returns are a bit lower around 20%. When the market has a flat year, vs. an up year, the algorithm is likely to perform closer to 30%. Down years that drop less than 10% will return closer to 30% as well. Up markets return lower.

I publish a white paper on this, and happy to share with anyone interested. It's a few quarters out of date, but the essence is all there. You can email me tylerjewell [at] gmail dot com for the paper.

For those that are curious, the algorithms depend upon a few assumptions: - The market has never crashed "up" - they only crash down. - As a result, the market climbs upward very orderly, but moves down very disorderly. - Time is infinite. - There is always volatility.

When you start with those assumptions, and then you apply maximum leverage (with safety nets for blue moon crashes with a max 35% loss), then you can start to derive algorithms that achieve the results expected, by using your money as an insurance provider to others in the market place by selling derivatives.

FWIW - when I started playing with the concept of the algorithms, I did not think it would be possible to achieve these results. So am quite pleased that it's possible to do so. Also, it's very easy to down dial the algorithms to be 1/2 the risk and get about 1/2 of the returns as well.




A lot of the efficacy of this depends on when you started.

The S&P500 total return last year (2013) was 32.39%. The year before (2012), 16%. [1] The two year annualized: 23.92% which is really near your 24% compounded. Weekly trading sounds like a lot of transaction cost for not much alpha. It sounds like you are doing better this year-to-date, but be careful drawing conclusions on a system when the market is going gangbusters.

Does this strategy involve a lot of covered calls? That would seem to fit better returns in flat/down markets and lesser in raging markets (since you'd be taken out early).

[1] http://en.wikipedia.org/wiki/S%26P_500


The strategy performs optimally in markets that are flat to +-5% on a given year. Last year's 32% gain in the S&P 500 was essentially the nightmare year and yielded 6%. 2008 would have been a nightmare year and yielded around the same. The strategy involves selling strangles with European contracts with portfolio margin using algorithms to determine a 95% likelihood of contracts expiring OTM, with a couple dozen adjustment techniques that occur if the 5% scenario plays out.




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: