Interesting, we’re in one of the largest crisis since decades and all these stock trading stories are popping up.
This has little to do with trading, and a lot to do with algorithms. I recommend reading the articl, it is well written :)
Offline Algorithms in Low-Frequency Trading
71–80 of 106 posts
Re: Offline Algorithms in Low-Frequency Trading
#72Earlier quoted context omitted.
Someone with a strong math background should cut Wilmott and go directly to Shreve: Stochastic Calculus for Finance II (or Björk: Arbitrage Theory in Continuous Time).
What does "strong math background" mean in this context? Would the equivalent of an undergrad degree in math be sufficient, or are we talking about graduate level analysis and stats here?
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Re: Offline Algorithms in Low-Frequency Trading
#73Earlier quoted context omitted.
Someone with a strong math background should cut Wilmott and go directly to Shreve: Stochastic Calculus for Finance II (or Björk: Arbitrage Theory in Continuous Time).
What does "strong math background" mean in this context? Would the equivalent of an undergrad degree in math be sufficient, or are we talking about graduate level analysis and stats here?
> Björk: Arbitrage Theory in Continuous Time
is standard graduate stochastic calculus course material. An undergrad degree in math usually specializes in a certain track: algebra or analysis. The analysis background would be a closer fit as the material is focused on the continuous applications (not HFT) and likely have covered the introductory measure and probability theory material. The finance portion focuses on the arbitrage-risk neutral model that is at least a semester worth a material.
Re: Offline Algorithms in Low-Frequency Trading
#74Earlier quoted context omitted.
None of the kinds of people you listed are good at trading (esp economists). From experience, professional traders do tend to use passive indices for part of their PA, but also actively trade a portion. But you're right in that if you don't have a passion for it, you'll never be able to truly outperform spy on a risk adjusted basis. However, if you do have the knowledge and the passion, I definitely think you can. In…
This strategy seems to make a lot of sense to me, so I just checked out the performance of UPRO over the last 5 years versus SPY (^GSPC). UPRO is up 426% (wow) $17.37-$74.01 and ^GSPC is up 192% (talk about a bull run) $1932-$3714 So with UPRO you would have had an average profit of 65.2% per year, and with SPY 18.4% per year. That's even better than x3 returns. Plus you'd have the bond returns. Interesting idea.
It depends a lot on the period (and I think you didn't include dividends?).
1 year: SPY +15% - UPRO +2%
3 years: SPY +37% - UPRO +33%
5 years: SPY +110% - UPRO +325%
Re: Offline Algorithms in Low-Frequency Trading
#75If low frequency trading interests you, here's a project some people might want to check out: https://github.com/brndnmtthws/thetagang It's designed to sell option premium on major indices (like the S&P500 or NASDAQ-100) to generate mostly passive income, with a fairly reasonable risk-adjusted return. It uses a combination of strategies that involve selling naked puts and covered calls, which both have the same risk…
Genuine question, does this strike others as immensely off-topic? I'm curious if the parent commenter even opened the link. I'm sure there are applications of generalized knapsack problems (or dynamic programming generally) in options trading, but this isn't it.
Are you a tourist on hacker news? This is almost the defining trait of a HN post.
Re: Offline Algorithms in Low-Frequency Trading
#76Earlier quoted context omitted.
This strategy seems to make a lot of sense to me, so I just checked out the performance of UPRO over the last 5 years versus SPY (^GSPC). UPRO is up 426% (wow) $17.37-$74.01 and ^GSPC is up 192% (talk about a bull run) $1932-$3714 So with UPRO you would have had an average profit of 65.2% per year, and with SPY 18.4% per year. That's even better than x3 returns. Plus you'd have the bond returns. Interesting idea.
It depends a lot on the period (and I think you didn't include dividends?). 1 year: SPY +15% - UPRO +2% 3 years: SPY +37% - UPRO +33% 5 years: SPY +110% - UPRO +325% Since 2016 is in line with the x3 promise. Since 2018 or 2020 definitely not.
Good catch, I forgot dividends.
Interesting that the last year performance was so bad - I think that stock market drop back in March and the general volatility / reshuffling since then must have hurt the leveraged strategy.
Re: Offline Algorithms in Low-Frequency Trading
#77Earlier quoted context omitted.
Genuine question, does this strike others as immensely off-topic? I'm curious if the parent commenter even opened the link. I'm sure there are applications of generalized knapsack problems (or dynamic programming generally) in options trading, but this isn't it.
Are you a tourist on hacker news? This is almost the defining trait of a HN post.
I honestly don't mind "look at this cool related thing I built" comments, especially if it's free and open source and something I can learn from.
Re: Offline Algorithms in Low-Frequency Trading
#78If low frequency trading interests you, here's a project some people might want to check out: https://github.com/brndnmtthws/thetagang It's designed to sell option premium on major indices (like the S&P500 or NASDAQ-100) to generate mostly passive income, with a fairly reasonable risk-adjusted return. It uses a combination of strategies that involve selling naked puts and covered calls, which both have the same risk…
Generally speaking, a seller of naked puts is looking to supplement income via a stock they are willing to own at a lower level. If you are not willing to take delivery, it is probably better to sell a vertical spread so that there is a built in stop out. Here I'm speaking of transactions of a reasonable premium amount, not 5 or 10 cents. While it is true that the upside is unlimited against a naked call (and the dow…
> downside is 0 on a naked put
What? If the stock goes lower than the strike price, the downside on a naked put is the difference between strike price and market price. You will be forced to take delivery of the stock at the strike price when you could have bought it for market price if you hadn't written the option.
It is not 0.
Re: Offline Algorithms in Low-Frequency Trading
#79Earlier quoted context omitted.
You absolutely do not want to own upro for 5 years. High fees and more importantly beta-slippage will eat you alive.
by beta slippage you mean volatility drag? On a risk adjusted basis, upro is definitely a loser due to volatility drag and high expense ratio. However, you can easily calculate optimal leverage ratio in order to maximize the geometric growth of your portfolio. The equation is: lev = E(r) / Var(r) So if the expected return is 10% and the expected volatility is 10%, optimal leverage to maximize geometric growth is 10x.…
> However, is 3x too high for the long term? I dunno, but over long time periods, a pure 3x leveraged spy portfolio is going to outperform significantly. The problem is most people will be unable to weather the storm as you can easily lose half of your money in a week.
You don't define "long time periods" but the storm may be much longer than one week.
If you had invested with 3x leverage (daily rebalanced) in the S&P 500 anytime in 1999 or 2000 you would have been down over 90% in 2009 and you wouldn't have broken even until 2014 or 2016.
Re: Offline Algorithms in Low-Frequency Trading
#80Just asking anybody figured out, how to find high low for a period of time. Say in a period of 6months, starting from a initial point, next point could be a high or low, if high, program needs to find next lowest point and afterward, it needs to find highest amd continues to do so in zigzag. For low it's vice versa.
You can do it in a single pass fairly easily. Loop over the rows of data. Store the current high to low, as well as the largest high to low since inception. If the current exceeds the largest since inception, simply replace it. Should be about 30 lines of code.