Offering auto-trading long-only options system "sys13"

[newwurldmn]

I cannot think of a better model than what was used in the system.
If you know better, let me know pls.

No, I'm not asking for millions. It is up to the customer who want to trade his account with this system. The bigger his account is the better it is regarding absolute profits, smooth equity curve, small drawdown (aka small risk) etc.
An account of size 600k is IMO an ideal size, for bigger accounts more titles would need to be traded, and this could mean adding some more exchanges.
I'm asking only for 15% to 20% (negotiable) of the profits the system makes.

What are the parameters of your Geometric Brownian motion model?
What formula are you using to calculate the option price?

 

[OddTrader]

Summary of 5 runs (each 252 trading days, ie. a trading year), details s. Examples:
                           |     1    |     2    |     3    |     4    |     5    |
---------------------------|----------|----------|----------|----------|----------|
Highest Daily Loss of AV   |   -5.05% |   -2.79% |   -3.06% |   -4.09% |   -3.55% |
Max Drawdown of AV         |   -8.46% |   -3.42% |   -3.06% |   -4.09% |   -7.14% |

So, that means there were no consecutive days of loss for #3 and #4 runs! Or, the maximum consecutive days of loss for #3 and #4 runs were just 1 day!

 

[botpro]

So, that means there were no consecutive days of loss for #3 and #4 runs! Or, the maximum consecutive days of loss for #3 and #4 runs were just 1 day!

There is another column named "DDpct" (column W). Here's a barchart of #3:

 

[botpro]

And here the drawdowns of #4:

 

[botpro]

What are the parameters of your Geometric Brownian motion model?
What formula are you using to calculate the option price?

The main parameters are:
- historical_volatility=30%
- initial_spot_value=50
- risk_free_interest_pct=0
- expiredays=63 (ie. 3 months)
- max_trade_days=252
- bars_per_day=702 (new: 780)
- nTradeDaysPerYear=252
- dividendPct=0
...

Black-Scholes: the usual input params, ie.
- spot=the current spot
- strike=system uses ATM, but this can also be a certain delta pct from ATM
- expdays=upto 63, cf. above, and: does not trade (and closes any open pos) if < 3.5 days
- volapct=30
- interestpct=0
...
It's a standard Block-Scholes formula, you can find it also on the net, wikipedia has also good explanation and maybe also links to implementations.

System has some more params, like nBots, Max_MinPosSize, ...

 

[newwurldmn]

Something isn't right if you are able to algorithmically beat a random price sequence where the expected value should be zero.

According to the blacksholes framework, the E() should be zero. You are saying you can earn 1000% / annually by timing the random data where volatility = time decay of your options. This is impossible. There has to be a bug in your system.

 

[monkeyjoe]

What are the parameters of your Geometric Brownian motion model?
What formula are you using to calculate the option price?

This really needs an answer. There should be no way for you to systematically extract profits from random noise. Unless you are imposing some structure on the randomness that your system can exploit. Are you imposing mean-reversion (or fractionality) in the simulated gBm? What about correlations between assets? Some form of stochastic volatility?

 

[OddTrader]

- This system does not and cannot predict the future, so instead it applies
some other (proprietary, ie. secret) methods based on the price action and the data of each position.

- The system is tested using Monte-Carlo with simulated bar data (702 bars/day, ie. 33.33-sec bars @ 23400 tradingseconds/day)
using GBM (Geom. Brownian Motion) and the Black-Scholes options pricing model, but limiting itself to market rules (s.b.).
For backtesting (and forwardtesting) the number of bars per day is configurable:
max. 23400 bars/day is possible (ie. 1-sec bars), but then of course the execution
of the program gets significantly slower (on a 4 x 2500MHz system).

... ...

- It is not an HFT system, so commission is not an headache (avg daily round-trip-trades is about 16 when 50 bots trade).
It is also not a pure daytrading system as the target of each bot needs on average up to 5 days to be reached,
so it can be said it is a swing trading system that is fulltime connected to the exchange.

Is that the time frame for decisions is based on 1-second bars?

What's the maximum days for a trade? 8 days ? 10 days?

 

[botpro]

This really needs an answer. There should be no way for you to systematically extract profits from random noise. Unless you are imposing some structure on the randomness that your system can exploit. Are you imposing mean-reversion (or fractionality) in the simulated gBm? What about correlations between assets? Some form of stochastic volatility?

Please see my previous posting (params used etc.).
Of course there is no way to systematically extract profits. The system temporarily increases its risk, upto a certain level, and then again reduces it...
Maybe indirectly it could use mean reversion tactics as it uses statistics and probabilities.
As said, correlation analysis between the assets is not done, but a kind of hedging is very well done, ie. risk sharing.
Stochastic vola: not that I'm aware of, as said the system doesn't make any use of the parameter volatility, neither the historic one nor the actually observed one.

 

[d08]

The system does not make use of any correlation in the market. So its task is then even harder...

As was stated, the system works with intraday data. To speed things up 702 bars/day was used (about 33.33 seconds/bar; in the next version this has been changed to 780 bars/day giving a round 30-sec bars).

The system uses limit orders, not market orders.

I'm offering the results of my research. Yes, there is still some work todo to connect this to the exchange, as was stated in the offer, and because I cannot know in advance which of the many APIs the customer has to connect to the exchange/broker.

Regarding the results: I would say they are very real. One just needs to apply the system nearly 1:1 to the market. And this is possible.

My point was that in year like 2008-2009, correlation was extreme and most likely your 5% DD target would look more like 35%. You yourself said that your model assumes normal markets and in normal markets, the correlation is much less.
It's the harsh market conditions that decide how good the system is.

I'm curious, why won't you test your method yourself using a smaller sum of money. As a programmer you probably have solid savings and could attract capital easily outside of ET if you have done your stuff properly.