Options Backtesting Software

[ironchef]

IMHO: My advice: Anyone tells you to do x, or y, beware! If it sounds too good to be true or it if is easy, .... beware. If told only good things about a trade, ignore that person forever, as they are exceeding evil or misguided.
There is little if any "low hanging fruit".

After several years trading options I came to the same conclusion - too many smart people in this space.

Backtesting could possibly be putting the buggy before the horse. This may not be the best way to develop a good trade, but may be a good way to refine/improve a trade. (IMO)

For me, it starts with the fundamentals. A model / strategy needs to make sense from a mathematical / common sense point of view.
Then it needs to be tested on the market. I've discarded a lot of models, as beautiful as they were and feeling sorry for the effort put into understanding then implementing them. But they didn't work, or at least not on that market.
Eventually I came to the conclusion that no model fits all markets and also markets change over time. So backtesting first determines what model(s) currently fit the market.

Both are very valuable perspectives. Thanks.

Live trading needs to both figure out when a model no longer fits and to control the risk such that one doesn't lose all the gains in one blow.

Aquarians, when you did your fundamental modeling, did you use the basic BSM model or did you have to use a more sophisticated higher level mathematical model? Also, my biggest problem is managing risk. Quite often I took profits too soon and missed out on big run up but other times, waited too long and saw my significant gains turned into significant losses. It was extremely frustrating.

This thread is extremely helpful.

Regards.

 

[stepandfetchit]

Two questions:

1) Do you think trading is something where everyone wins or it's a zero sum game?
2) Do you think you can open-source your model/strategy/code and still trade profitable using it afterwards?

I think:

1) It's zero sum. And when it's not, competition drives it to zero anyways.
2) No, you can't.

On #1, You can look at options as a form of insurance, so you can rightfully say that the relation between the option buyer and the option seller isn't necessarily zero-sum.
Compare it to the relation between two poker players: one has to lose in order for the other one to win.
But at least in theory, the insurance buyer is winning the protection from risk, and the insurance seller is winning the premium.
From this point of view it's both fair game and a mutual win.

The problem is that #2 kicks in: even if the insurance is not zero sum, you can't disclose your formula, or competition will drive you out.
Even when option sell prices are very close to the zero-profit point, a big insurance company like Goldman Sachs can still make money because it
can afford to have the volume which makes up for the losses.
A small company just needs higher margins in order to survive. And those higher margins do exist and do result from proprietary models/strategies.

The whole profitability in options revolves around knowing where zero is, because everything you add over that is profit.
What I have is the knowledge / code who at least gets the zero right. Actually it looks like it's profitable, but I need your feedback on it.
Will continue with that, but in the meantime I'm curious what is your position on #1 and #2.

IMHO: Neither question is specific enough for a Boolean response. My thinking, goes something like this...:
Even IFF one finds a trading strategy that is profitable and worthwhile for them, there exists a substantial amount of "noise" that could prove detrimental. So, for me, If something is working, I must dig to understand why, as more often than not, the basis for the success may NOT be what you think. This can be your worst nightmare, as you are likely to increase your trading size at wrong time and for wrong reason. The opposite is also true, where failure must also be understood, as to why! I have also pulled the plug early, when the strategy was actually just running thru a typical rough patch.
Also, we all must be logically aware that we are fodder for someone else's cannon, and eventually, we will be come the "slower hiker" that the bear catches. Being aware that nothing remains constant (edges are exploited, and therefore diminish), should always be kept in mind.

 

[Easy_Test]

I built back test tool using Python, and VBA. It's really easy to use, and when you finish running the back test the data is in Excel so you can review every single trade to make sure the test went perfectly. I have been using it with my SPX data that goes back to 1996. If someone has stock data to test earnings trades, I'm up for a trade.

business1031e@yahoo.com

 

[optquant]

for options in China market, now can try this https://github.com/qmhedging/poboquant

 

[mushinseeker]

hi .. can anyone suggest a way to create a way or a source of data to create a time series graph of an option over let's say past 1-2 months? I looked into data sources such as orat, TD Ameritrade API and both of them involve fetching snapshot data. This means I have to save it locally every hour, ticker-by-ticker. This also means I would'nt be able to miss any day for there would be null values. An api that enable trader to filter by past x weeks data by timestamp would solve it for one could just iterate through the timestamps and build the "chart" on the fly. Any ideas would be appreciated. I looked into ivol and CBOE and they are very expensive. Thanks.

 

[stepandfetchit]

If you have TOS, why not just select the option you wish to view with the aggregation and time span you wish? Guessing you mean something other than this?

If you want to produce independently (do it yourself), then you will need the data. I get mine from CBOE Livevol, but you are correct, it is not free. --

 

[ironchef]

hi .. can anyone suggest a way to create a way or a source of data to create a time series graph of an option over let's say past 1-2 months? I looked into data sources such as orat, TD Ameritrade API and both of them involve fetching snapshot data. This means I have to save it locally every hour, ticker-by-ticker. This also means I would'nt be able to miss any day for there would be null values. An api that enable trader to filter by past x weeks data by timestamp would solve it for one could just iterate through the timestamps and build the "chart" on the fly. Any ideas would be appreciated. I looked into ivol and CBOE and they are very expensive. Thanks.

Just trying to help. I can get this from my brokerage trading platform. Is this what you are looking for?

 

[mushinseeker]

Thanks guys.
I have to investigate liveVol and even the 2 graphs you guys pasted. If the data in the grpahs are downloadable in a csv, then that might work-- put it in a dataframe in python ,etc . I kinda want to do more stuff with it such as compare it with indicators in the underlying and create backtests off of it.