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Selling puts also eats into your margin which is an opportunity costs on its own.

I mentioned about walk-forward tests above. I wrote a simple python package here to generate indexes of dataset for the training, testing and boostrapping indexes. You may check it out under pypi page and pip install if you find it useful, https://pypi.org/project/bootstrapindex/

Could be out of market hours

Not really, I use volatility term structures and Garch based models. The article is just some self-contained python codes to place spread positions.

For what is worth, if anyone is keen on placing options spreads via IB gateway API , I wrote a short 101 tutorial here. Enjoy!

Personally, I try to tap on well researched risk premia that is less likely to experience decay in performance e.g. trend following, volatility risk premium, all-weather etc. Then I add bells and whistles with risk management layer. Life is too short to lose money on investment and trading. With...

For stocks, you have to account for splits and dividends. That's another set of problem.

Something it's better not to fiddle with your systems too much haha

How about Jim Simmons, Robert Mercer, Kenneth Griffin, Edward Thorp?

@globalarbtrader Rob, wrote a really great post on dynamic trend following, https://qoppac.blogspot.com/2020/12/dynamic-trend-following.html Extracting the relevant para here, We calculate an optimal position that we want to take We compare it to the position we currently have We adjust to...

It can be for trading or investing. You size your positions first based on volatility based measures such as standard deviation or ATRs; then you scale it up or down based on your forecasts. Let's say your forecast is only 50%, you place half a position. Few days later, when more data is in and...

Developing more diversified systematic strategies and achieving more consistent returns streams.

For non-options related strategy, you may consider continuous trading i.e. drop stop loss completely. You scale in and out of the positions according to your forecasts. It's an epiphany that I gotten from Robert Carver's 2 trading books (Systematic trading and Leveraged Trading). In particular...

Using COVID, 2008 crisis, 1987 scenario as the worst case scenario will be a good start.

If you are keen in a perspective from Euan Sinclair, author of several well known options trading books. He has a PhD in Physics. https://blog.quantinsti.com/hidden-truths-stop-loss-trading/

Thanks for your reply! Good to know the breakdown of the costs as this could really eat into the profits. I haven't done any detailed analysis on the slippage, execution side. At the moment, I'm just relying on the IB adaptive algos for trade placements.

@ValeryN Congratulations for a great performance this year. I think you are only 1 of the few legit traders in ET. Personally, I'm wary of running long-short portfolios with a retail account. I've some quick questions and would like to seek your views, - What's the slippage (e.g. commission...

Test your strategy using options chain data in Quantconnect first, For such negative skew strategy, trade small.

Use sharpe and sortino ratios. Understand the theoretical distribution of your strategy. Is it positive skew, negative skew, high or low kurtosis. Obtain the parameters and simulate using monte carlo. You may also use boostrapping to create a non parametric distribution to understand the risk...

Have fun! Although debugging and integrating error handling stuff is a nightmare to handle in TWS API async framework.