For our clients and trial users using CubitBlack as a standalone service, many have requested us to demonstrate how to build strategies and model portfolios. Sorry for the delay and here it is.
Understand the Market first
From our risk-controlled environment, you can see the market log returns, conditional volatility, rolling volatility, and next five-day forecast using auto-regressive model. From 2007 to 2014 is the training data set, and there after the testing data set that helps us learn and forecast the market volatility.
We applied the VIX front month futures statistics and generate the a hybrid conditional volatility for simulations.
As your can see, the simulation provides a clear picture the expected PL distributions using VaR.
With the understanding of the market’s variance risk and its volatility forecast, we can move on to learn about opportunities within different sectors, industries, and securities.
We can screen and analyze stocks based on their fundamentals.
For some cyclical stocks or ETFs, we can test our momentum parameters and build trading strategies.
With the filtered list of equities and ETFs ready to deploy, we can test strategies in the Pre-Trade section. Here is one of our Synertree ETF strategies.
We simulate prices and optimize the positions.
We analyzed performances, covariances, auto-correlations, and risk distributions.
Once we are satisfied with the risk analytics and performances for that they are closely represent our investment mandate and strategic principles, we are ready to deploy the strategy to the model portfolio.
After the model portfolio is created, Risk Controlled Environment runs daily and ensures the model’s actual risk is within the model’s mandate risk. A warning signal will alert you if your model portfolio’s risk of loss within certain confidence intervals exceeds your mandated risk of loss.
Hopefully, this example provides sufficient supports for those using the CubitBlack as a standalone solution. For PM clients, all monthly research, analysis, trades, and documentations are fully incorporated.
Again, any questions, please contact us firstname.lastname@example.org.