Welcome to my first post, and I apologise in advance for what may seem a slow start. First, I would just like to say that this blog is primarily here to document my research into investment strategies using the Python programming language. I will upload tutorials as a way of formalising my progression, however after a while these will subside and be replaced with research report style posts. Thus, I would like to think that eventually someone could follow this blog and replicate everything I do.
In addition to this, I am also in the process of developing a dynamic Black-Litterman asset allocation model, utilising quantitative 'investment views' derived through mean-reversion in investment risk premiums. Results and developments of this will be posted online, but the program itself will be proprietary at least for the time being. In the mean time, I will post strategies using momentum and mean-reversion tools, and univariate/multivariate data analysis.
As my 'about me' states, my background is in economics and econometrics, and I hope to utilise this knowledge to further improve the capabilities of Python as a great host language for developing quantitative investment strategies. On a final note, my use of 'investment' denotes my preference of medium to long term strategies, and is thus primarily involved in determining optimal allocations. However trading strategies are a very important part of learning Python and thus I will be writing a lot of these for the foreseeable future, until the point where I can backtest my asset allocation ideas.
In addition to this, I am also in the process of developing a dynamic Black-Litterman asset allocation model, utilising quantitative 'investment views' derived through mean-reversion in investment risk premiums. Results and developments of this will be posted online, but the program itself will be proprietary at least for the time being. In the mean time, I will post strategies using momentum and mean-reversion tools, and univariate/multivariate data analysis.
As my 'about me' states, my background is in economics and econometrics, and I hope to utilise this knowledge to further improve the capabilities of Python as a great host language for developing quantitative investment strategies. On a final note, my use of 'investment' denotes my preference of medium to long term strategies, and is thus primarily involved in determining optimal allocations. However trading strategies are a very important part of learning Python and thus I will be writing a lot of these for the foreseeable future, until the point where I can backtest my asset allocation ideas.
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