What I am doing:
I am currently developing intra day stat arb models used to estimate the fair value of an exchange rate using statistics. In order to optimize the parameters of my models machine learning is used, as this allows the model to adapt to the market. Because I am involved in mean reversion which is famous for draw down prior to profits, I hedge all my exposures, involving a form of pairs trading. While pairs trading involves volatility and beta hedging which helps reduce draw down, it also carries a second advantage being that you are not forecasting trends but rather correlations and return spreads and therefore it does not matter if commodities or regional economies backing the pair fall or rise, only that the spread acts as desired. This makes pairs trading better viewed as a contrived asset of its own. This is similar to how tri-arb does not forecast the direction of the market but only the difference between the bid offer spread of three currencies thus constructing an asset out of other assets.
My trading relies often on small discrepancies often 10bps or less in order to profit, and due to hedging of beta and volatility, high leverage is safe to use. The Strategy turns over 1k dollars in trading volume a year per dollar in the portfolio, and therefore over 1.5m USD in volume will be turnt over every year. Risk management is also very unique to my model, rather than allocating a fixed lot size, a fixed volatility is allocated. Volatility targeting allows a equal amount of volatility exist for every trade. This is part of what is known as the risk parity portfolio, which I talk about on my youtube and will include a video explaining it at the bottom of this page. A risk parity portfolio will have a higher sharpe ratio on average than a equal allocation method used by most investors.
My current anticipated return is 50% on investment and my targeted volatility is 25% however the volatility could potentially be higher as I only estimate vol of individual assets. I am currently benchmarking my sharpe ratio to the DBCR Dynamic FX index, which I will include a video of me explaining in detail. The DBCR Dynamic is a FX alpha index for actve managers to benchmark their sharpe ratio to, and in many ways is similar to the SP500 if you utilyze the SP500 as an alpha index rather than a beta index. Historically the DBCR Dynamic has achieved a sharpe ratio of one, which I hope to beat with my models. If you have any questions feel free to ask!
Benchmarking Method:
Risk Parity:
I am currently developing intra day stat arb models used to estimate the fair value of an exchange rate using statistics. In order to optimize the parameters of my models machine learning is used, as this allows the model to adapt to the market. Because I am involved in mean reversion which is famous for draw down prior to profits, I hedge all my exposures, involving a form of pairs trading. While pairs trading involves volatility and beta hedging which helps reduce draw down, it also carries a second advantage being that you are not forecasting trends but rather correlations and return spreads and therefore it does not matter if commodities or regional economies backing the pair fall or rise, only that the spread acts as desired. This makes pairs trading better viewed as a contrived asset of its own. This is similar to how tri-arb does not forecast the direction of the market but only the difference between the bid offer spread of three currencies thus constructing an asset out of other assets.
My trading relies often on small discrepancies often 10bps or less in order to profit, and due to hedging of beta and volatility, high leverage is safe to use. The Strategy turns over 1k dollars in trading volume a year per dollar in the portfolio, and therefore over 1.5m USD in volume will be turnt over every year. Risk management is also very unique to my model, rather than allocating a fixed lot size, a fixed volatility is allocated. Volatility targeting allows a equal amount of volatility exist for every trade. This is part of what is known as the risk parity portfolio, which I talk about on my youtube and will include a video explaining it at the bottom of this page. A risk parity portfolio will have a higher sharpe ratio on average than a equal allocation method used by most investors.
My current anticipated return is 50% on investment and my targeted volatility is 25% however the volatility could potentially be higher as I only estimate vol of individual assets. I am currently benchmarking my sharpe ratio to the DBCR Dynamic FX index, which I will include a video of me explaining in detail. The DBCR Dynamic is a FX alpha index for actve managers to benchmark their sharpe ratio to, and in many ways is similar to the SP500 if you utilyze the SP500 as an alpha index rather than a beta index. Historically the DBCR Dynamic has achieved a sharpe ratio of one, which I hope to beat with my models. If you have any questions feel free to ask!
Benchmarking Method:
Inserted Video
Risk Parity:
Inserted Video
Quant Trader - My Blog: quantstop.blogspot (dot) com
