Christopher Hausmann (@fr_chris24) 's Twitter Profile
Christopher Hausmann

@fr_chris24

ID: 1348229232745472007

calendar_today10-01-2021 11:24:41

919 Tweet

624 Followers

374 Following

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I have dealt with different time periods. I found that the randomness increases and the model validity decreases for short periods. This probably has to do with the trend aspect of the independent variables. Below you can see it for $QQQ as an example. #stockmarkets

I have dealt with different time periods. I found that the randomness increases and the model validity decreases for short periods. This probably has to do with the trend aspect of the independent variables. Below you can see it for $QQQ as an example. #stockmarkets
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brigde band time frame optimization with success rate when close to top or bottom, sharpe ratio and maximum return. Below you can see the example for $BTC and $ETH

brigde band time frame optimization with success rate when close to top or bottom, sharpe ratio and maximum return. Below you can see the example for $BTC and $ETH
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currently working on an evolutionary algorithm for portfolio selection and weighting optimization. This is an example of some of the US sector ETFs. It runs on various optimization strategies such as return maximization, Sharpe maximization, covariance minimization, etc.

currently working on an evolutionary algorithm for portfolio selection and weighting optimization. This is an example of some of the US sector ETFs. It runs on various optimization strategies such as return maximization, Sharpe maximization, covariance minimization, etc.
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Can we expect a correction in the $QQQ ? My forward return model expects a correction in the next 5 to 15 days. Several quantiles 1 print in all three time frames where the expected result is negative on average. Still a very bullish trend in the QQQs.

Can we expect a correction in the $QQQ ? My forward return model expects a correction in the next 5 to 15 days. Several quantiles 1 print in all three time frames where the expected result is negative on average. Still a very bullish trend in the QQQs.
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Portfolio construction using an evolutionary algorithm with influence of optimized Donchian midpoints and various other risk indicators. This applies to the ETFs of the US sectors compared to the SPY. The current weightings are behind the ticker in the legend.

Portfolio construction using an evolutionary algorithm with influence of optimized Donchian midpoints and various other risk indicators. This applies to the ETFs of the US sectors compared to the SPY. The current weightings are behind the ticker in the legend.
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a look at the current uptrend in $QQQ. In my optimized midpoint model for assessing an uptrend or downtrend, the number of consecutive up signals is still quite low. On this basis, we are slightly above the 100-day mark. #StockMarket #NASDAQ #QQQ $SPY

a look at the current uptrend in $QQQ. In my optimized midpoint model for assessing an uptrend or downtrend, the number of consecutive up signals is still quite low. On this basis, we are slightly above the 100-day mark. #StockMarket #NASDAQ #QQQ $SPY
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$QQQ it becomes likely that there will be a bottoming process after this small correction. Future returns would point to the middle to end of next week #StockMarket

$QQQ it becomes likely that there will be a bottoming process after this small correction. Future returns would point to the middle to end of next week #StockMarket