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Creating Dynamic Pretrade Models:<i>Beyond the Black Box</i>

Robert Kissell

The Journal of Trading2018https://doi.org/10.3905/jot.2018.13.4.041article
ABDC C
Weight
0.33

What the paper says

We provide a framework for investment managers to create dynamic pretrade models. The approach helps market participants shed light on vendor black-box models that often do not provide any transparency into the model’s functional form or working mechanics. In addition, this allows portfolio managers to create consensus estimates based on their own expectations, such as forecasted liquidity and volatility, and to incorporate firm proprietary alpha estimates into the solution. These techniques allow managers to reduce overdependency on any one black-box model, incorporate costs into the stock selection and portfolio optimization phase of the investment cycle, and perform “what-if” and sensitivity analyses without the risk of information leakage to any outside party or vendor. <b>TOPICS:</b>Portfolio construction, statistical methods

6 citations

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Cite this paper

https://doi.org/https://doi.org/10.3905/jot.2018.13.4.041

Or copy a formatted citation

@article{robert2018,
  title        = {{Creating Dynamic Pretrade Models:<i>Beyond the Black Box</i>}},
  author       = {Robert Kissell},
  journal      = {The Journal of Trading},
  year         = {2018},
  doi          = {https://doi.org/https://doi.org/10.3905/jot.2018.13.4.041},
}

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Creating Dynamic Pretrade Models:<i>Beyond the Black Box</i>

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Evidence weight

0.33

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.20 × 0.4 = 0.08
M · momentum0.20 × 0.15 = 0.03
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.