About:
Proprietary quantitative models
and algorithmic trading strategies for long/short equity optimization models
with specific risk and return parameters specified by the investor profile,
utilizing machine/deep learning, along with Q reinforcement learning agents.
Machine learning models utilizing multivariate/logistic regression, lasso/ridge regression, linear/quadratic discriminant analysis, decision trees, K neighbors, Naive Bayes, random forest, support vector machine, Adaptiveboost, GradientBoost, XGB, and portfolio optimization to maximize return and minimize volatility for various investor risk profiles.
Deep learning modeling using recurrent neural networks, Tensorflow, nltk, sentiment analyzer, Keras LSTM, and convolutional neural networks, in attempt to predict specific asset class forecasted prices through stocks, forex, bonds, futures, ETFs, and other derivatives.
Proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library.
Reviews
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Great work! Always a pleasure working and communicating with Sam, he is knowledgeable in his passion for trading and coding. Will look forward to working with him again in the future!
:Sam was able to deliver timely and according to requirements with quality. He is able to provide documentation as well. Overall great experience.
:Sam is a great person overall, he is willing and able to help, and great to work with. Hope to work with him again in the near future.
:Sam was excellent to work with. Very knowledgeable and excellent communication. I look forward to working with Sam again very soon.
:Sam is great to work with. He is very prompt, professional, and have the expertise that is needed to implement even very complex and large scale projects successfully. Will continue to work with him on many more projects, highly recommended !!!
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