Author: Stephanie Toper

Alternative Data: Users’ Data in Optimization

Optimization description A trader using alternative data who already forecasted expected returns of different stocks want to find what is the optimal weights of his portfolio. Let’s input the users’ data in the optimization. Our goal is to maximize the expected return given by the user divided by the square root of the variance and find what are the […]

Fordham-PortfolioEffect Algo Trading Workshop with Python, NYC

NYC, Sunday, May 21st from 9am to 4pm During the workshop, you will learn how to compute intraday risk with PortfolioEffect HFT package available on Anaconda. The complexity of tick market data will be explained. You will study how to build your own portfolio, create a strategy, backtest it, optimize it, and use vol forecasting. […]

Jupyter Notebook, Python or R Kernel & PortfolioEffect HFT Package

Using Jupyter notebook to develop strategies, do research or monitor your portfolio is a great idea.  Jupyter supports different languages. At PortfolioEffect, our users are currently using R or Python kernel. They directly login through our web browser to see their portfolios. Examples on how to develop strategies and monitor risks are provided. This solution […]

Princeton R Workshop

  Princeton-PortfolioEffect Algo Trading Workshop Sunday, April 9th from 9:00 am – 4:30 pm Princeton, NJ We are glad to announce that this year we are partnering with Quant Trading Conference to deliver an R Workshop. Prerequisite Beginner knowledge of R and finance, college level math with RStudio installed Agenda 9:00 AM          9:30 AM          Welcome […]

PortfolioEffect Utilizes Real-Time Risk Metrics To Create Alpha

Benzinga’s article on PorftolioEffect can be found on this link. We decided to post the article in the blog as it is a good description of what we do. You can vote for PortfolioEffect here on Facebook and Linkedin for 2 votes. PortfolioEffect Utilizes Real-Time Risk Metrics To Create Alpha Brett Hershman , Benzinga Staff Writer   […]

Moving Average Strategy using hft Python package

Package Installation For hft package installation, you will need to have Anaconda2 and JDK installed. Please take a look at the manual. conda install -c portfolioeffect hft Strategy description We use price vector to create a strategy based on moving average. We assume that prices tend to revert to its moving average. Therefore, if the […]