PortfolioEffect


 

Chicago Python Workshop [0.37]

Posted on Dec. 1, 2016, 5:40 p.m. by PortfolioEffect @ [source]

You will learn why the use of high frequency market data is necessary to be able to measure correctly the risk and rebalance your portfolio adequately. You will also learn how to build strategies to generate alpha.

alpha backtest build generate learn optimize portfolio strategies strategy study

 

Very interesting R and Python Workshops in NYC [0.09]

Posted on Nov. 28, 2016, 10:17 p.m. by PortfolioEffect @ [source]

During our 2 workshops, we covered how to compute intraday risk, backtest strategies, forecast metrics and optimize your portfolio to get more alpha. We went through classic moving average strategies to comparing high frequency strategies to low frequencies.

Attendees background classic comparing frequencies frequency moving present saving strategies

 

NYC R Workshops [0.33]

Posted on Oct. 31, 2016, 2:51 p.m. by PortfolioEffect @ [source]

You will learn why the use of high frequency market data is necessary to be able to measure correctly the risk and rebalance your portfolio adequately. You will also study how to build your own portfolio, create a strategy, backtest it, optimize it, and use vol forecasting with PortfolioEffectHFT package available on CRAN.

backtest build CRAN forecasting optimize package portfolio PortfolioEffectHFT strategy study

 

NYC Python Workshop [0.33]

Posted on Oct. 31, 2016, 2:12 a.m. by PortfolioEffect @ [source]

You will learn why the use of high frequency market data is necessary to be able to measure correctly the risk and rebalance your portfolio adequately. You will also study how to build your own portfolio, create a strategy, backtest it, optimize it, and use vol forecasting with PortfolioEffect hft package available on Anaconda.

backtest build forecasting HFT optimize package portfolio PortfolioEffect strategy study

 

We are happy to announce PortfolioEffectEstim toolbox availability for both R & MATLAB.

It is designed for high frequency market microstructure analysis and contains popular estimators for price variance, quarticity and noise.

 

Microstructure noise describes price deviation from its fundamental value induced by certain features of the market under consideration. We will investigate how severe could be noise contamination for different stocks as the we move towards transactional frequencies.

bid bounce contamination frequencies investigate noise severe stocks trades transactional

 

In this post we take intraday backtesting with PortfolioEffectHFT package one step further by adding a simple signal-based rebalancing rule. Using this rule we will create two trading portfolios – a high frequency strategy portfolio and a low frequency portfolio and compare them with each other in terms of their intraday risk and performance.

compare frequency holding intraday moving portfolio position stock strategy trading

 

PortfolioEffectHFT package was released on CRAN last week and allows all R users to backtest high frequency trading (HFT) strategies, perform intraday portfolio analysis and optimization on PortfolioEffect’s own compute cluster. You could even combine server-side and client-side data creating mixed data portfolios.

aapl access data default free GOOG ratio sharpe side trading