Tag Archives: applied

Applied Economic Analysis With R code walkthrough

It seems there are set of R exercises found on R-Bloggers (for R course walkthrough)  if you are interested in studying econometric data. I can find this very useful if you want to focus on forward looking data for proper forecast. I do this as part of my Quant Analytic service you can find below.

https://towardsdatascience.com/bayesian-linear-regression-in-python-using-machine-learning-to-predict-student-grades-part-2-b72059a8ac7e

 

I just posted this old legacy R course if you are interested. This include R code walkthrough. I have many posted on this language here 

Purchase here if interested

http://quantlabs.net/academy/buy-all-of-our-r-courses/

To be quite honest, I am quite surprised on how popular this seems to be among my site visitors.

Note that this is older version of R using version 2.15!

Here are the details with a video at this location

R Course with Technical Analysis

R Course with Technical Analysis

 

Module 1

Technical Analysis in R

 

Technical Analysis in R

Unit 1

30 day moving average function

Unit 2

2 sided moving average for mean rolling window

Unit 3

R Code Walkthrough Improved Moving Average using intra day for Forex data

Unit 4

The improved moving average

Unit 5

R Code Wakthrough Simple Moving Averag Strategy with Volatility Filter

Unit 6

Love level Improved Moving Average functions with testing code

Unit 7

R source code for trading script with update portfolio, position size, MA, cross over, SMA, optimize parameters pt 2

Unit 8

R source code for trading script including MACD, Omega performance, RSI, and Bollinger Band measuring strategy and portfolio performance with plots Pt 3

R Course with Quant including GARCH

 

Module 1

Quant trading in R

 

Quant trading in R

Unit 1

Walthrough Parallel R Model Prediction Building and Analytics

Unit 2

Intro to GARCH forecasting with various R packages

Unit 3

How to use GARCH for predict market movements

Unit 4

How to use GARCH to predict distributions

Unit 5

GARCH trading R script walkthrough with a rolling window

R Course with Quant

R Course with Quant

 

Module 1

Intro

 

Intro

Unit 2

An ARMA model R code walkthrough

Unit 3

Checklist of forecasting with ARIMA: is time series stationary, differentiate, ARIMA(p,d,q), and which AMRA model to use?

Unit 4

R code walkthrough: Detrend to use Auto ARIMA modelling and forecast with statistical data and Ljung BoxTest

Unit 5

My first version of ARIMA R script with Forex data and Equity 1 and 5 min frequency

Unit 6

Bayesian analysis to Compare algorithms with Gibbs

Unit 7

Markov Chain R source code walkthrough

Unit 8

Monte Carlo R Walkthrough Demo

Unit 9

An alternative to running a Monte Carlo simulation

Unit 10

R code walkthrough Mean Absolute Deviation with Efficiency Frontiers Demo

R Course with Mean Reversion and Pair Trading

 

Module 1

Mean Reversion in R

 

Mean Reversion in R

Unit 1

Backtesting a Strategy with Mean Reversion

Unit 2

Mean Reversion Euler with Ornstein Uhlenbeck process

Unit 3

Pairs trading R source code walkthrough with mean reverting logic, spread and beta calculation

Module 2

Pair Trading in R

 

Pair Trading in R

Unit 1

Poor mans Pair Trading with Cointegration R Walkthrough

Unit 2

Pair trading with S&P 500 companies

Unit 3

Pairs trading with testing cointegration

Unit 4

Seasonal pair trading

Unit 5

 

Unit 6

Pairs Trading R Code Walkthrough

Unit 7

Pairs trading with a Hedge Ratio Demo

Unit 8

R Code Walkthrough Back testing with trading pair with CAPM

Unit 9

Gold versus Fear in Cointegration test

R Course with Arbitrage and Volatility

Arbitrage and Volatility

 

Module 1

Arbitrage in R

 

Arbitrage in R

Unit 1

Beating a random walk with arbitrage

Unit 2

Beating a random walk with arbitrage

Unit 3

Time Based Arbitrage Opportunities in Tick Data: Why low latency is needed in HFT?

Unit 4

Building a currency graph with arbitrage

Unit 5

Arbitrage: Modelling returns with CAPM APT aka Abritrage Pricing Theory

Unit 6

Indian equity market index NIFTY anaysis with CAPM vs APT aribitrage pricing theory using PCA and moment analysis

Module 2

Volatility in R

 

Volatility in R

Unit 1

R Code Walkthrough Adding a volatility filter with VIX

Unit 2

R Code Wakthrough Simple Moving Averag Strategy with Volatility Filter

Unit 3

Mean Reverting with Volatility Spike

Unit 4

Trading with GARCH volatility R script walkthrough demo

Unit 5

Jeff Augen volatility spike code

 

Reminder from yesterday. This closes out TONIGHT as well:

 

 

 

This is the your chance to learn about behind the scenes of these trading patterns I presented on Monday night. I have made this replay video now private which means it is only available to my Quant Elite Members. This is a very limited and exclusive offering to access it! I even revealed the source of how the Python code was created to generate them, This will never be seen again after this Friday! It is way too valuable that I don’t need the world to know how these work.

 

This posting will be removed this Friday night Eastern Standard Time (same as NYC)!

 

I Want To Learn Trading Patterns Now

Get your access to this via my 3 month Quant Elite Membership if interested!

 

Please find the upcoming new items I will be adding the next few months for this membership:

 

1. Live Q&A workshop bootcamp for the Python 3 Infrastructure Course for a Primitive Algo/Automtated Trading System

2. Packaged up course of using Dukascopy JForex API for automated forex and CFD trading. (this is partially done now with access for this membership)

3. Daily charting within the Quant Analytics service.

 

Here are the details with benefits of this trial membership

http://quantlabs.net/academy/introduction-quant-elite-membership/

 

REMEMBER: My patterns talk will be removed forever as of Friday!!!

 

Always remember I just created the online store for all other product and services.

I Want to Learn Trading Patterns Now

Please find the upcoming new items I will be adding the next few months for this membership:

 

1. Live Q&A workshop bootcamp for the Python 3 Infrastructure Course for a Primitive Algo/Automtated Trading System

2. Packaged up course of using Dukascopy JForex API for automated forex and CFD trading. (this is partially done now with access for this membership)

3. Daily charting within the Quant Analytics service.

 

Here are the details with benefits of this trial membership

http://quantlabs.net/academy/introduction-quant-elite-membership/

 

RMEMEBER: My patterns talk will be removed forever as of Friday!!!

 

Always remember I just created the online store for all other product and services.

P.S. Let me know if you are interested in an annual term as well.

Buy all of our R courses with R code walkthrough

HOW DO YOU START A PROFITABLE TRADING BUSINESS? Read more NOW >>>

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Quant analytics: continuous time markov chains as applied to asset pricing (order book). Any knowledge/experience?

Quant analytics: continuous time markov chains as applied to asset pricing (order book). Any knowledge/experience?

Starting to look at continuous time markov chains as applied to asset pricing (order book). Does anyone have any knowledge/experience in this area?
==

I was recently exploring this:
This paper merges the literature on technical trading rules with the literature on Markovswitching to develop economically useful trading rules. The Markovmodels’ out-of-sample, excess returns modestly exceed those of standard technical rules and are profitable over the most recent subsample. A portfolio of Markov and standard technical rules outperforms either set individually, on a risk-adjusted basis. The Markov rules’ high excess returns contrast with mixed performance on statistical tests of forecast accuracy. There is no clear source for the trends, but permitting the mean to depend on higher moments of the exchange rate distribution modestly increases returns.
http://www.sciencedirect.com/science/article/pii/S037842660600166X
Don’t buy the article. Google the title.
On a side note, aren’t candlestick patterns Markov chains as their current state influences the probability of the next state?
If you consider, for example a 3 bar moving-window as a single state, then there are known 3 bar patterns with fixed probabilities for predicting the next state.

 

HOW DO YOU START A PROFITABLE TRADING BUSINESS? Read more NOW >>>

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Quant analytics: Is it possible to improve a predictive model using the data that come after the model is applied?

Quant analytics: Is it possible to improve a predictive model using the data that come after the model is applied?

The new data are supposed to be biased towards the treatment. So how to utilize them in this case? Thanks.

That depends on the model in question. Your initial question is, unfortunately, too general to give a specific answer. You should possibly look into Bayesian Inference or hierarchial Bayesian modelling, with your initial model as your prior.

 

Yes, consider a Self Organizing Map (SOM). This separates your variables and allows you to find those that have higher correlations between the other variables. “After this model is applied,” you can formulate weights based on these results into a stronger model such as a neural network.

 

 

HOW DO YOU START A PROFITABLE TRADING BUSINESS? Read more NOW >>>

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!