Articles
Market Making Strategies and Day Trading Strategies
Market Making Strategies Market making strategies are called execution strategies or sell-side metho...
Mean Reversion Strategies
Mean reversion strategies, also called pairs trading, tend to capture market anomalies or inefficiencies between p...
Momentum Strategies
Even though we classify momentum with a longer time frame than a day, it is necessary to point out that momentum can al...
Types of Quantitative Trading Strategies
There are different types of trading strategies which differ in terms of their time horizon, risk profiles, capital req...
Quantitative Trading - Advantages and Disadvantages
Advantages Quantitative trading has many advantages over the discretionary approach of trading. The perform...
Introduction to Quantitative Trading
Quantitative trading involves developing and executing trading strategies based on quantitative research. The quants tr...
Financial Time Series in R - Course Conclusion
This course provided an overview of the fundamentals of time series analysis and how we can perform time series analysi...
Automatic Identification of Model Using auto.arima() Functio...
auto.arima() Function R also has a package called forecast, which contains many forecasting functions for time serie...
Forecasting with ARIMA Modeling in R - Case Study
In this lesson, we will take a new dataset (stock prices) and use all that we have learned to create a forecast using t...
ARIMA Modelling - Identify Model for a Time Series
The first step is to identify a possible model for a given time series. To do so, we need three things: a time series p...
ARIMA Modelling in R
We now have a fair idea about how we can use ARIMA modelling in R to estimate and forecast a time series. This is al...
Estimating Moving Average (MA) Model in R
We will now see how we can fit an MA model to a given time series using the arima() function in R. Recall tha...
Moving Average (MA) Model in R
A Moving Average is a process where each value is a function of the noise in the past observations. These are the rando...
Forecasting with AutoRegressive (AR) Model in R
Now that we know how to estimate the AR model using ARIMA, we can create a simple forecast based on the model. Step ...
Estimating AutoRegressive (AR) Model in R
We will now see how we can fit an AR model to a given time series using the arima() function in R. Recall that AR model...
AutoRegressive (AR) Model in R
AutoRegressive (AR) model is one of the most popular time series model. In this model, each value is regressed to its p...
Simulate Random Walk (RW) in R
When a series follows a random walk model, it is said to be non-stationary. We can stationarize it by taking a first-or...
Simulate White Noise (WN) in R
The function arima.sim() can be used to simulate data from a variety of time series models. Based on the model we want ...
ARIMA Modeling
If we combine differencing with autoregression and a moving average model, we obtain a non-seasonal ARIMA model. ARIMA ...
Time Series Models
By now we have a strong foundational understanding of various concepts essential for time series analysis. The rest of ...
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