Familiarity with elementary trading procedures and algorithmic trading basics is essential: acquaint yourself with the relevant terminology. Comprehend statistical methods and measurements, including the autocorrelation function, partial autocorrelation function, Maximum Likelihood Estimation (MLE), Akaike Information Criterion (AIC), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE).
Possess foundational knowledge in time series analysis, ensuring an understanding of time series stationarity and proficiency in forecasting using ARIMA. Grasp the fundamentals of Autoregressive and GARCH Models, along with a comprehensive comprehension of volatility.
Employ logistic regression for predicting the conditional probability of market direction. Explore various methodologies for evaluating portfolio and strategy performance, encompassing back-testing methodologies and statistical metrics such as the Sharpe ratio, Sortino ratio, and Max drawdown.
Demonstrate a basic grasp of Asset Allocation Models. Acquire proficiency in practical indicators and oscillators, such as RSI, MA, and EMA. Discriminate between Macroeconomic and Microeconomic news.
Possess fundamental knowledge of models pertaining to spot prices and futures prices. Cultivate a general understanding of multifactor models and the updating process for traditional factor models.
Demonstrate knowledge about the basics of the financial market at large, with a specific focus on the stock market. Gain a clear understanding of various instruments and stock markets.
Comprehend the concept of the stock market index and its computation. Acquire basic knowledge in machine learning, pattern recognition, as well as Natural Language Processing (NLP).
Module 1: Sentiment: What and Whose
Module 2: Sentiment Data
Module 3: Structure and Coverage
Module 4: Other Sources: Alternative Data (I)
Module 5: Models to Exploit Sentiment Analysis (I)
Module 6: Models to Exploit Sentiment Analysis (II)
Module 7: Opinion and Biases
Module 8: AI, Machine Learning & Quantitative Models to predict market direction
Module 9: Role of Alternative Data in Financial Trading: Alternative Data (II)
CSAF Exam
Reviews
There are no reviews yet.