Use momentum in markets and fundamental factors which influence the forex markets to create new trading strategies. Learn to use Python to backtest your strategies.
Variables, Loops, Conditional statements, Functions, Objects, Containers, Namespaces, Classes
Lists, Dictionaries, Tuples, Sets
Pandas: Series and DataFrame, NumPyCode in Python: Moving Average Crossover trading strategy, Relative Strength Index (RSI) trading Strategy
Duplicate data, Missing values, Incomplete data, Mixed-up data
Important things to consider during backtesting: Slippages, transaction costsCode in Python: Momentum trading strategy
Analyze the performance of the strategy using different performance metrics
Brief history of forex trading, the macro economic factors that affect a forex market, and the major players in the forex market
A cross-sectional momentum trading strategy, backtesting the same strategy on the Quantra Blueshift platform and additional considerations to enhance the strategy
General pitfalls of intraday forex trading, the risk management techniques and ideas for further scope of research
Learn various macroeconomic factors such as Inflation, GDP, interest rate and balance of trade that affect the forex market
Learn the valuation of currency using different techniques such as purchasing power parity, real and nominal exchange rate.
Learn a forex trading strategy using the real effective exchange rate and additional considerations to enhance the strategy
Learn to step by step code the strategy discussed in section 3 and analyze the strategy performance using the sharpe ratio and CAGR.
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