Terms & faqs History of the Options Market Options give traders the right but not the obligation to buy or sell underlying assets at a specific price at a predetermined date. Options Trading has matured over the past century and has
Terms & faqs History of the Forex Market The forex market is the largest financial market in the world. It has a rich history, and many important global events have shaped modern foreign exchange trading. Here is a chronicle of the
Trading Maximum Favorable Excursion (MFE) Maximum Favorable Excursion (MFE) is the highest potential profit that a trade earns before it is closed. Traders can use MFE to evaluate the performance of the trading system and maximize their profit
Trading Maximum Adverse Excursion (MAE) The Maximum Adverse Excursion (MAE) measures the potential loss or distance a trade has moved against you. Traders use the MAE to determine where to place a stop-loss order for their trading system.
Data science The History of AI in Finance Artificial Intelligence is an indispensable part of the finance world due to its ability to understand complex mathematical relationships and its automation ability. With data and compute power growing exponentially, financial service providers
Data science Autoregressive Model Python Autoregression, or an autoregressive model, is a type of predictive modeling that uses linear regression on past values to predict the next value in a time series.
Data science How to Interpet ARIMA Results To analyze ARIMA results, you need to determine if the model meets the assumptions using Jlung-Box chi-square statistics and autocorrelation of residuals; understand if each term is significant using p-values, and recognize if
Data science How to Make a Time Series Stationary in Python You can make a time series stationary using adjustments and transformations. Adjustments such as removing inflation simplify the historical data making the series more consistent. Transforms like logarithms can stabilize the variance while
Data science How to Check Time Series Stationarity in Python You can use visual inspection, global vs. local analysis, and statistical tests such as the Augmented Dickey-Fuller (ADF) test to identify stationarity using Python.
Data science What Is Stationarity in Time Series Analysis? A Visual Guide Stationarity means that the statistical properties of a process that creates a time series are constant over time. This statistical consistency makes predictable distributions and is an assumption of many time series forecasting
