Data Science
-
Crypto futures trading can produce serious returns with predictive algorithms
Introduction to Crypto Futures Trading Crypto futures trading is a type of trading that involves buying and selling contracts that speculate on the future price of a cryptocurrency. This type of trading allows traders to profit from price movements without actually owning the underlying asset. Traderie, a popular trade finder platform, has facilitated over 236,474,422… Continue reading
-
Using ChatGPT for Data Cleaning
I’m always on the lookout for tools that can streamline financial analysis and provide valuable insights. One such tool that has caught my attention is ChatGPT’s data analysis features, which emphasize the importance of clean data for ensuring the accuracy and reliability of datasets. Data cleansing, especially when utilizing AI tools like ChatGPT, is crucial… Continue reading
-
An AI Crystal Ball? How We Predict Future Outcomes Using a Temporal Fusion Transformer Model
Introduction to Deep Learning Models Deep learning models have revolutionized the field of time series forecasting, offering significant performance improvements over traditional methods. These models are particularly well-suited for handling complex temporal relationships and high-dimensional data. In this section, we will introduce the basics of deep learning models and their applications in time series forecasting.… Continue reading
-
Payment Processing Optimization: How to Leverage Software to Maximize Revenue
In my years as a fractional CFO, I’ve watched promising companies hit a wall. It typically happens around the $5M ARR mark – the payment infrastructure that seemed robust at startup begins buckling under the weight of scale. The symptoms are similar: finance teams drowning in reconciliation, revenue leaking through failed payments, and customer churn… Continue reading
-
Wondering about machine learning in your efforts? Let’s talk the basics about Random Forest and XGBoost.
The business generalist or expert in a specific aspect of business operations might wonder about machine learning and data science. Random Forest and XGBoost are two techniques that are related and commonly used in business predictive modeling. I want to give you some basics for these frequently used techniques so you can be sharp enough… Continue reading
-
Recurring revenue modeling can be tricky, using cancellation curves can improve precision and results
In a recent post on SaaS financial modeling, I covered some of the main drivers that play a role in the construction of financial forecasts for SaaS and related business models. One of the most important aspects of such financial forecasts is the build out of contracted revenues. In general contracted revenues can be quite… Continue reading
-
Elevating Data Science with Operations Research Expertise
Introduction Who’s on a quest to develop advanced data science capabilities? One of my analytics team’s strategic expansion brought together diverse talents in statistics, applied math, and engineering. This case study explores the integration of operations research, fostering collaboration and knowledge diversity within analytics. Objective Our primary goal was to blend diverse skill sets, creating… Continue reading
-
Unlocking Consumer Loan Pricing: A Deep Dive into Survival Regression Algorithms
In the evolving landscape of consumer lending, fintech companies have revolutionized borrower experiences, introducing real-time approvals and swift fund transfers. While tree-based classification models like XGBoost currently dominate credit scoring, survival regression algorithms are an intriguing alternative. (Quick note: These survival algorithms extend beyond consumer credit to products with recurring payments, such as subscriptions or… Continue reading