Budgie Bytes & Bucks

Budgie Bytes & Bucks

Treasury Yields and the Fed: What Lower Rates Mean for Stocks and Industries

Treasury Yields and the Fed: What Lower Rates Mean for Stocks and Industries

When the Federal Reserve tweaks interest rates, the ripple isn’t just in the bond market — entire industries feel the shift. Some sectors tend to thrive when borrowing gets cheaper, while others lag behind. Think of lower rates as fuel: tech companies may sprint ahead, finance might catch a tailwind,

Fractional Differencing for Technical Analysis: Reducing Noise in MACD, ATR, and RSI Signals

Fractional Differencing for Technical Analysis: Reducing Noise in MACD, ATR, and RSI Signals

TL;DR This analysis explores whether fractional differencing can make common trading indicators more predictive. 👉 The purpose is not to prove or disprove the usefulness of MACD, RSI, ROC, Bollinger Bands, or Z-Score, but to test whether these signals can be made more predictive by make it less noisy and

How Markets Really Move Together: Smarter Insights with Fractional Differencing & Variation of Information

How Markets Really Move Together: Smarter Insights with Fractional Differencing & Variation of Information

Markets Move Together — But Not in Straight Lines In finance, we often hear that two markets are “highly correlated.” But what does that really mean? Most people rely on correlation, which assumes that relationships between assets are linear and stationary. That’s a problem—because markets are almost never either.

From Commodities to Currencies: Making Price Data Stationary with Fractional Differencing

From Commodities to Currencies: Making Price Data Stationary with Fractional Differencing

Financial prices tend to wander—they drift, trend, and shift in unpredictability. Statisticians call this non-stationarity—when a series doesn’t hold a stable mean and variance. A common remedy is full differencing (subtracting today’s price from yesterday’s), but that uses a whole “1” simply because it’s

Philippine Egg Price history

To track real-time retail prices of medium eggs in the Philippines, a data pipeline ingests daily listings from major online grocery retailers (e.g., SM Supermarket and Waltermart). Because stock-keeping units (SKUs) often bundle eggs in different counts (e.g., 6s, 10s, 12s, 30s), all prices are normalized to a

Forecasting EUR/USD with Interest Rate Gaps: What the Germany–US Spread Tells Us

Forecasting EUR/USD with Interest Rate Gaps: What the Germany–US Spread Tells Us

TL;DR — Can Interest Rate Gaps Help Predict EUR/USD? This study investigates whether German–U.S. interest rate differentials and related macro features can forecast EUR/USD moves using trend scanning, a supervised labeling method from Marcos López de Prado. The dataset includes simulations across multiple forecast windows and

Philippine Rice Price history

Methodology To track the real-time retail prices of rice in the Philippines, a data pipeline was implemented that extracts daily price information from major online grocery retailers such as SM Supermarket and Waltermart. The primary focus of this monitoring system is on two of the most widely consumed rice varieties

Budgie Testicular Tumor

Budgie Testicular Tumor

I wanted to share my experience with my budgie, Baden-Baden, and his testicular tumor because I found it incredibly difficult at the time to find clear, relevant information. Most of what I came across came from Facebook or Reddit posts—helpful, but often lacking specific details about what to expect.

Can COT Data Predict the EUR/USD? A Data-Driven FAQ on Positioning, Reversals, and Trading Models

Can COT Data Predict the EUR/USD? A Data-Driven FAQ on Positioning, Reversals, and Trading Models

The Commitments of Traders (COT) report, published every Friday by the U.S. Commodity Futures Trading Commission (CFTC), provides a breakdown of open interest in futures markets by trader type — including dealers, asset managers, leveraged money, and other reportables. For the EUR/USD currency pair, this report offers a valuable

Clustering Large Datasets

Data Techniques

Clustering Large Datasets

Clustering large datasets is often computationally expensive because many algorithms require computing pairwise distances or similarities between samples—a process that grows quadratically with the number of data points. This poses a significant challenge in high-dimensional datasets such as those in finance, where instruments and time series are numerous. One

Average Cash Flow to Debt Ratio by Industry

Average Cash Flow to Debt Ratio by Industry

Table Summary: Industry 2019 2020 2021 2022 2023 Energy/Transport 0.29 0.12 0.37 0.60 0.55 Finance 0.38 0.22 0.61 0.75 0.46 Industrial 0.45 0.63 0.75 0.56 0.62 LifeSci 0.79 0.93 1.58 1.

Budgie Sounds and Meanings: Analyzing Call Type Similarities Through Phoneme Patterns

Budgie Sounds and Meanings: Analyzing Call Type Similarities Through Phoneme Patterns

Budgies are some of the most vocal and socially complex birds. Through various sounds and calls, they express emotions ranging from excitement and affection to stress and urgency. In this analysis, I explore the idea that not only are these calls behaviorally distinct, but their underlying phoneme structures—the basic

Backtesting Financial Time Series Forecasting

Data Techniques

Backtesting Financial Time Series Forecasting

Time series forecasting plays a critical role in decision-making across industries. However, creating a predictive model is not enough — assessing whether the model generalizes to future data is essential. This is where model assessment and backtesting come in. A poorly executed backtest can lead to inflated expectations, poor real-world performance,

Budgie Sounds and Meanings: A Phonemic and Behavioral Analysis

Budgie Sounds and Meanings: A Phonemic and Behavioral Analysis

What if we could decode the language of budgies—not just by observing their body language, but by analyzing the structure of their chirps, calls, and chatter? Inspired by a groundbreaking study published in Nature, which found that budgerigars have brain regions specialized for vocalization that mirror those used for

Inflation Adjusted Capital Expenditures US companies

Inflation Adjusted Capital Expenditures US companies

Over the past decade, capital expenditures (CapEx) across major U.S. industries have revealed critical shifts in corporate strategy, economic resilience, and policy-driven priorities. By examining CapEx relative to operating cash flows (investment rate), we gain insight into how different sectors deploy their financial resources. This blog explores major CapEx

U.S. Public Company Tax Payments and Cash Flow Insights by Industry

U.S. Public Company Tax Payments and Cash Flow Insights by Industry

Companies generate trillions annually in operating cash flow, but how much of that actually translates into federal income tax paid? Using cash-based metrics and EDGAR filings, I’ve aggregated calendar-year estimates of both cash flow and taxes paid by industry. Here’s what the data reveals. This visualization presents a

Wilshire 5000 Companies Net Income

Wilshire 5000 Companies Net Income

In The Little Book of Common Sense Investing, John Bogle posits that the overall return on stocks is intrinsically linked to the revenue generated by the underlying companies. This notion aligns with the fundamental principle that owning a stock signifies a partial ownership stake in a business. Nevertheless, market pricing

Germany 10 Year Bund Yield – Constant Maturity

Methodology: Estimating the German 10-Year Nominal Yield (Constant Maturity) This analysis presents a time series of the German 10-Year Nominal Government Bond Yield, standardized to a constant maturity of 10 years. The objective is to estimate the market yield of a 10-year German Bund using observed bond pricing data and

German 10 Year Real Yield (Inflation-Linked Bund, Constant Maturity)

Methodology: Estimating the German 10-Year Real Yield (Inflation-Linked Bund, Constant Maturity) This analysis generates a time series for the German 10-Year Real Yield, which represents the market-based return on German inflation-linked government bonds (Bunds) over a fixed 10-year period. The goal is to approximate the real yield curve by normalizing

German 10 Year Breakeven Inflation

Methodology: Estimating the German 10-Year Breakeven Inflation Rate This analysis presents a derived time series for the German 10-year breakeven inflation rate, calculated by approximating the market’s implied inflation expectations using publicly available bond pricing and macroeconomic data. Objective The goal is to estimate the breakeven inflation rate by

Interest Rate Differential EUR USD: A Key Driver of EUR/USD Trends

Interest Rate Differential EUR USD: A Key Driver of EUR/USD Trends

The EUR/USD currency pair is the most actively traded in the global foreign exchange (FX) market. Here’s an overview of its market size and trading volume. In April 2022, the average daily trading volume in the global spot FX market reached $2.11 trillion. Reflecting the US dollar’

Loss Function for Time Series Prediction

Data Techniques

Loss Function for Time Series Prediction

Loss functions play a crucial role in determining the performance of time series regression models in real-world scenarios. In any machine learning task, there’s always a trade-off between over- and under-prediction. The choice of loss function determines whether the model will symmetrically or asymmetrically penalize it for either under-

Interest Rate Sensitive Stocks

Interest Rate Sensitive Stocks

Interest rates are a fundamental driver of economic activity, influencing everything from consumer spending to corporate investment. In the stock market, changes in interest rates can ripple through various sectors, altering profit margins, affecting debt costs, and shaping investor sentiment. While the effects of these changes are not always immediate

Time Series Data Labeling

Data Techniques

Time Series Data Labeling

There are several types of machine learning, and one of the most commonly used today is supervised learning. In this category, machine learning models are trained using labeled datasets. The objective of the model is to learn to map the input data to the corresponding labels. Price series are sequences

Fractional Difference Time Series

Data Techniques

Fractional Difference Time Series

Price information is a very common metric that investors use to make financial decisions. This is no wonder as price information signals to the investing world how buyers and sellers are reacting to certain information about an asset class. A whole host of techniques, more commonly known as technical analysis,