Why Exchange Clocks Matter In high frequency trading (HFT), time is literally money. An edge of a few microseconds could translate to millions in profits. The most popular markets for cash products (equity, bonds, etc.) are in New York (NYSE, Nasdaq), while the most popular futures and options market is in Chicago (CME). Since cash and futures influence each other, getting data between New York and Chicago as fast as possible is important....
The Question I, like many others, started learning to play piano when I was around 8 years old. I took lessons, learned songs, and gained an appreciation for the instrument. I have been playing (with some breaks) until today. Although I have been playing for a while, it wasn’t until taking my first music theory class in college that I started thinking deeply about why music is constructed in the way it is....
Introduction I spent the summer of 2019 as a physics research intern at the Stanford University Solar Lab. I was very fortunate to have a wonderful advisor and had a great summer overall. I created machine learning models to characterize time series data for solar flare prediction. In this article, I will first provide some physics background about solar flares, then dive into my research. For a more in-depth analysis, check out the source code and my poster....
Recently, I wondered if I could create a random number generator using the digits of pi. Disclaimer: this article’s purpose is not to create a computationally efficient random number generator; it is just a fun proof of concept. In order to create a random number generator with pi, we must first verify that the digits of pi are randomly distributed. This can be accomplished in a few lines of python code....
Introduction This project done for my CS221 class aims to classify classical music by musical era (Baroque, Classical, Romantic, Modern) with composers as a proxy. Using audio processing techniques, such as Short-time Fourier Transform, we extracted features such as the spectrogram and chromagram of the audio data from two datasets, Free Music Archive and MAESTRO. We used two ensemble classifiers, AdaBoost and Random Forest, and found that although Adaboost performed marginally better than Random Forest, the latter made more generalizable predictions....
Introduction I recently became interested in neural networks and sought interesting applications of what they could do. Neural networks are based on how the human brain works; the networks are made up of many nodes that take inputs and predict outputs. Over time, with more data, the networks improve by correcting for error, known as backpropagation. Neural networks become especially useful when there are many “layers” between the input and output that allow for more fine-tuned fitting of data....
This project done for my CS106X class mixes two given mp3 files together and has a visualization to go with it. Introduction I have always been awestruck by DJing and have had little idea of how it is done. I set out to create a python script to mix songs to understand the process a bit better. I first found that DJs use many effects in their mixes. These effects include changing tempo of songs, changing the pitch, as well as adding noises from other tracks....