## Quant And Machine Learning Portfolio Construction: Mimicking An Asset Price Series With Nearest Neighbors – Part 3

We present a combination of the ideas from Quant And Machine Learning Portfolio Construction: Mimicking An Asset Price Series With Nearest Neighbors and Quant And Machine Learning Portfolio Construction: Mimicking An Asset Price Series With Nearest Neighbors – Part 2...

## Quant And Machine Learning Links: 20230903

Quantocracy: This is a curated mashup of quantitative trading links. Review of Parameter Tuning Methods for Nature-Inspired Algorithms - Geethu Joy, Christian Huyck, Xin-She Yang Almost all optimization algorithms have algorithm-dependent parameters, and the setting...

## Quant And Machine Learning Links: 20230827

Quantocracy: This is a curated mashup of quantitative trading links. AutoAlpha: an Efficient Hierarchical Evolutionary Algorithm for Mining Alpha Factors in Quantitative Investment - Tianping Zhang, Yuanqi Li, Yifei Jin, Jian Li The multi-factor model is a widely used...

## Quant And Machine Learning Portfolio Construction: Random Weights, K-Means, Fixed Portfolio, KNN Projections

We combine ideas from: Quant And Machine Learning Portfolio Construction: KNN Projections Using Futures Calibration Data Quant And Machine Learning Portfolio Construction: Random Weights, K-Means, Fixed Portfolio to explore weights for the following portfolio. [table...

## Quant And Machine Learning Portfolio Construction: KNN Projections Using Futures Calibration Data

Introduction The idea behind projections is to take current data, match it with some previous data using some algorithm, then, as outcomes are known for previous data, we can use such information for statistical future projections of current data. Such analysis is...

## Quant And Machine Learning Links: 20230820

Quantocracy: This is a curated mashup of quantitative trading links. Portfolio Selection via Topological Data Analysis - Petr Sokerin, Kristian Kuznetsov, Elizaveta Makhneva, Alexey Zaytsev Portfolio management is an essential part of investment decision-making....

## Quant And Machine Learning Portfolio Construction: Mimicking An Asset Price Series With Nearest Neighbors – Part 2

In Quant And Machine Learning Portfolio Construction: Mimicking An Asset Price Series With Nearest Neighbors, we created a portfolio by computing nearest neighbors to an asset time series and deriving weights from distances to that time series. The method we employ...

## Quant And Machine Learning Links: 20230813

Quantocracy: This is a curated mashup of quantitative trading links. AutoGluon-TimeSeries: AutoML for Probabilistic Time Series Forecasting - Oleksandr Shchur, Caner Turkmen, Nick Erickson, Huibin Shen, Alexander Shirkov, Tony Hu, Yuyang Wang We introduce...

## Quant And Machine Learning Portfolio Construction: Diversification Via Dynamic Time Warping And K-Medoids With Momentum

For who knows what reason, percent price change has been designated "momentum" in financial jargon. Typically, momentum is used to measure trends and is then applied to trend following systems as an entry signal. We do the same here, trading a portfolio of stocks and...

## Quant And Machine Learning Portfolio Construction: Mimicking An Asset Price Series With Nearest Neighbors

We will use a specific example to illustrate how to create a portfolio that mimics the time series of prices of a given asset. Here, we will mimic abrdn Physical Platinum Shares ETF (PPLT) with a stock portfolio for which the weights are proportional to 1/distance....

## Quant And Machine Learning Portfolio Construction: Pairs Trading, Mean Reversion, Slope Weights

We construct a stock portfolio based on the assumption that stocks will revert to a given index represented by an ETF. In the example here, we use the entire stock market and VTI, the total stock market ETF. Slopes of zsore prices are the measure of deviation from VTI...

## Quant And Machine Learning Links: 20230806

Quantocracy: This is a curated mashup of quantitative trading links. Portfolio Management: A Deep Distributional RL Approach - David Pacheco Aznar This thesis presents the development and implementation of a novel Deep Distributional Reinforcement Learning (DDRL)...

## Quant And Machine Learning Links: 20230730

Quantocracy: This is a curated mashup of quantitative trading links. Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling - Masanori Hirano, Kentaro Minami, Kentaro Imajo Deep hedging is a deep-learning-based framework for derivative...

## K-Medoids Clusters With Dynamic Time Warping Distances Have Been Added To Daily Asset Analysis

Using the Dynamic Time Warping computation as explained in Dynamic Time Warping Nearest Neighbors, we construct distance matrices which are the input data for K-Medoids clustering: The k-medoids problem is a clustering problem similar to k-means. The name was coined...

## Quant And Machine Learning Portfolio Construction: Random Weights, K-Means, Fixed Portfolio

This is the first in what will be a series of articles exploring how to use quantitative and machine learning methods to construct portfolios. By construction, we mean some combination of selecting assets and determining weights. We describe a method of taking a fixed...

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