Essays about: "Random Portfolios"

Showing result 1 - 5 of 31 essays containing the words Random Portfolios.

  1. 1. CROSS-SECTIONAL AND TIME SERIES MOMENTUM RETURNS EVIDENCE FROM THE SWEDISH STOCK MARKET

    University essay from KTH/Matematisk statistik

    Author : Mahsa Badakhsh; [2023]
    Keywords : cross-sectional momentum; time-series momentum; market efficiency; random walk; ex-ante volatility; cross-sectional momentum; time-series momentum; marknadseffektivitet; random walk; ex-ante volatilitet;

    Abstract : The study investigates the presence of the momentum effect in the Swedish stock market by utilizing both cross-sectional introduced by Jegadeesh and Titman (1993) and time-series momentum introduced by Moskowtozt et al. (2011). The period of analysis is between 1998 to 2022. READ MORE

  3. 2. Portfolio Risk Modelling in Venture Debt

    University essay from KTH/Matematisk statistik

    Author : John Eriksson; Jacob Holmberg; [2023]
    Keywords : Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

    Abstract : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. READ MORE

  4. 3. Applying the Shadow Rating Approach: A Practical Review

    University essay from KTH/Matematik (Avd.)

    Author : Viktor Barry; Carl Stenfelt; [2023]
    Keywords : Shadow Rating; probability of default; low default portfolio; credit risk; statistical learning; financial regulation; Basel; Pluto and Tasche; Skuggrating; sannolikhet av fallissemang; lågfallissemangsportfölj; kreditrisk; statistisk inlärning; finansiella regelverk; Basel; Pluto och Tasche;

    Abstract : The combination of regulatory pressure and rare but impactful defaults together comprise the domain of low default portfolios, which is a central and complex topic that lacks clear industry standards. A novel approach that utilizes external data to create a Shadow Rating model has been proposed by Ulrich Erlenmaier. READ MORE

  5. 4. An Investigation and Comparison of Machine Learning Methods for Selecting Stressed Value-at-Risk Scenarios

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Moa Tennberg; [2023]
    Keywords : Value-at-Risk; Total margin; Procyclicality; Machine learning; Binary classification; Supervised learning; Unsupervised learning; Random forest; Multilayer perceptron;

    Abstract : Stressed Value-at-Risk (VaR) is a statistic used to measure an entity's exposure to market risk by evaluating possible extreme portfolio losses. Stressed VaR scenarios can be used as a metric to describe the state of the financial market and can be used to detect and counter procyclicality by allowing central clearing counterparities (CCP) to increase margin requirements. READ MORE

  6. 5. Predicting the Options Expiration Effect Using Machine Learning Models Trained With Gamma Exposure Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Alexander Dubois; [2022]
    Keywords : AdaBoost; LSTM; Machine learning; Random forests; Stock markets; SVM;

    Abstract : The option expiration effect is a well-studied phenome, however, few studies have implemented machine learning models to predict the effect on the underlying stock market due to options expiration. In this paper four machine learning models, SVM, random forest, AdaBoost, and LSTM, are evaluated on their ability to predict whether the underlying index rises or not on the day of option expiration. READ MORE