Sökning: "Index optioner"

Visar resultat 1 - 5 av 13 uppsatser innehållade orden Index optioner.

1. 1. Dispersion Trading: A Way to Hedge Vega Risk in Index Options

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Albin Irell Fridlund; Johanna Heberlein; [2023]
   Nyckelord :Dispersion Trading; Volatility Trading; Volatility Hedging; Vega Hedging; Option Trading; Back-testing; Liquidity provider; OMXS30 options; Index options; Spridningshandel; Volitilitetshandel; Volitilitetssäkring; Vega säkring; Optionshandel; Back-testing; Likviditetgivare; OMXS30 optioner; Index optioner;

   Sammanfattning : Since the introduction of derivatives to the financial markets, volatility trading has emerged as a method for investors to make money in every market condition. In parallel with introducing derivatives to the financial markets, hedging methods have emerged and are today essential instruments for the liquidity providers active in the markets. LÄS MER

3. 2. Predicting the Options Expiration Effect Using Machine Learning Models Trained With Gamma Exposure Data

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Sammanfattning : 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. LÄS MER

4. 3. Volatility Forecasting using GARCH Processes with Exogenous Variables

   Master-uppsats, KTH/Matematisk statistik

   Författare :Ellis Larson; [2022]
   Nyckelord :Stochastic process; GARCH model; Volatility; Exogenous variables; Evaluation metrics.; GARCH; Volatilitet; Exogena variabler; Evalueringsmetriker.;

   Sammanfattning : Volatility is a measure of the risk of an investment and plays an essential role in several areas of finance, including portfolio management and pricing of options. In this thesis, we have implemented and evaluated several so-called GARCH models for volatility prediction based on historical price series. LÄS MER

5. 4. Option strategies using hybrid Support Vector Regression - ARIMA

   Master-uppsats, KTH/Matematisk statistik

   Författare :Negin Nayeri; [2020]
   Nyckelord :;

   Sammanfattning : In this thesis, the use of machine learning in option strategies is evaluated with focus on the S&P 500 Index. The first part of the thesis focuses on testing the performance power of the Support Vector Regression (SVR) method for the historical realized volatility with a window of 20 days. LÄS MER

7. 5. Option pricing models: A comparison between models with constant and stochastic volatilities as well as discontinuity jumps

   Kandidat-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Carl Paulin; Maja Lindström; [2020]
   Nyckelord :Financial mathematics; option pricing; calibration; options; parameter calibration; Black Scholes Merton model; Heston model; Bates model; Merton jump diffusion model; Black Scholes;

   Sammanfattning : The purpose of this thesis is to compare option pricing models. We have investigated the constant volatility models Black-Scholes-Merton (BSM) and Merton’s Jump Diffusion (MJD) as well as the stochastic volatility models Heston and Bates. LÄS MER