Technical Indicators and LSTM Prediction for Stock Prices

Download

Term Project of Aslihan Akar.pdf

Date

2021-8

Author

Akar, Aslıhan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

574
views

1039
downloads

In this report, we study, first, Tesla Motors’ stock price prediction in a traditional way using technical indicators like Moving Average, Relative Strength Index, Parabolic SAR, Commodity Channel Index, Stochastic Oscillator, and Awesome Oscillator in the first part. Having analyzed Tesla Motors’ stock price with traditional technical indicators, we use long short term memory model for prediction. In long short term memory model, closing prices of Tesla Motors stock are used for the last two years. The model can predict the trend successfully. The technical indicators can provide context to trends, be used to identify divergences, and even help with the timing of potential entry and exit signals. But using just one of the technical indicators is generally considered a risky decision because one must be aware of announcements and headlines that play a crucial role in determining the stock price.

Subject Keywords

Technical Indicators, Long Short Term Memory, Stock price prediction

URI

https://hdl.handle.net/11511/91531

Collections

Graduate School of Applied Mathematics, Term Project

Suggestions

OpenMETU
Core

Stochastic volatility and stochastic interest rate model with jump and its application on General Electric data Celep, Betül; Hayfavi, Azize; Department of Financial Mathematics (2011) In this thesis, we present two different approaches for the stochastic volatility and stochastic interest rate model with jump and analyze the performance of four alternative models. In the first approach, suggested by Scott, the closed form solution for prices on European call stock options are developed by deriving characteristic functions with the help of martingale methods. Here, we study the asset price process and give in detail the derivation of the European call option price process. The second appr...
Volatility indexes and an implementation of the Turkish BIST 30 index Karakurt, Caner; Uğur, Ömür; Department of Financial Mathematics (2018) In 1993, by representing of CBOE Vix, global financial markets met volatility indexes. In 2003, methodology of the CBOE Vix is updated and it took the form which used today. Day after day, volatility indexes have attracted more and more investors and financial institutions, and soon volatility indexes have succeeded in becoming one of the most followed financial indicators. Following these developments, many countries have introduced their implied volatility indexes by using CBOE Vix methodology or its vari...
Volatility spillover from world oil spot markets to aggregate and electricity stock index returns in Turkey Soytaş, Uğur; Oran, Adil (2011-01-01) This study examines the inter-temporal links between world oil prices, ISE 100 and ISE electricity index returns unadjusted and adjusted for market effects. The traditional approaches could not detect a causal relationship running from oil returns to any of the stock returns. However, when we examine the causality using Cheung-Ng approach we discover that world oil prices Granger cause electricity index and adjusted electricity index returns in variance, but not the aggregate market index returns. Hence, ou...
Hydro Inflow Forecasting and Virtual Power Plant Pricing in the Turkish Electricity market Çabuk, Sezer; Kestel, Sevtap Ayşe; Kalaycı, Erkan (2019-05-23) Hydro inflow forecasting with most accurate quantitative models is a very crucial subject for effective hydro optimization, virtual power plant pricing, volume risk management and weather derivatives pricing in the Turkish electricity market. Predicting increase or decrease in hydro inflow, seasonal characteristics of hydrological years such as wet, dry or normal, allow the decision-makers to economically use water for optimal periods, quantify of volume risk and determine effective portfolio management str...
Advances in optimal control of markov regime-switching models with applications in finance and economics Savku, Emel; Weber, Gerhard Wilhelm; Department of Financial Mathematics (2017) We study stochastic optimal control problems of finance and economics in a Markov regime-switching jump-diffusion market with and without delay component in the dynamics of our model. We formulate portfolio optimization problems as a two player zero-sum and a two player nonzero-sum stochastic differential games. We provide an extension of Dynkin formula to present the Hamilton-Jacobi-Bellman-Isaacs equations in such a more general setting. We illustrate our results for a nonzero-sum stochastic differential ...

Citation Formats

A. Akar, “Technical Indicators and LSTM Prediction for Stock Prices,” M.S. - Master Of Science Without Thesis, Middle East Technical University, 2021.