People have been trying to predict the stock marketsince its inception and financial investors have made it theirprofession. What makes predicting the stock market such ahard task is its seemingly random dependency on everythingfrom Elon Musks tweets to future earnings. Machine learninghandles this apparent randomness with ease and we will try itout by implementing a Hidden Markov Model. We will modeltwo different stocks, Tesla, Inc. and Coca-Cola Company, andtry using the forecasted prices as a template for a simple tradingalgorithm. We used an approach of calculating the log-likelihoodof preceding observations and correlated it with the log-likelihoodof all the preceding subsequences of equivalent size by turningthe time window by one day...
The prediction and understanding of market fluctuations are of great interest in today’s society. A ...
The main focus of this research is the enhancement of the Hidden Markov Model by using some features...
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. T...
People have been trying to predict the stock marketsince its inception and financial investors have ...
Stock market prediction is, when successful, a means of generating large amount of wealth. It remain...
Introduction – All actors in the financial market strive towards earning risk-adjusted excess return...
Future stock prices depend on many internal and external factors that are not easy to evaluate. In t...
This paper presents Hidden Markov Models (HMM) approach for forecasting stock price for interrelated...
Bakalaura darba pētāmā problēma ir slēpto Markova modeļu pielietojums akciju tirgus cenu prognozēšan...
Stock market forecasting is one of the most challenging problems in today’s financial markets. Accor...
Over the last decades, financial markets have undergone dramatic changes. With the advent of the arb...
This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models...
Around the world, the Hidden Markov Models (HMM) are the most popular methods in the machine learnin...
In this master's thesis, hidden Markov models (HMM) are evaluated as a tool for forecasting movement...
Algorithmic trading has increased in popularity since the publication of Agent-Human Interactions in...
The prediction and understanding of market fluctuations are of great interest in today’s society. A ...
The main focus of this research is the enhancement of the Hidden Markov Model by using some features...
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. T...
People have been trying to predict the stock marketsince its inception and financial investors have ...
Stock market prediction is, when successful, a means of generating large amount of wealth. It remain...
Introduction – All actors in the financial market strive towards earning risk-adjusted excess return...
Future stock prices depend on many internal and external factors that are not easy to evaluate. In t...
This paper presents Hidden Markov Models (HMM) approach for forecasting stock price for interrelated...
Bakalaura darba pētāmā problēma ir slēpto Markova modeļu pielietojums akciju tirgus cenu prognozēšan...
Stock market forecasting is one of the most challenging problems in today’s financial markets. Accor...
Over the last decades, financial markets have undergone dramatic changes. With the advent of the arb...
This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models...
Around the world, the Hidden Markov Models (HMM) are the most popular methods in the machine learnin...
In this master's thesis, hidden Markov models (HMM) are evaluated as a tool for forecasting movement...
Algorithmic trading has increased in popularity since the publication of Agent-Human Interactions in...
The prediction and understanding of market fluctuations are of great interest in today’s society. A ...
The main focus of this research is the enhancement of the Hidden Markov Model by using some features...
The hidden Markov model (HMM) is typically used to predict the hidden regimes of observation data. T...