Financial Time Series Analysis

Time Series Analysis and its applications have become increasingly important in various fields of research, such as business, Finance, economics, engineering, medicine, environometrics, social sciences, politics, and others. Time series analysis have applications like it can be useful to see how a given asset, security or economic variable changes over time. It can also be used to examine how the changes associated with the chosen data point compare to shifts in other variables over the same time period.

Finance Asssignment Experts has the experts who are always ready with a helping hand. We have managed to help students with Financial Time Series Analysis Assignments, and desire more to help each and every student of this field. We also take deep consideration for all those who seek Financial Time Series Analysis problem solution and offer them best kind of Financial Time Series Analysis project help in the following topics:

  • Analysis of Time Series with Calendar Effects 
  • Analysis and application of univariate financial time series
  • ARIMA Modeling Using Expert Systems 
  • Arithmetic and geometric returns
  • Autocorrelation function
  • Autoregressive Integrated Moving Average Models
  • Bayesian inference in finance methods
  • Conditional Heteroscedastic Models
    • Kurtosis of GARCH Models
    • Long-Memory Stochastic Volatility Model
    • Random Coefficient Autoregressive Models
    • Stochastic Volatility Model
    • The CHARMA Model
    • The Integrated, Exponential & Threshold GARCH Model
    • The ARCH Model
    • The GARCH Model
  • Continuous-Time Models and Their Applications
    • Black–Scholes Pricing Formulas
    • Continuous-Time Stochastic Processes
    • Derivation of Black–Scholes Differential Equation
    • Distributions of Stock Prices and Log Returns
    • Estimation of Continuous-Time Models
    • Extension of Ito's Lemma
    • Jump Diffusion Models
    • Stochastic Integral
  • Forecasting Using Exponential Smoothing Methods 
  • Intervention Analysis and Outlier Detection  
  • Linear Time Series Analysis and Its Applications
    • Consistent Covariance Matrix Estimation
    • Correlation and Autocorrelation Function
    • Long-Memory Models
    • Regression Models with Time Series Errors
    • Seasonal Models
    • Simple ARMA Models
    • Unit-Root Nonstationarity
    • White Noise and Linear Time Series
  • Marginal and conditional return distribution
  • Multivariate Time Series Analysis and Forecasting Using Simultaneous Transfer Function Models
  • Multivariate Time Series Analysis and Forecasting Using Vector ARMA Models
  • Markov Chain Monte Carlo Methods with Applications
  • Nonlinear Time Series Models
  • Power Transformations and Forecasting
  • Nonlinear Models and Their Applications
  • High-Frequency Data Analysis and Market Microstructure
    • Bivariate Models for Price Change and Duration
    • Empirical Characteristics of Transactions Data
    • Models for Price Changes
    • Nonlinear Duration Models
  • Extreme Values, Quantiles, and Value at Risk
  • Multivariate Time Series Analysis and Its Applications
    • Cointegrated VAR Models
    • Threshold Cointegration and Arbitrage
    • Unit-Root Nonstationarity and Cointegration
    • Vector Autoregressive Models
    • Vector Moving-Average Models
    • Weak Stationarity and Cross-Correlation Matrices
  • Principal Component Analysis and Factor Models
  •  Multivariate Volatility Models and Their Applications
    • Exponentially Weighted Estimate
    • Factor–Volatility Models
    • GARCH Models for Bivariate Returns
    • Higher Dimensional Volatility Models
    • Multivariate t Distribution
  • State-Space Models and Kalman Filter
  • Segmented Time Series Modeling and Forecasting
  • The Constant Conditional Correlation model
  • The Normal Inverse Gaussian (NIG) distribution
  • Time Series Data Mining 
  • Time Series Models with Heteroscedasticity
  • Transfer Function Models
  • The return series of multiple assets