EXAMINATION ON THE RELATIONSHIP BETWEEN VHSI, HSI AND FUTURE REALIZED VOLATILITY WITH KALMAN FILTER

2013 ◽  
pp. 200-216 ◽  
Author(s):  
Yanhui Chen ◽  
Kin Keung Lai
Keyword(s):  
Kalman Filter ◽  
Realized Volatility ◽  
The Relationship ◽  
Future Realized Volatility

Investor sentiment, realized volatility and stock returns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wafa Abdelmalek
Keyword(s):  
Stock Returns ◽  
Investor Sentiment ◽  
Realized Volatility ◽  
Causality Test ◽  
Content Type ◽  
Volatility Index ◽  
Negative Sentiment ◽  
Work Supports ◽  
The Relationship ◽  
Future Realized Volatility

PurposeThis paper examines the relationship between volatility, sentiment and returns in terms of levels and changes for both lower and higher data frequencies using quantile regression (QR) method.Design/methodology/approachIn the first step, the study applies the Granger causality test to understand the causal relationship between realized volatility, returns and sentiment as levels and changes. In the second step, the study employs a QR method to investigate whether investor sentiment and returns can predict realized volatility. This regression method gives robust results irrespective of distributional assumptions and to outliers in the dependent variable.FindingsEmpirical results show that the VIX volatility index is a better fear gauge of market-wide investors' sentiments and has a predictive power for future realized volatility in terms of levels and changes for both higher and lower data frequencies. This study provides evidence that the relationship between realized volatility, investor sentiment and returns, respectively, is not symmetric for all quantiles of QR, as opposed to OLS regression. Furthermore, this work supports the behavioral theory beyond leverage hypothesis in explaining the asymmetric relation between returns and volatility at higher and lower data frequencies.Originality/valueThis paper adds to the limited understanding of investor sentiment’s impact on volatility by proposing a QR model which provides a more complete picture of the relationship at all parts of the volatility distribution for both higher and lower data frequencies and in terms of levels and changes. To the author knowledge, this is the first paper to study the volatility responses to positive and negative sentiment changes for developed market and to use both lower and higher data frequencies as well as data in terms of levels and changes.

scholarly journals Predictability of OTC Option Volatility for Future Stock Volatility

2020 ◽  
Vol 12 (12) ◽  
pp. 5200
Author(s):  
Jungmu Kim ◽  
Yuen Jung Park
Keyword(s):  
Information Content ◽  
Unbiased Estimator ◽  
Implied Volatility ◽  
Realized Volatility ◽  
Stock Index ◽  
Options Market ◽  
Over The Counter ◽  
Index Options ◽  
Stock Volatility ◽  
Future Realized Volatility

This study explores the information content of the implied volatility inferred from stock index options in the over-the-counter (OTC) market, which has rarely been studied in the literature. Using OTC calls, puts, and straddles on the KOSPI 200 index, we find that implied volatility generally outperforms historical volatility in predicting future realized volatility, although it is not an unbiased estimator. The results are more apparent for options with shorter maturity. However, while implied volatility has strong predictability during normal periods, historical volatility is superior to implied volatility during a period of crisis due to the liquidity contraction of the OTC options market. This finding suggests that the OTC options market can play a role in conveying important information to predict future volatility.

scholarly journals The Relationship between Credit Volume and Current Account Deficit: A Dynamic Analysis for Turkey

2017 ◽  
Vol 2 (1) ◽  
pp. 31
Author(s):  
Pinar Karahan ◽  
Nilgun Caglarirmak Uslu
Keyword(s):  
Kalman Filter ◽  
Financial Crisis ◽  
Current Account ◽  
Global Financial Crisis ◽  
Current Account Deficit ◽  
Filter Method ◽  
Kalman Filter Method ◽  
The Global Financial Crisis ◽  
Bound Test ◽  
The Relationship

One of Turkey’s most important macroeconomic problems is persistent current account deficit. Credit volume has been shown as one of the basic determinants of current account rate, especially after the global financial crisis in Turkish economy. The Central Bank of Turkey has begun to implement the policy to ensure financial stability by slowing down credit volume in response to current account deficit affected by rapid credit expansion after the global financial crisis of 2008. In this study, we investigated the relationship between credit volume and current account deficit covering the period of 2005:Q1- 2015:Q3 employing Bound test approach, ARDL model and Kalman filter method. Bound test results suggest the existence of co-integration relationship between current account deficit and credit volume.  ARDL model results indicate that the credit volume is statistical significant and positively affects current account deficit in the short and long run. The results show that a 1 % increase in credit volume leads to nearly a 0.62 % increase in current account deficit. Kalman Filter method results indicate that the effect of credit volume on current account deficit increased after global financial crisis and started to decrease after 2013. 

scholarly journals Apreçamento de Ativos Referenciados em Volatilidade

2006 ◽  
Vol 4 (2) ◽  
pp. 203
Author(s):  
Alan De Genaro Dario
Keyword(s):  
Stochastic Volatility ◽  
Foreign Currency ◽  
Asset Price ◽  
Realized Volatility ◽  
Contingent Claims ◽  
Stochastic Volatility Model ◽  
Currency Options ◽  
Variance Swaps ◽  
Volatility Model ◽  
Future Realized Volatility

Volatility swaps are contingent claims on future realized volatility. Variance swaps are similar instruments on future realized variance, the square of future realized volatility. Unlike a plain vanilla option, whose volatility exposure is contaminated by its asset price dependence, volatility and variance swaps provide a pure exposure to volatility alone. This article discusses the risk-neutral valuation of volatility and variance swaps based on the framework outlined in the Heston (1993) stochastic volatility model. Additionally, the Heston (1993) model is calibrated for foreign currency options traded at BMF and its parameters are used to price swaps on volatility and variance of the BRL / USD exchange rate.

scholarly journals Trajectory Prediction of Three Dimensional Forming Tube Based On Kalman Filter

2021 ◽  
Author(s):  
Jianjun Wu ◽  
Liang Bo ◽  
Junzhou Yang
Keyword(s):  
Kalman Filter ◽  
Spline Interpolation ◽  
Three Dimensional ◽  
Processing Parameters ◽  
Trajectory Prediction ◽  
Forming Process ◽  
Variable Curvature ◽  
Relevant Calculation ◽  
The Relationship ◽  
Initial Process

Abstract This article focuses on the prediction of forming trajectory and process optimization during the forming process for the variable curvature tubes. Firstly, through cubic B-spline interpolation, the geometric characteristics of the axis of the target tube are obtained. An overall tube is "separated and then integrated", and the relationship between geometric parameters and processing parameters is established to obtain the initial process parameters. Based on the Extended Kalman Filter (EKF) algorithm, the motion model and observation model of tube forming using simulation are presented section by section, and the relevant calculation and analysis are carried out. The forming trajectory has been predicted and the processing parameters are optimized during the processing process, in which the effectiveness of the processing optimum scheme is illustrated.

scholarly journals Realized Measures to Explain Volatility Changes over Time

2020 ◽  
Vol 13 (6) ◽  
pp. 125
Author(s):  
Christos Floros ◽  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Athanasios Tsagkanos
Keyword(s):  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Leverage Effect ◽  
Frequency Data ◽  
Specific Group ◽  
Volatility Feedback ◽  
Changes Over Time ◽  
The Relationship ◽  
Over Time

We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain volatility changes over time for both the S&P500 and FTSE100 indices. The period of analysis spanned from January 2000 to June 2017 incorporating various market phases, such as booms and crashes. Based on the estimated regressions, we found evidence that the returns of S&P500 and FTSE100 indices were well explained by a specific group of realized measure estimators, and the returns negatively affected realized volatility. These results are highly recommended to financial analysts dealing with high frequency data and volatility modelling.

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