Costa Rica’s economy looks set for a strong recovery

2021 ◽  
Keyword(s):  
United States ◽  
Exchange Rate ◽  
High Frequency ◽  
The United States ◽  
Economic Recovery ◽  
High Frequency Data ◽  
Frequency Data ◽  
Short Term ◽  
Content Type ◽  
Credit Quality

Significance GDP posted growth of 9.4% year-on-year in the second quarter, the highest rate in 23 years. According to high-frequency data, economic recovery appears to have continued between July and September albeit at a slightly slower pace. Impacts Low inflation will allow the Central Bank to maintain an accommodative stance in the short term; any rate hikes next year will be gradual. Banks’ profitability and credit quality may deteriorate in 2022 as loan restructuring measures expire and lagged pandemic effects kick in. The exchange rate may further depreciate amid uncertainty over the country’s fiscal prospects and the outcome of the 2022 elections. While tourism appears to be on a strong trajectory, the spread of Omicron in Europe and the United States could reverse its recovery.

The nonlinear characteristics of Chinese stock index futures yield volatility

2019 ◽  
Vol 10 (2) ◽  
pp. 175-196 ◽  
Author(s):  
Xuebiao Wang ◽  
Xi Wang ◽  
Bo Li ◽  
Zhiqi Bai
Keyword(s):  
High Frequency ◽  
Futures Market ◽  
Stock Index ◽  
High Frequency Data ◽  
Stock Index Futures ◽  
Frequency Data ◽  
Short Term ◽  
Content Type ◽  
Index Futures ◽  
Basic Characteristics

Purpose The purpose of this paper is to consider that the model of volatility characteristics is more reasonable and the description of volatility is more explanatory. Design/methodology/approach This paper analyzes the basic characteristics of market yield volatility based on the five-minute trading data of the Chinese CSI300 stock index futures from 2012 to 2017 by Hurst index and GPH test, A-J and J-O Jumping test and Realized-EGARCH model, respectively. The results show that the yield fluctuation rate of CSI300 stock index futures market has obvious non-linear characteristics including long memory, jumpy and asymmetry. Findings This paper finds that the LHAR-RV-CJ model has a better prediction effect on the volatility of CSI300 stock index futures. The research shows that CSI300 stock index futures market is heterogeneous, means that long-term investors are focused on long-term market fluctuations rather than short-term fluctuations; the influence of the short-term jumping component on the market volatility is limited, and the long jump has a greater negative influence on market fluctuation; the negative impact of long-period yield is limited to short-term market fluctuation, while, with the period extending, the negative influence of long-period impact is gradually increased. Research limitations/implications This paper has research limitations in variable measurement and data selection. Practical implications This study is based on the high-frequency data or the application number of financial modeling analysis, especially in the study of asset price volatility. It makes full use of all kinds of information contained in high-frequency data, compared to low-frequency data such as day, weekly or monthly data. High-frequency data can be more accurate, better guide financial asset pricing and risk management, and result in effective configuration. Originality/value The existing research on the futures market volatility of high frequency data, mainly focus on single feature analysis, and the comprehensive comparative analysis on the volatility characteristics of study is less, at the same time in setting up the model for the forecast of volatility, based on the model research on the basic characteristics is less, so the construction of a model is relatively subjective, in this paper, considering the fluctuation characteristics of the model is more reasonable, characterization of volatility will also be more explanatory power. The difference between this paper and the existing literature lies in that this paper establishes a prediction model based on the basic characteristics of market return volatility, and conducts a description and prediction study on volatility.

Forecasting Exchange Rate Realized Volatility Through Decomposition Using High-Frequency Data

2017 ◽  
Author(s):  
Rim mname Lamouchi ◽  
Russell mname Davidson ◽  
Ibrahim mname Fatnassi ◽  
Abderazak Ben mname Maatoug
Keyword(s):  
Exchange Rate ◽  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Frequency Data

The dependence structure in volatility between Shanghai and Shenzhen stock market in China

2016 ◽  
Vol 6 (3) ◽  
pp. 264-283 ◽  
Author(s):  
Mingyuan Guo ◽  
Xu Wang
Keyword(s):  
Stock Market ◽  
High Frequency ◽  
Estimation Method ◽  
Garch Model ◽  
Price Volatility ◽  
Market Volatility ◽  
High Frequency Data ◽  
Dependence Structure ◽  
Frequency Data ◽  
Content Type

Purpose – The purpose of this paper is to analyse the dependence structure in volatility between Shanghai and Shenzhen stock market in China based on high-frequency data. Design/methodology/approach – Using a multiplicative error model (hereinafter MEM) to describe the margins in volatility of China’s Shanghai and Shenzhen stock market, this study adopts static and time-varying copulas, respectively, estimated by maximum likelihood estimation method to describe the dependence structure in volatility between Shanghai and Shenzhen stock market in China. Findings – This paper has identified the asymmetrical dependence structure in financial market volatility more precisely. Gumbel copula could best fit the empirical distribution as it can capture the relatively high dependence degree in the upper tail part corresponding to the period of volatile price fluctuation in both static and dynamic view. Originality/value – Previous scholars mostly use GARCH model to describe the margins for price volatility. As MEM can efficiently characterize the volatility estimators, this paper uses MEM to model the margins for the market volatility directly based on high-frequency data, and proposes a proper distribution for the innovation in the marginal models. Then we could use copula-MEM other than copula-GARCH model to study on the dependence structure in volatility between Shanghai and Shenzhen stock market in China from a microstructural perspective.

Block trading, information asymmetry, and the informativeness of trading

2015 ◽  
Vol 5 (3) ◽  
pp. 215-235 ◽  
Author(s):  
Ningning Pan ◽  
Hongquan Zhu
Keyword(s):  
Information Asymmetry ◽  
High Frequency ◽  
Stock Return ◽  
High Frequency Data ◽  
Individual Investors ◽  
Specific Information ◽  
Frequency Data ◽  
Information Effect ◽  
Content Type ◽  
Two Measures

Purpose – The purpose of this paper is to investigate how block trading and asymmetric information contribute to the firm-specific information measured by the stock return synchronicity. Based on China stock market which is dominated by individual investors, this study focus on whether traders of block trading, which are usually institutional investors, are “information trader.” Design/methodology/approach – Based on the high frequency data, the paper constructs two measures of information asymmetry, intraday measure and inter-day measure. Then the paper constructs a multiple regression model and examine how block trading and information asymmetry contribute to the firm-specific information measured by the stock return synchronicity. Findings – The results show that: on the one hand, block trading transmits more firm-specific information, and can reduce the synchronicity; on the other hand, when the degree of information asymmetry is higher, block trading contains more firm-specific information and has a stronger effect on synchronicity. The effect of information asymmetry specifically displays as: block trading during the first half-hour of the trading day has a stronger effect on synchronicity; and block trading occurred in the days with publicly announced trading information has greater impact on synchronicity. Practical implications – The conclusions have important practical implications: for market regulators, monitoring for block trading can improve the recognition and prevention of insider trading; for individual investors, especially the risk aversion investors, recognition of intraday and inter-day information asymmetry is beneficial for them to avoid the risk of asymmetric information. Originality/value – First, the domestic and foreign research mostly concentrated impact of block trading on stock prices. However, reasons of stock price changes include the information effect and non-information effect, this paper selects stock return synchronicity as firm-specific information measure, and mainly focus on the information effect of block trading. Second, based on the high frequency data, the paper constructs two measures of information asymmetry, intraday measure and inter-day measure. Compared with general measure of information asymmetry, such as firm size, earnings quality, the two measures based on high frequency data are more precisely.

Stock market predictability

2014 ◽  
Vol 31 (4) ◽  
pp. 354-370 ◽  
Author(s):  
Silvio John Camilleri ◽  
Christopher J. Green
Keyword(s):  
Stock Market ◽  
High Frequency ◽  
Serial Correlation ◽  
Design Methodology ◽  
High Frequency Data ◽  
Frequency Data ◽  
Content Type ◽  
Lag Effects ◽  
Daily Data ◽  
Indian Stock Market

Purpose – The main objective of this study is to obtain new empirical evidence on non-synchronous trading effects through modelling the predictability of market indices. Design/methodology/approach – The authors test for lead-lag effects between the Indian Nifty and Nifty Junior indices using Pesaran–Timmermann tests and Granger-Causality. Then, a simple test on overnight returns is proposed to infer whether the observed predictability is mainly attributable to non-synchronous trading or some form of inefficiency. Findings – The evidence suggests that non-synchronous trading is a better explanation for the observed predictability in the Indian Stock Market. Research limitations/implications – The indication that non-synchronous trading effects become more pronounced in high-frequency data suggests that prior studies using daily data may underestimate the impacts of non-synchronicity. Originality/value – The originality of the paper rests on various important contributions: overnight returns is looked at to infer whether predictability is more attributable to non-synchronous trading or to some form of inefficiency; the impacts of non-synchronicity are investigated in terms of lead-lag effects rather than serial correlation; and high-frequency data is used which gauges the impacts of non-synchronicity during less active parts of the trading day.

Implied volatility smirk and future stock returns: evidence from the German market

2015 ◽  
Vol 41 (12) ◽  
pp. 1357-1379
Author(s):  
Di Mo ◽  
Neda Todorova ◽  
Rakesh Gupta
Keyword(s):  
High Frequency ◽  
Implied Volatility ◽  
Stock Index ◽  
High Frequency Data ◽  
Frequency Data ◽  
European Options ◽  
German Market ◽  
Content Type ◽  
The Relationship ◽  
Option Market

Purpose – The purpose of this paper is to investigate the relationship between option’s implied volatility smirk (IVS) and excess returns in the Germany’s leading stock index Deutscher-Aktien Index (DAX) 30. Design/methodology/approach – The study defines the IVS as the difference in implied volatility derived from out-of-the-money put options and at-the-money call options. This study employs the ordinary least square regression with Newey-West correction to analyse the relationship between IVS and excess DAX 30 index returns in Germany. Findings – The authors find that the German market adjusts information in an efficient way. Consequently, there is no information linkage between option volatility smirk and market index returns over the nine years sample period after considering the control variables, global financial crisis dummies, and the subsample test. Research limitations/implications – This study finds that the option market and the DAX 30 index are informationally efficient. Implications of the findings are that the investors cannot profit from the information contained in the IVS since the information is simultaneously incorporated into option prices and the stock index prices. The findings of this study are applicable to other markets with European options and for market participants who seek to exploit short-term market divergence from efficiency. Originality/value – The relationship between IVS and stock price changes has not been investigated sufficiently in academic literature. This study looks at this relationship in the context of European options using high-frequency transactions data. Prior studies look at this relationship for only American options using daily data. Pricing efficiency of the European option market using high-frequency data have not been studied in the prior literature. The authors find different results for the German market based on this high-frequency data set.

scholarly journals Keynes and the dollar in 1933: the gold-buying program and exchange rate gyrations

2017 ◽  
Vol 24 (3) ◽  
pp. 209-238 ◽  
Author(s):  
Sebastian Edwards
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Gold Standard ◽  
High Frequency ◽  
High Frequency Data ◽  
Frequency Data ◽  
Open Letter ◽  
The Ideal

In December 1933, John Maynard Keyes published an open letter to President Roosevelt, where he wrote: ‘The recent gyrations of the dollar have looked to me more like a gold standard on the booze than the ideal managed currency of my dreams.’ This was a criticism of the ‘gold-buying program’ launched in October 1933. In this article I use high-frequency data on the dollar–pound and dollar–franc exchange rates to investigate whether the gyrations of the dollar were unusually high in late 1933. My results show that although volatility was pronounced, it was not higher than during some other periods after 1921. Moreover, dollar volatility began to subside towards the end of the period alluded to by Keynes.

Brazil government coalition risks unraveling

2015 ◽  
Keyword(s):  
United States ◽  
The United States ◽  
Short Term ◽  
Content Type ◽  
Political Coalition ◽  
The Future ◽  
Spending Cuts ◽  
Government Coalition ◽  
Economic Outlook

Significance On her return from the United States and Russia, President Dilma Rousseff's problems have not changed; indeed, most worsened during her absence. Brazil's economic outlook is bleaker, the governing political coalition weaker and the scope of the corruption scandal has widened. Impacts Congress will push back more strongly against spending cuts as the government's situation weakens. The PMDB as a whole is unlikely to follow Cunha's lead, at least in the short term. Lula's fate will have major longer-term implications for the future of the PT.

EU global regulatory influence faces rising challenges

2020 ◽  
Keyword(s):  
United States ◽  
The United States ◽  
Economic Recovery ◽  
Political Values ◽  
Content Type ◽  
Recovery Plan ◽  
Democratic Candidate ◽  
Regulatory Influence ◽  
The Eu

Significance However, the economic and geopolitical environment which facilitated its global regulatory success is changing. Impacts The EU’s unprecedented economic recovery plan should strengthen unity and give it confidence to act stronger on the global stage. Political values will play an increasingly prominent role in shaping the bloc’s relationship with countries such as China. The election of Democratic candidate Joe Biden will not guarantee closer regulatory ties between the United States and the EU.

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