scholarly journals Does the high-frequency data is helpful for forecasting Russian inflation?

2021 ◽  
Vol 37 (2) ◽  
pp. 318-343
Author(s):  
Dmitriy Tretyakov ◽  
◽  
Nikita Fokin ◽  
Keyword(s):  
Monetary Policy ◽  
Central Bank ◽  
High Frequency ◽  
Inflation Targeting ◽  
Low Frequency ◽  
High Frequency Data ◽  
Frequency Data ◽  
Policy Regime ◽  
The Future ◽  
Forecasting Inflation

Due to the fact that at the end of 2014 the Central Bank made the transition to a new monetary policy regime for Russia — the inflation targeting regime, the problem of forecasting inflation rates became more relevant than ever. In the new monetary policy regime, it is important for the Bank of Russia to estimate the future inflation rate as quickly as possible in order to take measures to return inflation to the target level. In addition, for effective monetary policy, the households must trust the actions of monetary authorities and they must be aware of the future dynamics of inflation. Thus, to manage inflationary expectations of economic agents, the Central Bank should actively use the information channel, publish accurate forecasts of consumer price growth. The aim of this work is to build a model for nowcasting, as well as short-term forecasting of the rate of Russian inflation using high-frequency data. Using this type of data in models for forecasting is very promising, since this approach allows to use more information about the dynamics of macroeconomic indicators. The paper shows that using MIDAS model with weekly frequency series (RUB/USD exchange rate, the interbank rate MIACR, oil prices) has more accurate forecast of monthly inflation compared to several basic models, which only use low-frequency data.

scholarly journals Portfolio investment and U.S. monetary policy announcements: An event study analysis using high-frequency data from Mexico

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Marco Hernandez-Vega
Keyword(s):  
Monetary Policy ◽  
High Frequency ◽  
Balance Of Payments ◽  
Bad News ◽  
High Frequency Data ◽  
Special Focus ◽  
Portfolio Investment ◽  
Fixed Income ◽  
Frequency Data ◽  
Insight Into

We study how unconventional monetary policy announcements affected the entry of foreign investment in debt and equity in Mexico, placing special focus on announcements related to the third QE program and the taper tantrum episode. A novel dataset on daily debt and equity flows, that maps Balance of Payments data quite well, allows this paper to provide a better insight into movements of capital. The results suggest that both equity and debt flows reacted immediately to unexpected U.S. monetary policy announcements, particularly if these are considered as bad news by investors. In turn, results using weekly data support the idea that investors interested in fixed income instruments move more prudently than those interested in equity which react quickly.

scholarly journals Shake, Rattle, and Roll

2001 ◽  
Vol 123 (11) ◽  
pp. 56-58
Author(s):  
John DeGaspari
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
High Frequency Data ◽  
Frequency Data ◽  
Low Frequencies ◽  
Mems Accelerometer ◽  
Running Shoes ◽  
Low Costs ◽  
New Applications ◽  
Thin Reservoir

This article highlights that airbag has been a boon to MEMS business. Sales of the tiny accelerometers that sense when the bags should deploy have helped to drive down prices significantly since the devices were first implemented. Now, the high volumes, low costs, and dependable performance of micro devices are opening the way to new applications. Sneaker companies are looking at MEMS accelerometers in running shoes to act as speedometers of sorts. Advantage of the MEMS accelerometer is that it has a wide bandwidth, capable of reading high as well as low frequencies. High-frequency data provides information about thin reservoir zones, faults, and changes that are taking place as fluids are being drained from pores in the rock, said Denver. Higher frequency signals are critical to accurate interpretation. Low-frequency signals are useful in identifying the type of rock, be it sandstone, shale, or carbonate, for example. The VectorSeis is as rugged as a conventional geophone and can be successfully deployed in down-hole environments to get a closer reading of a reservoir.

scholarly journals Spatial price transmission analysis in Ghanaian agricultural markets: Does the data frequency improve our estimation?

2011 ◽  
Vol 4 (2) ◽  
pp. 301-316
Author(s):  
Joseph Amikuzuno
Keyword(s):  
Developing Countries ◽  
High Frequency ◽  
Low Frequency ◽  
Price Transmission ◽  
Price Adjustment ◽  
High Frequency Data ◽  
Agricultural Markets ◽  
Frequency Data ◽  
Monthly Data ◽  
Data Frequency

Unavailability of high frequency weekly or daily data compels most studies of price transmission in developing countries to use low frequency monthly data for their analyses. Analysing price dynamics, especially in agricultural markets, with monthly data may however yield imprecise price adjustment parameters and lead to wrong inferences on price dynamics. This is because agricultural markets in developing countries usually operate daily or weekly, not monthly, as implied by the market analysts who use low frequency data. This paper investigates the relevance of data frequency in price transmission analysis by using a standard and a threshold vector error correction model to estimate and compare price adjustment parameters for high frequency semi-weekly data and low frequency monthly data obtained from five major fresh tomato markets in Ghana. The results reveal that adjustment parameters estimated from the low frequency data are higher in all cases than those estimated from the high frequency data. There is reason to suspect that using low frequency data, as confirmed in some literature, leads to an overestimation of the price adjustment parameters. More research involving a large number of observations is however needed to enhance our knowledge about the usefulness of high frequency data in price transmission analysis.

Accurate Drilling Data Interpretations Brought Significant Values to a Major Drilling Project

2021 ◽  
Author(s):  
Faisal Rashid ◽  
Hamdan Mohamed Al Saadi ◽  
Shahid Yakubbhai Duivala ◽  
Steve Butt ◽  
Sultan Al Mansoori ◽  
...  
Keyword(s):  
Data Analysis ◽  
High Frequency ◽  
Performance Enhancement ◽  
Low Frequency ◽  
High Frequency Data ◽  
Coding System ◽  
Frequency Data ◽  
Drilling Data ◽  
The Many ◽  
Drilling Project

Abstract With the launch of a mega drilling project in the Middle East, the drilling data during the execution stage was collected in two formats; Low-Frequency Data and High-Frequency Data. This paper explains the effective utilization of data in the performance enhancement scheme. The paper also demonstrates the combination of Low-frequency and High-frequency data can reveal the many secrets of the drilling operations and can open the many sides of drilling operations for improvements. Low-Frequency data was entered manually at the rig-site using an improved coding system to identify the activities start and end times. High-Frequency data was collected through real-time transmission from the different data streaming services at the rig-site. Both data forms were collected simultaneously using stringent rules and close follow-ups to make sure that data collection was free of any reporting mistakes and gaps. Later, the collected data was extracted for different types of analyses and interpretations. Low-frequency data was studied in a novel way to get the best analytical and critical outcome to make sure that the right areas for improvements were identified and actions were implemented for enhanced performance. Improved operations coding system helped the team to categorize the operations and failures in an effective way to set new standards in data analysis. More than 100 different types of analyses using the best data analysis technique, such as trailing average, normalization, trends, etc., were conducted based on the information collected during the execution phase, and many new KPIs were established with challenging milestones to be achieved in the prescribed period. High-Frequency data was split into different sets of KPIs to identify the multiple Invisible Lost Time (ILT) areas to boost the operational efficiency. Various performance enhancement schemes were developed based on High-frequency data. As a result, these schemes were proven to enhance the performance of the mega drilling project. This paper discusses the novel methods of drilling data analysis based on low and high-frequency data and shows the effectiveness of the data presented in a standardized format over a period. It deliberates how the teams were challenged to enhance the performance. Such detailed data analysis will bring valuable information for the industry to utilize the conventional database in modernized ways to get the best outcomes from the data analysis results.

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