6/19/15

Europeen Union - perfect storm is coming?

1. Extremely slow economic growth
2. Price deflation
3. Greek default and Grexit
4. UK referendum 2017
5. Rights, lefties, and Euro-sceptics destabilise the power of elites
6. Economic loss due to unrest in Ukraine
7. Economic loss due to mutual sanctions against Russia
8. Migrants
9. Political scandals
etc.

Not too much?


5/13/15

Использование метода согласованного фильтра на малоапертурной сейсмической антенне “Михнево”

Сейсмические приборы. 2014. Т. 50, № 3, с.5-18.
http://si.ifz.ru/fileadmin/user_upload/documents/journals/si/50-3/01-SI-50-3.pdf

Одна из задач, решаемых малоапертурной сейсмической антенной (МСА) “Михнево”, – создание каталога промышленных взрывов в пределах Восточно-Европейской платформы. Начиная с момента установки антенны в 2004 г., с ее помощью ежегодно обнаруживается до 1000 взрывов разной мощности. Метод формирования лучей, основанный на суммировании приведенных к центральной станции записей индивидуальных каналов сейсмической антенны, значительно повышает отношение сигнал/шум по сравнению с трехкомпонентной станцией и снижает амплитудный порог обнаружения. Это позволяет выделять очень слабые сигналы и значительно увеличивает число обнаруживаемых карьерных взрывов. Для сигналов с малым отношением сигнал/шум даже разрешающей способности антенны не- достаточно для однозначной идентификации источника. Метод согласованного фильтра с шаблонными волновыми формами, тщательно выбранными из десятилетнего архива цифровых записей МСА “Михнево”, позволяет создать кросскорреляционные алгоритмы, обладающие исключительно высокой точностью относительной локации и идентификации карьеров. Это делает возможным создание эффективной системы автоматической обработки данных и выпуска точного каталога промышленных взрывов.

Обнаружение региональных фаз объемных сейсмических волн с помощью группы трехкомпонентных датчиков

Сейсмические приборы. 2015. Т. 51, № 1, с.27-45

Малоапертурная сейсмическая группа (МСГ), состоящая из семи трехкомпонентных сейсмометров, в течение четырех месяцев 2013 г. осуществляла режимные наблюдения региональной сейсмичности в районе выбранной площадки Нижегородской атомной станции.
Автоматическое обнаружение сигнала с помощью метода регулируемого направленного
приема применялось для каждой компоненты движения отдельно, причем две горизонтальные компоненты преобразовывались в радиальную и трансверсальную компоненты для заданных значений скорости и азимута фронта плоской волны. Для оценки ожидаемого увеличения отношения сигнал/шум, что имеет определяющее значение для обнаружения сигнала, мы исследовали зависимость когерентности микросейсмического шума от частоты,
азимута и медленности, а также определили уровень взаимной корреляции сигналов на от-
дельных каналах. Основной поток сигналов, зарегистрированных сейсмической группой от
региональных источников, связан с карьерными взрывами. Используя повторяющиеся
взрывы на семи карьерах, мы количественно оценили рост эффективности обнаружения региональных сейсмических фаз с помощью трехкомпонентной МСГ по сравнению с подгруппой вертикальных датчиков. Горизонтальные датчики показали более высокую эффективность в обнаружении поперечных волн, в то время как подгруппа вертикальных датчиков пропускала S-волны от некоторых событий. Для одного из ближних карьеров вертикальная подгруппа пропускала до 25 % событий (5 из 20). Результаты работы указывают на необходимость использования трехкомпонентных сейсмических групп для исследования
региональной сейсмичности.

ОБНАРУЖЕНИЕ СВЕРХСЛАБЫХ СИГНАЛОВ НА МАЛОАПЕРТУРНОЙ СЕЙСМИЧЕСКОЙ АНТЕННЕ “МИХНЕВО” С ПОМОЩЬЮ КРОССКОРРЕЛЯЦИИ ВОЛНОВЫХ ФОРМ

ДОКЛАДЫ АКАДЕМИИ НАУК, 2015, том 460, № 6, с. 707–709
DOI: 10.7868/S0869565215060158
ISSN 1028 334X, Doklady Earth Sciences, 2015, Vol. 460, Part 2, pp. 189–191. © Pleiades Publishing, Ltd., 2015.

В целом использование метода кросскорреля ции волновых форм на малоапертурной сейсмиче ской антенне “Михнево” позволило примерно на порядок величины понизить порог обнаружения сигналов от различных источников по сравнению с трехкомпонентной станцией за счет подавления не коррелированного шума при формировании луча (3.5 раза для 12 каналов) и применения согласован ного фильтра (∼3 раз). Для подземных взрывов сни жение амплитудного порога обнаружения в 10 раз означает возможность обнаружения взрывного ис точника мощностью, также пониженной в 10 раз. Дополнительные меры по снижению уровня мик росейсмического шума (например, установка в скважинах глубиной несколько десятков метров), увеличение апертуры антенны и числа сейсмоприемников позволили бы снизить порог обнаружения еще в несколько раз.

3/28/15

New issue of Theoretical and Practical Research in Economic Fields

Theoretical and Practical Research in Economic Fields Volume V, Issue 2(10), Winter 2014

Contents: AASERS Publishing http://www.asers.eu/asers-publishing ISSN 2068-7710

Journal's Issue DOI: http://dx.doi.org/10.14505/tpref.v5.2(10).0

1 Analyzing the Dynamics of Gross Domestic Product Growth. a Mixed Frequency Model Approach Ray John Gabriel FRANCO, Dennis S. MAPA …117

2 Estimates of Income Inequality are Biased or Misinterpreted
Ivan KITOV …142

3 Differential Effects of Target Price Releases on Stock Prices: Psychological Aspects Andrey KUDRYAVTSEV, Shosh SHAHRABANI, Aviad DIDI, Eyal GESUNDHEIT …153

4 Study on Pre-Assessment and Evaluation System Indicators Energo - Mining Complex in Basin of Oltenia Elena BICĂ …167 

3/1/15

Modeling the price of crude oil and motor fuel: a five-year revision

I've published a new research paper as based on many posts in this blog. This is a five-year revision of our model predicting oil and energy price. The paper is available on RePEc:

Modeling the price of crude oil and motor fuel: a five-year revision

Abstract
We present a five-year revision of an empirical study started in 2007. Seven years ago, we found two three distinct periods characterized by sustainable linear trends in the difference between the headline consumer price index (CPI) and the core CPI in the USA. Then we revealed similar behavior in the differences between the CPI and indices of various consumer expenditure categories. We estimated the duration of these trends which varies in a wide range from 5 years to more than 20 years. The transition periods to new trends span shorter intervals of 2 to 5 years. The transition is characterized by a higher level of volatility in the studied CPI differences. In April 2009, we introduced a simple quantitative model representing the evolution of motor fuel price (a subcategory of the consumer price index of transportation) relative to the core CPI as a linear function of time. Under our framework, all price deviations from this linear trend are transient and the price must return to the sustainable trend. The model predicted that oil price would fall to $30-$60 per barrel in 2016, which is very close to the current price. The behavior of actual oil and motor fuel price since 2010 has shown that this prediction is accurate in both amplitude and trajectory shape – a good support for the credibility of our empirical mode. We conclude that the concept of price decomposition into a short-term (oscillating) and long-term (linear trend) components deserves a deeper theoretical consideration of the driving forces behind linear time trends and can be used as a workhorse for a wide spectrum of commodity investors. According to the model, the price of crude oil will be falling to the level of $30 per barrel during the next 6 years and motor fuel will follow up the oil price. Moreover, the periodicity of the related normalized difference indicates that this low-price level may extend into the second half of the 2020s. The secular fall in energy prices may induce a lengthy period of very low inflation.

2/13/15

The era of low energy price will last 10 years with oil at $20

We have been studying the long-term evolution of energy prices in the USA since 2007 and reported several important observations useful for profitable and safe investments. The simplest fact we have discussed is the effect of energy/oil price on stock prices. Share price of Exxon Mobil and ConocoPhillips does depend on oil price. The link is direct and positive – oil price increase is reflected in share price growth. We have calculated regression coefficients in order to understand which company is most sensitive.
In 2008, we reported that several major categories of consumer prices (various goods and services) have sustainable and quasi-linear in time trends relative to energy prices. Similar behavior was reported for producer prices and oil. One can easily imagine what a great opportunity arises for sound investments. Moreover, our observations demonstrate that many of these sustainable trends have clear turning points which provide investors with invaluable information on effective buy/sell decision. In this article, we revisit our previous results related to energy (oil) in order to demonstrate that the fall in the energy price in 2014 was well predicted. Then we extend our investigation of the future evolution of the consumer price index (CPI) of energy with new data obtained since the beginning of 2013 when the fall prediction was done.  Currently, one is interested to know how deep the price will fall and when it will come back to $100.
Our theoretical approach was first published more than six years ago in a paper on the presence of long-term sustainable trends in the differences between various components of the CPI in the USA. We started with the difference between the core CPI (i.e., the headline CPI less food and energy) and the CPI. Then the consumer price index of energy, which gives approximately 9% of the CPI, was analyzed. In the beginning of 2008, we successfully identified and predicted that difference between the CPI and the energy index was approaching a turning point (actually observed in the summer of 2008) and forecasted the energy prices to fall relative to the core CPI through the first half of the 2010s. Based on the general approach, we also estimated that after the turning point in 2008/2009 oil price would go down from $100 to $50 per barrel in 2015 and $30-60 in 2016.  As one may know this prediction of the turning point timing and the level of oil price and the duration of higher oil prices is relatively accurate. 

Here we revisit the relative evolution of the core consumer price index (CPI) and the CPI of energy. Figure 1 displays the difference between the core CPI and the index for energy for the period between 1960 and 2014. All CPIs are seasonally adjusted and borrowed from the BLS.  Before 1980, these two indices had been growing almost in sync with fluctuation around 10 units of price index. Between 1981 and 1999, the difference grew from -10 to almost 80 units. Between 2001 and 2008, a period of intensive growth in the energy index was observed. Qualitatively, one can distinguish three periods of linear trend and three turning periods with a higher volatility. The last turning point was in 2008 and the index of energy is now on decline relative to the core CPI.  However, the extremely high volatility masked the new trend in the difference before 2011. Currently, the new trend is clear and shows the expected behavior - energy price goes down.

The question is - when will it reach its bottom? And when the price will reach the hard bottom?
Six years ago we expected that oil price might go down to $22. Is this the case now?


Figure 1. The difference between the core CPI and the index for energy between 1960 and 2014. There are three periods of linear trend and three turning periods. The most recent turning point was in 2008 and the new trend emerged more of less clearly in 2011.

Figure 2 illustrates the most recent period. Since 2001, we observe a slow decrease in energy price relative to the core CPI. Their difference in Figure 2 is below the green line representing the predicted trend for the period after 2010 - the slope is as between 2001 and 2008 but with an opposite sign. Since summer 2014, the energy index has been falling much faster than before and the (green line) trend was intercepted in November 2014. Linear regression gives a slope of +6 for the difference curve since 2011 which is still much lower that the absolute value of the slope between 2001 and 2008 (-14). The energy price had extremely high volatility between 2005 and 2011. Then the price calmed down and demonstrated only short term and low amplitude fluctuations. The level of volatility is again high since summer 2015. One might expect a few years of larger volatility from deep falls to sky heights.
Data between 2001 and 2014 give clear indication of the new trend direction and slope. Following this trend, the difference of core CPI and consumer price index of energy will likely reach its peak value in 2016-2018. We expect no further decrease in oil price beyond 2018. The question is when the trend will change to the opposite like that was observed in 2001 and 2010? Historic evidences are unbreakable – cycles rule this world. There are many explanations of the current energy price behavior. Various actors are suggested as drivers with own motives open and hidden. We do not consider them as wise and explanatory. To say “cycle” does not mean to explain something as well. This is just a set of observation in favor of future evolution.


Figure 2. Same as in Figure 1, for the period after 2002. Linear trends are shown.

We used only absolute difference so far. It is instructive to analyze the difference in relative terms and we have normalized the difference to the core CPI. Figure 3 illustrates the new pattern. In contrast to Figure 1, the amplitudes and periods of long term fluctuations are similar and the overall evolution seems to be repeatable, i.e. cyclic. Figure 4 exercises the assumption of repeatability. We have shifted the original curve by 27 years ahead and obtained a striking similarity in the amplitude and timing of the energy price falls and rises.


Figure 3. The difference between the core and energy CPIs normalized to the core CPI.


Figure 4. Same as in Figure 3 with red curve representing the original (black) curve shifted 27 years ahead
Finally, Figure 5 shows a detailed picture which could be helpful in the bottom price estimation. The current difference presented by black curve is expected to reach red line in during this phase of energy price fall. The intercept price is about $20 per barrel. Two years ago we foresaw a cliff in energy price and it is here today. When the black line touch the red one - the energy index returns to the long term sustainable trend stretching into the 2020s. The era of low energy prices has come and the trend will not change to the opposite before, say, 2025.    
.  

Figure 5. An energy cliff is not over.

We have three general conclusions:
-        The energy price will be falling another two years with the bottom of $20.
-        The change in energy price will be characterized by an elevated level of volatility in the next two to three years.

-        The era of low energy price will extend into the 2020s.