The Wanderings of Tashkent

Excellent article Tash. Much obliged :-)

you are welcome, C!

A short statistical study of the EUR/USD pair

By Joaquin Monfort on March 3, 2011, 6:47:GMT Forex Research

In this study I have attempted to go back to the very basic elements of price open, close, high, low, daily range, daily change and attempted to analyse these phenomena statistically.
Latter I discuss my conclusions and possible ways in which they can be used in trading.
The study was undertaken using the EUR/USD pair, using daily data only.

Types of days

In total 2594 days were included.
Initially these were categorised into 3 classifications: up days, down days and unchanged days. The results are below:
Total up days = 1319
Total down days = 1260
Total unchanged days = 15
This leads to a percentage breakdown as follows:
Up days as a percentage of all days = 50.85%
Down days as a percentage of all days = 48.57%
Unchanged days as a percentage of all days = 0.58%

Sequences of days

Another phenomenon which was studied was sequences of the same type of day occurring uninterrupted in a row. Below is a list of the sequences for up days, the number of times they occurred in the sample and the total number of days in brackets.
2 in a row occurred 178 times (356 days)
3 in a row occurred 89 times (267 days)
4 in a row occurred 40 times (160 days)
5 in a row occurred 13 times (65 days)
6 in a row occurred 9 times (54 days)
7 in a row occurred 4 times (28 days)
8 in a row occurred 2 times (16 days)
9 in a row occurred 1 time (9 days)


The table below compares clustering in the data to what might be expected from a random sample:

Attached Image (click to enlarge)

https://blog.forex4you.com/wp-conten.../03/random.jpg

The first column shows the length of the sequences studied.
The second column shows the Discrete Frequency of the clustering, which is the number of separate individual incidences of the sequence occurring.
The Total Frequency column is a sum of the discrete incidences and also the number of times the sequence occurred within a larger sequence for example when 2 up days in a row repeated twice, once after each other within a longer sequence of 4 up days in a row.
Probability represents the random chance of the sequences occurring using the base chance of an up day happening, which was 50.85%.
Finally Probable Frequency uses the empirical probability of the previous column to calculate the number of times the sequences should have occurred randomly within the data.

From single days to 2 or more.

The number of single up days which extended to 2 or more up days was also analyzed.
Below are the calculations:
362 up days occurred on their own and were not followed by a further up day.
Another 337 days that is one for each cluster longer than 1 day were also not followed by a further up day as they completed the sequences ie they constituted the final day of a sequence.
In total this gives 699 up days which were not followed by another up day.
This leaves 1319 699 = 620 up days which were followed by another up day.
This means that 47% of up days were followed by one or more further up days in a continuous sequence, and 53% were not.

2 day sequences which led to 3 or more days in a row

The data was also analysed to check how many of the 2 in a row up days were followed by a further up day.
Total number of 2 in a row or more days = 337
The 2 in a row days which failed to become 3 in a row days = 178
Therefore those which extended = 337 178 = 159
In percentage terms = 47.2% of 2 in a row up days led to 3 or more up days and,
52.8% of 2 in a row up days did not extend to 3 or more up days in a row.

Distribution according to Change

The change in price during a day was analysed. This was the difference between the opening price and the closing price. The results were rounded up and down in order to allow them to be categorised and analysed more easily. This process is described as binning. In this case the percentage change was rounded up or down to the nearest first decimal place. The results are shown in the study below. The x-axis at the bottom shows the percentage change in the day and the y axis the number of occurrences of days with that level of change.

https://blog.forex4you.com/wp-conten...stribution.jpg

The table below shows the raw data used in the graph above. The 95% column shows where 95% of the days fell. This is bounded by the light blue row. It occurs between the -1.4% and +1.4% change levels. This means that the majority of days have a 1.4% or less level of change. Furthermore the data showed that 80% of days had less than a 0.8% change. Overall the data showed a tendency to low volatility or reversion.

https://blog.forex4you.com/wp-conten.../03/Change.jpg

Distribution according to Range

The percentage change in price or range was also analysed. The range is the difference between the high and the low. The graph below shows the results:

https://blog.forex4you.com/wp-conten...tribution2.jpg

The raw data is also shown in a table below. The table shows that roughly 95% of days had a range of between 0.2% and 1.9%. 80% of days had a range of between 0.4% and 1.3% and 57% (It wasnt possible to get closer to 50% than this without going below 50%) had a range of between 0.5% and 1.0%.

https://blog.forex4you.com/wp-conten...1/03/range.jpg

Conclusion

The distribution of up and down days was roughly equal ie 50:50. This implied a purely random distribution.
The frequency of uninterrupted sequences of days was slightly higher than would have been expected randomly using the chance of an up day occurring at all (50.85%). This was particularly true for 2, 3 and 4 sequence clusters.
The 2 cluster occurred 427 times when it would have been expected to occur only 335 times randomly. The 3 sequence happened 177 times versus 113 expected randomly and finally the 4 happened 73 versus 43 times. These are quite large differences and maight point to a bias in market data to clustering.
Despite the higher frequency of clustering the chances of sequences lengthening based on statistical evidence was less than 50%. This seems to imply a bias to discontinuation of sequences of up days although the sample was probably too small to prove this given most of the results were near to 50%.
Regarding Range, 80% of days in EUR/USD showed a daily range of between 0.3% and 1.3%, and this data could be useful to construct probable ranges in which future price movements might be expected to probably range between.
Likewise the fact that 80% of daily changes occur within a 0.8% band around the opening price is also a useful statistic. These two stats could even be used together possibly to trade range extremes, given the probability prices will pull back as the day progresses; however, this may require further study to confirm.
The increased frequency of days with a low percentage change may explain the preponderance of Options strategies such as the Butterfly, Condor and Iron Condor which profit from low volatility non-directional movement.
Indeed it may be that strategies based on the same principles are best placed to take advantage of the daily changes in price in EUR/USD, particularly on an intraday basis.

Source: https://blog.forex4you.com/a-short-s...he-eurusd-pair

The Price of Oil and the Price of Carbon


Posted on December 2, 2015 by iMFdirect
By Rabah Arezki and Maurice Obstfeld

The human influence on the climate system is clear and is evident from the increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and understanding of the climate system. Intergovernmental Panel on Climate Change, Fifth Assessment Report

Fossil fuel prices are likely to stay low for long. Notwithstanding important recent progress in developing renewable fuel sources, low fossil fuel prices could discourage further innovation in and adoption of cleaner energy technologies. The result would be higher emissions of carbon dioxide and other greenhouse gases.

Policymakers should not allow low energy prices to derail the clean energy transition. Action to restore appropriate price incentives, notably through corrective carbon pricing, is urgently needed to lower the risk of irreversible and potentially devastating effects of climate change. That approach also offers fiscal benefits.

Low for long

Oil prices have dropped by over 60 percent since June 2014 (see Chart 1). A commonly held view in the oil industry is that the best cure for low oil prices is low oil prices. The reasoning behind this adage is that low oil prices discourage investment in new production capacity, eventually shifting the oil supply curve backward and bringing prices back up as existing oil fieldswhich can be tapped at relatively low marginal cost are depleted. In fact, in line with past experience, capital expenditure in the oil sector has dropped sharply in many producing countries, including the United States. The dynamic adjustment to low oil prices may, however, be different this time around.

Oil prices are expected to remain lower for longer. The advent of shale oil production, made possible by hydraulic fracturing (fracking) and horizontal drilling technologies, has added about 4.2 million barrels per day to the crude oil market, contributing to a global supply glut. Shale oil will lead to shorter and more limited oil-price cycles. Indeed, shale requires a lower level of sunk costs than conventional oil, and the lag between first investment and production is much shorter. Furthermore, shale is still at a relatively early stage of its industry life cycle, where the scope for learning is substantial, as shown by production levels that have proven resilient thanks to phenomenal efficiency gains forced by the big drop in oil prices.

In addition, other factors are putting downward pressure on oil prices: change in the strategic behavior of the Organization of Petroleum Exporting Countries, the projected increase in Iranian exports, the scaling down of global demand (especially from emerging markets), the secular drop in petroleum consumption in the United States, and some displacement of oil by substitutes. These likely persistent forces, like the growth of shale, point to a low for long scenario, even after the supply legacy left by the high-price era of the 2000s has dissipated. Futures markets, which show only a modest recovery of prices to around $60 a barrel by 2019, support this view.

Natural gas and coalalso fossil fuelshave similarly seen price declines that look to be long-lived. Coal and natural gas are mainly inputs to electricity generation, whereas oil is used mostly to power transportation, yet the prices of all these energy sources are linked, including through oil-indexed contract prices. The North American shale gas boom has resulted in record low prices there. The recent discovery of the giant Zohr gas field off the Egyptian coast will eventually have repercussions on pricing in the Mediterranean region and Europe, and there is significant development potential in many other locales, notably Argentina. Coal prices also are low, owing to oversupply and the scaling down of demand, especially from China, which burns half of the worlds coal.

Renewables at risk

Technological innovations have unleashed the power of renewables such as wind, hydro, solar, and geothermal. Even Africa and the Middle East, home to economies that are heavily dependent on fossil fuel exports have enormous potential to develop renewables. For example, the United Arab Emirates has endorsed an ambitious target to draw 24 percent of its primary energy consumption from renewable sources by 2021.

Progress in the development of renewables could be fragile, however, if fossil fuel prices remain low for long. Renewables account for only a small share of global primary energy consumption, which is still dominated by fossil fuels30 percent each for coal and oil, 25 percent for natural gas (see Table). But renewable energy will have to displace fossil fuels to a much greater extent in the future to avoid unacceptable climate risks. Unfortunately, the current low prices for oil, gas, and coal may provide scant incentive for research to find even cheaper substitutes for those fuels. There is strong evidence that both innovation and adoption of cleaner technology are strongly encouraged by higher fossil fuel prices. The same is true for new technologies for mitigating fossil fuel emissions.

The current low fossil-fuel price environment will thus certainly delay the energy transition. That transitionfrom fossil fuel to clean energy sourcesis not the first one. Earlier transitions were those from wood/biomass to coal in the eighteenth and nineteenth centuries, and from coal to petroleum in the nineteenth and twentieth centuries. One important lesson is that these transitions take a long time to complete. But this time we cannot wait.

We owe to electric lighting the fact that there are still whales in the sea. Unless renewables become cheap enough that substantial carbon deposits are left underground for a very long time, if not forever, the planet will likely be exposed to potentially catastrophic climate risks.

Some climate impacts may already be discernible. For example, the United Nations Childrens Fund estimates that some 11 million children in eastern and southern Africa face hunger, disease, and water shortages as a result of the strongest El Nio weather phenomenon in decades. Many scientists believe that El Nio events, caused by warming in the Pacific, are becoming more intense as a result of climate change.

Getting the price of carbon right

Nations from around the world have gathered in Paris for the United Nations Climate Change Conference, COP-21, with the goal of a universal and potentially legally binding agreement on reducing greenhouse gas emissions. We need very broad participation to address fully the global tragedy of the commons that results when countries fail to take into account the negative impact of their carbon emissions on the rest of the world. Moreover, free riding by non-participants, if sufficiently widespread, can undermine the political will to action of participating countries.

The nations participating at COP-21 are focusing on quantitative emissions-reduction commitments (the Intended Nationally Determined Contribution, or INDCs). Economic reasoning shows that the least expensive way for each country to implement its INDC is to put a price on carbon emissions. The reason is that when carbon is priced, those emissions reductions that are least costly to implement will happen first. The IMF calculates that countries can generate substantial fiscal revenuesrevenues that would allow lower distorting taxes and new investments in the economyby eliminating fossil fuel subsidies and levying carbon charges that capture the domestic damages caused by emissions. A tax on upstream carbon sources is one easy way to put a price on carbon emissions, although some countries may wish to use other methods, such as emissions trading schemes.

Countries that implement their INDCs through a domestic carbon price will reach their goals at lowest cost to themselves, but without global coordination on carbon prices, the cost to the world economy of whatever aggregate emissions reduction is achieved will be unnecessarily high. In order to maximize global welfare, every countrys carbon pricing should reflect not only the purely domestic damages from emissions (for example, health effects of the particulates associated with burning coal), but also the damages to foreign countries.

Setting the right carbon price will therefore efficiently align the costs paid by carbon users with the true social opportunity cost of using carbon. By raising relative demand for clean energy sources, a carbon price would also help to align the market return to clean-energy innovation with its social return, spurring the refinement of existing technologies and the development of new ones. And it would raise the demand for mitigation technologies such as carbon capture and storage, spurring their further development. If not corrected by the appropriate carbon price, low fossil fuel prices are not accurately signaling to markets the true social profitability of clean energy. While alternative estimates of the damages from carbon emissions differ, and it is especially hard to reckon the likely costs of possible catastrophic climate events, most estimates suggest substantial negative effects.

Direct subsidies to R&D have been adopted by some governments but are a poor substitute for a carbon price: they do only part of the job, leaving in place market incentives to over-use fossil fuels and thereby add to the stock of atmospheric greenhouse gases without regard to the collateral costs.

Politically, low oil prices may provide an opportune moment to eliminate subsidies and introduce carbon prices that could gradually rise over time toward efficient levels. However, it is probably unrealistic to aim for the full optimal price in one go. Global carbon pricing will have important redistributive implications, both across and within countries, and these call for gradual implementation, complemented by mitigating and adaptive measures that shield the most vulnerable.

The hope is that the success of the Paris conference opens the door to future international agreement on carbon prices. Agreement on an international carbon-price floor would be a good starting point in that process. Failure to address comprehensively the problem of greenhouse gas emissions, however, exposes all generations, present and future, to incalculable risks.

eu sell order filled. hoping to ride it for good profit. looks like a pretty good spot.

added more shorts.

also short uj (probably just should have shorted ej instead of shorting uj and eu)

eu did not work out. still holding uj

uj shorts are struggling. this damn thing does not want to go lower. if 123.15 reached i will have to close everything. target 122.50

buy au 7214

10 shorts and bastard finally lost the ground. started taking partial profits


remaining 3 shorts reached the target

closing another position, this will leave with one short just in case if downtrend resumes

and it did
sucked the blood out of short trend. it was worth all efforts.

now lets see how the long will work out

uj long stopped out yesterday.
decided to close the last eu short and probably will open long.

holding 2 au longs and not happy with the range. maybe will close one and let the other one run.

one more attempt. long uj.
short ga and willing to add more

ga stopped out but uj running

bad day. uj longs stopped out
buy au and sell ga. weak confidence in these positions. pissed off with giving up good amount of pips today. may take a few aggressive trades after us data release.
*edit. long uj 121.48

Careful Bro... remember this is nearly FED... it might be that technical is less important than fundamental for this month. at least until FED.

you are right. trying to catch a reversal these volatile times, unfortunately today lost several trades, some at BE some, 10-20 pips. luckily not big positions. closely watching GBP pairs. happy pipping