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Crude oil is undergoing a bounce, but should remain under pressure for the rest of 2019…this is what we have predicted in the last issue of the Spread report our premium subscribers received on the New Year’s Eve.

Today, I will take a closer look at the situation in crude oil and also mention natural gas briefly. I will describe the fundamental or rather geopolitical forces behind this outlook and outline the strategies suitable for this environment.

You can find the whole article HERE.

The post What strategy to choose for oil & gas in 2019 appeared first on Quastic.

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At the end of next year (2019), the CME Group will raise storage rates in corn and soybeans futures contracts from 0.165 of one cent per bushel per day to 0.265 of one cent per bushel per day. The change will take effect…

You can find the whole article HERE.

The post Bear spreads in corn will become even more profitable appeared first on Quastic.

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Dear Readers and Traders, in this article I want to summarize our gas trading activities, show you the changes in the portfolio as well as the conclusions we have made in our models regarding the temperature adjusted balance between supply and demand. Also, I would like to thank you for a number of very good suggestions, ideas and information that you have sent me. I made from them some important conclusions that I am going to describe at the end of today’s article.

Summary of the week

Since last week, natural gas has grown steadily, shifting our portfolio back to the negative numbers. Although gas prices reached its maximum since our strategy was launched, the portfolio is roughly 2% higher than was at its minimum.

Figure 1: Account Overview

Changes in the portfolio

Now the prices of the nearest futures contracts are around 2.95 USD / MBtu, which is a level where we no longer mind having larger part of our gas portfolio in short. For this reason, we will maintain our short position ETF: KOLD on a similar levels and we will roll the ETF: KODL  positions ideally in horizontal direction.

Last week we made several changes in the portfolio in respect to above mentioned. August options for BOIL with strikes 26 and 27 were rolled horizontally for one month later with a credit of USD 80, that is an average of about 20 cents per contract. August’s BOIL option could have been rolled for a month and strike later also credit-wise, so we did not hesitate to roll it up rather than roll it horizontally.

2 options for August on KOLD were closed with almost full 15 cent profit and we opened two new September options with a strike of 39 for one dollar each. We opened the new third option on KOLD with the August expiration and strike of 37 for 60 cents (if the gas goes up or stagnates, this option will make a full profit and will hedge other positions, if the gas will go down, the time premium will disintegrate and we will roll it for September). By the third one – at the money options on KOLD we compensate our short on UNG, where we now have an exposure of about $ 20,000.

We would also like to show how our total delta of the portfolio have changed since the last update. Now we have increased the short on gas to about 50% of our account, compared to just 7% three weeks ago. Much of this movement in our exposition has taken place due to the change in the delta of the options and it is consistent with our statement from the past: that we want to build more positions near 3USD / MBtu.

Figure 2: Summary of the portfolio´s delta

Model of temperature-adjusted balance between supply and demand

Why do we still believe in a drop of the natural gas prices and why are we still willing to go short? We will try to provide a more detailed analysis in the following paragraphs.

If I would only show you the following graph of the development of natural gas reserves, it would be clear why the price of the last two weeks is rising. Stock growth almost stopped to grow and stocks reached 5-year low. In absolute terms, the situation does not look very positive for the short and is diametrically different from the situation two years ago, when the market was filled with natural gas and the gas drop to 2USD / MBtu was only a matter of time.

Figure 3: Development of natural gas reserves

But if we want to compare apples with apples, we need to look deeper into the data. We are now analyzing the period from 1.5. to 4.8. in 2017 and 2018 (in 2017, shorting gas was a profitable strategy) to compare the fundamentals in both years.

Why in this period? This part of the year represents the so-called injection season, ie the season of the year, when stock inventory growth occurs, and the development of gas reserves is not affected by so-called heating degree days (HDD = heating days when gas is burned in heating plants, – part of the year where HDD is prevailing is called the withdrawal season. The Injection Season is simply a well-defined part of the year that can be compared year-on-year, and where demand-side factors are purely limited to cooling degrees days (CDD = i.e. factor measuring how warm it is and how much it needs to be air-conditioned).

In these 14 weeks, stocks grew by 238 Bcf more than last year (stocks are 1011 Bcf this year – 773 Bcf last year), despite the cumulative higher temperatures in the past 14 weeks (827 CDDs instead of 763 CDDs last year). This means that, despite the warmer weather, the stocks are being built faster. The reason why we are moving on the chart to an absolute 5-year minimum of stocks volume is not because of slow stock growth but because of hard winter with an extremely low stocks left.

Figure 4: Development of natural gas reserves

Our thermally neutral estimate of year-on-year surplus of supply over demand is +2.43 BCf per day due to stock growth ((1011-773) / 14/7) and +0.65 Bcf daily due to higher temperatures, ie +3.08 Bcf daily.

How did we calculate 0.65 Bcf?

Looking at the year-on-year comparison of natural gas consumption in order to gain electricity (so-called Powerburn – during the summer season – this is an increase in consumption due to air conditioners), the chart below shows that blue points belonging to 2018 as well as orange points belonging to 2017 are showing a positive correlation between the number of cooling degrees days and the daily volume of Bcf of burned natural gas in gas power plants. One marginal CDD means this year’s daily gas consumption growth by about 0.1426 Bcf. We can deduct that if the last 14 weeks in the US were 64 CDD warmer (827 CDD in 2018 – 763 CDD in 2017), then one week was 4.57 CDD cooler. As a result, daily gas consumption was +0.65 Bcf / d (0.1426 * 4.57) higher due to higher temperature. Therefore, the thermally neutral year-on-year change in the balance between gas supply and demand must also be cleared, so we look at the overall year-on-year change of supply by +3.07 Bcf.

Interestingly, from the comparison of both regression equations (blue 2018 and orange 2017) in the chart below, we see an increase in gas consumption in gas power plants. We see an increase from 21.1 Bcf per day to 23.7 Bcf per day. This increase is a result of the closure of coal power plants and the opening of new gas power plants across the US. We will certainly meet in the upcoming years a similar rate of structural growth in demand. The other two sources of domestic gas demand in the US (industry and gas consumption in heating plants) did not show year-on-year structural growth. Structurally, only export is growing, but we will talk about it at other times.

Fig.5: Powerburn vs. CDD

Conclusions from your questions

I would like to thank you once again for the questions I am receiving from you. They gave me very good feedback and confirmed the weak points I felt when writing articles. From my side there are several conclusions:

– Today’s articles are not completely intended as an investment strategy for copying, it’s some kind of style that not everyone can and will do, but it can show things from inefficient ETFs, options, and working with fundaments. Writing is also quite time consuming for me, and I know it could be better.

– Your observations are leading me to do a complete structured publication (“cookbook”) and perhaps even – for better clarity – a video tutorial where I would discuss all the theoretical and practical things about gas fundamentals, inefficient ETFs and the use of options, so that a trader, even when he makes a mistake with the fundaments, has a greater chance of success than in a pure shorting of the underlying asset.

– For those who would like to trade, I am thinking about creating a weekly report, where there would be current fundamentals, let’s say one to three educational model portfolios with a possible trade set-up and planning for possible trajectories in the sense of when the price is on X, then I do Y, and on the contrary, if it drops to Z, I take a profit and I’m waiting. Since everyone has different account sizes and different levels of trading aggressivity, I will have to think about how to design the educational model portfolios.

The post Option trading in practice – Weeks 14 and 15 appeared first on Quastic.

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Tesla’s share trading had been suspended on last Monday for one hour, as the share price jumped by 11% to $ 382. The reason was the announcement by E. Musk about a possible withdrawal of Tesla’s shares from the market.

E. Musk has set the price to $ 420 per share, for which he would withdraw shares from the market. This price is equivalent to a 20% premium compared to the price after Q2 2018 announcement. E. Musk has so far stated that it is a consideration that he is not yet 100% determined about. This corresponds to Monday’s closing price $ 382. The reason for this is the great volatility of the company’s stock price, which affects the actual operation. Withdrawal of shares from the market would solve the volatility factor. It would be on each investor, whether he will sell his shares for $ 420 per share or keep holding a stake in the company without publicly traded shares. A disadvantage for investors would be a loss of liquidity.

How much would cost Tesla buy back?

There are 127.5 million publicly traded shares. A total of $ 53.5 billion would be needed to buy all of them. According to the existing indications, this would be the so-called leveraged buyout (LBO), ie the purchase of shares thanks to a loan. This would be the biggest LBO in the history. Of course, the more investors keep their shares, the less funding will be needed. Therefore, his efforts will be to convince as many investors as possible to keep their shares. E. Musk does not plan to significantly increase his share, which oscillates about 20 percent.

He said that Tesla and Space X will continue to function as separate entities with their own management and investor structure. However, he did not mention the future financing of Tesla’s operation, which is not yet possible from its own cash flow.

PS: Similarly, five years ago Michael Dell applied to his company the withdrawal of the Dell shares from the market. Now he is talking about re-launching these shares through a special transaction.

Who will sponsor Tesla share buyout?

There are several variants:

  • Japanese Veture Capital SoftBank
  • Chinese Tencent
  • Sovereign Wealth funds of some countries – most often speculated is Saudi Arabia.

There are also several private investors including the largest banks or mutual funds. The funds Fidelity and T Rowe Price together hold one sixth of the stake in the company. Together with third biggest fund Scottish Mortgage, they are holding nearly 20% of shares. If these funds would keep their shares even after the shares were withdrawn from the stock exchange, they would have helped significantly reduce the capital needed to buyout shares.

Already, some facts are being revealed which are questioning this decision.

Why now?

1 The price is relatively high. Is he trying to prevent a drop of the share price?

2 He didn´t like the by analysts’ questions about the recent announcement of Tesla’s results when E. Musk did not keep his nerves and refused to answer?

  • Why did he choose a tweet form for notification?
  • Musk completely underestimated the legal aspect of the whole thing. He was obliged to inform the SEC about this fact when he began to think about it. He did not. The SEC began to investigate him promptly.
  • China’s customs duties will hit every fifth car sold
  • Musk is trying to maintain total control. He approves any expense over $ 1 million. This may seem sufficient, but this limit is 0.25 per thousand from quarterly turnover. When compared to a family, this is roughly the same case as if you had to agree each expense over about 2 dollar.

The post What’s behind the growth of Tesla motors shares (TSLA) appeared first on Quastic.

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Today, I have an interesting topic for you, and the topic is artificial intelligence. The article will be a little longer, so I’ll split it into more parts:

  1. Introduction
  2. What is artificial intelligence and what we can imagine under this name
  3. What, on the contrary, is not artificial intelligence
  4. How does artificial intelligence work in trading?
  5. Artificial Intelligence in the Czech RepublicČR
 A few words to begin with

I decided to write this article for two reasons.

The first is that the name artificial intelligence sounds sexy today, and so it is often used by the sellers of any kind of trading systems. Thanks to this article, you will know what artificial intelligence is and what it is not.

The second reason are the benefits of this technology. At first glance it may seem complicated, but it does not matter. The goal of professionals is to create tools that can be easily used by ordinary people. Therefore, it is a good idea to know something about this topic and to have an idea of ​​what artificial intelligence really is and what is not.

Therefore, the goal of the article is clear and let’s get to the point.

What is artificial intelligence and what to imagine under this name?

A self-adaptable model could be for example called an artificial intelligence. It is a system (I do not say a strategy), which, with every new trade, evaluates the state of the market in the historical context and learns how to trade better.

It is therefore like a discretionary trader who improves and trades with every trade better and better. The good discretionary trader learns from his mistakes and successes instead of doing the same mistake all the time and therefore he is not fulfilling Einstein’s definition of insanity (doing the same thing again and again and expecting different results).

Under Artificial Intelligence, you can simply imagine a computer program that is learning and constantly improving. It also has one great advantage over a discretionary trader – it learns very quickly at the beginning, because it goes through tens of years of historical data, and in a dozen hours it can handle what a discretionary trader would learn in years. It’s kind of a “virtual trader.”

In addition, just as different real traders are, also different models of artificial intelligence (virtual traders) are different. So, there are more ways to work with Artificial Intelligence and you can have for example 20 different “virtual traders”.

What is not artificial intelligence

I consider this part to be very important. As I wrote above, many people consider as “artificial” also ordinary trading systems.

If the strategy is self-optimized based on certain values, it is not an artificial intelligence. The so-called dominant frequency approach is used in trading. We have 3 main frequencies – low, high and dominant. Low frequencies are used for indicators like moving average and are relatively smoothed. High frequencies are typical for oscillators such as RSI.

The dominant frequency, on the contrary, is the frequency that dominates the market and is used, for example, as the value of an indicator. The moving average does not necessarily need have to have frequency 200, but the period can be defined by the dominant frequency, so it is changing with each candle and constantly adapting to the market.

Basically, it’s not a new approach, but it’s not artificial intelligence. However, many people are able to consider this (or similar approaches) as artificial intelligence.

Artificial intelligence in it´s true sense of the word will also not work as a strategy in the trading platform, because virtually no trading platform is designed to work with artificial intelligence. Let’s look at this now.

How we work with Artificial Intelligence in Trading

As I mentioned above, Artificial Intelligence does not work in common trading platforms. And because of their extreme computational demands, these algorithms have to be tightly tailored for the specific hardware they are running on.

For this we have special tools, such as the TensorFlow library, which manages your final code for optimal running on your hardware.

TensorFlow is working with a so-called computational graph that clusters individual operations into higher aggregates and where data flows in a specified order. I cannot program it myself, so I know it theoretically from Pavel Hala. You can see a small part of the computational graph here:

An example of a small part of Pavel Hála’s artificial intelligence architecture

But these tools work separately and if you want to use them for Metatrader or other platforms, you have to do it a bit differently.

Basically, there are three ways:

  1. You work with signals

The strategy generates signals and you enter to the positions manually. It is especially useful for daily timeframe, so you can execute everything on time.

  1. Signals are automatically being traded

The strategy generates signals and automatically sends them to the platform. In this case, execution is automatically executed and there is not a problem with time.

  1. Regular strategy generation

An approach that generates a new file for trading platform with every change in strategy. Usually, a new strategy is created on a monthly basis.

So, if someone offers you a strategy based on artificial intelligence, do not trust him.

Artificial Intelligence on Financial Markets in the Czech Republic

Czech Republic has a relatively interesting reputation in the field of artificial intelligence research for financial markets. I personally know more professionals, but Pavel Hála has reached the peak from my point of view. Paul is an astrophysicist and a very intelligent person. After what I know from him, I can confirm that not everyone should be interested in use of artificial intelligence in trading, but it makes sense to have an idea about this topic.

Why?

It’s simple. Although Paul is a very clever person, for whom there is hardly something complicated, he has something to pass on. I like to use the comparison with Nikola Tesla. Nikola Tesla was a genius who invented unreal things. Even if almost none of us understood and do not understand what he was talking about, we use the results of his work (I recommend reading his CV). The task of these people is not to pass on their knowledge in raw form, but to give it to you so that you can use it. Their ideas must be adapted to the tools we can easily use.

The same it is with artificial intelligence, you will meet in places where you would not even expect it. For example, search on Google, client support (sometimes communicating with a robot, not a real person), etc.

Pavel is the SpreadCharts architect, which is a great platform for futures analysis, and it is completely free of charge. Paul and his application made such impact on me, that I have decided joining SpreadCharts as an investor last year, so you can look forward to new interesting features.

The post Automated trading systems based on artificial intelligence appeared first on Quastic.

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Dear readers and traders, since last week, we saw a slight loss due to an increase in the gas prices. What makes us happier is the overview of our trading since first May, when we started. Since then, ETF: UNG has grown by about 1%. Since we are trying to be short on gas, an independent observer would expect the value of our portfolio to decline. However, by using the options and dynamic hedging, we have increased the portfolio’s value by 1.5% over given period. Gas (UNG) had the largest drop during this period by 7.2%, while we had 3.45%. So, we are pleased to be able to demonstrate you the added value of using options in trading.

Obr.1: Account Overview

Changes in the portfolio

Last week, we closed all call options on UNG with the 23.50 strike, as the delta was already very low, and such positions are generally best to be closed not increase the tail portfolio risk. As a new position, we sold 8 put options of the underlying UNG with strike 22 and expiration during the last day in August. Logic is simple. Basically, we see the price of natural gas increasing towards winter, and at these higher levels we want to open bigger shorts again. So, in order to make a little profit in this period, we sold put options as covering options to our assigned UNG call options.

Thus, we have 800 UNG shorts with an average short value 22.12, and in addition we have sold 8 put options with strike 22 and a credit bonus of 23 cents per option. So, if the ETF: UNG will stagnate for a whole month (Contango will push the ETF: UNG down, but fundaments due to low reserves can push the gas upward) ending at $ 22 level, we take profit on both sides of the position.

As can be seen from our text above, day by day we are nearing the winter season, when gas volatility increases, and lack of stocks along with abnormally low temperatures during the heating season can cause sharp spikes upward. That is why we are trying to push the construction of bigger short positions towards to prices around 3USD for Bcf. In the meantime, we want to keep only a smaller short and smaller delta.

The post Option trading in practice – Week 13 appeared first on Quastic.

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