Author: Asset Investment Management

Futures Education Homepage

What is Fundamental Analysis?

Many traders are familiar with fundamental analysis when trading stocks, but fundamental analysis can also be applied to the pricing of futures contracts.

Stock analysts will use the financial information of a company to help determine its health. Most of the analysis will center around accounting ratios, an analysis of how the company is performing compared to their peers, and how the sector is performing in general. The resulting price models are compared to the current market price and the decision to invest or not is made based on those numbers.

Futures contracts represent a market, not just one company; when analyzing the fundamentals of an entire market, the trader will adjust their methodology, substituting economic variables for accounting ratios, and look at the factors influencing supply and demand. Fundamental analysis is the process of determining the model price of a futures contract, now and in the future using factors like micro economic data, macro-economic data and industry financial conditions. The analyst is looking to determine where supply and demand will move, price at a later date and whether the contract is priced fairly today.

Did you know? – Stock fundamentals are typically calculated using accounting ratios to determine potential for future growth. In the futures market, fundamental analysis will look at factors that could impact supply and demand.

For example, a trader who is looking to analyze crude oil may want to research the factors that drive supply, such as OPEC production limits, disruptions in the supply chain and natural disasters.

They might also want to look at factors that affect demand, such as economic expansion and more cars on the road, to determine an assessment of how they think supply and demand will increase or decrease in the future.

One trader might see that OPEC production has increased, creating downward pressure on the price of Crude. While another trader could also see that due to population growth and economic prosperity that demand for Crude is going to increase and will look for price to increase in the future.

Macroeconomics

Macroeconomic factors are variables influenced by the economy, which can lead to price movement of a futures contract. These factors affect many, or all, sectors at once, and are typically the highest-level factors that affect the financial health of a country’s economy.

Macro-economic factors such as GDP, inflation and interest rates, create upward and downward pressure on the prices of key sectors and commodities.

For example, if GDP is increasing and the economy is growing and driving an increase in construction, commodities, such as copper that are used in construction could see increased demand and as a result increasing prices.

In another scenario, what happens if interest rates are increased domestically? For example, if the U.S. increases rates and we see no economic changes in the European Union, then the EUR/USD (6E) contract should decrease in price given that the U.S. dollar has strengthened in relation to the Euro.

Microeconomics

Microeconomics is the study of supply and demand for a commodity. These factors are specific to the commodity and sector being analyzed. Factors that might impact supply and demand are consumer preferences, technological advancements and substitute and complementary goods.

Improvements in technology could make it more efficient to produce goods, thus increasing supply while changing the products that consumers are interested in, decreasing demand.

As consumers change their preferences or as trends change and consumers no longer want a particular item, demand dynamics are changed.

Demand for products can also change as substitutes come on to the market. In the futures market, this relationship occurs between different contracts. For example, corn and soy meal are both used to feed livestock and both are represented by futures contracts. At certain price levels, there may be farmers who will move from using corn to using soy meal and vice versa, resulting in the price change of one commodity affecting demand in both commodities.

When an increase in the price of one good impacts the demand of another, they are called complementary goods. For example, the price of feed can affect the price of livestock. These markets move together and demand in one market can affect the other market.

Industry or Sector Health

Industry or sector analysis also factors into the decision-making process. The trader will look at the industry and see whether the industry is growing or contracting and if there are any factors that might impact growth in the future.

For example, a trader might see the demand for crude oil declining in the future with price possibly moving lower. However, if there are factors within the crude oil industry that are leading to production issues, supply might decrease and, even though demand is lower, the reduction in supply means that even the new lower levels of demand cannot be met and price might increase.

Summary

Traders are looking to understand what is ultimately driving price and if the current market price of the futures contract is higher or lower than the model price.

If the model price is higher than the current market price, then the trader believes that the market is undervalued and would want to buy contracts of the undervalued contract.

If the model price is lower than the current market price, then the trader would want to sell contracts of the overvalued futures contract.

The relationship of supply and demand is complex, global and everchanging. Fundamental analysis can involve tracking and understanding multiple variables. Each variable can have a small or large effect on any another variable in the pricing model.

Traders who are using fundamental analysis should always be looking for signals in the market that could impact the balance of supply and demand. And they should also recognize there can be influences, outside of their analysis, that could move the price of the market they are trading.

If you have questions send us a message or schedule an online review.

Regards,
Peter Knight Advisor

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Futures Education Homepage

There are several ways for Commodity Trading Advisors to make money in the markets, but the two most common strategies fall under the categories of systematic and discretionary.

While the purpose of this lesson is not to discuss which strategy is superior, investors in managed futures should have a good understanding of these two leading strategies employed by CTAs.  Those new to managed futures should certainly comprehend the advantages and pit falls of each.  And, there are some CTAs that combine elements of both strategies!

Systematic CTAs

A systematic CTA usually makes trades based on models or computer programs.   These signals could be based on technical analysis using charts, trend following, momentum indicators, and stochastics.  Also, they could be derived from fundamental factors such as economic data like energy supply and demand, employment data etc.

A true systematic CTA will rely solely on the buy and sell signals generated by their computer model.  All human intervention and guess work or trading from the gut is eliminated.  Given that human emotions are susceptible to wide swings, trading off models keeps this issue at bay.  One of the complaints about systematic trading is that models usually need to be tweaked.    A system that appears to generate profitable signals in a high interest rate environment might not be as profitable in a low interest rate environment.  The same goes for low volatility vs. high volatility environments…which can play havoc with the best of models.

Discretionary CTAs.

Discretionary CTAs are nearly the exact opposite – trading decisions are made at the discretion of the portfolio manager.   Again, they can be based on fundamentals or technical, but a human is at the heart of the trading decision.  While the term “gut feeling” arises when talking about discretionary traders, most discretionary CTAs have very elaborate trading strategies based on solid research as well as very precisely defined risk management strategies.  But ultimately, all trading decisions lie with the traders.   As you can imagine this has pros and cons.    Unlike a model, the discretionary trader may at times let emotions get in the way.  This can lead to suboptimal results at times.

For example, during the financial crisis, the sense of panic caused many traders to make poor decisions.  But to be fair, there were models that didn’t work very well in a market panic too.

Neither strategy is fool proof – both can be profitable but can also generate losses.  This is part of the investment world.  There are CTAs with very long and successful track records in each category.

Can a CTA blend the two strategies?  Of course.  One thing about the financial markets is that they adapt over time.   A CTA could have many models they work with (the systematic component), but override final decisions at their discretions.  Or one could be a practitioner of discretionary strategies, but use computers to analyze fundamental and technical data (the systematic component).   It’s like the debate about fundamental analysis and technical analysis.  Can the two be blended?  Over the years a great many investors have had good success in the markets integrating both.

Comparison of the two strategies:

If you have questions send us a message or schedule an online review.

Regards,
Peter Knight Advisor

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Futures Education Homepage

Once an investor, whether it be a large institutional investor, a family office or a high net worth investor, decides to allocate funds to managed futures, they begin the process of due diligence. During this process, the investor will drill down to find out as much as possible about a Commodity Trading Advisor(CTA). The investor will want to know about returns, risk, length of track record, fees, investment strategy (systematic, discretionary) and dozens of other pertinent facts about the CTA. With large pension funds, allocations can run into the hundreds of millions (or higher) so you can imagine how particular and detailed this drill down can be. But even smaller investors will often want details about a particular CTA. The purpose of this module is to examine the basics of how to evaluate a CTA and his managed futures program.

Risk and Return

Many novice investors look at returns only. We are mesmerized by track records and all aim to obtain the greatest return possible. However, when more advanced investors do their homework, they also look at the risks taken to generate those returns.

We will compare two CTAs: CTA A and CTA B. Notice A generates consistent profits of between 12% and 14% over four years. CTA B has had a few years of stellar returns but also some large negative returns. Both CTAs grew the money to nearly identical sums; but CTA B did so with measurably greater volatility. His portfolio demonstrated substantial swings up and down evident of a volatile portfolio. Although CTA A took greater risk, he was not able to generate greater returns for his investors.

While some investors appreciate the wild ride in search of returns, others wish to reduce volatility in their investments. Investors with CTA B were not adequately compensated for the increased risk. When you take larger risks, you should generally be compensated with greater returns. In the investment world, you want the greatest returns consistent with the lowest risk. CTA A thus compares more favorably.

	CTA-A	CTA-B
Starting portfolio Value	$1,000	$1,000
Year one performance	12.4%	25.0%
Year two performance	13.9%	90.0%
Year three performance	13.2%	-20.0%
Year four performance	14.0%	-13.0%
Ending portfolio value	$1,652	$1,653

Sharpe Ratio

The Sharpe Ratio is a measure for calculating risk-adjusted return and has become the industry standard for such calculations. It was developed by Nobel laureate William Sharpe. The Sharpe Ratio is the average return earned (i.e. returns in excess of risk free returns) per unit of volatility or total risk. Volatility is generally measured using standard deviation.

Sharpe Ratio = Return – Risk free return/standard deviation

In our CTA example above, CTA B would have a lower Sharpe Ratio than CTA A because of the large volatility, yet identical returns. You are penalized for taking greater risks yet failing to achieve commensurate returns.

The greater the Sharpe Ratio, the greater the risk–adjusted return; investors would like to see this number as high as possible. Usually, a Sharpe Ratio of 1.0 or greater is considered to be good and implies that for every unit of risk you assume, you achieve an equal amount of return. In short, the larger the Sharpe Ratio the better. Negative Sharpe Ratios are also possible.

In the absence of additional information, a Sharpe Ratio alone is not as informative. But its becomes more useful when you compare the Sharpe Ratios of several CTAs.

Drawdowns, Depth of Drawdown and Recovery

Another critical item investors look at with managed futures accounts is drawdowns, which are the peak to valley performance of a managed futures account.

Since most CTAs report their performance numbers monthly, investors can look to see the largest losses or drawdowns in any given month. Investors can also look well beyond the drawdowns themselves. They look for length of drawdown: is it just one month, or several months?

They also look for the amount of time need to recover from a drawdown. Ideally you want small, infrequent drawdowns with quick recovery times. A general rule practiced by investors is to have drawdowns representing no more than 50% of the CTAs annualized returns. So, if a CTA obtains 20% annualized returns over time, you would want to see no more than a 10% drawdown in any given month.

Moreover, some investors require greater detail on drawdowns and want information on daily drawdowns.

For example, say a CTA shows a monthly drawdown of 10%. While that gives you some information, it does not let you know how things are going day-to-day. CTAs that take great risks might have drawdowns intra month of far greater than 10%, but you could not glean this from a monthly drawdown report and would need daily data.

Digging Beyond Returns

Looking at the diagram below, you can see a comparison of returns, risk (standard deviation), Sharpe Ratios and drawdowns.

10 Year Annualized Returns	17.54%
Std Deviation	13.98%
Sharpe Ratio	0.89
Max Monthly Drawdown	9.47%
Max Drawdown	12.71%

10 Year Annualized Returns	17.91%
Std Deviation	31.22
Sharpe Ratio	0.44
Max Monthly Drawdown	19.88%
Max Drawdown	30.07%

Notice, both CTAs have very similar 10-year returns. But the risk (as measured by standard deviation) of CTA 2 is substantially higher than CTA 1. CTA 2 took 2.5 times the risk, but achieved a mere 37 more basis points of return than CTA 1. Clearly, investors with CTA 2 were not compensated with higher returns, making the Sharpe ratio for CTA 2 is much lower than CTA 1.

In addition, consistent with higher risk are higher drawdowns. With CTA 2, the drawdowns are substantial (more than twice CTA 1) and are greater than 50% of the annualized returns; a rule many investors do not like to see violated.

In Summary

Sophisticated investors look well beyond returns on an investment to see what risks are taken to generate those returns, the Sharpe Ratio compared with other CTAs and how steep drawdowns are in relationship to annualized returns.
While there are many other elements that go into choosing a CTA, these make for a solid start. The topic of due diligence is vast and investors, especially institutional investors, will take months, if not longer, investigating a potential CTA candidate for investment.

Regards,
Peter Knight Advisor

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Gold Performance Homepage

1) Disclosure of Trading Methodology (21:11)

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1) Gold Symbol (GC)

1.1)   20 Year chart using monthly data
1.2)   10 Year Chart, monthly Data
1.3)   3 Year chart, weekly data
1.4)   3 month chart, daily data
1.5)   10 day chart 60 minute data
1.6)   Today’s using 5 minute data
1.7)   Today’s Technical Opinion
1.8)   Ranges & Price Performance
1.9)   Support & Resistance
1.10) Barchart Quotes, All Deliveries
1.11) Barchart Options Quotes
1.12) CME Futures Quotes, All Deliveries
1.13) CME Option Quotes
1.14) Contract Specifications each 1.00 = $100.00
1.15) Exchange Margin Requirement
1.16) Gold Collar Analysis Page
1.17) Gold Collar Spreadsheet

2) Silver Symbol (SI)

2.1) Silver Quotes (SI)
2.2) SI 2000-2018
2.3) SI Option Quotes
2.4) SI Technical Opinion
2.5) SI Contract Specifications ($1.00 = $50.00)
2.6) Silver Futures Video

3) Platinum Symbol (PL)

3.1) Platinum Quotes (PL)
3.2) PL 2000-2018 chart
3.3) PL Option Quotes
3.4) PL Technical Opinion
3.5) PL Contract Specifications ($1.00 = $50.00)
3.6) Platinum Futures Video

4) Copper Symbol (HG)

4.1) Copper Quotes (HG)
4.2) HG 2000-2018 chart
4.3) HG Option Quotes
4.4) HG Technical Opinion
4.5) HG Contract Specifications ($0.01 = $250.00)

5) Palladium Symbol (PA)

5.1) Palladium Quotes (PA)
5.2) PA 2000-2018 chart
5.3) PA Option Quotes
5.4) PA Technical Opinion
5.5) PA Contract Specifications ($1.00 = $50.00)

6) Metals Spreads

6.1) Platinum (PL) – Gold (GC)  20 year using monthly data
6.2) PL–GC last 12 months using daily data
6.3) Understanding Platinum and Gold Spread (Video)

6.4) Gold GC) Silver (SI) Ratio 20 year using monthly data
6.5) GC/SI last 12 months using daily data
6.6) Gold & Silver Ratio Spread (Video)

6.7) Palladium (PA) – Gold (GC) 20 year using monthly data
6.8) PA – GC last 12 months using daily data

6.9)   Gold (GC) Copper (HG) Ratio 20 year using monthly data
6.10) GC/HG last 12 months using daily data

6.11) Gold (GC) Oil (CL) Ratio last 20 years using monthly data
6.12) GC/CL last 12 months using daily data

7) Gold to Major Currencies

7.1) Gold (GC) Priced in British Pounds (B6) 20 year
7.2) GC/B6 last 12 months using daily price data

7.3) Gold (GC) Priced in Australian (A6) 20 year
7.4) GC/A6 last 12 months using daily price data

7.5) Gold (GC) Priced in U.S. Dollars DX 20 year
7.6) GC/DX last 12 months using daily price data

7.7) Gold (GC) Priced in Euro Currency (E6) 20 year
7.8) GC/E6 last 12 months using daily price data

7.9)   Gold (GC) Priced in Canadian (D6) 20 year
7.10) GC/D6 last 12 months using daily price data

7.11) Gold (GC) Priced in Japanese Yen (J6) 20 year
7.12) GC/J6 last 12 months using daily price data

7.13) Gold (GC) Priced in Swiss Franc (S6) 20 year
7.14) GC/S6 last 12 months using daily price data

8) Gold to Global Stock Indices

8.1) S&P 500 (ES) Gold (GC) Ratio 20 year using monthly data
8.2) ES/GC last 12 months using daily data

8.3) Euro Stoxx 50 (FX) Gold (GC) Ratio 20 year using monthly data
8.4) FX/GC last 12 months using daily data

8.5) FTSE 100 (X) Gold (GC Ratio) 20 year using monthly data
8.6) X/GC last 12 months using daily data

8.7) DAX (DY) Gold (GC) Ratio 20 year using monthly data
8.8) DY/GC last 12 months using daily data

8.9)   CAC 40 (MX) Gold (GC) Ratio 20 year using monthly data
8.10) MX/GC  last 12 months using daily data

9) Gold to Energy

9.3) Gold to New York Crude Oil  20 year using monthly data
9.4) GC/CL last 12 months using daily data

9.3) Gold to Heating Oil  20 year using monthly data
9.4) GC/HO last 12 months using daily data

9.1) Gold to New York Wholesale Gasoline  10 year using monthly data
9.2) GC/RB last 12 months using daily data

 10) Primary Metals Exchanges

10.1) Chicago Mercantile Exchange/Comex
10.2) Additional Gold trading Information From the CME
10.3) London Metal Exchange

If you have questions send us a message or schedule an online review .

Regards,
Peter Knight Advisor

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1) Looking at income relative to increases in the cost of living in the US I really don’t see true long-term US economic recovery occurring.

1.1) Median household income 1986 $52,068 to $59,039 = +12.22%
1.2) Median home price 1986 $92,025 to $328,600 = +257.08%
Income in gold 141.41 ounces in 1986 to 44.34 in 2017 = -68.65%
Median Home Price in gold 249.93 ounces down to 245.21 = -1.89%
1.3) Mortgage debt  1986 436.1 billion up to 1,321.9 billion in 2017 = +203.11

Growth of the US National Debt in Gold

2) Compare Median Household Income to other costs.

2.1) Median Household Income 2000 $58,544 to $59,417 2017 = +1.49%
2.2) Median Rent Indexed to 2000 = +74.4%
2.3) Groceries indexed to 2000 = +97.60%
2.4) Health care indexed to 2000 = +135.60%
2.5) Gasoline indexed indexed to 2000 = +93.70%
2.6) Consumer price indexed to 2000 = +46.50%
2.7) Gross Domestic product 2000 12.35T up to 17.27T 2018 = +39.75%
2.8) S&P 500 2000 1,394.46 up to 2,762.13 in 2017 = +98.07%
2.9) Tax receipts. median home, M1, gold, CPI

3) I believe the US has misrepresented true inflation for more than 2 decades to contain US debt service cost. Low inflation justifies artificially low Treasury deposit rates which is saving the US Government trillions in debt service costs and made US budget deficits  appear less horrific. Since 1986 US Federal debt has increased by 859.05% yet US Federal debt service cost by only 102.89%.

3.1) Federal debt to debt service cost
3.2) National debt 1986-2017 = + 859.05%
3.3) US debt service cost 1986-2017 = +102.89%

4) These negative rates of return stripped savers of trillions of dollars in interest income that would have been spent in the free market economy.

4.1) CPI relative to short term deposit rates (negative rates of return)
4.2) CPI relative to long term deposit rates

5) With near zero inflation, historic low short-term deposit rates and record low borrowing costs for banks, credit card rates never went below 11.96%. Adding insult to injury The Fed created over 1.7 trillion US dollars with keypunch entries to bail out these banks which enabled the problem to occur in the first place.

5.1) US bank borrowing cost to lending rate
5.2) Emergency purchases of bank debt by the Federal Reserve

6) If US inflation were to be reported using 1990 CPI calculations deposit rates would rise with US debt service cost increasing by over 800 billion annually, using 1980 calculations over 1.6 trillion annually.

33) CPI using pre 1980 & 1990 calculations.
51) BLS.GOV “official CPI

7) During “Economic Recovery” savers were stripped of trillions in interest income, US Federal debt to GDP, Federal debt to income and Federal debt to the employed population are all at or near record highs.

7.1) US debt to GDP ratio at 103.74%
7.2) US debt has grown 5 times faster than  personal income ratio
7.3) US debt +859.05%  employed population +6.80%

8) The Fed has created over 4 trillion US dollars backed by no tangible asset or income flow which in the long-term will be detrimental to the US dollar.

8.1) Total purchased by the Fed with created money

9) US fiscal mismanagement hasn’t gone unnoticed, there are now 11 countries with a higher credit rating than the United states.

9.1) US credit rating versus other countries

10) The US dollar is now in an established down-trend

10.1) 20 Year Chart US dollar Index

11) The United States is vulnerable to liquidation of US assets help by foreign investors, the 6.3 trillion in US Treasuries is just the tip of the iceberg.

11.1) US Treasury debt held by non US investors

12) I believe USD selling will engage, net new USD shorts will enter the market and the USD could eventually test the lows we saw in

12.1) 20 Year Chart US dollar Index

Although I always trade with the trend up or down I believe in the long-term we’ll see gold continue to outperform Global shares and currencies.

13) Global Stock Index to Gold Ratios

13.1) S&P 500 (ES) Gold (GC) Ratio 20 year using monthly data
13.2) ES/GC last 12 months using daily data

13.3) Euro Stoxx 50 (FX) Gold (GC) Ratio 20 year using monthly data
13.4) FX/GC last 12 months using daily data

13.5) FTSE 100 (X) Gold (GC Ratio) 20 year using monthly data
13.6) X/GC last 12 months using daily data

13.7) DAX (DY) Gold (GC) Ratio 20 year using monthly data
13.8) DY/GC last 12 months using daily data

13.9)   CAC 40 (MX) Gold (GC) Ratio 20 year using monthly data
13.10) MX/GC  last 12 months using daily data

14) Gold Charts in Major Currencies

14.1) Gold (GC) Priced in Euro Currency (E6) 20 year using monthly data
14.2) GC/E6 last 12 months using daily price data

14.3) Gold (GC) Priced in British Pounds (B6) 20 year using monthly data
14.4) GC/B6 last 12 months using daily price data

14.5) Gold (GC) Priced in Swiss Franc (S6) 20 year using monthly data
14.6) GC/S6 last 12 months using daily price data

14.7) Gold (GC) Priced in Japanese Yen (J6)  20 year using monthly data
14.8) GC/J6 last 12 months using daily price data

14.9)   Gold (GC) Priced in Australian (A6) 20 year using monthly data
14.10) GC/A6 last 12 months using daily price data

14.11) Gold (GC) Priced in Canadian (D6) 20 year using monthly data
14.12) GC/D6 last 12 months using daily price data

 

If you have questions send us a message or schedule an online review .

Regards,
Peter Knight Advisor

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Currency ATA Performance Homepage    Currency ATA Aggressive Homepage

1) Euro-FX – Today’s Technical Opinion  Symbol (E6)

1.1)   20 Year Chart, Monthly Data
1.2)   5 Year Chart, Weekly Data
1.3)  1 Year Chart, Daily Data
1.4)   Last 3 Days, 15 minute data
1.5)   Technicals
1.6)   Support & Resistance
1.7)   Ranges & Price Performance
1.8)   Barchart Quotes, All Deliveries
1.9)   Barchart Options Quotes
1.10) CME Futures Quotes, All Deliveries
1.11) CME Option Quotes
1.12) Contract Specifications  each 0.01 = $12.50
1.13) Exchange Margin Requirement per 125,000 Euro FX
1.14) Option Collars
1.15) Working Example of Collaring a Position
1.16) EUR Collar Spreadsheet
1.17) Euro FX Futures Video

2) British Pound – Today’s Technical Opinion Symbol (B6)

2.1)   20 Year Chart Monthly Data
2.2)   5 Year Chart Weekly Data
2.3)   1 Year Chart Daily Data
2.4)   Last 3 Days, 15 minute data
2.5)   Technicals
2.6)  Support & Resistance
2.7)   Ranges & Price Performance
2.8)   Barchart Quotes All Deliveries
2.9)   Barchart Options Quotes
2.10) CME Futures Quotes All Deliveries
2.11) CME Option Quotes
2.12) Contract Specifications  each 0.01 = $6.25
2.13) Exchange Margin Requirement per 62,500 Pounds
2.14) Option Collars
2.15) Working Example of Collaring a Position
2.16) GBP Collar Spreadsheet
2.17) British Pound Futures Video

3) Australian Dollar – Today’s Technical Opinion Symbol (A6)

3.1)   20 Year Chart Monthly Data
3.2)   5 Year Chart Weekly Data
3.3)   1 Year Chart Daily Data
3.4)   Last 3 Days, 15 Minute Data
3.5)   Technicals
3.6)   Support & Resistance
3.7)   Ranges & Price Performance
3.8)   Barchart Quotes All Deliveries
3.9)   Barchart Options Quotes
3.10) CME Futures Quotes All Deliveries
3.11) CME Option Quotes
3.12) Contract Specifications  each 0.01 = $10.00
3.13) Exchange Margin Requirement per 100,000 Australian
3.14) Option Collars
3.15) Working Example of Collaring a Position
3.16) AUD Collar Spreadsheet
3.17) Australian Dollar Futures Video

4) Canadian Dollar – Today’s Technical Opinion Symbol (D6)

4.1)   20 Year Chart Monthly Data
4.2)   5 Year Chart Weekly Data
4.3)   1 Year Chart Daily Data
4.4)   Last 3 Days, 15 Minute Data
4.5)   Technicals
4.6)   Support & Resistance
4.7)   Ranges & Price Performance
4.8)   Barchart Quotes All Deliveries
4.9)   Barchart Options Quotes
4.10) CME Futures Quotes All Deliveries
4.11) CME Option Quotes
4.12) Contract Specifications  each 0.01 = $10.00
4.13) Exchange margin requirement per 100,000 Canadian
4.14) Option Collars
4.15) Working Example of Collaring a Position
4.16) CAD Collar Spreadsheet
4.17) Canadian Dollar Futures Video

5) Japanese Yen Today’s Technical Opinion Symbol (J6)

5.1)   20 Year Chart Monthly Data
5.2)   5 Year Chart Weekly Data
5.3)   1 Year Chart Daily Data
5.4)   Last 3 Days, 15 Minute Data
5.5)   Technicals
5.6)   Support & Resistance
5.7)   Ranges & Price Performance
5.8)   Barchart Quotes All Deliveries
5.9)   Barchart Options Quotes
5.10) CME Futures Quotes All Deliveries
5.11) CME Option Quotes
5.12) Contract Specifications  each 0.01 = $12.50
5.13) Exchange Margin Requirement per 12,500,000 Yen
5.14) JPY Collar Spreadsheet
5.15) Option Collars
5.16) Working Example of Collaring a Position
5.17) Japanese Yen Futures Video 

6) Swiss Franc Today’s Technical Opinion Symbol (S6)

6.1)   20 Year Chart Monthly Data
6.2)   5 Year Chart Weekly Data
6.3)   1 Year Chart Daily Data
6.4)   Last 3 Days, 15 Minute Data
6.5)   Technicals
6.6)   Support & Resistance
6.7)   Ranges & Price Performance
6.8)   Barchart Quotes All Deliveries
6.9)   Barchart Options Quotes
6.10) CME Futures Quotes All Deliveries
6.11) CME Option Quotes
6.12) Contract Specifications  each 0.01 = $12.50
6.13) Exchange Margin Requirement per 125,000 Swiss
6.14) Option Collars
6.15) Working Example of Collaring a Position

7) Gold in Major Currencies

7.1) Gold (GC) Priced in Euro Currency (E6) 20 year using monthly data
7.2) GC/E6 last 12 months using daily price data

7.3) Gold (GC) Priced in British Pounds (B6) 20 year using monthly data
7.4) GC/B6 last 12 months using daily price data

7.5) Gold (GC) Priced in Swiss Franc (S6) 20 year using monthly data
7.6) GC/S6 last 12 months using daily price data

7.7) Gold (GC) Priced in Japanese Yen (J6) 20 year using monthly data
7.8) GC/J6 last 12 months using daily price data

7.9)   Gold (GC) Priced in Australian (A6) 20 year using monthly data
7.10) GC/A6 last 12 months using daily price data

7.11) Gold (GC) Priced in Canadian Dollars (D6) 20 year using monthly data
7.12) GC/D6 last 12 months using daily price data

If you have questions send us a message or schedule an online review .

Regards,
Peter Knight Advisor

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Gold ATA Performance Homepage

1) Gold – Today’s Technical Opinion  Symbol (GC)

1.1)   20 Year Chart, Monthly Data
1.2)   5 Year Chart, Weekly Data
1.3)   1 Year Chart, Daily Data
1.4)   Technicals
1.5)   Support & Resistance
1.6)   Ranges & Price Performance
1.7)   Barchart Quotes, All Deliveries
1.8)   Barchart Options Quotes
1.9)   CME Futures Quotes, All Deliveries
1.10) CME Option Quotes
1.11) Contract Specifications  each 1.00 = $100.00
1.12) Exchange Margin Requirement
1.13) Gold Futures Video
1.14) Defining Trend, Trade Duration & Number of Contracts Traded
1.15) Option Collars
1.16) Working Example of Collaring a Position

2) Economic Calendar

If you have questions send us a message or schedule an online review .

Regards,
Peter Knight Advisor

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Index Analysis Homepage (all indices charts & quotes)

Disclosure of long/short defined risk trading methodology (21:56)

Links to track trades

1) S&P 500 Symbol (ES)

1.1) 1983 – 2018 chart
1.2) 10 Year, Monthly Data
1.3) 3 Year, Weekly Data
1.4) 6 Month Daily Data (ESM23)
1.5) 10 Day Using 60 Minute (ESM23)
1.6) Today’s using 5 minute data (ESM23)
1.7) Today’s Technical Opinion (ESM23)
1.8) Ranges & Price Performance (ESM23)
1.9) Support & Resistance (ESM23)
1.10) Barchart Quotes, All Deliveries
1.11) Barchart Options Quotes
1.12) CME Futures Quotes, All Deliveries
1.13) CME Option Quotes
1.14) Contract Specifications each 1.00 = $50.00
1.15) Exchange Margin Requirement
1.16) S&P 500 Collar Spreadsheet

2) Educational videos and links to get you up to speed

2.1) Basics of the Futures
2.2) Basics of Futures Options
2.3) S&P Educational Videos and Links
2.4) Introduction to Order Types
2.5) Detailed Description of Order Types With Examples
2.6) Understanding Futures Margin Requirements
2.7) Understanding Moving Averages
2.8) Understanding Support and Resistance
2.9) About Bollinger Bands & How to Set Them
2.10) Defining Trend, Trade Duration & Number of Contracts Traded
2.11) Explaining Call Options (Short and Long)
2.12) Explaining Put Options (Short and Long)
2.13) Option Collars
2.14) Working Examples of Collaring Positions and Potential Profit/Loss
2.15) 20 year chart of the S&P Priced in Gold
2.16) Test this strategy on any Bull or Bear market from 1983 to 2018
2.17) Test this strategy on any of these 17 related and unrelated markets
2.18) Quotes, charts and analysis for all 500 stocks
2.19) SEC filings & information for all 500 stocks

3)_Major/Minor Bull, Bear markets

3.1) 1983-2019 chart
3.2) January 1983 – August 1987 Bull 139.72 – 337.89 =+141.83%
3.3) August 1987 – October 1987 Bear 337.89 – 216.47 =-35.93%
3.4) August 1987 – August 1989 Bear to recovery (2 years)
3.5) August 1987 – July 1990 Bull 216.47 – 369.78 = +70.82%
3.6) July 1990 October 1990 Correction 369.78 – 294.51 =-20.36%
3.7) July 1990 – February 1991 Correction to recovery (7 months)
3.8) October 1990 – July 1998 Bull 294.51 – 1,190.58 =+304.26%
3.9) July 1998 – October 1998 Correction 1,190.58 – 923.52 =-22.43%
3.10) July 1998 – November 1998 Correction to recovery (4 months)
3.11) October 1998 – March 2000 Bull 923.52 – 1,552.87 =+68.15%
3.12) March 2000 October 2002 Bear 1,52.87 – 768.63 =-50.50%
3.13) March 2000 December 2007 Bear to recovery (7 years 9 months)
3.14) October 2002 – October 2007 Bull 768.63 – 1,576.09 =+105.05%
3.15) October 2007 – March 2009 Bear 1,576.09 – 666.79 =-57.68%
3.16) October 2007- April 2013 Bear to recovery (5 years 6 months)
3.17) March 2009 – January 2018 Bull 666.79 – 2,872.87 = +330.87%

4) S&P 500 Symbol ES

4.1) 6 Month Chart, Daily Data
4.2) 3 Year Chart, Weekly Data
4.3) 7 Year Chart, Monthly Data
4.4) Today’s Technical Opinion
4.5) Futures Quotes
4.6) Options Quotes
4.7) Contract Specifications

5) Euro Stoxx 50 Symbol FX

5.1) 6 Month Chart, Daily Data
5.2) 3 Year Chart, Weekly Data
5.3) 7 Year Chart, Monthly Data
5.4) Today’s Technical Opinion
5.5) Futures Quotes
5.6) Options Quotes
5.7) Contract Specifications

6) Stoxx E600 Banks Symbol FA

6.1) 6 Month Chart, Daily Data
6.2) 3 Year Chart, Weekly Data
6.3) 7 Year Chart, Monthly Data
6.4) Today’s Technical Opinion
6.5) Futures Quotes
6.6) Contract Specifications

7) Dax Index Symbol DY

7.1) 6 Month Chart, Daily Data
7.2) 3 Year Chart, Weekly Data
7.3) 7 Year Chart, Monthly Data
7.4) Today’s Technical Opinion
7.5) Futures Quotes
7.6) Options Quotes
7.7) Contract Specifications

8) CAC 40 Symbol MX

8.1) 6 Month Chart, Daily Data
8.2) 3 Year Chart, Weekly Data
8.3) 7 Year Chart, Monthly Data
8.4) Today’s Technical Opinion
8.5) Futures Quotes
8.6) Options Quotes
8.7) Contract Specifications

9) Swiss Market Index Symbol SZ

9.1) 6 Month Chart, Daily Data
9.2) 3 Year Chart, Weekly Data
9.3) 7 Year Chart, Monthly Data
9.4) Today’s Technical Opinion
9.5) Futures Quotes
9.6) Options Quotes
9.7) Contract Specifications

10) Hang Seng Index Symbol HS

10.1) 6 Month Chart, Daily Data
10.2) 3 Year Chart, Weekly Data
10.3) 7 Year Chart, Monthly Data
10.4) Today’s Technical Opinion
10.5) Futures Quotes
10.6) Options Quotes
10.7) Contract Specifications

11) ASX 200 Index Symbol AP

11.1) 6 Month Chart, Daily Data
11.2) 3 Year Chart, Weekly Data
11.3) 3 Year Chart, Monthly Data
11.4) Today’s Technical Opinion
11.5) Futures Quotes
11.6) Options Quotes
11.7) Contract Specifications

12) FTSE 100 Symbol X

12.3) 6 Month Chart, Daily Data
12.2) 3 Year Chart, Weekly Data
12.1) 7 Year Chart, Monthly Data
12.4) Today’s Technical Opinion
12.5) Futures Quotes
12.6) Options Quotes
12.7) Contract Specifications

13) Other markets I use this procedure on

13.1) Any of the top 100 performing ETFs on this link
13.2) Any of the top 100 performing stocks
13.3) Any of the 500 stocks in the S&P with options liquidity
13.4) U.S. Futures markets
13.5) European Futures markets

14) Program Structure and Account Opening Procedure

14.1) ATA’s, What They Are and How They Work
14.2) The Fee Structure For This Program
14.3) Defining Overall Risk For Your Account
14.4) Exchanges Traded
14.5) Brokerage Firms
14.6) How Balances Are Guaranteed Plus or Minus Trading
14.7) How To Open An Account

If you have questions send a message or contact me.

Regards,
Peter Knight Advisor

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