Wrong Use of Historical Volatility and Implied Volatility Crossovers

Not all volatilities are constructed equal. It is critical to differentiate between Historical Volatility and Implied Volatility, so retail traders learn how to trade options focused on what is material to theoretically price option spreads forward.

Historical Volatility (HV) measures past price movements of the underlying asset recording the asset's actual or realized volatility. The more commonly known type of HV is Statistical Volatility, which computes the underlying assets return over a finite but adjustable number of days. Let me explain what “finite but adjustable” means. You can vary the number of days to measure the Statistical Volatility: for example, 5-10-50-200 days, that’s how time-based moving averages and momentum/oscillator studies are built. Though, it is not the case with Implied Volatility.

Implied Volatility measures expected values by repetitively refining bid-ask estimates. These estimates are based on the expectations of buyers and sellers. The buyers and sellers (85+% of floor traded volume is driven by institutions, floor traders and market makers) behind the bid and ask values, who do change their estimates within the day, as new information be it macro-economic news or micro-economic data impacting the underlying product becomes available. What is being estimated is the underlying asset’s future fluctuation with certain assumptions embedded into the changes in information of the underlying. That refinement of bid-ask estimates must be completed within finite time-bound option expiration periods. That’s why there are monthly and quarterly option expiration cycles. You cannot change these expiration periods, either by shortening or lengthening the number of days, to “construct” a time period that gives you faster or slower crossover indicators.

Why point out the wrong use of Historical Volatility and Implied Volatiity Crossovers? It is to caution you against the defective use of HV-IV crossovers, which is not a reliable trading signal. Remember, for a given expiration month, there can only be one volatility over that specific period. Implied Volatility must leave from where it is currently trading at, to converge at zero on expiration date. Implied Volatility (be it IV for ITM, ATM or OTM strikes) must return to zero on expiry; but, price can go anywhere (up, down or stay flat).

To continually sell “overpriced” and buy “under priced” options would eventually cause the implied volatility of every single non-zero bid option to line up exactly. Meaning the phenomenon of IV’s “smiling” skew disappears, as IV becomes perfectly flat. This hardly happens, especially in highly liquid products. Take for example, the SPY, a broad-based Index; or, GLD – the SPDR Shares ETF in a fast market like Gold. With open interest at the non-zero bid strikes going into the thousands and tens of thousands, do you really think a retail off the floor trader is going to be allowed to “out price” the professional hedger on the floor? Unlikely. Calls and Puts in highly liquid products, are like items in an inventory with high supply because there is high demand. This type of inventory does not get “mispriced” because floor traders have to make a daily living from trading the Calls and Puts –they will refuse to carry the risk of mispricing overnight.

So, what are the key considerations to banking in your edge as a retail trader?

• IV’s percentage impact on an option’s extrinsic value is much more sizeable for ATM and OTM strikes, versus ITM strikes which are laden with intrinsic value but lack extrinsic value. Most retail option traders with an account size USD $25-$50K (or less), gravitate towards ATM and OTM strikes for reasons of affordability. The deeper the ITM you go, the wider the Bid-Ask spread becomes compared to the narrower Bid-Ask spread differences in the ATM or OTM strikes, making ITM strikes more costly to trade.
  

• When you trade IV, you are buying time decay for a rise in IV at a % point below; or, selling time premium for a drop in IV at a % point above the theoretical price of market value, that participants are willing to pay or sell for. Depending on the market ranges of that day, price debit spreads to get filled at 0.10-0.15 below the Theoretical Price of the spread. With credit spreads, raise the credit to sell the spread by 0.10-0.15 above the Theoretical Price of the spread. The price you pay below; or, receive above the Theoretical Price of a spread is your edge, purely based on price-performance of Implied Volatility alone. Remember, you Theoretically Price a spread to fill the order for its forward value, never backward.

Where can I learn how to trade options with consistent profits focused on Implied Volatility without Historical Volatility? See Trading Profit | Consistent Results to view a model retail option trader’s portfolio that excludes the use of HV and focuses on trading only IV.

I’ll cite these actual historical events, to bolster the argument for removing Historical Volatility from your trading process altogether.

27 Feb, 2007: Widespread Panic from the sizeable China sell-off in equities. If you were trading the options of an index like the FXI which is the iShares product of China’s 25 largest and most liquid Chinese companies though listed in the US; but they are headquartered in China, you would have been impacted. While you can argue it’s possible to have market events recreate the ranges of the Dow, Nasdaq & S&P, how do you recreate the scenario of the VIX and VXN soaring 59% and 39%?

22Jan, 2008: Fed cuts rates by 75 basis points prior to the scheduled policy meeting on Jan 30th, whereby the FOMC cut another 50 basis points on the date of the meeting. If you were trading interest-rate sensitive sectors using the options on a Financial ETF or a Banking Index like the BKX; or, the Housing Index like the HGX, you would have been impacted. And in the current environment of rates being near zero, the FOMC while they still have a rate policy tool, they are unable to cut rates by the same number of basis points like before. What was a historical event is not successively repeatable going forward, not until rates are raised again and subsequently they get cut again.

Question: How do you reconstruct history? That is the history of events forming Historical Volatility. The answer is in the real examples cited, as with any other financially related historical event - you cannot reconstruct history. You may be able to mimic parts of HV but you cannot repeat it in its entirety. So, if you continue using HV-IV crossovers, you visually confuse yourself by searching for volatility “mispricing” patterns that you would like to see; but, you will end up with poor profit performance instead. It makes more practical trading sense to focus purely on IV; then, diversify the trading of volatilities across multiple asset classes beyond equities.

Where can I learn more about trading IV across multiple asset classes using only options, without having to own stock? See details of an Original Curriculum, that uses IV Mean Reversion/Mean Repulsion and IV Forecasting, as reliable methods to trade the implied volatilities across broad-based Equity Indexes, Commodity ETFs, Currency ETFs and Emerging Market ETFs.

Fundamental Flaw in Fundamental Analysis and Stock Picking

Clinging on to Fundamental Analysis and stock picking software, only keeps you stuck in trading equities. Trading this way, compounds concentration risk in one asset class and fails to adequately diversify risks across Equities, Bonds, Currencies and Commodities. There’s much more to stock option trading, than stock itself.

I cite Benjamin F. King’s study, quoted repeatedly since 1966, because it remains valid and has yet to be disproved to the point of dismissing its logic.

Market and Industry Factors, Journal of Business, January 1966: “ Of a stock’s move ...

• 31% can be attributed to the general stock market,
  
• 13% to industry influence,
  
• 36% to influence of other groupings, and the remaining
  
• 20% is peculiar to the one stock.”
  

There must be a more compelling reason for you to trade stock other than just for the movement, if only 20% is unique to the underlying equity in question. Consider this, in context of the Fundamental Analysis or stock picking software that you bought on a per $1 basis. For each $1 dollar you spend, you “outsourced” the analysis at a cost of 80 cents, only to receive back 20 cents worth of work. Shouldn’t the 80:20 rule of “outsourcing” be the other way round? The problem is that you are still stuck with 80% of the work, to analyze price movement! Plus, the more you use FA techniques/stock picking software, the more trading capital is stuck in equities alone.

Now, you can say “special” research papers help you pick stocks. Let’s have a look at some of the more common fundamental metrics in these research subscriptions:

1. Dividend Yield: the problem is in the variability of yields as firms are in different stages of their business development. A Mature company that dominates in a well established sub-segment/sector is able to afford a different dividend yield; versus, a Young company in a growth-oriented field; versus, a Small firm in a growing area that may not be able to afford a dividend payout. Bear in mind there is nothing special about firms that pay a dividend.

A company that gives away a portion of it’s retained earnings - which is what a dividend is - effectively gives away part of its valuation, which means it is not worth as much as a company that does need to give investors candy to commit capital to it. So, a dividend paying stock has to be far superior to a non-dividend paying stock for reasons other than the dividend. If it is not, there’s no point looking for dividend paying products to trade, there are plenty of non-dividend paying Indexes to trade.

2. Price/Book Ratio: the problem is this metric varies across industries and from company to company, as the asset base and capital structures of companies change over time. It lacks cross sector applicability and accounting complexity arises from a firm’s capital structure as it changes due to acquisitions/divestments/CAPEX for new product lines; or, product line cut-backs, as recently seen in the restructuring of major US car companies.

3. Price/Cash Flow Ratio (the cousin of the P/E): accounting laws on depreciation vary across Asia, Europe and US. As accounting rules are driven by tax codes, which change considerably across regions despite adoption of global accounting standards, there is a lack of uniformity in homogenizing a fundamental ratio that will fit as a common benchmark across geographies.

These metrics fail to help you compare say a Dell parented in the US to an Acer parented in Taiwan; but, is listed as an ADR in the US, even though both are competitors in the same sector as computer manufacturers.

Furthermore, the current dislocated cost of capital in credit markets, impairs the ability of corporations to optimize the operating cost of their balance sheets. In essence, corporations are left with the working capital cash flows remaining on their balance sheets, as testament to their financial strength. Do not waste your money on Fundamental Analysis software or research paper subscriptions.

As there is a fundamental flaw in fundamental analysis and stock picking, how do you select trades? Trade the options of a broad-based Equity Index to replace single stock exposure. To replace Fundamental Analysis, use the Relative Strength measure based on Point & Figure methods.

What is Relative Strength? It is nothing more than taking one price as the Numerator, divided by another price as the Denominator, then multiplied by 100. RS = (Price 1 / Price 2) x 100. Typically, RS calculations use daily closing prices. Though simple in its mathematical construction, RS is ingeniously powerful when it is applied not only within a sector; but, across sectors and between asset classes.

Let’s start of within a sector. For example, if you choose 2 semiconductor stocks trading at different prices, how do you know if one stock is outperforming the other in the same sector, when the 2 stocks have price changes at different rates; plus, the sector’s price itself is also changing?

SOX = Semiconductor Sector Index, trades up from 452.24 to 467.81.

Numerator1: Price1 = BRCM 33.15 RS1 = 7.33 Price2 = 33.80 RS2 = 7.23
Numerator2: Price1 = TSM 9.91 RS1 = 2.19 Price2 = 13.43 RS2 = 2.87
Common Denominator: SOX Price 1 = 452.24 Price 2 = 467.81

BRCM’s RS1 = (33.15/452.24) x 100 = 7.33. BRCM's RS2 = (33.80/467.81) x 100 = 7.23.
TSM’s RS1 = (9.91/452.24) x 100 = 2.19. TSM's RS2 = (13.43/467.81) x 100 = 2.87.

BRCM's price rises from 33.15 to 33.80 and TSM's price also rises from 9.91 to 13.43. Simply because BRCM is a larger stock, does that mean it benefits from the SOX trading up? No, the RS reading (RS1 compared to RS2) shows BRCM’s RS reading dropped (7.33 down to 7.23) against TSM’s RS reading, which increased (2.19 to 2.87). RS confirms TSM as the outperformer rising in price strength versus BRCM’s weakened price. RS is constructed on pure price rules. Using an Index as the denominator, acts as a much more durable benchmark and is structurally more reliable, compared to any “magical” TA indicator; or, combination of income statements, balance sheets and cash flow statements touted in stock picking programmes.

You can replace BRCM or TSM with Indexes or ETFs. Using Indexes with Relative Strength enables a common denominator to compare Equities against Bonds, Commodities and Currencies, to crossover into asset classes other than stocks to trade. It’s not that Relative Strength is infallible. But compared to the fundamental metrics cited above, Relative Strength fails the least. Break the mould on what you learnt about stock option trading.

Is there an example of an optionable and consistently profitable portfolio that trades using Relative Strength across multiple asset classes? Yes. See Trading Profit | Consistent Results to view a retail online option trading portfolio that excludes the use of single stocks and Fundamental Analysis, using broad based equity Indices, Commodity ETFs and Currency ETFs. There is no need to trade FX directly. Just trade the options of Currency ETFs.

Candlesticks & OHLC Bars Lose their Patterns on a Distribution Curve

Time-based charts (namely Candlesticks, OHLC Bars and Heikin-Ashi) fail to truly depict price. This article will help you realize that time-based pattern recognition is an unreliable method for stock option trading.

Some retail training firms like to popularize the myth that, “Everyone looks at these patterns in the charts”. They are partly right. Though, their use of the term “Everyone” applies to retail off-the-floor traders who collectively only make up ~ 15% at most, in some cases even less, of the total traded volume on exchanges, depending on which exchange it is.

Which raises the question: What are the eyes of those on the floor moving 80+% of traded volume looking at? Some of you have visited the exchanges organized through your broker. If you’ve picked up the paper scattered on the floor, all you’ll find is quick math notation: addition, subtraction, division and multiplication. Nothing more. No drawings of a Tri-Star Doji, Dumpling Tops or Frypan Bottoms. It makes sense, because all that is in front of floor traders are screens with price data and price alone. With truck loads of calls and puts to hedge, floor traders could care less how many times during the day, price touched the tail of a dragon fly doji. They’ve already pre-planned to get more of; or, offload their inventory of calls/puts at a specific strike, for a given price.

As a retail option trader, trading less than 10 contracts per trade, you are not exempt from tuning your eyes to focus only on price. How do you simulate the observation of price alone from off-the-floor, if you remove the use of Candlesticks, OHLC Bars and Heikin-Ashi charts? Use Point & Figure charts instead.

Why is it valid to only use Point & Figure charting for trading options? It is the only method that plots just one type of data – price alone without time – price is the only data element needed on a distribution curve. The same distribution curve used in the Bjerksund-Stensland, Black-Scholes or Binomial pricing models in your options trading platform.

What about other charting methods like Candlesticks and OHLC Bars? Let’s take the Doji, a well known candlestick, as an example. The Doji is characterized by it’s Open and Close at the same price, the High is a different price from the Low. Remember with a Distribution Curve, it records Price on the Horizontal axis and Frequency on the Vertical axis. To map the doji onto the relevant axis of the distribution curve, it needs to be flipped on to its side, for the doji’s price points to line up against the vertical axis. So, a price that Closes at the same price it Opened, is recorded as 2 price points with twice the frequency of the High and Low. With a distribution curve, you cannot leave the lines joining the dots of the doji on the graph. All that is mapped is 4 dots representing the doji’s price points. Take away the lines joining the dots. Question: Where’s the doji? Not relevant anymore. Same logic applies to any candlestick (spinning top, hammer, etc.). Candlesticks lose their characteristics, once they are mapped onto a distribution curve. The implication is the same for the OHLC method used to count fractals in Elliot Waves and wave counts once price is mapped in its dispersion mode, the waves lose their characteristics.

To visualize this problem with time-based charts, watch the video on Why Time-Based Charts (Bar/ Candlesticks/Heikin Ashi, etc.) lose their characteristics once mapped onto a Distribution Curve.

Is it necessary to reconcile a charting method with the distribution curve? Yes, 68% is equal to one Standard Deviation (?). –/+1? sets the parameters for the probabilities, which you construct an option spread around to test if the strikes will be touched or not touched, from the date a spread is filled till its expiry date.

Bear in mind, changing the time frames in time-based charts be it Candlesticks, Heikin-Ashi, OHLC from minute/hour/day/week to reconcile conflicting patterns in one time-frame against another, does nothing to help you work out the Theta as decay in a debit spread; or, the positive Theta as premium sold in a Credit spread. The only unit of time required to feed into a Theoretical pricing model is the expiration date, in turn affecting the probabilities per day for the number of days that passes. As the units of time in time-based charts have no value in Theoretically pricing an option, it makes no sense to use them.

So, what are time-based charts (Candlesticks, OHLC Bars and Heikin-Ashi) useful for? They are useful, for trading the underlying itself. When you trade the underlying itself, aside from dealing with +/- Delta (directional risk), all the other Greeks (Gamma, Theta and Vega) are equal to zero. Time-based charts are relevant for trading deep ITM options as a surrogate to the product for purely directional trading of the underlying itself.

Do bear in mind with options, the deeper the ITM you go, the wider the Bid-Ask spread becomes compared to the narrower Bid-Ask spread differences in the ATM or OTM strikes. Have you got enough capital in the account to keep trading at the ITM strikes only? This is why many retail traders with account sizes below USD $25K look for increasing lower priced products, for e.g. $20 and below, as they search for ITM strikes that are affordable for them to trade using Candlestick/OHLC/Heikin-Ashi charts. By virtue of being lower priced, these products often suffer illiquid open interest at their strikes, making you chase price for an uncompetitive fill, only to result in poor price-profit performance. The other extreme is to over spend on ITM strikes of a higher priced product, for example $100 and above, as you found a trade candidate using some “special” pattern scanning software, only to breach the money management rule of 2%-5% per trade, in filling the order.

Is there an example of a portfolio with consistent wins and limited losses that applies Point & Figure methods without the use of Candlesticks/OHLC/Heikin Ashi? Yes. See Trading Profit | Consistent Results to view a retail option trader’s portfolio that only uses Point & Figure techniques. Other than stock option trading, the portfolio includes option trades from non-equity asset classes.

Light is needed to see; but, trading enlightenment will not come from a candlestick. And counting fractals within waves only serves to oscillate your pupils.

Portfolio Measures and Trade Performance Metrics

The Reward of Profit and the Risk of Losses for retail option trading needs to be managed at 2 related levels of performance: Portfolio and Trade Specific.

At the Portfolio level for online options trading, there are 3 types of Targets that must be set, even before you trade.

Maximum Return Target: complete achievement of the “ideal” measure. Dream of the “ideal” that stretches you beyond what is practical. For example, earn 2-3 times your monthly living expenses with the monthly trading profit. This is to stretch your imagination well beyond mediocrity. Even if you fail, you just might end up with more than your original target.

Minimum Return Target: the lowest acceptable measure, achievable under most conditions, excluding a catastrophic market event. Use the historical annualized return of the S&P 500 between 10%-12% (prior to the 2008 financial pandemic), as the lowest acceptable boundary. The S&P 500 being a widely accepted benchmark for trading equities is adequate to base the minimum target off, though your portfolio needs to be profitable – being ahead of the $SPX in negative territory does not count. Below the historical annualized return range of 10%–12%, is the 3 Month T-Bill, presently near zero. While the T-bill theoretically represents an “absolutely” zero risk investment, even the safest investments will still carry a residual amount of risk no matter how small that risk is. The point is this. You got into options and all that Greek terminology, not to make salads; but to beat the performance of equities as an asset class. If your portfolio's return is between what is near zero-risk and 10%–12% per annum, you are just delaying reaching a point of pain that marks failure in grasping the base-line ability to control risks. If the returns of your portfolio are between 0%–12% and you plan to continue trading options, processes within your trading process will need to be re–engineered.

"Halt Trade" Target: cumulative losses reach an absolute amount below the Minimum Return, making it necessary to stop trading altogether for a stated period. 10% of [(60% x Cash Balance at the start of the year); or Net Liquidating Value]. Example, for a $50,000 trading account, 10% x (60% x $50,000) = $3,000 of losses in total, is the absolute amount to halt trading. Why 10%? Blowing up your self-funded capital is final. There is no bail out package, as a home options trading business does not have access to bank loans; or, shareholders’ equity to finance your personal trades.

Now, drilling down to Trade Specific performance measures.

Even before you calculate the metrics, characteristically, what makes for a consistently managed portfolio are these traits:

• The largest loser does not wipe out the largest winner. The largest winner should be in multiples of the largest loser, for e.g. 2-3 times more.
  
• Above the largest loss, there are many more winners with progressively higher profit values than the value of the largest loser.
  
• The profits should step up gradually, depending on the size of your account. If it’s in the tens of thousands, the profits should step up consistently like a ladder from the low hundreds, to the higher hundreds; then, move up from the higher hundreds into the thousands. If your account is above $100K, profits should step up from the high hundreds into the thousands. Profits that jump from low hundreds into the thousands signal an over-reliance on gapping plays, which fail to help you step up consistently profitable results.
  

Where can I see this step up function in a consistently profitable portfolio, with these portfolio measures and trade performance metrics? See Trading Profit | Consistent Results to view a model retail option trader’s portfolio that shows these traits.

Moving onto the hard metrics. There’s 2 ways to count the Return on your trading capital.

• The first way is to take the Total Profit of the trading account and divide it by the Start of Year Cash Balance, as of 01/01/YYYY.
  
• The second way is if you take the Total Profit of the trading account and divide it by the ongoing Net Liquidating Value.
  

In both cases, you can minus the Total Cost of Commissions from Total Profit, to get a Total Net Profit number. Then, divide the Total Net Profit by the Start of Year Cash Balance; or, Net Liquidating Value. Net Liquidating Value is how much your entire trading account is worth, which is equal to Total Cash + Options Value + Stocks Value + Commodities Value + Bonds Value. The Start of Year Cash Balance is straightforward – it is the money in the account at the beginning of that trading year. Cash increases when you are short securities; but, cash decreases, as you get long on securities.

To review your performance, calculate these metrics using the Profit (wins) and Loss (losers) from your account:

• Win/Loss Probability: is the number of wins divided by the total number of trades. The other way to express this Win/Loss ratio is to take the number of wins and divide it by the number of losers. The Win/Loss Probability; or, Wins per 1 Loss measures your ACCURACY in selecting trades.


• Average Win is equal to the sum of all profits divided by number of wins.


• Average Loss is equal to the sum of all losses divided by the number of losers.
  

The Average Win divided by the Average Loss measures how RESPONSIVE you are in taking profits and cutting losses.

Combine the Accuracy ratio with the Responsiveness ratio to get your Performance Ratio.
Performance Ratio = (Win/Loss Probability) x (Average Win / Average Loss). Always aim to maintain the Performance Ratio above 1.00. Why? The commonly known money management rule is to allocate 2%-5% of (60% x Net Liquidating Value of the account) per trade. What is not commonly practiced is the discipline of moderating a +/- 1% in trade allocation between the 2%-5% allocation.

• If you are allocating 2% per option trade, you would increase this by +1% to 3%, if you can sustain your Performance Ratio above 1.00 for the next month. Subsequently, you would increase +1% for each month that you exceed 1.00, until you reach the upper limit of 5%.


• If you are allocating 2% per option trade, you would decrease this by -1% to lower it down to 1%, if you fail to sustain your Performance Ratio above 1.00 for the next month. You would keep the allocation per trade at 1% for every subsequent month, until you are able to fix your Performance Ratio above 1.00 to raise the allocation per trade again by +1%.
  

This is how to achieve a ladder effect in stepping up profits and stepping down losses. This mechanism of stepping up/down is an indispensable tool for rewarding profit and to discipline the risk of losses. It forces you to improve both ACCURACY and RESPONSIVENESS before raising your position size.

Where can I learn more about portfolio measures and trade performance metrics as part of a total trading system? See details of an Original Curriculum, for 55 hours of video-based learning of online options trading from home.

Intermarket Analysis in Brief for Retail Asset Allocation

If you are trading a mix of Verticals, Calendars and Iron Condors across highly liquid indexes like the DJX, DIA, MNX, QQQQ, RUT, SMH, SPY and XSP, is your trading risk adequately diversified? No.

In choosing the MNX, QQQQ, SMH, SPY and XSP, there is a duplication of stock components in these Indexes: for example, AMAT (Applied Materials) is a component of all 5 Indexes. Bear in mind the MNX and the QQQQ are both smaller versions of the Nasdaq100 Index, the only difference being the MNX is an European styled cash settled Index and the cubes (QQQQ) is an American style stock settled Index. Another example, Apple (AAPL) is a component of the MNX/QQQQ and SPY/XSP - both the SPY and the XSP track the S&P 500, the SPY is American style stock settled and the XSP is European style cash settled. Duplication is not diversification. Even if you allocated capital to the smaller versions of the Dow: DJX, the European style cash settled version of the DIA which is the American style stock settled version. Moreover, if you extended capital allocation to trade the RUT, thinking you are diversifying into small-cap stocks and away from large-caps, you just sunk more of your trading capital into equities. Again, you cannot achieve diversification by adding more capital in the same asset class. You need to learn how to trade options without concentration risk in stocks. Do not confuse asset category (market capitalization) with asset class.

This is where there is a need to understand Intermarket relationships. Intermarket analysis requires the simultaneous analysis of 4 main Asset Classes: Currencies (U.S. Dollar remains most liquid of all major traded currencies), Commodities, Bonds and Stocks. Synchronizing the rotation of asset allocation within your own portfolio lies in getting a grip on how these four markets interrelate with each other.

Here’s the synopsis of the relationships. Commodities lead bonds, bonds lead stocks and stocks lead commodities. The cycle holds true at least in a normal inflationary/disinflationary environment. Other than itself, Commodities affects 2 markets (Bonds and Stocks); effectively, impacting 3 out of the 4 Intermarket relationships. Even if you do not trade Commodity ETFs as part of your portfolio, you need to track Commodities as a leading economic cycle indicator. The futures/Mini Futures that you see on news headlines/trading screens are relevant only as daily gauges for stock market behaviour. They are not a cycle indicator across Asset Classes.

So, you may already understand the criteria to define a "normal" economic cycle for the Directional Relationships to behave "ideally" (see below); BUT, how do you determine which Asset Class is driving the cycle? In other words, at a given point in the Intermarket cycle, how do you determine which Asset Class has the DOMINANT Relative Strength to trade? See details of an Original Curriculum, to learn how Relative Strength - a rotational algorithmic measure is used to replace conventional Fundamental Analysis, as an asset allocation technique.

Moving on, here’s the Business Cycle in brief. Bonds lead stocks, to trend in the same direction – except during deflation when bonds rise and stocks fall. On average bonds are 18 months ahead of stocks in rising to their peak or falling to their bottoms; thereafter, stocks follow in the same direction. If bonds have not broken down yet, this extends the gains in the stock market, acting as support for prevailing stock market levels. The real risk begins to build 5-7 months after the bond market peaks or bottoms, thereafter the next 6 months stocks accelerate in the direction bonds have set.

Typically, commodities and bonds have an inverse relationship: as commodities rise, bonds falls but as commodities fall, bonds rise. Inflationary expectations affect bond prices. US Dollar movements which is tied into Monetary Policy changes affects commodity prices. Commodities lead bonds 12–18 months in advance (it takes this long for Monetary Policy to come into effect) and 24–27 months before the economy fully absorbs the policy changes.

Now, the relationship between commodities and stocks. Stocks tend to lead commodities. Commodities are a hedge against inflation, with price inflation and higher inflation expectations occurring towards the end of the business cycle.

Money and company growth using credit (loans) takes time to make its way through the economic system, from making prices rise to raising expectations on inflation. Thus, commodities usually outperform at the end of the business cycle.

Rising bond prices generally raise stock prices in recovery, with falling commodity prices confirming an economic expansion phase is in play. As the expansion matures and begins to decelerate, watch for bonds to turn down first (as interest rates rise), followed by stocks.

Finally, it is after commodities outperform stocks and start turning down, this signals the end of an economic expansion with the probable start of activity decelerating, then slipping into an impending recession.

Retail traders can keep reading about the economics of inter–market analysis and asset diversification. Though, they will not solve these key issues, every option trader trading with USD $25-$50K or less, must deal with for retail asset allocation purposes:

• How much capital is adequate to sufficiently diversify risk away from any one Asset Class?
  

... if you can afford to diversify ...

• How do you practically reconcile the multiple and continually dynamic macro-economic relationships, to trade in the relevant asset class?
  

Where can I learn how to trade options profitably using Intermarket analysis with retail asset allocation methods? See Trading Profit | Consistent Results to view a retail option trader’s portfolio that is set up to cycle in and cycle out of Intermarket relationships, between asset classes.

Why is it possible? I’m using optionable ETFs (Commodity, Currency, Emerging Market and REIT), as well as optionable broad based/sector Equity Indexes, to trade the volatilities of each respective asset class. I do not need to trade Commodities and Currencies directly. Remember, volatility can be added to/reduced from the portfolio, as not all Asset Classes or Sectors or Individual Companies or Countries move up/down in value ALL at the same time; and/or, ALL at the same rate.

Diversified Trading Stock Options but Still Suffering Concentration Risk

Applying a more complete definition of diversification can help retail option traders diversify their portfolio profitably, beyond equities.

A buddy started online options trading from home, in the last 6 months. He was trading a mix of Verticals, Calendars and Iron Condors using highly liquid Indexes but was failing to get consistent profits. Naturally, I asked, “Which Indexes?”

He answered, “DJX, DIA, MNX, QQQQ, RUT, SMH, SPY and XSP. I’ve incorporated broad-based Indexing across large, mid and small-cap stocks to remove single stock exposure. Having learnt how to trade options with Verticals, Calendars and Iron Condors, I’m spreading across these various Indexes. I’m being careful with money management, 2%-5% per trade, I’ve diversified risk, yes?”

No. He has partially diversified a portion within his portfolio; but, is still suffering concentration risk. All he has really done is allocate capital across multiple products, using various option spread types; yet, all his trading capital is stuck in equities.

In choosing the MNX, QQQQ, SMH, SPY and XSP, there is a duplication of stock components in these Indexes: for example, AMAT (Applied Materials) is a component of all 5 Indexes. Bear in mind the MNX and the QQQQ are both smaller versions of the Nasdaq100 Index, the only difference being the MNX is an European styled cash settled Index and the cubes (QQQQ) is an American style stock settled Index. Another example, Apple (AAPL) is a component of the MNX/QQQQ and SPY/XSP - both the SPY and the XSP track the S&P 500, the SPY is American style stock settled and the XSP is European style cash settled. Duplication is not diversification. Even if you allocated capital to the smaller versions of the Dow: DJX, the European style cash settled version of the DIA which is the American style stock settled version. Moreover, if you extended capital allocation to trade the RUT, thinking you are diversifying into small-cap stocks and away from large-caps, you just sunk more of your trading capital into equities. Again, you cannot achieve diversification by adding more capital in the same asset class. That is concentration risk in stocks. Do not confuse asset category (market capitalization) with asset class.

Why bother diversifying across Asset Classes? To answer this question, I’ll use an example of a well known traded stock: Apple (AAPL). You won’t need to understand Fundamental Analysis to follow the reasoning.

Summarizing a financial extract from its Annual Report, Apple has almost ~30% of its Net Sales distributed across: UK, France, Germany, Spain & Ireland and Japan. Apple’s customers in Europe are paying in EUR/GBP and customers in Japan will be paying in JPY. Even though you are trading Apple directly as a US parented firm listed in the US and the currency of the parent is USD denominated, the company has currency exposure to the EUR/GBP and JPY arising from operating sales entities in those jurisdictions. So, you are already exposed to currency and geographic risks by choosing Apple as a product to trade, even though you are constructing an option trade on the stock.

So, it makes sense, rather than have these exposures wrapped inside the stock, where you are subordinating non-equity risks to the stock, to deliberately surface the risks in Geography, Commodities and Currencies. Then, isolate these elements and trade them directly using optionable Geographic ETFs, Commodity ETFs and Currency ETFs.

Is there an example of a consistently profitable and diversified portfolio to see the merits of trading options beyond equities? Yes. See Trading Profit | Consistent Results to view how to trade options using a multi-asset class set up. Notice how the profits step up gradually, from the mid hundreds to the higher hundreds; then, from the higher hundreds into the thousands. While, the losses are contained within the mid to lower hundreds. Diversification to trade options in non-stock asset classes using Geographic ETFs, Commodity ETFs and Currency ETFs, deliberately dilutes the concentration risk in the portfolio’s P/L.

If you are puzzled, yet intrigued, you may well ask, “I don’t need to Beta-weight the Deltas of my option positions; then, hedge using Futures? Do I need to adjust my existing positions by embedding single options; or, morph the original spread into a hybrid option strategy?”

No, is the answer to both questions. Just as it would not make sense within stocks to say Beta-weight a company like GE to the SMH (Semiconductors Holdrs), there is even less sense to Beta-weight a broad-based Index like the SPY to an Emerging Market ETF, Commodity ETF or Currency ETF. Diversification is designed to break the commonality in correlation between the asset price movements of products, in the retail trader’s portfolio structured for online options trading. Adjustments fail to provide the consistency in laddering up the profits as seen in the portfolio, because an adjusted trade often fails to restore, let alone improve the original profile of the trade’s volatility and probability that was bought or sold.

How is this possible? Volatility can be added to/reduced from the portfolio, as not all Asset Classes or Sectors or Individual Companies or Countries move up/down in value ALL at the same time; and/or, ALL at the same rate. It is the volatility level across various asset classes that is targeted for diversification.

To conclude, here’s the point to reflect on. While diversification alone does not guarantee a profitable portfolio, do you think you are diversified trading stock options but still suffering concentration risk? Think deeper.

Treat Implied Volatility of Calls Separate From the IV of Puts

The Implied Volatility (IV) of Calls needs separate treatment from the IV of Puts. Also, for specific options trading strategies treat the IV of both Puts and Calls as a combined bundle.

Each option at each strike implies its own individual percentage value of the underlying product's future volatility. This makes it unique from any other option within the same chain of a given expiry month. The individuality of an option's percentage value at each strike is what draws the "smile" in the IV's Skew.

So, while an ITM Call has a corresponding OTM Put sharing the same strike, conversely an ITM Put has an OTM Call counterpart at the same strike, the Call must be treated uniquely as a Call and the Put uniquely as a Put. The more ITM an option becomes, its intrinsic value becomes higher and its extrinsic value is lowered. Conversely, at the same strikes where an ITM Call (or Put) gets deeper In The Money, the corresponding Put (or Call) becomes further OTM. The more OTM an option becomes, its extrinsic value rises higher and its intrinsic value is lowered. Even with ATM options, where the Call's Delta is exactly 0.50 and the Put also has a Delta of exactly 0.50, the Implied Volatility on either side of that same ATM strike is different.

While Calls and Puts appear side-by-side for a given strike, they are not identical twins to simply trade places. Think of it this way, each option has its own Intrinsic-Extrinsic fingerprint that makes that Call or Put identifiable only to itself.

The logic for treating the Implied Volatility of Calls separate from the IV of Puts becomes obvious in the construction of specific spread types. Let's break down the components making up the following spreads.

• A Vertical Call, be it a Credit Vertical or a Debit Vertical only uses ALL Calls. No Puts are used in the spread's construction.


• A Back Ratio Call is typically done as a Debit spread. It is effectively Net Long an additional Call. The spread only uses ALL Calls. There are no Puts involved.


• A Vertical Put, be it a Credit Vertical or a Debit Vertical only uses ALL Puts. There are no Calls involved.


• A Back Ratio Put is typically done as a Debit spread. It is effectively Net Long an additional Put. The spread only uses ALL Puts. There are no Calls involved.


• A Put Calendar is typically initiated for a small Debit. It only uses ALL Puts. A Call Calendar is comprised of Calls ONLY.
  

Now, let's compare the above spreads with these other types of spreads.

• An Iron Condor is typically constructed as a Credit spread. It uses BOTH Calls and Puts. Remember, a short Iron Condor is made up of a Credit Vertical Call combined with a Credit Vertical Put.


• A Straddle/Strangle is typically constructed as a Debit spread. It combines BOTH a Call and a Put.
  

Clearly, there are more spreads that require the Implied Volatility to be differentiated between Calls versus Puts, compared to the use of a combined IV. So, in choosing a data provider of Implied Volatility, make sure you get the IV data of Calls that is set apart from the IV of Puts; as well as, data that combines the IV of Calls and Puts together. That means 3 sets of IV data in one service.

We have just established the structural logic for decoupling the IV of Calls from the IV of Puts. How do you apply this to a trade? Here's how.

• A long Vertical Call is a Debit spread. By definition of it being a negative Theta spread, also means it is a positive Vega trade. Positive Vega means the spread needs IV to rise. There is a need to forecast an increase in Implied Volatility within 30-60 days, specific to the IV of Calls for a long Vertical that expires between 90-120 days. The IV forecast must be specific to the traded product itself. Likewise, this technique is relevant for a Back Ratio Call. Apply the same logic for a Debit Vertical Put to the IV of Puts for that traded product and similarly for the Back Ratio Put. The variation of this is in a Straddle/Strangle, which is still a Debit spread, so there is still a need to forecast a rise in IV, except the IV combines both Call IV plus Put IV.
  

• A short Vertical Call is a Credit spread. By definition of it being a positive Theta spread, also means it is a negative Vega trade. Negative Vega means the spread needs IV to fall. There is a need to forecast a decrease in Implied Volatility within 30 days, specific to the IV of Calls for a short Vertical that expires between 30-50 days. Again, the IV forecast must be specific to the traded product itself. The same logic applies to a credit Iron Condor. However, the relevant IV to forecast is the IV of Calls combined with the IV of Puts.
  

• The Calendar requires unique treatment. Why? The short leg expires in a different month from the long leg. Due to this inter-month expiration in its construction, the Implied Volatility forecast requires a drop in the front month of its short leg but an IV rise in subsequent back months of the Calendar's long leg. Remember, with a Calendar, if it is a Put Calendar, forecast only the IV of Puts. Similarly, if you construct a Call Calendar, only the forecast of the Call IV applies.
  

Is there a working example of a consistently profitable portfolio that treats Implied Volatility of Calls separate from the IV of Puts? Yes. See Trading Profit | Consistent Results to view a model retail option trader's portfolio that applies this logic.

To conclude, I'll use an analogy. Though an egg comes in one shell, the yolk is separated from the white, for a different purpose that distinguishes the individual parts of that same egg. Treat Implied Volatility of an option's anatomy in the same way.

12 Tenets of Daily Trade Discipline

Whoever told you trading is "easy", is likely inexperienced and lazy; or has become experienced but remains lazy, looking to dupe an even more inexperienced and lazier person. You need more than "Believe and Achieve" mantras.

Sustaining profitable trading results requires cultivating daily trade discipline. Like any other demanding profession, online options trading from home is no different. Choose one tenet to practise each month. There are 12, so you have a year to build your skill progressively.

1. Become a price puritan. The ONLY reason for price to exist and change is because of Supply and Demand. Where there are more buyers with reasons to buy than sellers with reasons to sell, price must rise. If there are more sellers with reasons to sell than buyers have reasons to buy, price must fall. If buyers and sellers have equal reasons or none to engage each other, price remains unchanged. Pure price trading techniques are true to this inescapable economic law.

2. Dilute concentration risk. S&P 500 accounts for slightly over 3/4 of the market capitalization in the entire universe of mutual funds. The top 100 stocks in the S&P500 (with minimal changes in inclusion/exclusion) accounts for ~43% of what mutual funds use in constructing their funds, i.e. the overwhelming majority of mutual funds gravitate to the same stocks in their holdings. As the top 100 stocks are large–cap oriented, two thirds of these funds are into large caps with only one third of these funds choosing to include only small and/or mid caps exclusively. Large caps tend to have weaker relative strength compared to small and mid caps. You were sold “Sector Diversification” – printed on the marketing prospectus. But you are actually intensifying exposure to weaker relative strength, given the cap-weighted concentration, even if the large caps you have holdings in, are distributed across sectors.

3. Being “trendy” but missing the Trend – the style junkie. Fund managers typically stay within their style. An equity fund is not going to become a fixed income fund. Their company’s charter is pre–defined in the type of fund house they operate as. A large growth fund remains a large growth fund, even when large growth funds underperform, while small and mid–cap funds are outperforming in relative terms. It’s not the fund manager’s fault, you funded the fund with your money to manage. This also partly explains why the high turnover of fund managers can affect the fund’s performance, as the fund manager wants to change styles but is constrained. Diversify outside what the news tells you is "Trendy". Replace reliance on funds with the use of optionable Indexes/ETFs.

4. Limit the Fundamentals – the Paper Poker Game. The psyche of investors behind Supply and Demand is expressed in price, beyond fundamentals alone. Investors sold off fundamentally sound stocks, after the unfortunate 9-11 incident and it was repeated with the financial pandemic of 2008, going into 2009. Benjamin F. King: Market and Industry Factors; Journal of Business, January 1966: “ Of a stock’s move ... 20% is peculiar to the one stock.” A Fundamental Analyst fusses with paper (Balance Sheet, Income Statement & Cash Flow Statement), only to explain 20% of price behaviour. As valid as all the FA work is, would you gamble against the house armed with only 20% of the odds with paperwork done by Analysts?

5. Divorce the underlying. You may think you are intimate (be it "love" or "lust") with the traded product. So, you go looking for patterns, setups, indicators that simply do not exist. Love is indeed blind. It’s more sensible to understand the cyclical/seasonal behavior of the asset class the underlying is in; and, how the underlying behaves near support/resistance levels with changes in supply/demand. You really do not know the underlying. Marrying one underlying imposes opportunity costs of not trading other more valid candidates. The stock isn’t going to “love” you back.

6. Define losses first, before profits. Manage risk ABOVE and BEFORE profits AND as finite. However well planned a trade is, it may never reach its profit target. Some choose to use a 1% absolute loss rule of the original trading capital, to define the absolute risk per trade. E.g. if your trading capital is USD $50’000, 1% is equal to USD $500 maximum loss per trade to incur; versus, accepting a 50% loss on the P/L of that specific position.

7. Doubling down accelerates losses. Doubling down only accelerates the average cost towards the losses – known as – “catching a falling knife”. The breakeven will keep moving away, as you chase the price. Trade for profit. Do not trade for breakeven with odds against you. Only add to a winner, if the entry criteria and Reward to Risk Ratio repeats the setup of the original winning trade. Limit adjustments – ever tried to "adjust" the sharpness of a knife?

8. Keep the learning real and thematically consistent. Counter the fixation with “magic” tricks of “technical analysis wizards” by learning from trades you have lived through. Price signals tend to be the strongest. Add depth to your insights into the dimensions of price. Set aside 1%-2% of your portfolio for continual self-education. With whatever you learn, if you struggle to relate it to some field or function in the trading platform, unlearn it if you cannot relate what is taught to what you can price in the platform. You will have to drop the “L” plates from “L”-earn, to earn.

9. Ditch the software crutches. Software is not a substitute for critical thinking. Break down the logic in the software (how, what and why). Black box software cultivates an addiction for repeatedly mindless subscriptions. Break the habit, trust your logic to reason – you have profitable trades that you thought through yourself. As you “outsource” the administrative tasks associated with trading (e.g. record keeping of trades), do not outsource your brain.

10. Plan trades with business discipline. Most plans cover Entries, Exits, Stops and Profit Targets. Still, no one enters a business with a few bullet points. Your trading plan must address the very defining reason of “Why trade?” What is your motivation (each day, month and quarter)? E.g. build up the children’s education fund, pay for household expenses or self-directed retirement? How robust do you want your home business to be? It’s reflected in the construction of your portfolio and trade plan.

11. Unrealistic expectations. Build wealth slowly and consistently. Forget dream chasing home runs. Trading is a life endeavour. The markets will outlive all of us.

12. Scrooge – cheap is not smart. Volatility dominates price-performance. Do not make option decisions simply on cost alone. Options are not fairly priced on bid-ask alone. Options perform based on what you pay for them. E.g. buying High(er) Deltas may not be the cheapest but may give the required directional bias. Rethink for a set amount of Theta decay, what that buys you. Like in real life, bargain shopping can lead to more junk than you've got room to store. Don’t end up with an inventory of junk Calls and Puts in your portfolio. Get savvy, seek value.

In adopting these practices as part of the daily trade discipline for online options trading, what can I expect to achieve? See Trading Profit | Consistent Results to view a retail option trader’s portfolio that exercises the discipline of the tenets.

As you exercise stricter daily trade discipline, you should see these characteristics of a more stable portfolio performance:

• Profits should step up gradually, depending on the size of your account. If it’s in the tens of thousands, the profits should step up consistently like a ladder from the low hundreds, to the higher hundreds; then, move up from the higher hundreds into the thousands. If your account is above $100K, profits should step up from the high hundreds into the thousands.


• Profits that jump from low hundreds into the thousands signal an over-reliance on gapping plays, which fail to help you step up consistently profitable results.

Paradox - More Trades on Dull Days and Normal Days than Big Days

Contrast these 2 days. 29 Sep, 2008: Dow down -7.50%, Nasdaq down -10.06% and S&P 500 down -9.63%. Versus 13 Nov, 2008: Dow up +6.25%, Nasdaq up +6.11% and S&P 500 up +6.47%.

Many retail option traders would have rushed to get their spreads filled on such big days, either to get short or long. The discerning few, mindful that a +/- X% change in equities, is a day to avoid entry; instead, it is a signal to scale-off profits or reduce exposure, would have profited or limited losses on such days.

Here’s the logic for categorizing what type of day it is. If you theoretically priced a long Calendar or a short Iron Condor on a Big Day – be it up or down, it is likely the product’s price has moved near or outside 1 Standard Deviation, even if the order was filled at mid-price for that spread.

The following day, if conditions turned into a Dull Day be it up or down, let’s say the Futures did not even move more than a third within 1 Standard Deviation. On the extreme day when you priced the entry, even though you were filled at mid-price, you still overpaid for the Calendar; or, sold more Theta as premium than is necessary to protect the wing span of the short Iron Condor, possibly increasing the risk of Gamma instability. Alternatively, if you priced a directional spread on a Big Day, be it a Short Vertical or a Long Vertical you need a continuation in extreme days - after the Big Day that you filled the order on, for price to move.

If price has already moved 68% (1 Standard Deviation) on a Big Day, moving towards 2 or 3 Standard Deviations is not the problem. The issue is – can the price action sustain a 2 or 3 Standard Deviation move day after day, after the extreme day? It’s not an impossible event, just an infrequent occurrence.

Pricing spreads for entry under extreme conditions, places huge pressure on your orders to outperform. That’s a tough way to trade. You are punishing the Profit and Loss of the trading account unnecessarily. Psychologically and visually, continually entering trades on Big Days makes you search for “magical” chart patterns for another huge breakout or breakdown in price. No, you won’t go blind. Though, you will cultivate a trading habit that must be broken, if you plan to have consistent results with online options trading.

So, how do you work out the X% change, be it up or down to differentiate a Dull Day, from a Normal Day versus a Big Day? Use the implied volatility of the front month’s options on the DJX, MNX and SPY – the mini versions of the Dow, Nasdaq and S&P 500 respectively, to categorize the market ranges of the day. For example, take the:

• DJX: let’s say, the front month volatility is 27.38%, divide 27.38% by 16 = 1.71%. That’s +/- 1.71%, meaning IV representing the collective expectations of market participants trading that product, expect the DJX to move 1.71% up or down for that day. Your trading platform should allow you to add a column in the watch list called “%Change”. That’s what we’ve just calculated. So, a %Change below +/- 1% is a Dull Day. A %Change between +/- 1% to +/- 2% is a Normal Day, take the lower whole digit of the calculation, in this case 1%; and, the higher whole digit of the calculation, in this case 2%. A move of +/- 2%, would be a Big Day Up/Down for the DJX. Even though the DJX is the mini version of the Dow, because we are using a % calculation versus an absolute number, applying the meaning of +/- %Change remains valid for the Dow.
  

• Repeat for the MNX: say the front month IV is 30.73%/16 = +/- 1.92%. Dull Day for the MNX is where the %Change is below +/-1%. Normal Day for the MNX is where the %Change is between +/-1% to +/-2%. A %Change number bigger than +/- 2% is a Big Day for the MNX. Same +/- %Change applies to the Nasdaq.
  

• Repeat for the SPY: front month IV is 31.25%/16 = +/- 1.95%. A Dull Day = %Change below +/- 1%. A Normal Day = %Change between +/- 1% to +/- 2%. And a Big Day = %Change bigger than +/- 2%. Same +/- %Change applies to the S&P 500.
  

You can apply this calculation to the VIX, or any optionable product that you have identified a trade on.

Why divide the front month’s volatility by 16? As you know, volatility is expressed as an annualized number. So, to get the daily volatility number, we divide it by the square root of the number of trading days in a year, which is 256 (rounded off). There is no trading on weekends and exchange holidays, because prices cannot change on these days. There are some years with more or less than 256 days, but using 256 is the norm. The square root of 256 = 16.

As part of your pre-market preparation, calculate on a spreadsheet the market ranges of the day (Dull, Normal or Big) for the DJX, MNX, SPY and the VIX at minimum. This is not to pick direction, as you will not know if the market will open to the upside/downside and STAY there, even if futures indicate an upside/downside bias. The calculation gives you a measured gauge, once the market opens to see if the trading range of the day is leaning towards a Dull, Normal or Big Day. Then, assess if it makes sense to theoretically price a spread, be it a Calendar, Iron Condor, Vertical, etc. This guards you from chasing price near 1 Standard Deviation, to get your orders filled on a Big Day. Doing this pre-market work, determines if you will be filling orders or scaling off for profit; alternatively, reducing exposure to losses, when the market opens.

Want to see a consistently profitable portfolio that prices entries on Dull/Normal Days but takes profit/limits losses on Big Days, at work? See Trading Profit | Consistent Results to view a retail online option trading portfolio that practices this daily discipline.

Statistically there are more Dull and Normal Days to price spreads for entry, especially during mid-July till August, as many floor traders go on leave. On Dull and Normal Days aggressively pricing the order 0.10-0.15 below Theoretical Price for a debit spread; or, 0.10-0.15 above for a credit spread just means it takes 1-2 hours more to get filled. If your order is filled within 5 minutes, you were lax in working the entry hard; versus, getting filled in 1-2 hours. Diligence does make a material difference in the trade’s price-performance. In avoiding entries on Big Days, you are not missing out on not getting in, when most retail traders are chasing price to get filled. One key factor of the consistency in your account’s P/L is the price you got in and out of. The discipline of staying consistent is to get filled within a sustainable range of the spread’s fair value for that particular trading day. Remaining in the business of online options trading requires as much sense to stay out of trades, as it does to get in to trades.