Entry 8 Apr & 15 Apr 23: Becoming an Options Trading Quant

By: nic

One Month of Learning with Python to Become a Quant Finance Trader

This was my last week learning to become an options trading quant, doing the Getting Started with Python for Quant Finance. The course has been set up by Jason Strimpel, Head of Startup Data Strategy at Amazon Web Services and founder of Pyquant News.

Since I was again traveling last week, this entry covers the last two weeks. This time for Easter I went to the Dordogne. So this entry again covers two weeks.

I already learned a lot, and due to time issues having a backlog, I need to catch up over this weekend.

So what did I do in the past few weeks?

In the introductory or ‘onboarding’ week, I met the team behind Pyquant News (which actually is Jason Strimpel), set up my profile and joined the community on Podia, and Twitter , and registered for the live sessions in the next four weeks.

I immediately received some helpful guides on pricing options and implied volatility, and options positions, breakevens sheet, and other bonuses.

The first week was dedicated to setting the stage with subjects like:

  • Building in Public (see #buildinginpublic in Twitter)
  • What quants are (legacy versus modern)
  • Connecting with the quant community
  • Getting started with Python for quant finance
  • Setting up your own Python environment in Anaconda (data science platform)
  • Installing packages and linking to brokerages (in this case Interactive Brokers)
  • How to get the most out of the course and get help with your code
  • And much more

Packages I installed:

  • pandas – powerful and flexible open-source data analysis and manipulation tool
  • NumPy – hundreds of mathematical functions that let you work on arrays from simple (e.g., exponents) to more complex (e.g., eigenvectors)
  • SciPy – a collection of mathematical algorithms and convenience functions built on the NumPy extension of Python
  • Matplotlib – comprehensive library for creating static, animated, and interactive visualizations in Python
  • Statsmodels – classes and functions for estimating different statistical models and conducting statistical tests and statistical data exploration
  • Pyfolio – Python library for performance and risk analysis of financial portfolios that works well with the Zipline open-source backtesting library
  • IB API – Interactive Brokers’ TWS API is a simple yet powerful interface through which IB clients can automate trading strategies, request market data, monitor account balances and portfolios in real-time
  • QuantStats – portfolio profiling, allowing quants and portfolio managers to understand their performance better by providing them with in-depth analytics and risk metrics
  • Zipline – algorithmic trading simulator
  • OpenBB SDK – access to normalized financial data from dozens of data providers and a toolbox to perform financial analysis on a variety of asset classes, including stocks, crypto, ETFs, funds, and the economy, as well as portfolio optimization and attribution
  • RiskFolio-Lib – portfolio optimization and quantitative, strategic asset allocation.

You can find more information on the course and follow Pyquant and Jason here:

  • Website: https://www.pyquantnews.com
  • Twitter: https://twitter.com/pyquantnews

Two weeks ago, I asked myself whether undertrading is a good strategy since, in few weeks before, my returns went up considerably! By doing not too much. This week I woke up when I saw my P/L rapidly going down and realized I should have started looking at adjusting positions earlier.

And how is my Beta-weighting Exercise Going?

I can use Tastyworks’ beta-weighting deltas indicator to benchmark individual positions and sum them to understand the directional exposure of my whole portfolio.

I still have a negative delta beta which caused my P/L to go down this week, and I should consider adding some more positive delta, since the market is still showing bullishness.

How am I Doing Overall?

I am now over a year into options trading. Although I am still far away from the goals I have set for myself, I have shown a consistently positive balance since September of last year. I had two dips, but in March reached the optimum of my options trading by making close to $900. I am down to $700 now.

I still make many mistakes, my trading discipline has become better but still needs further working on.

I am now at a $740 P/L YTD of which $79 is unrealized gain.

What am I Reading?

And I started re-reading another ‘must-read-for-options-traders’ book that is really helping me in learning options trading.

The book is over 400 pages, and I am cherry-picking my way through the book.

Quant finance
Quant finance

Table of Contents

Last Week’s Options Trading

We’re at low (17) volatility, so I need to adjust my trades again. I only had 8 positions end of the week, using around 15% of Buying Power. One of my rules is not to put on more than 30% trades at low volatility.

Options Strategy Risk Management Rules​

  1. In high volatility (VIX >20) sell high vol (IVR>30) options to collect premium income while spreading the risk over various expiration dates (staggering dates to avoid expiration density); the higher the volatility, the more of your account you can allocate to short premium strategies.
  2. Sell options at high IVR (>30)  to extract high (overpriced) premiums (‘overpriced’, since predicted volatility is nearly always overestimated, and stocks are less volatile than predicted, so implied volatility implosion or IV reversion to the mean allows for profits to be taken early when stocks fail to be as volatile as predicted). ​
  3. In low volatility (VIX < 20) buy low vol (IVR <30) debit options (you pay the premium) and lower the total allocation; the less volatility, the less money you should allocate to options trading. New rule: only sparingly enter into debit spreads (especially bear puts!), and only do this when more than three signals (technical indicators) confirm this.
  4. Sell and buy options on underlyings that are liquid in the options market (to open and close positions easily and ensure trades can be filled with narrow bid-to-ask spreads for optimal option pricing ​).
  5. Sell and buy options across tickers with broad sector diversity across uncorrelated sectors to spread risk (too much concentration into any given sector runs the risk of stocks auto-correlating in the same direction and potentially jeopardizing all trades within the sector-specific bucket of trades).
  6. As much as possible (given a small account) stick to risk-defined trades (put spreads, call spreads, and iron condors) to mitigate risk and reduce the amount of capital required for any given trade.
  7. Probability of success (P50 in Tastyworks platform)> 70% to ensure a statistical edge
  8. Close the trade and realize profits at >50% premium early in the option lifecycle (21 DTE)
  9. Re-invest the capital made free towards additional trades.
  10. Close-out trades prior to expiration (before strike price gets challenged just before expiration (high volatility and higher loss probability!).
  11. Maximize the number of trades to allow the expected probabilities to play out (trade small, trade often).
  12. Size position/portfolio allocation to manage risk exposure (worst-case scenarios always need to be considered therefore, I conservatively use small allocations to options trades, so only 4% of my portfolio should only be used for any given trade). 
  13. Keep an adequate amount of cash on hand (~40% in my case) to protect your portfolio against any major market downturns (i.e., Covid-19 and Q1 2022, 2023 recession(?). Cash also gives me the possibility of buying stocks/long equity at heavily discounted valuations. ​

Alternatives for Short Premium Strategies

I prefer short premium strategies so high volatility. But volatility is still relatively low. I need to be able to enter trades in all market conditions.

Historically, implied volatility has outperformed realized implied volatility in the markets. For this reason, we always sell implied volatility to give us a statistical edge in the markets. While I often search for a high IV rank at order entry, the market does not always accommodate me.

I, therefore, will start looking at adding these options strategies that benefit from increases in volatility, as well as more directional strategies to use during low-volatility markets to my playbook:

  1. Long bull call and (sparingly) bear put vertical spreads
  2. Ratio spreads
  3. Long put calendars and call calendars
  4. Long diagonal spreads
  5. Long volatility products

In bull(-ish) markets, as the VIX drops, implied volatility tends to be low in equities. Just like I take advantage of reversion to the mean when IV is high, I continue to stay engaged and do the same when it gets to an extreme on the low end. Therefore, in low IV, I will use strategies that benefit from this volatility extreme, expanding to a more normal value.

This doesn’t mean, however, that, in low IV markets, I stop looking for underlyings in the market that have high IV. Premium selling is where the majority of the statistical edge lies.

Opened Positions

Opened on 13 Apr: 2 x MRVL May 12/Jun16 Long Put Diagona Spread -51/50 for $61 debit

Date

15/4/23

Underlying

40.29

PoP/P50

11

DTE

27/62

IVR

3.5

Δ Delta

24.97

Θ Theta

-1.670

Other

Date

13/4/23

Underlying

40.59

PoP/P50

–/>99.5%

DTE

29/64

IVR

4.4

Δ Delta

26.43

Θ Theta

-1.705

Other

delta 0.04/0.17

15 Apr 23: -$14 (-11.5%) now

Opened on 13 Apr: 5 x CHPT May 19/Jun16 Long Put Calendar Spread -8/8 for $28 debit

Date

15/4/23

Underlying

8.71

PoP/P50

<1%

DTE

34

IVR

6.2

Δ Delta

-13.20

Θ Theta

0.845

Other

Date

13/4/23

Underlying

8.60

PoP/P50

–/–

DTE

36/64

IVR

3.9

Δ Delta

-8.90

Θ Theta

0.880

Other

delta: -0.33/0.14

15 Apr 23: $0 (0%) P/L now

Opened on 11 Apr: NKE May 26 (w) Bear Put 126/120 for $257 debit

Date

15/4/23

Underlying

125.91

PoP/P50

41%

DTE

41

IVR

-2.1

Δ Delta

-21.86

Θ Theta

-0.287

Other

Date

11/4/23

Underlying

123.24

PoP/P50

52%/68%

DTE

45

IVR

0.0

Δ Delta

-23.12

Θ Theta

0.362

Other

15 Apr 23: -$63 (-24.5%) now

Opened on 5 Apr: XLE Jun 16 (w) Bear Put 88/83 for $225 debit

Date

15/4/23

Underlying

87.24

PoP/P50

44

DTE

62

IVR

0.9

Δ Delta

-21.11

Θ Theta

0.005

Other

15 Apr 23: -$44 (-19.6%) now

Opened on 4 Apr: MCD May 19 Bear Put 285/280 for $215 debit

Date

15/4/23

Underlying

289.01

PoP/P50

35%

DTE

34

IVR

6.0

Δ Delta

-10.85

Θ Theta

0.845

Other

15 Apr 23: Two weeks later, it still doesn’t look like a good idea. $89 (-47.5%) in the red and very close to 50% loss level. I may need to close it this week.

04 Apr 23: Here I followed Cherry Bomb’s Tom Preston’s advice.

Closed: Opened on 3 Apr: GLD May 5 (w) Iron Condor 175.5/178.5/193/196 for $100 credit and closed on 14 Apr for $62 debit

14 Apr 23: My GLD iron condor was at 21 DTE and getting too close in the past few days to the call legs, and since I have two other iron condors in GLD I wanted to reduce my GLD exposure. $38 profit anyway.

03 Apr 23: Opened another GLD iron condor

Running and Closed Positions

Opened on 31 Mar: GLD May 12 (w) Iron Condor 175/178/194/197 for $103 credit

Date

29/3/23

Underlying

183.21

PoP/P50

58%

DTE

40

IVR

37.4

Δ Delta

4.61

Θ Theta

1.376

Other

01 Apr 23: -$3 now

Opened on 29 Mar: GLD May 19 Iron Condor 171/174/191/194 for $101 credit

Date

29/3/23

Underlying

183.21

PoP/P50

59%

DTE

40

IVR

37.4

Δ Delta

-0.66

Θ Theta

1.08

Other

01 Apr 23: $6 in the green

Opened on 27 Mar: KRE May 19 Iron Condor 34/38/49/53 for $145 credit

Date

27/3/23

Underlying

43.84

PoP/P50

65%

DTE

47

IVR

37.9

Δ Delta

-5.3

Θ Theta

1.652

Other

1 Apr 23: $11 in the green

Closed: Running: Opened on 15 Mar: XLF Apr 28 (w) Iron Condor 27/30/33/36 for $106 credit and closed the 30/36 call leg on Mar 21 for $60 debit and closed on 3 Apr for $18 debit

Date

1/4/23

Underlying

32.13

PoP/P50

88%

DTE

26

IVR

30.8

Δ Delta

13.55

Θ Theta

0.619

Other

Deltas: -3.9/17.45

Date

18/3/23

Underlying

31.07

PoP/P50

50%/71%

DTE

43

IVR

70.3

Δ Delta

-12.43

Θ Theta

1.297

Other

Deltas: -0.10/-0/27/0.38/-0.08

4 Apr 23: closed for a $28 profit, so not exactly on target but still positive.

21 Mar 23: price getting too close to call legs

16 Mar 23: opened another high volatility play with XLF (surfing on the bearish bank trend).

I found this on the Internet (source below).

” … Selling near-dated OTM cash-secured puts or bull puts on KRE, given the incredibly high IV and the substantial skew in the near-dated options, may be an extremely high-probability trade.

Calendar or diagonal spreads to bet on a mean reversion of volatility, while expressing some directional preference, may also work. For instance, one can buy an ITM call option expiring in a year and sell an OTM call expiring in a month.

So, selling near-dated options and taking an upward bias on price (positive delta).

XLF also lends itself to a similar setup but it’s IV profile did not seem as egregiously overpriced as KRE.”

Source: Seeking Alpha

Closed: Running: opened on 16 Mar: KRE Apr 28(w) Iron Condor 37/41/50/54 for $180 credit and closed on 5 Apr for $120 debit

Date

1/4/23

Underlying

43.84

PoP/P50

68%

DTE

26

IVR

37.9

Δ Delta

7.49

Θ Theta

2.039

Other

Deltas: -12.45/28.76/-13.34/4.53

Date

18/3/23

Underlying

45.26

PoP/P50

47%/59%

DTE

43

IVR

71.3

Δ Delta

-3.23

Θ Theta

1.776

Other

Deltas: -0.18/-0.30/0.32/0.17

5 Apr 23: closed at 33% profit

21 Mar 23: Closed the call leg since it was getting challenged (price up)

15 Mar 23: Opened another high volatility play with KRE (regional banks which are bearish). Short deltas may be not enough OTM. Normally I play 20 deltas. Let’s see.

Closed: Opened on 14 Mar: IWM Apr 28 Iron Condor 158/163/187.5/192.5 for $167 credit and closed on 6 Apr for $67 debit

Date

01/4/23

Underlying

178.36

PoP/P50

76%

DTE

26

IVR

14.6

Δ Delta

-7.59

Θ Theta

3.391

Other

Deltas: -6.04/10.31/-21.28/9.43

Date

18/3/23

Underlying

177.59

PoP/P50

56%/76%

DTE

45

IVR

34.5

Δ Delta

-5.0

Θ Theta

2.378

Other

Deltas: -0.18/-0.13/0.26/0.15

6 Apr 23: Closed for $100 profit = 60%.

14 Mar 23: opened another high volatility play with IWM

End-of-Week Active Positions Overview

Portfolio 18 Mar 23

Financials

Cash Balance 15 April 2023

P/L YTD went down to $740 from $857 two weeks ago. Low volatility and bullish GLD cost me some money!

I am more and more trading optimally, making full use of my cash, optimizing my positions etc . but I am still making mistakes in choosing the right directions and the right options strategies.

The points I have to look at are:

  • In general, my positions are placed on the safe side with low deltas, low risk, and low profit. I am already increasing risk by widening spreads and picking higher deltas.
  • For a better-balanced portfolio allocation (based on VIX), I am adding non-short premium and passive income strategies to optimize my portfolio.
  • Except for a small short put undefined risk play in RIOT, I have been only doing a limited number of defined risk strategies which are lower risk but also less profitable: I may need to start looking at adding other defined risk strategies, and once in a while short straddles and strangles based on low prices underlyings. But my account is, at this stage, really too small for this.
  • I now select positions with higher premiums than the commissions and fees I have to pay and the target profit I have set as a rule (50%).
  • I am now also monitoring the beat-weighted delta of my positions and total portfolio; in periods like this, I need to manage it in such a way that it remains close to 0. I am far away from achieving this.
  • BUT MOST IMPORTANTLY: I SHALL ABIDE BY MY ENTRY, ADJUSTMENT, AND EXIT RULES !

Find out more about the platform I love to use for my options trading:

If you like it as much as I do, and want to open an account, click here:

Disclosure: for each referral I will get credits for items or cash to support this website! Thanks!

Market Sentiment 15 April 2023

Maintaining this part of the journal is taking too much time, so I will start rationalizing it.

The stock market continues to levitate in a sideways range as the pressure between bulls and bears continues to build. Despite tamer CPI, PPI inflation data this week and softer retail sales, rate hike expectations remain for a 25-bps hike in May then likely pause in June – while major averages remain “trapped” in a tight trading range heading into the beginning of earnings season.

U.S. stocks retreat from mid-February high as traders digest bank better banking earnings (JPM, Citi, WFC), weaker retail sales, and mixed Fed comments, but finish well off the lows of the session as stocks bounce into the close again.

I mostly use eOption’s Closing Bell emails, StockTwits, BarChart, and Seeking Alpha I receive daily as a source.

1. Geopolitical Events and Economic Trends

During the week, I capture the most important news. Every weekend before the new trading week, I review the current markets, the general geopolitical events, and economic trends determining the sentiment in the world of options trading.

  • The war between Russia and Ukraine is still raging.

2. VIX Index

  • The CBOE Volatility index (VIX) is back at 17.07
  • The VIX Index measures the level of the expected volatility of the S&P 500 Index over the next 30 days that is implied in the bid/ask quotations of SPX options. Thus, the VIX Index is a forward-looking measure, in contrast to realized (or actual) volatility, which measures the variability of historical (or known) prices.
  • A VIX below 15% is very low volatility. A 15% or below VIX is assumed to be a market at rest. Since the intrinsic nature of the Stock Market is to move up, a VIX close to 15% or lower will tell us that the broader market is likely to head higher. 
  • Up to 19% VIX means the market is in ‘lull’ mode. 19% is seen as the ‘steady state’ VIX. This arena is inadequate for short premium plays, which require high volatility. This is where long calls, puts, and debit spreads may be set up. Only when VIX gets closer to 30%, selling options become viable.
  • At 20% or higher means medium volatility.
  • A VIX of 30% or higher means high volatility. When selling options, you want to sell out of stocks when the VIX is near 30. This is where credit spreads, short strangles, straddles, short iron condors, etc., can be played.
  • Above a VIX of 40%, this is still the case, but given the extreme volatility, you should be very careful.

VIX for position sizing

So my maximum portfolio capital allocation for short premium strategies should remain at 30% of net liq. Last week it was higher an I could trade 35%. At the end of this week I closed and now only have 15% allocated.

See also on this subject this Tastytrade video.

VIX

< 15

15-19

20-29

30-40

>40

Volatility

Lowest volatility, all comfortable

Market in ‘lull’ mode

Volatility high

Volatility very high

Volatility and fear levels highest

Maximum portfolio capital allocation

25%

30%

35%

40%

50%

Volatility and the VIX are significant in how I size positions and portfolio allocation. Since my focus is on short premium trading, I must balance exposure to substantial losses and reaching sufficient occurrences.

In 2022 the VVIX Index (VIX Volatility Index) has also traded within a fairly reasonable range (roughly between 83 and 150). The long-term average is 86, and the VVIX is mean-reverting.

The VVIX is nicknamed the “VIX of VIX” because it is calculated using the implied volatility of ATM and OTM options in the VIX itself, using the same calculation method as VIX. The index measures the “volatility of volatility, or the “vol of vol.”

Today, the VVIX is at 84.01, close to 13 points below the all-time average of 97.

The VVIX/VIX Ratio

See more in this Tastyworks video.

3. Oil and Gas, GOLD, SILVER, AND COPPER (METALS & MINING)

The following sectors I look at – to understand the market sentiment – are, due to their massive impact on the global economy, commodities.

  • Oil prices finished the day higher, with WTI crude rising +$0.36 or 0.44% to settle at $82.52 per barrel and up 2.26% for the week. Brent Crude rises $0.22 or 0.26% to settle at $86.31 per barrel. Prices at the pump have risen for 17 straight days and are now up $0.46/gallon since the end of 2022: currently at $3.66/gallon. Natural gas prices rebound after falling as much as 2% to $1.967, lowest since September 2020 before rebounding to settle at $2.114M btus.
  • Gold prices slide -$39.50 or 1.9% to settle at $2,015.80 an ounce after coming within striking distance of all-time highs as the dollar and Treasury yields rebounded despite weaker U.S. retail sales, import/export prices. Gold ends the week lower by around -0.5% after today’s pullback.

4. USD and Other Currencies, BITCOIN AND CRYPTO

The DXY, the symbol for the US dollar index, tracks the price of the US dollar against a basket of six foreign currencies that have a significant trading relationship with the US and are also hard floating currencies. The index will rise if the dollar strengthens against these currencies and will fall if the dollar weakens against these currencies. I also look at crypto trends, especially Bitcoin

  •  The U.S. dollar turns higher even after data showed U.S. retail sales fell by more than expected in March, although the previous month’s figures were revised higher. Retail sales dropped 1.0% month-on-month in March, versus the 0.5% decline expected. The dollar index (DXY) rises to 101.60 from 100.931 before the data.
  • Bitcoin went over the magic 30.000 level is now at 30.476!

5. Yield Curves

  • Treasury yields rose sharply after March retail sales came in weaker than expected. The 10-year is at 3.52% after hovering around 3.45% ahead of the data. The two-year rises to 4.08% from below 4%. Overall sales shrunk 1% in March, after declining a revised 0.2% in February.

Understanding yield curves also adds to better reading the market sentiment.

“A yield curve is a line that plots bonds’ yields (interest rates) having equal credit quality but differing maturity dates. The yield curve’s slope gives an idea of future interest rate changes and economic activity.

There are three main yield curve shapes: regular (upward-sloping curve), inverted (downward-sloping curve), and flat. Upward sloping (standard yield curves) is where longer-term bonds have higher yields than short-term ones. 

Standard curves point to economic expansion, and downward-sloping (inverted) curves point to economic recession.

Yield curve rates are published on the Treasury’s website each trading day.”

Source: Investopedia

i. The 10-Year Treasury Constant Maturity minus 3-Month Treasury Constant Maturity Yield Curve

The yield curve (T10Y3M) compares the 10-year with the 3-month U.S. Treasury bond yield. It gives insight into bank profitability, which is correlated with economic activity. Historically, the yield curve has been a reliable predictor of economic recessions.

An inverted yield curve has been a good indicator of an economic slowdown ahead. A 10-year-3-month treasury spread approaching 0 signifies a “flattening” yield curve. Furthermore, a negative 10-year-3-month spread has historically been viewed as a precursor or predictor of a recessionary period.

  • For some time now, the indicator has been predicting a recession.

ii. The 2-Year/10-Year Yield Curve

  • The 2s10s curves dropped considerably this week: 2-year on pace for biggest monthly drop in 15 years. The benchmark 10-year Treasury yield fell to 3.50%, its largest monthly drop in three years (down 42-bps); the 2-yr down 4 basis points at 4.08% (down 72-bps for March marking its biggest monthly drop since January 2008).
  • The separation between the two instruments still predicts recession.

“An inverted yield curve can be an important economic indicator and a likely precursor to a recession. 

When the curve inverts, the longer-dated bond (I am using the 10-year) will offer a lower annual yield than a short-dated bond (I am using the 2-year). This means that investors have bid up the prices on longer-dated bonds to the point where they yield less than short-dated bonds.

An inverted yield curve results from investor concerns about the economy and the stock market. History shows that investors tend to be right about economic weakness on the horizon when the yield curve is inverted. Since WWII, every recession has been preceded by a yield curve inversion.

Recessions don’t start immediately after the yield curve inverts, however. The inversion tends to precede the recession by 6 to 18 months.”

Source: SeekingAlpha

6. Producer Price Index (PPI), Consumer Price Index (CPI), Consumer Sentiment Index (CSI)

The Producer Price Index (PPI) program measures the average change over time in the selling prices received by domestic producers for their output. The prices included in the PPI are from the first commercial transaction for many products and some services.

Source: Bureau of Labor Statistics (BLS).

  • Industrial Production for February was unchanged vs. consensus +0.2% and below Jan +0.3%; Capacity utilization rate 78.0% vs. est. 78.4% and in-line with January; U.S. Feb manufacturing output +0.1% vs. est. (-0.2%) and Jan +1.3% 

The measure that is most often used to measure inflation in terms of consumers is the consumer price index (CPI). Tens of thousands of items in several categories are tracked. The basket of products or services is considered each month, and economists and statisticians look for trends. If the CPI rises, prices could trend higher, with inflation on the rise.

  • Consumer Inflation in the United States cooled down further in March as the consumer price index rose 0.1% in the month, following a 0.4% increase in February. Annual inflation also dropped from 6% to 5%, the smallest annual gain since May 2021, and is now down by almost half from its peak of more than 9% in June last year.
  • U.S. Producer Price Index (PPI) too recorded the biggest annual decline since January 2021. The Producer Price Index for final demand declined 0.5% in March. The PPI rise of -0.5% in March came in against the expected PPI of 0.1%. On the year-on-year basis, the March PPI inflation increased 2.7%, against the expected rise of 3%. Whereas the year-on-year PPI inflation rise in February was 4.9%.
  • The significant downside surprise in U.S. PPI has led people to believe that the Fed will soon be done with the policy tightening and may even start to cut rates before the end of the year. If this happens, we may see the comeback of risk-on trade sentiments ahead despite the regional banking crisis emanating in Mar 2023. Source: BarChart.

A low CSI index reflects the general (dis-)satisfaction with managing U.S. economic policies. A high satisfaction rating suggests approval of the current policy management and implies market stability. 

Source: Surveys of Consumers (umich.edu).

  • University of Michigan sentiment reported at 63.5 vs. est. 62.0; consumers current conditions index prelim April 68.6 (consensus 67.3) vs final March 66.3 and consumers expectations index prelim April 60.3 (consensus 60.0) vs final March 59.2

7. Put/Call Ratio

  • Moving sideways
  • A Put/call Ratio of below .5 could mean the market is very bullish. Maybe too bullish. It could be an excellent time to sell stocks high.
  • Moving sideways if the Put/call Ratio oscillates between 0.5 and 1.0.
  • Between 1.0 and 2.0, the Put/call Ratio indicates a bearish market.
  • A Put/call Ratio above 2.0 could mean it is very bearish. It could be an excellent time to consider buying low.
  • The put/call ratio went at 1.0, which indicates sideways movement.

Warning: previous research conducted by tastytrade revealed that the Put/Call Ratio is not a reliable trading indicator. Readers can check out this installment to review that research in greater detail this installment.

8. NASDAQ, DJI, SPX, Russel 2000 Indices, and Main Market Sectors

In general, I look at the leading indices DJIA, SPX, and Russell 2000 (IWM) and the level of volatility or ‘market thrashing’ (excessive volatility with significant rising then near proportionate falling in markets’ values within a trading period): above 1% in any or all of them might indicate indecision in the market.

NASDAQ, DJIA, SPX, IWM

  • All in the red.

Major Stock Market Sectors

I also follow the major market sectors in Barchart.

  • 3 of 11 sectors closed green. Financials (+0.98%) led, and real estate (-1.72%) lagged
2 April 2023 Barchart
15 April 2023 Barchart

Summary Market Sentiment

Bull market

Bullish

Neutral

Bearish

Bear market/crash

1. Geopolitical events and economic trends

Positive trends, stable supply chains

Minor market issues, minor supply chain issues

National events, market issues, bad economic data, mini-corrections

Negative indicators, international events, serious market issues, broader market correction (-10%)

The total collapse of the global market, deep recession

2. VIX (VIX)

<15

Lowest volatility, all comfortable

15-19

Market in ‘lull’ mode

20-29

Volatility high (down from above 30)

30-39

Volatility very high

>40

Volatility and fear levels highest

3. Commodities

Oil & gas (XOP), gold (GLD), silver SLV), and copper (COPX) stable

Minor market issues, minor supply chain issues

National events, market issues

International supply chain interruptions, high oil & gas prices

International conflicts involving US, Russia or China, and other main producing countries

4. Currencies & Crypto

Very weak dollar (DXY) versus other currencies, crypto (BTCUSD) crashing)

Weak dollar, Bitcoin

Neither weak/nor strong dollar, Bitcoin

Strong dollar, Bitcoin

Very strong dollar, Bitcoin

5. US Yield Curve s(T10Y3M and US10Y vs US02Y)

Considerably steep curve

Steep curve

Average but still positive curve

Flattening, inverting, and approaching zero

Inverted curve and negative

6. Producer Price Index (PPI), Consumer Price Index (CPI), Consumer Sentiment Index (CSI)

Lowest price level

High consumer confidence

Price level higher than normal

Consumer confidence is less high

Price levels rising fast

Consumer confidence going up and down from very high or up from very low

The price level is very high

Low consumer confidence

Highest price level

7. S&P 500 Put/call ratio (PCR)

Well below 0.5 (very bullish)

Close to 0.5 (bullish)

Between 0.5 and 1.0 (neutral)

Between 1.0 and 2.0 (bearish)

Above 2.0 (severely bearish)

8. Dow Jones (DJI)

S&P 500 (SPX)

Russel 2000 (RUT)

Major Market Sectors (XLE, XLF, etc)

Strong bull market
No real changes in an upward trend

Bullish market
Minor changes in an upward trend

Moving to neutral bullish/bearish market

Increased (positive/negative) changes and “thrashing”

Bearish market (with bear rallies)

In general, going down, many negative changes

Bear market

A deep recession or the market is collapsing, or already did so

Trading style

No restrictions on trading (except for VIX rules)

Closer watch and reduce trades

More caution needed and reduce trades further

Extreme caution and reduce trades even further

Look to close any open positions and no new trades

This Week’s Economic Calendar

  • ECB
  • CPIs

Earnings and Dividend Calendar

In general, I tend to avoid earnings or dividends (and other major events within 30 days of opening a position). Earnings are somewhat out again (start next month).

Portfolio allocation

See above: I need to start working on a balance between defined and undefined risk strategies to be added to my playbook.

This Week’s Guidelines

Positions at Beginning Of the Coming Week

I now have 6positions which is way below the average I need to have running to maximize my portfolio allocation at 2-3% position sizes and 50% overall allocations.

I am now at 15% buying power usage of which most is for short premium strategies. I have set the maximum allocation at 50%, so I need to add new positions quickly

I can exceptionally go up to 70% but I want to have at least a minimum of 30% in cash at all times, so can use 20% more in my account for emergencies or opportunities (so now 35% short premium and 15% debit/long strategies and 20% for emergencies).

Goals and Schedule for this week

Sunday: set up options strategy ideas and perform backtesting; select at least two options strategy ideas.

Until Tuesday: open one more vertical spread or iron condor and a long position.

Rest of the week: start looking at strategies involving buying bills or bonds for the remaining 10% of the 50%.

For short premium strategies, I need high IVR underlyings and underlyings trading in ranges with apparent resistance and support areas.

Underlyings Selected for Trading This Week

And during the week I will monitor stocks going into earnings.

For this week, I will continue applying my underlying selection rules and focus on high volatility (IVR >40) and higher premium underlyings that have no significant events (like earnings < 30 days) coming up.

My expectation (or rather: hope) is that this week’s volatility will increase again.

Options Buying Power and Portfolio Allocation This Week

Based on my current buying power and portfolio allocation rules, I determine whether I can open new positions to maximize such portfolio allocation.

I use VIX to determine the allocation percentage for short premium strategies. Since I until now only opened short strategies, this is still applicable to my whole portfolio.

However, with VIX going down to 20, I should be looking at using 5% of my total NetLiq for other strategies.

Allocation based on VIX (for short premium strategies)

VIX

< 15

15-19

20-29

30-40

>40

Volatility

Lowest volatility, all comfortable

Market in ‘lull’ mode

Volatility high

Volatility very high

Volatility and fear levels highest

Maximum portfolio capital allocation

25%

30%

35%

40%

50%

In allocating portfolio capital, I need to use Buying Power (NetLiq)

Cash Balance

$10,515.26
(was $11,670.39 )

Buying Power/Net Liq

$11,046.26
(was $11,192.38 )

Max Portfolio Capital Allocation Short Premium (Cash Available for Trading)

30%

$3,313,88

Max Portfolio Capital Allocation Other (low risk, long positions)

20%

$2,209.25

Average Max Position Allocation (BP)

3%

$331,39

I am now under-allocated for short premium, so need to add new debit position (s).

Portfolio allocation undefined vs defined risk

All my plays are ‘defined risk.’ I need to add undefined risk positions at a later stage. I will explain why in my blog post on constructing trades.

Since my average maximum position allocation is up to 3% and close to $330, I need to be looking for higher priced underlyings or increasing the number of contracts per position.

This Week’s Rules

I will start a post this week with my entry, adjustment, and exit rules per the options strategy. I will describe how I set up a playbook with all the strategies I want to deploy.

Conclusion

To continue to work on: weekly reminder: I still need to get more mechanical and disciplined in entering and adjusting the positions and remembering why I (or the platform) close positions.

The same for exiting. The focus is now on learning Python and quant finance to further support and improve my options trading.

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