WTF is wrong with you people?

When I was laid off as editor of my town's daily newspaper, I went silent on social media. I knew it was coming and had been quietly removing personal items each day, but the pain was intense.

I posted a day later. I didn't bad-mouth GateHouse Media but expressed my sadness at leaving the newspaper industry, pride in my accomplishments, and hope for success in another industry.

Normal job-loss response.

What do you recognize as abnormal?

The bullshit I’ve been reading from laid-off folks on LinkedIn.

If you're there, you know. Many Twitter or Facebook/Meta employees recently lost their jobs.

Well, many of them did not “lose their job,” actually. They were “impacted by the layoffs” at their former employer. I keep seeing that phrase.

Why don’t they want to actually say it? Why the euphemism?

Many are excited about the opportunities ahead. The jobless deny being sad.

They're ecstatic! They have big plans.

Hope so. Sincerely! Being laid off stinks, especially if, like me, your skills are obsolete. It's worse if, like me, you're too old to start a new career. Ageism exists despite denials.

Nowadays, professionalism seems to demand psychotic levels of fake optimism.

Why? Life is unpredictable. That's indisputable. You shouldn't constantly complain or cry in public, but you also shouldn't pretend everything's great.

It makes you look psychotic, not positive. It's like saying at work:

“I was impacted by the death of my spouse of 20 years this week, and many of you have reached out to me, expressing your sympathy. However, I’m choosing to remember the amazing things we shared. I feel confident that there is another marriage out there for me, and after taking a quiet weekend trip to reset myself, I’ll be out there looking for the next great marital adventure! #staypositive #available #opentolove

Also:

“Now looking for our next #dreamhome after our entire neighborhood was demolished by a wildfire last night. We feel so lucky to have lived near so many amazing and inspirational neighbors, all of whom we will miss as we go on our next housing adventure. The best house for us is yet to come! If you have a great neighborhood you’d recommend, please feel free to reach out and touch base with us! #newhouse #newneighborhood #newlife

Admit it. That’s creepy.

The constant optimism makes me feel sick to my stomach.

Viscerally.

I hate fakes.

Imagine a fake wood grain desk. Wouldn't it be better if the designer accepted that it's plastic and went with that?

Real is better but not always nice. When something isn't nice, you don't have to go into detail, but you also shouldn't pretend it's great.

How to announce your job loss to the world.

Do not pretend to be happy, but don't cry and drink vodka all afternoon.

Say you loved your job, and that you're looking for new opportunities.

Yes, if you'll miss your coworkers. Otherwise, don't badmouth. No bridge-burning!

Please specify the job you want. You may want to pivot.

Alternatively, try this.

You could always flame out.

If you've pushed yourself too far into toxic positivity, you may be ready to burn it all down. If so, make it worthwhile by writing something like this:

Well, I was shitcanned by the losers at #Acme today. That bitch Linda in HR threw me under the bus just because she saw that one of my “friends” tagged me in some beach pics on social media after I called in sick with Covid. The good thing is I will no longer have to watch my ass around that #asspincher Ron in accounting, but I’m sad that I will no longer have a cushy job with high pay or access to the primo office supplies I’ve been sneaking home for the last five years. (Those gel pens were the best!) I am going to be taking some time off to enjoy my unemployment and hammer down shots of Jägermeister but in about five months I’ll be looking for anything easy with high pay and great benefits. Reach out if you can help! #officesupplies #unemploymentrocks #drinkinglikeagirlboss #acmesucks

It beats the fake positivity.

I apologize if this sounds basic, but throughout my career, I've always been clear that a company's activities are shaped by its founder(s)' morality.

I consider Palantir, owned by PayPal founder Peter Thiel, evil. He got $5 billion tax-free by hacking a statute to help middle-class savings. That may appear clever, but I think it demonstrates a shocking lack of solidarity with society. As a result of this and other things he has said and done, I early on dismissed Peter Thiel as someone who could contribute anything positive to society, and events soon proved me right: we are talking about someone who clearly considers himself above everyone else and who does not hesitate to set up a company, Palantir, to exploit the data of the little people and sell it to the highest bidder, whoever that is and whatever the consequences.

The German courts have confirmed my warnings concerning Palantir. The problem is that politicians love its surveillance tools because they think knowing more about their constituents gives them power. These are ideal for dictatorships who want to snoop on their populace. Hence, Silicon Valley's triumphalist dialectic has seduced many governments at many levels and collected massive volumes of data to hold forever.

Dangerous company. There are many more. My analysis of the moral principles that disclose company management changed my opinion of Facebook, now Meta, and anyone with a modicum of interest might deduce when that happened, a discovery that leaves you dumbfounded. TikTok was easy because its lack of morality was revealed early when I saw the videos it encouraged minors to post and the repercussions of sharing them through its content recommendation algorithm. When you see something like this, nothing can convince you that the firm can change its morals and become good. Nothing. You know the company is awful and will fail. Speak it, announce it, and change it. It's like a fingerprint—unchangeable.

Some of you who read me frequently make its Facebook today jokes when I write about these firms, and that's fine: they're my moral standards, those of an elderly professor with thirty-five years of experience studying corporations and discussing their cases in class, but you don't have to share them. Since I'm writing this and don't have to submit to any editorial review, that's what it is: when you continuously read a person, you have to assume that they have moral standards and that sometimes you'll agree with them and sometimes you won't. Morality accepts hierarchies, nuances, and even obsessions. I know not everyone shares my opinions, but at least I can voice them. One day, one of those firms may sue me (as record companies did some years ago).

Palantir is incredibly harmful. Limit its operations. Like Meta and TikTok, its business strategy is shaped by its founders' immorality. Such a procedure can never be beneficial.

Kim Kardashian created Skky Partners. Consumer products, internet & e-commerce, consumer media, hospitality, and luxury are company targets.

Some call this another Kardashian publicity gimmick.

This maneuver is brilliance upon closer inspection. Why?

1) Kim has amassed a sizable social media fan base:

Over 320 million Instagram and 70 million Twitter users follow Kim Kardashian.

Kim Kardashian's Instagram account ranks 8th. Three Kardashians in top 10 is ridiculous.

This gives her access to consumer data. She knows what people are discussing. Investment firms need this data.

Quality, not quantity, of her followers matters. Studies suggest that her following are more engaged than Selena Gomez and Beyonce's.

Kim's followers are worth roughly $500 million to her brand, according to a research. They trust her and buy what she recommends.

2) She has a special aptitude for identifying trends.

Kim Kardashian can sense trends.

She's always ahead of fashion and beauty trends. She's always trying new things, too. She doesn't mind making mistakes when trying anything new. Her desire to experiment makes her a good business prospector.

Kim has also created a lifestyle brand that followers love. Kim is an entrepreneur, mom, and role model, not just a reality TV star or model. She's established a brand around her appearance, so people want to buy her things.

Her fragrance collection has sold over $100 million since its 2009 introduction, and her Sears apparel line did over $200 million in its first year.

SKIMS is her latest $3.2bn brand. She can establish multibillion-dollar firms with her enormous distribution platform.

Early founders would kill for Kim Kardashian's network.

Making great products is hard, but distribution is more difficult. — David Sacks, All-in-Podcast

3) She can delegate the financial choices to Jay Sammons, one of the greatest in the industry.

Jay Sammons is well-suited to develop Kim Kardashian's new private equity fund.

Sammons has 16 years of consumer investing experience at Carlyle. This will help Kardashian invest in consumer-facing enterprises.

Sammons has invested in Supreme and Beats Electronics, both of which have grown significantly. Sammons' track record and competence make him the obvious choice.

Kim Kardashian and Jay Sammons have joined forces to create a new business endeavor. The agreement will increase Kardashian's commercial empire. Sammons can leverage one of the world's most famous celebrities.

“Together we hope to leverage our complementary expertise to build the next generation consumer and media private equity firm” — Kim Kardashian

Kim Kardashian is a successful businesswoman. She developed an empire by leveraging social media to connect with fans. By developing a global lifestyle brand, she has sold things and experiences that have made her one of the world's richest celebrities.

She's a shrewd entrepreneur who knows how to maximize on herself and her image.

Imagine how much interest Kim K will bring to private equity and venture capital.

I'm curious about the company's growth.

Python Volatility-Based Catapult Indicator

As a catapult, this technical indicator uses three systems: Volatility (the fulcrum), Momentum (the propeller), and a Directional Filter (Acting as the support). The goal is to get a signal that predicts volatility acceleration and direction based on historical patterns. We want to know when the market will move. and where. This indicator outperforms standard indicators.

Knowledge must be accessible to everyone. This is why my new publications Contrarian Trading Strategies in Python and Trend Following Strategies in Python now include free PDF copies of my first three books (Therefore, purchasing one of the new books gets you 4 books in total). GitHub-hosted advanced indications and techniques are in the two new books above.

The Foundation: Volatility

The Catapult predicts significant changes with the 21-period Relative Volatility Index.

The Average True Range, Mean Absolute Deviation, and Standard Deviation all assess volatility. Standard Deviation will construct the Relative Volatility Index.

Standard Deviation is the most basic volatility. It underpins descriptive statistics and technical indicators like Bollinger Bands. Before calculating Standard Deviation, let's define Variance.

Variance is the squared deviations from the mean (a dispersion measure). We take the square deviations to compel the distance from the mean to be non-negative, then we take the square root to make the measure have the same units as the mean, comparing apples to apples (mean to standard deviation standard deviation). Variance formula:

As stated, standard deviation is:

# The function to add a number of columns inside an array
def adder(Data, times):
    
    for i in range(1, times + 1):
    
        new_col = np.zeros((len(Data), 1), dtype = float)
        Data = np.append(Data, new_col, axis = 1)
        
    return Data

# The function to delete a number of columns starting from an index
def deleter(Data, index, times):
    
    for i in range(1, times + 1):
    
        Data = np.delete(Data, index, axis = 1)
        
    return Data
    
# The function to delete a number of rows from the beginning
def jump(Data, jump):
    
    Data = Data[jump:, ]
    
    return Data

# Example of adding 3 empty columns to an array
my_ohlc_array = adder(my_ohlc_array, 3)

# Example of deleting the 2 columns after the column indexed at 3
my_ohlc_array = deleter(my_ohlc_array, 3, 2)

# Example of deleting the first 20 rows
my_ohlc_array = jump(my_ohlc_array, 20)

# Remember, OHLC is an abbreviation of Open, High, Low, and Close and it refers to the standard historical data file

def volatility(Data, lookback, what, where):
    
  for i in range(len(Data)):

     try:

        Data[i, where] = (Data[i - lookback + 1:i + 1, what].std())
     except IndexError:
        pass
        
  return Data

The RSI is the most popular momentum indicator, and for good reason—it excels in range markets. Its 0–100 range simplifies interpretation. Fame boosts its potential.

The more traders and portfolio managers look at the RSI, the more people will react to its signals, pushing market prices. Technical Analysis is self-fulfilling, therefore this theory is obvious yet unproven.

RSI is determined simply. Start with one-period pricing discrepancies. We must remove each closing price from the previous one. We then divide the smoothed average of positive differences by the smoothed average of negative differences. The RSI algorithm converts the Relative Strength from the last calculation into a value between 0 and 100.

def ma(Data, lookback, close, where): 
    
    Data = adder(Data, 1)
    
    for i in range(len(Data)):
           
            try:
                Data[i, where] = (Data[i - lookback + 1:i + 1, close].mean())
            
            except IndexError:
                pass
            
    # Cleaning
    Data = jump(Data, lookback)
    
    return Data
def ema(Data, alpha, lookback, what, where):
    
    alpha = alpha / (lookback + 1.0)
    beta  = 1 - alpha
    
    # First value is a simple SMA
    Data = ma(Data, lookback, what, where)
    
    # Calculating first EMA
    Data[lookback + 1, where] = (Data[lookback + 1, what] * alpha) + (Data[lookback, where] * beta)    
 
    # Calculating the rest of EMA
    for i in range(lookback + 2, len(Data)):
            try:
                Data[i, where] = (Data[i, what] * alpha) + (Data[i - 1, where] * beta)
        
            except IndexError:
                pass
            
    return Datadef rsi(Data, lookback, close, where, width = 1, genre = 'Smoothed'):
    
    # Adding a few columns
    Data = adder(Data, 7)
    
    # Calculating Differences
    for i in range(len(Data)):
        
        Data[i, where] = Data[i, close] - Data[i - width, close]
     
    # Calculating the Up and Down absolute values
    for i in range(len(Data)):
        
        if Data[i, where] > 0:
            
            Data[i, where + 1] = Data[i, where]
            
        elif Data[i, where] < 0:
            
            Data[i, where + 2] = abs(Data[i, where])
            
    # Calculating the Smoothed Moving Average on Up and Down
    absolute values        
                             
    lookback = (lookback * 2) - 1 # From exponential to smoothed
    Data = ema(Data, 2, lookback, where + 1, where + 3)
    Data = ema(Data, 2, lookback, where + 2, where + 4)
    
    # Calculating the Relative Strength
    Data[:, where + 5] = Data[:, where + 3] / Data[:, where + 4]
    
    # Calculate the Relative Strength Index
    Data[:, where + 6] = (100 - (100 / (1 + Data[:, where + 5])))  
    
    # Cleaning
    Data = deleter(Data, where, 6)
    Data = jump(Data, lookback)

    return Data

def relative_volatility_index(Data, lookback, close, where):

    # Calculating Volatility
    Data = volatility(Data, lookback, close, where)
    
    # Calculating the RSI on Volatility
    Data = rsi(Data, lookback, where, where + 1) 
    
    # Cleaning
    Data = deleter(Data, where, 1)
    
    return Data

The Arm Section: Speed

The Catapult predicts momentum direction using the 14-period Relative Strength Index.

As a reminder, the RSI ranges from 0 to 100. Two levels give contrarian signals:

• A positive response is anticipated when the market is deemed to have gone too far down at the oversold level 30, which is 30.

• When the market is deemed to have gone up too much, at overbought level 70, a bearish reaction is to be expected.

Comparing the RSI to 50 is another intriguing use. RSI above 50 indicates bullish momentum, while below 50 indicates negative momentum.

The direction-finding filter in the frame

The Catapult's directional filter uses the 200-period simple moving average to keep us trending. This keeps us sane and increases our odds.

Moving averages confirm and ride trends. Its simplicity and track record of delivering value to analysis make them the most popular technical indicator. They help us locate support and resistance, stops and targets, and the trend. Its versatility makes them essential trading tools.

This is the plain mean, employed in statistics and everywhere else in life. Simply divide the number of observations by their total values. Mathematically, it's:

We defined the moving average function above. Create the Catapult indication now.

Indicator of the Catapult

The indicator is a healthy mix of the three indicators:

• The first trigger will be provided by the 21-period Relative Volatility Index, which indicates that there will now be above average volatility and, as a result, it is possible for a directional shift.

• If the reading is above 50, the move is likely bullish, and if it is below 50, the move is likely bearish, according to the 14-period Relative Strength Index, which indicates the likelihood of the direction of the move.

• The likelihood of the move's direction will be strengthened by the 200-period simple moving average. When the market is above the 200-period moving average, we can infer that bullish pressure is there and that the upward trend will likely continue. Similar to this, if the market falls below the 200-period moving average, we recognize that there is negative pressure and that the downside is quite likely to continue.

lookback_rvi = 21
lookback_rsi = 14
lookback_ma  = 200
my_data = ma(my_data, lookback_ma, 3, 4)
my_data = rsi(my_data, lookback_rsi, 3, 5)
my_data = relative_volatility_index(my_data, lookback_rvi, 3, 6)

Two-handled overlay indicator Catapult. The first exhibits blue and green arrows for a buy signal, and the second shows blue and red for a sell signal.

The chart below shows recent EURUSD hourly values.

def signal(Data, rvi_col, signal):
    
    Data = adder(Data, 10)
        
    for i in range(len(Data)):
            
        if Data[i,     rvi_col] < 30 and \
           Data[i - 1, rvi_col] > 30 and \
           Data[i - 2, rvi_col] > 30 and \
           Data[i - 3, rvi_col] > 30 and \
           Data[i - 4, rvi_col] > 30 and \
           Data[i - 5, rvi_col] > 30:
               
               Data[i, signal] = 1
                           
    return Data

Signals are straightforward. The indicator can be utilized with other methods.

my_data = signal(my_data, 6, 7)

Lumiwealth shows how to develop all kinds of algorithms. I recommend their hands-on courses in algorithmic trading, blockchain, and machine learning.

Summary

To conclude, my goal is to contribute to objective technical analysis, which promotes more transparent methods and strategies that must be back-tested before implementation. Technical analysis will lose its reputation as subjective and unscientific.

After you find a trading method or approach, follow these steps:

• Put emotions aside and adopt an analytical perspective.

• Test it in the past in conditions and simulations taken from real life.

• Try improving it and performing a forward test if you notice any possibility.

• Transaction charges and any slippage simulation should always be included in your tests.

• Risk management and position sizing should always be included in your tests.

After checking the aforementioned, monitor the plan because market dynamics may change and render it unprofitable.

Offices without books are like bodies without souls.

After 10 years, my CEO sold his company for $30 million. I've shared many of his lessons on medium. You could ask him anything at his always-open office. He also said we could use his office for meetings while he was away. When I used his office for work, I was always struck by how many books he had.

Books are useful in almost every aspect of learning. Building a business, improving family relationships, learning a new language, a new skill... Books teach, guide, and structure. Whether fiction or nonfiction, books inspire, give ideas, and develop critical thinking skills.

My CEO prefers non-fiction and attends a Friday book club. This article discusses 5 books I found in his office that impacted my life/business. My CEO sold his company for $30 million, but I've built a steady business through blogging and video making.

I recall events and lessons I learned from my CEO and how they relate to each book, and I explain how I applied the book's lessons to my business and life.

Note: This post has no affiliate links.

1. The One Thing — Gary Keller

Gary Keller, a real estate agent, wanted more customers. So he and his team brainstormed ways to get more customers. They decided to write a bestseller about work and productivity. The more people who saw the book, the more customers they'd get.

Gary Keller focused on writing the best book on productivity, work, and efficiency for months. His business experience. Keller's business grew after the book's release.

The author summarizes the book in one question.

"What's the one thing that will make everything else easier or unnecessary?"

When I started my blog and business alongside my 9–5, I quickly identified my one thing: writing. My business relied on it, so it had to be great. Without writing, there was no content, traffic, or business.

My CEO focused on funding when he started his business. Even in his final years, he spent a lot of time on the phone with investors, either to get more money or to explain what he was doing with it. My CEO's top concern was money, and the other super important factors were handled by separate teams.

• Product tech and design

• Incredible customer support team

• Excellent promotion team

• Profitable sales team

My CEO didn't always focus on one thing and ignore the rest. He was on all of those teams when I started my job. He'd start his day in tech, have lunch with marketing, and then work in sales. He was in his office on the phone at night.

He eventually realized his errors. Investors told him he couldn't do everything for the company. If needed, he had to change internally. He learned to let go, mind his own business, and focus for the next four years. Then he sold for $30 million.

The bigger your project/company/idea, the more you'll need to delegate to stay laser-focused. I started something new every few months for 10 years before realizing this. So much to do makes it easy to avoid progress. Once you identify the most important aspect of your project and enlist others' help, you'll be successful.

2. Eat That Frog — Brian Tracy

The author quote sums up book's essence:

Mark Twain said that if you eat a live frog in the morning, it's probably the worst thing that will happen to you all day. Your "frog" is the biggest, most important task you're most likely to procrastinate on.

"Frog" and "One Thing" are both about focusing on what's most important. Eat That Frog recommends doing the most important task first thing in the morning.

I shared my CEO's calendar in an article 10 months ago. Like this:

CEO's average week (some information crossed out for confidentiality)

Notice anything about 8am-8:45am? Almost every day is the same (except Friday). My CEO started his day with a management check-in for 2 reasons:

• Checking in with all managers is cognitively demanding, and my CEO is a morning person.

• In a young startup where everyone is busy, the morning management check-in was crucial. After 10 am, you couldn't gather all managers.

When I started my blog, writing was my passion. I'm a morning person, so I woke up at 6 am and started writing by 6:30 am every day for a year. This allowed me to publish 3 articles a week for 52 weeks to build my blog and audience. After 2 years, I'm not stopping.

3. Deep Work — Cal Newport

Deep work is focusing on a cognitively demanding task without distractions (like a morning management meeting). It helps you master complex information quickly and produce better results faster. In a competitive world 10 or 20 years ago, focus wasn't a huge advantage. Smartphones, emails, and social media made focus a rare, valuable skill.

Most people can't focus anymore. Screens light up, notifications buzz, emails arrive, Instagram feeds... Many people don't realize they're interrupted because it's become part of their normal workflow.

Cal Newport mentions Bill Gates' "Think Weeks" in Deep Work.

Microsoft CEO Bill Gates would isolate himself (often in a lakeside cottage) twice a year to read and think big thoughts.

Inside Bill's Brain on Netflix shows Newport's lakeside cottage. I've always wanted a lakeside cabin to work in. My CEO bought a lakehouse after selling his company, but now he's retired.

As a company grows, you can focus less on it. In a previous section, I said investors told my CEO to get back to basics and stop micromanaging. My CEO's commitment and ability to get work done helped save the company. His deep work and new frameworks helped us survive the corona crisis (more on this later).

The ability to deep work will be a huge competitive advantage in the next century. Those who learn to work deeply will likely be successful while everyone else is glued to their screens, Bluetooth-synced to their watches, and playing Candy Crush on their tablets.

4. The 7 Habits of Highly Effective People — Stephen R. Covey

It took me a while to start reading this book because it seemed like another shallow self-help bible. I kept finding this book when researching self-improvement. I tried it because it was everywhere.

Stephen Covey taught me 2 years ago to have a personal mission statement.

A 7 Habits mission statement describes the life you want to lead, the character traits you want to embody, and the impact you want to have on others. shortform.com

I've had many lunches with my CEO and talked about Vipassana meditation and Sunday forest runs, but I've never seen his mission statement. I'm sure his family is important, though. In the above calendar screenshot, you can see he always included family events (in green) so we could all see those time slots. We couldn't book him then. Although he never spent as much time with his family as he wanted, he always made sure to be on time for his kid's birthday rather than a conference call.

My CEO emphasized his company's mission. Your mission statement should answer 3 questions.

• What does your company do?

• How does it do it?

• Why does your company do it?

As a graphic designer, I had to create mission-statement posters. My CEO hung posters in each office.

5. Measure What Matters — John Doerr

This book is about Andrew Grove's OKR strategy, developed in 1968. When he joined Google's early investors board, he introduced it to Larry Page and Sergey Brin. Google still uses OKR.

Objective Key Results

• Objective: It explains your goals and desired outcome. When one goal is reached, another replaces it. OKR objectives aren't technical, measured, or numerical. They must be clear.

• Key Result should be precise, technical, and measurable, unlike the Objective. It shows if the Goal is being worked on. Time-bound results are quarterly or yearly.

Our company almost sank several times. Sales goals were missed, management failed, and bad decisions were made. On a Monday, our CEO announced we'd implement OKR to revamp our processes.

This was a year before the pandemic, and I'm certain we wouldn't have sold millions or survived without this change. This book impacted the company the most, not just management but all levels. Organization and transparency improved. We reached realistic goals. Happy investors. We used the online tool Gtmhub to implement OKR across the organization.

My CEO's company went from near bankruptcy to being acquired for $30 million in 2 years after implementing OKR.

I hope you enjoyed this booklist. Here's a recap of the 5 books and the lessons I learned from each.

1. The 7 Habits of Highly Effective People — Stephen R. Covey

Have a mission statement that outlines your goals, character traits, and impact on others.

1. Deep Work — Cal Newport

Focus is a rare skill; master it. Deep workers will succeed in our hyper-connected, distracted world.

1. The One Thing — Gary Keller

What can you do that will make everything else easier or unnecessary? Once you've identified it, focus on it.

1. Eat That Frog — Brian Tracy

Identify your most important task the night before and do it first thing in the morning. You'll have a lighter day.

1. Measure What Matters — John Doerr

On a timeline, divide each long-term goal into chunks. Divide those slices into daily tasks (your goals). Time-bound results are quarterly or yearly. Objectives aren't measured or numbered.

Thanks for reading. Enjoy the ride!