Inspired by someone I never met

Inspiration is good and bad.

Paul Jarvis inspires me. He's a web person and writer who created his own category by being himself.

Paul said no thank you when everyone else was developing, building, and assuming greater responsibilities. This isn't success. He rewrote the rules. Working for himself, expanding at his own speed, and doing what he loves were his definitions of success.

Play with a problem that you have

The biggest problem can be not recognizing a problem.

Acceptance without question is deception. When you don't push limits, you forget how. You start thinking everything must be as it is.

For example: working. Paul worked a 9-5 agency work with little autonomy. He questioned whether the 9-5 was a way to live, not the way.

Another option existed. So he chipped away at how to live in this new environment.

Don't simply jump

Internet writers tell people considering quitting 9-5 to just quit. To throw in the towel. To do what you like.

The advice is harmful, despite the good intentions. People think quitting is hard. Like courage is the issue. Like handing your boss a resignation letter.

Nope. The tough part comes after. It’s easy to jump. Landing is difficult.

The landing

Paul didn't quit. Intelligent individuals don't. Smart folks focus on landing. They imagine life after 9-5.

Paul had been a web developer for a long time, had solid clients, and was respected. Hence if he pushed the limits and discovered another route, he had the potential to execute.

Working on the side

Society loves polarization. It’s left or right. Either way. Or chaos. It's 9-5 or entrepreneurship.

But like Paul, you can stretch polarization's limits. In-between exists.

You can work a 9-5 and side jobs (as I do). A mix of your favorites. The 9-5's stability and creativity. Fire and routine.

Remember you can't have everything but anything. You can create and work part-time.

My hybrid lifestyle

Not selling books doesn't destroy my world. My globe keeps spinning if my new business fails or if people don't like my Tweets. Unhappy algorithm? Cool. I'm not bothered (okay maybe a little).

The mix gives me the best of both worlds. To create, hone my skill, and grasp big-business basics. I like routine, but I also appreciate spending 4 hours on Saturdays writing.

Some days I adore leaving work at 5 pm and disconnecting. Other days, I adore having a place to write if inspiration strikes during a run or a discussion.

I’m a part-time creator

I’m a part-time creator. No, I'm not trying to quit. I don't work 5 pm - 2 am on the side. No, I'm not at $10,000 MRR.

I work part-time but enjoy my 9-5. My 9-5 has goodies. My side job as well.

It combines both to meet my lifestyle. I'm satisfied.

Join the Part-time Creators Club for free here. I’ll send you tips to enhance your creative game.

People are slowly recognizing entrepreneurship's downside.

Growing up, entrepreneurship wasn't common. High school class of 2012 had no entrepreneurs.

Businesses were different.

They had staff and a lengthy history of achievement.

I never wanted a business. It felt unattainable. My friends didn't care.

Weird.

People desired degrees to attain good jobs at big companies.

When graduated high school:

• 9 out of 10 people attend college

• Earn minimum wage (7%) working in a restaurant or retail establishment

• Or join the military (3%)

Later, entrepreneurship became a thing.

2014-ish

I was in the military and most of my high school friends were in college, so I didn't hear anything.

Entrepreneurship soared in 2015, according to Google Trends.

Then more individuals were interested. Entrepreneurship went from unusual to cool.

In 2015, it was easier than ever to build a website, run Facebook advertisements, and achieve organic social media reach.

There were several online business tools.

You didn't need to spend years or money figuring it out. Most entry barriers were gone.

Everyone wanted a side gig to escape the 95.

Small company applications have increased during the previous 10 years.

2011-2014 trend continues.

2015 adds 150,000 applications. 2016 adds 200,000. Plus 300,000 in 2017.

The graph makes it look little, but that's a considerable annual spike with no indications of stopping.

By 2021, new business apps had doubled.

Entrepreneurship will return to its early 2010s level.

I think we'll go backward in 5 years.

Entrepreneurship is half as popular as it was in 2015.

In the late 2020s and 30s, entrepreneurship will again be obscure.

Entrepreneurship's decade-long splendor is fading. People will cease escaping 9-5 and launch fewer companies.

That’s not a bad thing.

I think people have a rose-colored vision of entrepreneurship. It's fashionable. People feel that they're missing out if they're not entrepreneurial.

Reality is showing up.

People say on social media, "I knew starting a business would be hard, but not this hard."

More negative posts on entrepreneurship:

Luke adds:

Is being an entrepreneur ‘healthy’? I don’t really think so. Many like Gary V, are not role models for a well-balanced life. Despite what feel-good LinkedIn tells you the odds are against you as an entrepreneur. You have to work your face off. It’s a tough but rewarding lifestyle. So maybe let’s stop glorifying it because it takes a lot of (bleepin) work to survive a pandemic, mental health battles, and a competitive market.

Entrepreneurship is no longer a pipe dream.

It’s hard.

I went full-time in March 2020. I was done by April 2021. I had a good-paying job with perks.

When that fell through (on my start date), I had to continue my entrepreneurial path. I needed money by May 1 to pay rent.

Entrepreneurship isn't as great as many think.

Entrepreneurship is a serious business.

If you have a 9-5, the grass isn't greener here. Most people aren't telling the whole story when they post on social media or quote successful entrepreneurs.

People prefer to communicate their victories than their defeats.

Is this a bad thing?

I don’t think so.

Over the previous decade, entrepreneurship went from impossible to the finest thing ever.

It peaked in 2020-21 and is returning to reality.

Startups aren't for everyone.

If you like your job, don't quit.

Entrepreneurship won't amaze people if you quit your job.

It's irrelevant.

You're doomed.

And you'll probably make less money.

If you hate your job, quit. Change jobs and bosses. Changing jobs could net you a greater pay or better perks.

When you go solo, your paycheck and perks vanish. Did I mention you'll fail, sleep less, and stress more?

Nobody will stop you from pursuing entrepreneurship. You'll face several challenges.

Possibly.

Entrepreneurship may be romanticized for years.

Based on what I see from entrepreneurs on social media and trends, entrepreneurship is challenging and few will succeed.

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.

I placed a link on HackerNews and got 300 signups in a week. This post explains what happened.

Product Concept

The product is DbSchemaLibrary. A library of Database Schema.

I'm not sure where this idea originated from. Very fast. Build fast, fail fast, test many ideas, and one will be a hit. I tried it. Let's try it anyway, even though it'll probably fail. I finished The Lean Startup book and wanted to use it.

Database job bores me. Important! I get drowsy working on it. Someone must do it. I remember this happening once. I needed examples at the time. Something similar to Recall (my other project) that I can copy — or at least use as a reference.

Frequently googled. Many tabs open. The results were useless. I raised my hand and agreed to construct the database myself.

It resurfaced. I decided to do something.

Due Diligence

Lean Startup emphasizes validated learning. Everything the startup does should result in learning. I may build something nobody wants otherwise. That's what happened to Recall.

So, I wrote a business plan document. This happens before I code. What am I solving? What is my proposed solution? What is the leap of faith between the problem and solution? Who would be my target audience?

My note:

In my previous project, I did the opposite!

I wrote my expectations after reading the book's advice.

“Failure is a prerequisite to learning. The problem with the notion of shipping a product and then seeing what happens is that you are guaranteed to succeed — at seeing what happens.” — The Lean Startup book

These are successful metrics. If I don't reach them, I'll drop the idea and try another. I didn't understand numbers then. Below are guesses. But it’s a start!

I then wrote the project's What and Why. I'll use this everywhere. Before, I wrote a different pitch each time. I thought certain words would be better. I felt the audience might want something unusual.

Occasionally, this works. I'm unsure if it's a good idea. No stats, just my writing-time opinion. Writing every time is time-consuming and sometimes hazardous. Having a copy saved me duplication.

I can measure and learn from performance.

Last, I identified communities that might demand the product. This became an exercise in creativity.

The MVP

So now it’s time to build.

A MVP can test my assumptions. Business may learn from it. Not low-quality. We should learn from the tiniest thing.

I like the example of how Dropbox did theirs. They assumed that if the product works, people will utilize it. How can this be tested without a quality product? They made a movie demonstrating the software's functionality. Who knows how much functionality existed?

So I tested my biggest assumption. Users want schema references. How can I test if users want to reference another schema? I'd love this. Recall taught me that wanting something doesn't mean others do.

I made an email-collection landing page. Describe it briefly. Reference library. Each email sender wants a reference. They're interested in the product. Few other reasons exist.

Header and footer were skipped. No name or logo. DbSchemaLibrary is a name I thought of after the fact. 5-minute logo. I expected a flop. Recall has no users after months of labor. What could happen to a 2-day project?

I didn't compromise learning validation. How many visitors sign up? To draw a conclusion, I must track these results.

Posting Time

Now that the job is done, gauge interest. The next morning, I posted on all my channels. I didn't want to be spammy, therefore it required more time.

I made sure each channel had at least one fan of this product. I also answer people's inquiries in the channel.

My list stinks. Several channels wouldn't work. The product's target market isn't there. Posting there would waste our time. This taught me to create marketing channels depending on my persona.

Statistics! What actually happened

My favorite part! 23 channels received the link.

I stopped posting to Discord despite its high conversion rate. I eliminated some channels because they didn't fit. According to the numbers, some users like it. Most users think it's spam.

I was skeptical. And 12 people viewed it.

I didn't expect much attention on a startup subreddit. I'll likely examine Reddit further in the future. As I have enough info, I didn't post much. Time for the next validated learning

No comment. The post had few views, therefore the numbers are low.

The targeted people come next.

I'm a Toptal freelancer. There's a member-only Slack channel. Most people can't use this marketing channel, but you should! It's not as spectacular as discord's 27% conversion rate. But I think the users here are better.

I don’t really have a following anywhere so this isn’t something I can leverage.

The best yet. 10% is converted. With more data, I expect to attain a 10% conversion rate from other channels. Stable number.

This number required some work. Did you know that people use many different clients to read HN?

Unknowns

Untrackable views and signups abound. 1136 views and 135 signups are untraceable. It's 11%. I bet much of that came from Hackernews.

Overall Statistics

The 7-day signup-to-visit ratio was 17%. (Hourly data points)

First-day percentages were lower, which is noteworthy. Initially, it was little above 10%. The HN post started getting views then.

When traffic drops, the number reaches just around 20%. More individuals are interested in the connection. hn.algolia.com sent 2 visitors. This means people are searching and finding my post.

Interesting discoveries

1. HN post struggled till the US woke up.

11am UTC. After an hour, it lost popularity. It seemed over. 7 signups converted 13%. Not amazing, but I would've thought ahead.

After 4pm UTC, traffic grew again. 4pm UTC is 9am PDT. US awakened. 10am PDT saw 512 views.

2. The product was highlighted in a newsletter.

I found Revue references when gathering data. Newsletter platform. Someone posted the newsletter link. 37 views and 3 registrations.

3. HN numbers are extremely reliable

I don't have a time-lapse graph (yet). The statistics were constant all day.

• 2717 views later 272 new users, or 10.1%

• With 293 signups at 2856 views, 10.25%

• At 306 signups at 2965 views, 10.32%

Learnings

1. My initial estimations were wildly inaccurate

I wrote 30% conversion. Reading some articles, looks like 10% is a good number to aim for.

2. Paying attention to what matters rather than vain metrics

The Lean Startup discourages vanity metrics. Feel-good metrics that don't measure growth or traction. Considering the proportion instead of the total visitors made me realize there was something here.

What’s next?

There are lots of work to do. Data aggregation, display, website development, marketing, legal issues. Fun! It's satisfying to solve an issue rather than investigate its cause.

In the meantime, I’ve already written the first project update in another post. Continue reading it if you’d like to know more about the project itself! Shifting from Quantity to Quality — DbSchemaLibrary

These four, when combined, destroy procrastination.

You're not rushed. You waste it on busywork.

You'll accept this eventually.

• In 2022, the daily average usage of a user on social media is 2.5 hours.

• By 2020, 6 billion hours of video were watched each month by Netflix's customers, who used the service an average of 3.2 hours per day.

When we see these numbers, we think "Wow!" People squander so much time as though they don't contribute. True. These are yours. Likewise.

We don't lack time; we just waste it. Once you realize this, you can change your habits to save time. This article explains. If you adopt ALL 4 of these simple behaviors, you'll see amazing benefits.

Time-blocking

Cal Newport's time-blocking trick takes a minute but improves your day's clarity.

Divide the next day into 30-minute (or 5-minute, if you're Elon Musk) segments and assign responsibilities. As seen.

Here's why:

• The procrastination that results from attempting to determine when to begin working is eliminated. Procrastination is a given if you choose when to begin working in real-time. Even if you may assume you'll start working in five minutes, it won't take you long to realize that five minutes have turned into an hour. But if you've already determined to start working at 2:00 the next day, your odds of procrastinating are greatly decreased, if not eliminated altogether.

• You'll also see that you have a lot of time in a day when you plan your day out on paper and assign chores to each hour. Doing this daily will permanently eliminate the lack of time mindset.

5-4-3-2-1: Have breakfast with the frog!

“If it’s your job to eat a frog, it’s best to do it first thing in the morning. And If it’s your job to eat two frogs, it’s best to eat the biggest one first.”

Eating the frog means accomplishing the day's most difficult chore. It's better to schedule it first thing in the morning when time-blocking the night before. Why?

• The day's most difficult task is also the one that causes the most postponement. Because of the stress it causes, the later you schedule it, the more time you risk wasting by procrastinating.

• However, if you do it right away in the morning, you'll feel good all day. This is the reason it was set for the morning.

Mel Robbins' 5-second rule can help. Start counting backward 54321 and force yourself to start at 1. If you acquire the urge to work on a goal, you must act within 5 seconds or your brain will destroy it. If you're scheduled to eat your frog at 9, eat it at 8:59. Start working.

Micro-visualisation

You've heard of visualizing to enhance the future. Visualizing a bright future won't do much if you're not prepared to focus on the now and develop the necessary habits. Alexander said:

People don’t decide their futures. They decide their habits and their habits decide their future.

I visualize the next day's schedule every morning. My day looks like this

“I’ll start writing an article at 7:30 AM. Then, I’ll get dressed up and reach the medicine outpatient department by 9:30 AM. After my duty is over, I’ll have lunch at 2 PM, followed by a nap at 3 PM. Then, I’ll go to the gym at 4…”

etc.

This reinforces the day you planned the night before. This makes following your plan easy.

Set the timer.

It's the best iPhone productivity app. A timer is incredible for increasing productivity.

Set a timer for an hour or 40 minutes before starting work. Your call. I don't believe in techniques like the Pomodoro because I can focus for varied amounts of time depending on the time of day, how fatigued I am, and how cognitively demanding the activity is.

I work with a timer. A timer keeps you focused and prevents distractions. Your mind stays concentrated because of the timer. Timers generate accountability.

To pee, I'll pause my timer. When I sit down, I'll continue. Same goes for bottle refills. To use Twitter, I must pause the timer. This creates accountability and focuses work.

Connecting everything

If you do all 4, you won't be disappointed. Here's how:

• Plan out your day's schedule the night before.

• Next, envision in your mind's eye the same timetable in the morning.

• Speak aloud 54321 when it's time to work: Eat the frog! In the morning, devour the largest frog.

• Then set a timer to ensure that you remain focused on the task at hand.