More on Entrepreneurship/Creators
Raad Ahmed
3 years ago
How We Just Raised $6M At An $80M Valuation From 100+ Investors Using A Link (Without Pitching)
Lawtrades nearly failed three years ago.
We couldn't raise Series A or enthusiasm from VCs.
We raised $6M (at a $80M valuation) from 100 customers and investors using a link and no pitching.
Step-by-step:
We refocused our business first.
Lawtrades raised $3.7M while Atrium raised $75M. By comparison, we seemed unimportant.
We had to close the company or try something new.
As I've written previously, a pivot saved us. Our initial focus on SMBs attracted many unprofitable customers. SMBs needed one-off legal services, meaning low fees and high turnover.
Tech startups were different. Their General Councels (GCs) needed near-daily support, resulting in higher fees and lower churn than SMBs.
We stopped unprofitable customers and focused on power users. To avoid dilution, we borrowed against receivables. We scaled our revenue 10x, from $70k/mo to $700k/mo.
Then, we reconsidered fundraising (and do it differently)
This time was different. Lawtrades was cash flow positive for most of last year, so we could dictate our own terms. VCs were still wary of legaltech after Atrium's shutdown (though they were thinking about the space).
We neither wanted to rely on VCs nor dilute more than 10% equity. So we didn't compete for in-person pitch meetings.
AngelList Roll-Up Vehicle (RUV). Up to 250 accredited investors can invest in a single RUV. First, we emailed customers the RUV. Why? Because I wanted to help the platform's users.
Imagine if Uber or Airbnb let all drivers or Superhosts invest in an RUV. Humans make the platform, theirs and ours. Giving people a chance to invest increases their loyalty.
We expanded after initial interest.
We created a Journey link, containing everything that would normally go in an investor pitch:
- Slides
- Trailer (from me)
- Testimonials
- Product demo
- Financials
We could also link to our AngelList RUV and send the pitch to an unlimited number of people. Instead of 1:1, we had 1:10,000 pitches-to-investors.
We posted Journey's link in RUV Alliance Discord. 600 accredited investors noticed it immediately. Within days, we raised $250,000 from customers-turned-investors.
Stonks, which live-streamed our pitch to thousands of viewers, was interested in our grassroots enthusiasm. We got $1.4M from people I've never met.
These updates on Pump generated more interest. Facebook, Uber, Netflix, and Robinhood executives all wanted to invest. Sahil Lavingia, who had rejected us, gave us $100k.
We closed the round with public support.
Without a single pitch meeting, we'd raised $2.3M. It was a result of natural enthusiasm: taking care of the people who made us who we are, letting them move first, and leveraging their enthusiasm with VCs, who were interested.
We used network effects to raise $3.7M from a founder-turned-VC, bringing the total to $6M at a $80M valuation (which, by the way, I set myself).
What flipping the fundraising script allowed us to do:
We started with private investors instead of 2–3 VCs to show VCs what we were worth. This gave Lawtrades the ability to:
- Without meetings, share our vision. Many people saw our Journey link. I ended up taking meetings with people who planned to contribute $50k+, but still, the ratio of views-to-meetings was outrageously good for us.
- Leverage ourselves. Instead of us selling ourselves to VCs, they did. Some people with large checks or late arrivals were turned away.
- Maintain voting power. No board seats were lost.
- Utilize viral network effects. People-powered.
- Preemptively halt churn by turning our users into owners. People are more loyal and respectful to things they own. Our users make us who we are — no matter how good our tech is, we need human beings to use it. They deserve to be owners.
I don't blame founders for being hesitant about this approach. Pump and RUVs are new and scary. But it won’t be that way for long. Our approach redistributed some of the power that normally lies entirely with VCs, putting it into our hands and our network’s hands.
This is the future — another way power is shifting from centralized to decentralized.
Jenn Leach
3 years ago
How Much I Got Paid by YouTube for a 68 Million Views Video
My nameless, faceless channel case study
The Numbers
I anonymize this YouTube channel.
It's in a trendy, crowded niche. Sharing it publicly will likely enhance competition.
I'll still share my dashboard numbers:
A year ago, the video was released.
What I earned
I'll stop stalling. Here's a screenshot of my YouTube statistics page displaying Adsense profits.
YouTube Adsense made me ZERO dollars.
OMG!
How is this possible?
YouTube Adsense can't monetize my niche. This is typical in faceless niches like TikTok's rain videos. If they were started a while ago, I'm sure certain rain accounts are monetized, but not today.
I actually started a soothing sounds faceless YouTube channel. This was another account of mine.
I looped Pexels films for hours. No background music, just wind, rain, etc.
People could watch these videos to relax or get ready for bed. They're ideal for background noise and relaxation.
They're long-lasting, too. It's easy to make a lot from YouTube Adsense if you insert ads.
Anyway, I tried to monetize it and couldn’t. This was about a year ago. That’s why I doubt new accounts in this genre would be able to get approved for ads.
Back to my faceless channel with 68 million views.
I received nothing from YouTube Adsense, but I made money elsewhere.
Getting paid by the gods of affiliate marketing
Place links in the video and other videos on the channel to get money. Visitors that buy through your affiliate link earn you a commission.
This video earned many clicks on my affiliate links.
I linked to a couple of Amazon products, a YouTube creator tool, my kofi link, and my subscribe link.
Sponsorships
Brands pay you to include ads in your videos.
This video led to many sponsorships.
I've done dozens of sponsorship campaigns that paid $40 to $50 for an end screen to $450 for a preroll ad.
Last word
Overall, I made less than $3,000.
If I had time, I'd be more proactive with sponsorships. You can pitch brand sponsorships. This actually works.
I'd do that if I could rewind time.
I still can, but I think the reaction rate would be higher closer to the viral video's premiere date.
Alex Mathers
2 years ago
How to Produce Enough for People to Not Neglect You
Internet's fantastic, right?
We've never had a better way to share our creativity.
I can now draw on my iPad and tweet or Instagram it to thousands. I may get some likes.
With such a great, free tool, you're not alone.
Millions more bright-eyed artists are sharing their work online.
The issue is getting innovative work noticed, not sharing it.
In a world where creators want attention, attention is valuable.
We build for attention.
Attention helps us establish a following, make money, get notoriety, and make a difference.
Most of us require attention to stay sane while creating wonderful things.
I know how hard it is to work hard and receive little views.
How do we receive more attention, more often, in a sea of talent?
Advertising and celebrity endorsements are options. These may work temporarily.
To attract true, organic, and long-term attention, you must create in high quality, high volume, and consistency.
Adapting Steve Martin's Be so amazing, they can't ignore you (with a mention to Dan Norris in his great book Create or Hate for the reminder)
Create a lot.
Eventually, your effort will gain traction.
Traction shows your work's influence.
Traction is when your product sells more. Traction is exponential user growth. Your work is shared more.
No matter how good your work is, it will always have minimal impact on the world.
Your work can eventually dent or puncture. Daily, people work to dent.
To achieve this tipping point, you must consistently produce exceptional work.
Expect traction after hundreds of outputs.
Dilbert creator Scott Adams says repetition persuades. If you don't stop, you can persuade practically anyone with anything.
Volume lends believability. So make more.
I worked as an illustrator for at least a year and a half without any recognition. After 150 illustrations on iStockphoto, my work started selling.
With 350 illustrations on iStock, I started getting decent client commissions.
Producing often will improve your craft and draw attention.
It's the only way to succeed. More creation means better results and greater attention.
Austin Kleon says you can improve your skill in relative anonymity before you become famous. Before obtaining traction, generate a lot and become excellent.
Most artists, even excellent ones, don't create consistently enough to get traction.
It may hurt. For makers who don't love and flow with their work, it's extremely difficult.
Your work must bring you to life.
To generate so much that others can't ignore you, decide what you'll accomplish every day (or most days).
Commit and be patient.
Prepare for zero-traction.
Anticipating this will help you persevere and create.
My online guru Grant Cardone says: Anything worth doing is worth doing every day.
Do.
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Ryan Weeks
3 years ago
Terra fiasco raises TRON's stablecoin backstop
After Terra's algorithmic stablecoin collapsed in May, TRON announced a plan to increase the capital backing its own stablecoin.
USDD, a near-carbon copy of Terra's UST, arrived on the TRON blockchain on May 5. TRON founder Justin Sun says USDD will be overcollateralized after initially being pegged algorithmically to the US dollar.
A reserve of cryptocurrencies and stablecoins will be kept at 130 percent of total USDD issuance, he said. TRON described the collateral ratio as "guaranteed" and said it would begin publishing real-time updates on June 5.
Currently, the reserve contains 14,040 bitcoin (around $418 million), 140 million USDT, 1.9 billion TRX, and 8.29 billion TRX in a burning contract.
Sun: "We want to hybridize USDD." We have an algorithmic stablecoin and TRON DAO Reserve.
algorithmic failure
USDD was designed to incentivize arbitrageurs to keep its price pegged to the US dollar by trading TRX, TRON's token, and USDD. Like Terra, TRON signaled its intent to establish a bitcoin and cryptocurrency reserve to support USDD in extreme market conditions.
Still, Terra's UST failed despite these safeguards. The stablecoin veered sharply away from its dollar peg in mid-May, bringing down Terra's LUNA and wiping out $40 billion in value in days. In a frantic attempt to restore the peg, billions of dollars in bitcoin were sold and unprecedented volumes of LUNA were issued.
Sun believes USDD, which has a total circulating supply of $667 million, can be backed up.
"Our reserve backing is diversified." Bitcoin and stablecoins are included. USDC will be a small part of Circle's reserve, he said.
TRON's news release lists the reserve's assets as bitcoin, TRX, USDC, USDT, TUSD, and USDJ.
All Bitcoin addresses will be signed so everyone knows they belong to us, Sun said.
Not giving in
Sun told that the crypto industry needs "decentralized" stablecoins that regulators can't touch.
Sun said the Luna Foundation Guard, a Singapore-based non-profit that raised billions in cryptocurrency to buttress UST, mismanaged the situation by trying to sell to panicked investors.
He said, "We must be ahead of the market." We want to stabilize the market and reduce volatility.
Currently, TRON finances most of its reserve directly, but Sun says the company hopes to add external capital soon.
Before its demise, UST holders could park the stablecoin in Terra's lending platform Anchor Protocol to earn 20% interest, which many deemed unsustainable. TRON's JustLend is similar. Sun hopes to raise annual interest rates from 17.67% to "around 30%."
This post is a summary. Read full article here
Justin Kuepper
3 years ago
Day Trading Introduction
Historically, only large financial institutions, brokerages, and trading houses could actively trade in the stock market. With instant global news dissemination and low commissions, developments such as discount brokerages and online trading have leveled the playing—or should we say trading—field. It's never been easier for retail investors to trade like pros thanks to trading platforms like Robinhood and zero commissions.
Day trading is a lucrative career (as long as you do it properly). But it can be difficult for newbies, especially if they aren't fully prepared with a strategy. Even the most experienced day traders can lose money.
So, how does day trading work?
Day Trading Basics
Day trading is the practice of buying and selling a security on the same trading day. It occurs in all markets, but is most common in forex and stock markets. Day traders are typically well educated and well funded. For small price movements in highly liquid stocks or currencies, they use leverage and short-term trading strategies.
Day traders are tuned into short-term market events. News trading is a popular strategy. Scheduled announcements like economic data, corporate earnings, or interest rates are influenced by market psychology. Markets react when expectations are not met or exceeded, usually with large moves, which can help day traders.
Intraday trading strategies abound. Among these are:
- Scalping: This strategy seeks to profit from minor price changes throughout the day.
- Range trading: To determine buy and sell levels, range traders use support and resistance levels.
- News-based trading exploits the increased volatility around news events.
- High-frequency trading (HFT): The use of sophisticated algorithms to exploit small or short-term market inefficiencies.
A Disputed Practice
Day trading's profit potential is often debated on Wall Street. Scammers have enticed novices by promising huge returns in a short time. Sadly, the notion that trading is a get-rich-quick scheme persists. Some daytrade without knowledge. But some day traders succeed despite—or perhaps because of—the risks.
Day trading is frowned upon by many professional money managers. They claim that the reward rarely outweighs the risk. Those who day trade, however, claim there are profits to be made. Profitable day trading is possible, but it is risky and requires considerable skill. Moreover, economists and financial professionals agree that active trading strategies tend to underperform passive index strategies over time, especially when fees and taxes are factored in.
Day trading is not for everyone and is risky. It also requires a thorough understanding of how markets work and various short-term profit strategies. Though day traders' success stories often get a lot of media attention, keep in mind that most day traders are not wealthy: Many will fail, while others will barely survive. Also, while skill is important, bad luck can sink even the most experienced day trader.
Characteristics of a Day Trader
Experts in the field are typically well-established professional day traders.
They usually have extensive market knowledge. Here are some prerequisites for successful day trading.
Market knowledge and experience
Those who try to day-trade without understanding market fundamentals frequently lose. Day traders should be able to perform technical analysis and read charts. Charts can be misleading if not fully understood. Do your homework and know the ins and outs of the products you trade.
Enough capital
Day traders only use risk capital they can lose. This not only saves them money but also helps them trade without emotion. To profit from intraday price movements, a lot of capital is often required. Most day traders use high levels of leverage in margin accounts, and volatile market swings can trigger large margin calls on short notice.
Strategy
A trader needs a competitive advantage. Swing trading, arbitrage, and trading news are all common day trading strategies. They tweak these strategies until they consistently profit and limit losses.
Strategy Breakdown:
Type | Risk | Reward
Swing Trading | High | High
Arbitrage | Low | Medium
Trading News | Medium | Medium
Mergers/Acquisitions | Medium | High
Discipline
A profitable strategy is useless without discipline. Many day traders lose money because they don't meet their own criteria. “Plan the trade and trade the plan,” they say. Success requires discipline.
Day traders profit from market volatility. For a day trader, a stock's daily movement is appealing. This could be due to an earnings report, investor sentiment, or even general economic or company news.
Day traders also prefer highly liquid stocks because they can change positions without affecting the stock's price. Traders may buy a stock if the price rises. If the price falls, a trader may decide to sell short to profit.
A day trader wants to trade a stock that moves (a lot).
Day Trading for a Living
Professional day traders can be self-employed or employed by a larger institution.
Most day traders work for large firms like hedge funds and banks' proprietary trading desks. These traders benefit from direct counterparty lines, a trading desk, large capital and leverage, and expensive analytical software (among other advantages). By taking advantage of arbitrage and news events, these traders can profit from less risky day trades before individual traders react.
Individual traders often manage other people’s money or simply trade with their own. They rarely have access to a trading desk, but they frequently have strong ties to a brokerage (due to high commissions) and other resources. However, their limited scope prevents them from directly competing with institutional day traders. Not to mention more risks. Individuals typically day trade highly liquid stocks using technical analysis and swing trades, with some leverage.
Day trading necessitates access to some of the most complex financial products and services. Day traders usually need:
Access to a trading desk
Traders who work for large institutions or manage large sums of money usually use this. The trading or dealing desk provides these traders with immediate order execution, which is critical during volatile market conditions. For example, when an acquisition is announced, day traders interested in merger arbitrage can place orders before the rest of the market.
News sources
The majority of day trading opportunities come from news, so being the first to know when something significant happens is critical. It has access to multiple leading newswires, constant news coverage, and software that continuously analyzes news sources for important stories.
Analytical tools
Most day traders rely on expensive trading software. Technical traders and swing traders rely on software more than news. This software's features include:
-
Automatic pattern recognition: It can identify technical indicators like flags and channels, or more complex indicators like Elliott Wave patterns.
-
Genetic and neural applications: These programs use neural networks and genetic algorithms to improve trading systems and make more accurate price predictions.
-
Broker integration: Some of these apps even connect directly to the brokerage, allowing for instant and even automatic trade execution. This reduces trading emotion and improves execution times.
-
Backtesting: This allows traders to look at past performance of a strategy to predict future performance. Remember that past results do not always predict future results.
Together, these tools give traders a competitive advantage. It's easy to see why inexperienced traders lose money without them. A day trader's earnings potential is also affected by the market in which they trade, their capital, and their time commitment.
Day Trading Risks
Day trading can be intimidating for the average investor due to the numerous risks involved. The SEC highlights the following risks of day trading:
Because day traders typically lose money in their first months of trading and many never make profits, they should only risk money they can afford to lose.
Trading is a full-time job that is stressful and costly: Observing dozens of ticker quotes and price fluctuations to spot market trends requires intense concentration. Day traders also spend a lot on commissions, training, and computers.
Day traders heavily rely on borrowing: Day-trading strategies rely on borrowed funds to make profits, which is why many day traders lose everything and end up in debt.
Avoid easy profit promises: Avoid “hot tips” and “expert advice” from day trading newsletters and websites, and be wary of day trading educational seminars and classes.
Should You Day Trade?
As stated previously, day trading as a career can be difficult and demanding.
- First, you must be familiar with the trading world and know your risk tolerance, capital, and goals.
- Day trading also takes a lot of time. You'll need to put in a lot of time if you want to perfect your strategies and make money. Part-time or whenever isn't going to cut it. You must be fully committed.
- If you decide trading is for you, remember to start small. Concentrate on a few stocks rather than jumping into the market blindly. Enlarging your trading strategy can result in big losses.
- Finally, keep your cool and avoid trading emotionally. The more you can do that, the better. Keeping a level head allows you to stay focused and on track.
If you follow these simple rules, you may be on your way to a successful day trading career.
Is Day Trading Illegal?
Day trading is not illegal or unethical, but it is risky. Because most day-trading strategies use margin accounts, day traders risk losing more than they invest and becoming heavily in debt.
How Can Arbitrage Be Used in Day Trading?
Arbitrage is the simultaneous purchase and sale of a security in multiple markets to profit from small price differences. Because arbitrage ensures that any deviation in an asset's price from its fair value is quickly corrected, arbitrage opportunities are rare.
Why Don’t Day Traders Hold Positions Overnight?
Day traders rarely hold overnight positions for several reasons: Overnight trades require more capital because most brokers require higher margin; stocks can gap up or down on overnight news, causing big trading losses; and holding a losing position overnight in the hope of recovering some or all of the losses may be against the trader's core day-trading philosophy.
What Are Day Trader Margin Requirements?
Regulation D requires that a pattern day trader client of a broker-dealer maintain at all times $25,000 in equity in their account.
How Much Buying Power Does Day Trading Have?
Buying power is the total amount of funds an investor has available to trade securities. FINRA rules allow a pattern day trader to trade up to four times their maintenance margin excess as of the previous day's close.
The Verdict
Although controversial, day trading can be a profitable strategy. Day traders, both institutional and retail, keep the markets efficient and liquid. Though day trading is still popular among novice traders, it should be left to those with the necessary skills and resources.
Sofien Kaabar, CFA
3 years ago
How to Make a Trading Heatmap
Python Heatmap Technical Indicator
Heatmaps provide an instant overview. They can be used with correlations or to predict reactions or confirm the trend in trading. This article covers RSI heatmap creation.
The Market System
Market regime:
Bullish trend: The market tends to make higher highs, which indicates that the overall trend is upward.
Sideways: The market tends to fluctuate while staying within predetermined zones.
Bearish trend: The market has the propensity to make lower lows, indicating that the overall trend is downward.
Most tools detect the trend, but we cannot predict the next state. The best way to solve this problem is to assume the current state will continue and trade any reactions, preferably in the trend.
If the EURUSD is above its moving average and making higher highs, a trend-following strategy would be to wait for dips before buying and assuming the bullish trend will continue.
Indicator of Relative Strength
J. Welles Wilder Jr. introduced the RSI, a popular and versatile technical indicator. Used as a contrarian indicator to exploit extreme reactions. Calculating the default RSI usually involves these steps:
Determine the difference between the closing prices from the prior ones.
Distinguish between the positive and negative net changes.
Create a smoothed moving average for both the absolute values of the positive net changes and the negative net changes.
Take the difference between the smoothed positive and negative changes. The Relative Strength RS will be the name we use to describe this calculation.
To obtain the RSI, use the normalization formula shown below for each time step.
The 13-period RSI and black GBPUSD hourly values are shown above. RSI bounces near 25 and pauses around 75. Python requires a four-column OHLC array for RSI coding.
import numpy as np
def add_column(data, times):
for i in range(1, times + 1):
new = np.zeros((len(data), 1), dtype = float)
data = np.append(data, new, axis = 1)
return data
def delete_column(data, index, times):
for i in range(1, times + 1):
data = np.delete(data, index, axis = 1)
return data
def delete_row(data, number):
data = data[number:, ]
return data
def ma(data, lookback, close, position):
data = add_column(data, 1)
for i in range(len(data)):
try:
data[i, position] = (data[i - lookback + 1:i + 1, close].mean())
except IndexError:
pass
data = delete_row(data, lookback)
return data
def smoothed_ma(data, alpha, lookback, close, position):
lookback = (2 * lookback) - 1
alpha = alpha / (lookback + 1.0)
beta = 1 - alpha
data = ma(data, lookback, close, position)
data[lookback + 1, position] = (data[lookback + 1, close] * alpha) + (data[lookback, position] * beta)
for i in range(lookback + 2, len(data)):
try:
data[i, position] = (data[i, close] * alpha) + (data[i - 1, position] * beta)
except IndexError:
pass
return data
def rsi(data, lookback, close, position):
data = add_column(data, 5)
for i in range(len(data)):
data[i, position] = data[i, close] - data[i - 1, close]
for i in range(len(data)):
if data[i, position] > 0:
data[i, position + 1] = data[i, position]
elif data[i, position] < 0:
data[i, position + 2] = abs(data[i, position])
data = smoothed_ma(data, 2, lookback, position + 1, position + 3)
data = smoothed_ma(data, 2, lookback, position + 2, position + 4)
data[:, position + 5] = data[:, position + 3] / data[:, position + 4]
data[:, position + 6] = (100 - (100 / (1 + data[:, position + 5])))
data = delete_column(data, position, 6)
data = delete_row(data, lookback)
return dataMake sure to focus on the concepts and not the code. You can find the codes of most of my strategies in my books. The most important thing is to comprehend the techniques and strategies.
My weekly market sentiment report uses complex and simple models to understand the current positioning and predict the future direction of several major markets. Check out the report here:
Using the Heatmap to Find the Trend
RSI trend detection is easy but useless. Bullish and bearish regimes are in effect when the RSI is above or below 50, respectively. Tracing a vertical colored line creates the conditions below. How:
When the RSI is higher than 50, a green vertical line is drawn.
When the RSI is lower than 50, a red vertical line is drawn.
Zooming out yields a basic heatmap, as shown below.
Plot code:
def indicator_plot(data, second_panel, window = 250):
fig, ax = plt.subplots(2, figsize = (10, 5))
sample = data[-window:, ]
for i in range(len(sample)):
ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)
if sample[i, 3] > sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)
if sample[i, 3] < sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
if sample[i, 3] == sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
ax[0].grid()
for i in range(len(sample)):
if sample[i, second_panel] > 50:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)
if sample[i, second_panel] < 50:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)
ax[1].grid()
indicator_plot(my_data, 4, window = 500)
Call RSI on your OHLC array's fifth column. 4. Adjusting lookback parameters reduces lag and false signals. Other indicators and conditions are possible.
Another suggestion is to develop an RSI Heatmap for Extreme Conditions.
Contrarian indicator RSI. The following rules apply:
Whenever the RSI is approaching the upper values, the color approaches red.
The color tends toward green whenever the RSI is getting close to the lower values.
Zooming out yields a basic heatmap, as shown below.
Plot code:
import matplotlib.pyplot as plt
def indicator_plot(data, second_panel, window = 250):
fig, ax = plt.subplots(2, figsize = (10, 5))
sample = data[-window:, ]
for i in range(len(sample)):
ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)
if sample[i, 3] > sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)
if sample[i, 3] < sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
if sample[i, 3] == sample[i, 0]:
ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)
ax[0].grid()
for i in range(len(sample)):
if sample[i, second_panel] > 90:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)
if sample[i, second_panel] > 80 and sample[i, second_panel] < 90:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'darkred', linewidth = 1.5)
if sample[i, second_panel] > 70 and sample[i, second_panel] < 80:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'maroon', linewidth = 1.5)
if sample[i, second_panel] > 60 and sample[i, second_panel] < 70:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'firebrick', linewidth = 1.5)
if sample[i, second_panel] > 50 and sample[i, second_panel] < 60:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5)
if sample[i, second_panel] > 40 and sample[i, second_panel] < 50:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5)
if sample[i, second_panel] > 30 and sample[i, second_panel] < 40:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'lightgreen', linewidth = 1.5)
if sample[i, second_panel] > 20 and sample[i, second_panel] < 30:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'limegreen', linewidth = 1.5)
if sample[i, second_panel] > 10 and sample[i, second_panel] < 20:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'seagreen', linewidth = 1.5)
if sample[i, second_panel] > 0 and sample[i, second_panel] < 10:
ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)
ax[1].grid()
indicator_plot(my_data, 4, window = 500)
Dark green and red areas indicate imminent bullish and bearish reactions, respectively. RSI around 50 is grey.
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.
When you find a trading strategy or technique, follow these steps:
Put emotions aside and adopt a critical mindset.
Test it in the past under conditions and simulations taken from real life.
Try optimizing it and performing a forward test if you find any potential.
Transaction costs and any slippage simulation should always be included in your tests.
Risk management and position sizing should always be considered in your tests.
After checking the above, monitor the strategy because market dynamics may change and make it unprofitable.