Donor-Advised Fund Tax Benefits (DAF)
Giving through a donor-advised fund can be tax-efficient. Using a donor-advised fund can reduce your tax liability while increasing your charitable impact.
Grow Your Donations Tax-Free.
Your DAF's charitable dollars can be invested before being distributed. Your DAF balance can grow with the market. This increases grantmaking funds. The assets of the DAF belong to the charitable sponsor, so you will not be taxed on any growth.
Avoid a Windfall Tax Year.
DAFs can help reduce tax burdens after a windfall like an inheritance, business sale, or strong market returns. Contributions to your DAF are immediately tax deductible, lowering your taxable income. With DAFs, you can effectively pre-fund years of giving with assets from a single high-income event.
Make a contribution to reduce or eliminate capital gains.
One of the most common ways to fund a DAF is by gifting publicly traded securities. Securities held for more than a year can be donated at fair market value and are not subject to capital gains tax. If a donor liquidates assets and then donates the proceeds to their DAF, capital gains tax reduces the amount available for philanthropy. Gifts of appreciated securities, mutual funds, real estate, and other assets are immediately tax deductible up to 30% of Adjusted gross income (AGI), with a five-year carry-forward for gifts that exceed AGI limits.
Using Appreciated Stock as a Gift
Donating appreciated stock directly to a DAF rather than liquidating it and donating the proceeds reduces philanthropists' tax liability by eliminating capital gains tax and lowering marginal income tax.
In the example below, a donor has $100,000 in long-term appreciated stock with a cost basis of $10,000:
Using a DAF would allow this donor to give more to charity while paying less taxes. This strategy often allows donors to give more than 20% more to their favorite causes.
For illustration purposes, this hypothetical example assumes a 35% income tax rate. All realized gains are subject to the federal long-term capital gains tax of 20% and the 3.8% Medicare surtax. No other state taxes are considered.
The information provided here is general and educational in nature. It is not intended to be, nor should it be construed as, legal or tax advice. NPT does not provide legal or tax advice. Furthermore, the content provided here is related to taxation at the federal level only. NPT strongly encourages you to consult with your tax advisor or attorney before making charitable contributions.
More on Economics & Investing

Quant Galore
3 years ago
I created BAW-IV Trading because I was short on money.
More retail traders means faster, more sophisticated, and more successful methods.
Tech specifications
Only requires a laptop and an internet connection.
We'll use OpenBB's research platform for data/analysis.
Pricing and execution on Options-Quant
Background
You don't need to know the arithmetic details to use this method.
Black-Scholes is a popular option pricing model. It's best for pricing European options. European options are only exercisable at expiration, unlike American options. American options are always exercisable.
American options carry a premium to cover for the risk of early exercise. The Black-Scholes model doesn't account for this premium, hence it can't price genuine, traded American options.
Barone-Adesi-Whaley (BAW) model. BAW modifies Black-Scholes. It accounts for exercise risk premium and stock dividends. It adds the option's early exercise value to the Black-Scholes value.
The trader need not know the formulaic derivations of this model.
https://ir.nctu.edu.tw/bitstream/11536/14182/1/000264318900005.pdf
Strategy
This strategy targets implied volatility. First, we'll locate liquid options that expire within 30 days and have minimal implied volatility.
After selecting the option that meets the requirements, we price it to get the BAW implied volatility (we choose BAW because it's a more accurate Black-Scholes model). If estimated implied volatility is larger than market volatility, we'll capture the spread.
(Calculated IV — Market IV) = (Profit)
Some approaches to target implied volatility are pricey and inaccessible to individual investors. The best and most cost-effective alternative is to acquire a straddle and delta hedge. This may sound terrifying and pricey, but as shown below, it's much less so.
The Trade
First, we want to find our ideal option, so we use OpenBB terminal to screen for options that:
Have an IV at least 5% lower than the 20-day historical IV
Are no more than 5% out-of-the-money
Expire in less than 30 days
We query:
stocks/options/screen/set low_IV/scr --export Output.csv
This uses the screener function to screen for options that satisfy the above criteria, which we specify in the low IV preset (more on custom presets here). It then saves the matching results to a csv(Excel) file for viewing and analysis.
Stick to liquid names like SPY, AAPL, and QQQ since getting out of a position is just as crucial as getting in. Smaller, illiquid names have higher inefficiencies, which could restrict total profits.
We calculate IV using the BAWbisection model (the bisection is a method of calculating IV, more can be found here.) We price the IV first.
According to the BAW model, implied volatility at this level should be priced at 26.90%. When re-pricing the put, IV is 24.34%, up 3%.
Now it's evident. We must purchase the straddle (long the call and long the put) assuming the computed implied volatility is more appropriate and efficient than the market's. We just want to speculate on volatility, not price fluctuations, thus we delta hedge.
The Fun Starts
We buy both options for $7.65. (x100 multiplier). Initial delta is 2. For every dollar the stock price swings up or down, our position value moves $2.
We want delta to be 0 to avoid price vulnerability. A delta of 0 suggests our position's value won't change from underlying price changes. Being delta-hedged allows us to profit/lose from implied volatility. Shorting 2 shares makes us delta-neutral.
That's delta hedging. (Share price * shares traded) = $330.7 to become delta-neutral. You may have noted that delta is not truly 0.00. This is common since delta-hedging means getting as near to 0 as feasible, since it is rare for deltas to align at 0.00.
Now we're vulnerable to changes in Vega (and Gamma, but given we're dynamically hedging, it's not a big risk), or implied volatility. We wanted to gamble that the position's IV would climb by at least 2%, so we'll maintain it delta-hedged and watch IV.
Because the underlying moves continually, the option's delta moves continuously. A trader can short/long 5 AAPL shares at most. Paper trading lets you practice delta-hedging. Being quick-footed will help with this tactic.
Profit-Closing
As expected, implied volatility rose. By 10 minutes before market closure, the call's implied vol rose to 27% and the put's to 24%. This allowed us to sell the call for $4.95 and the put for $4.35, creating a profit of $165.
You may pull historical data to see how this trade performed. Note the implied volatility and pricing in the final options chain for August 5, 2022 (the position date).
Final Thoughts
Congratulations, that was a doozy. To reiterate, we identified tickers prone to increased implied volatility by screening OpenBB's low IV setting. We double-checked the IV by plugging the price into Options-BAW Quant's model. When volatility was off, we bought a straddle and delta-hedged it. Finally, implied volatility returned to a normal level, and we profited on the spread.
The retail trading space is very quickly catching up to that of institutions. Commissions and fees used to kill this method, but now they cost less than $5. Watching momentum, technical analysis, and now quantitative strategies evolve is intriguing.
I'm not linked with these sites and receive no financial benefit from my writing.
Tell me how your experience goes and how I helped; I love success tales.

Jan-Patrick Barnert
3 years ago
Wall Street's Bear Market May Stick Around
If history is any guide, this bear market might be long and severe.
This is the S&P 500 Index's fourth such incident in 20 years. The last bear market of 2020 was a "shock trade" caused by the Covid-19 pandemic, although earlier ones in 2000 and 2008 took longer to bottom out and recover.
Peter Garnry, head of equities strategy at Saxo Bank A/S, compares the current selloff to the dotcom bust of 2000 and the 1973-1974 bear market marked by soaring oil prices connected to an OPEC oil embargo. He blamed high tech valuations and the commodity crises.
"This drop might stretch over a year and reach 35%," Garnry wrote.
Here are six bear market charts.
Time/depth
The S&P 500 Index plummeted 51% between 2000 and 2002 and 58% during the global financial crisis; it took more than 1,000 trading days to recover. The former took 638 days to reach a bottom, while the latter took 352 days, suggesting the present selloff is young.
Valuations
Before the tech bubble burst in 2000, valuations were high. The S&P 500's forward P/E was 25 times then. Before the market fell this year, ahead values were near 24. Before the global financial crisis, stocks were relatively inexpensive, but valuations dropped more than 40%, compared to less than 30% now.
Earnings
Every stock crash, especially earlier bear markets, returned stocks to fundamentals. The S&P 500 decouples from earnings trends but eventually recouples.
Support
Central banks won't support equity investors just now. The end of massive monetary easing will terminate a two-year bull run that was among the strongest ever, and equities may struggle without cheap money. After years of "don't fight the Fed," investors must embrace a new strategy.
Bear Haunting Bear
If the past is any indication, rising government bond yields are bad news. After the financial crisis, skyrocketing rates and a falling euro pushed European stock markets back into bear territory in 2011.
Inflation/rates
The current monetary policy climate differs from past bear markets. This is the first time in a while that markets face significant inflation and rising rates.
This post is a summary. Read full article here

Trevor Stark
3 years ago
Economics is complete nonsense.
Mainstream economics haven't noticed.
What come to mind when I say the word "economics"?
Probably GDP, unemployment, and inflation.
If you've ever watched the news or listened to an economist, they'll use data like these to defend a political goal.
The issue is that these statistics are total bunk.
I'm being provocative, but I mean it:
The economy is not measured by GDP.
How many people are unemployed is not counted in the unemployment rate.
Inflation is not measured by the CPI.
All orthodox economists' major economic statistics are either wrong or falsified.
Government institutions create all these stats. The administration wants to reassure citizens the economy is doing well.
GDP does not reflect economic expansion.
GDP measures a country's economic size and growth. It’s calculated by the BEA, a government agency.
The US has the world's largest (self-reported) GDP, growing 2-3% annually.
If GDP rises, the economy is healthy, say economists.
Why is the GDP flawed?
GDP measures a country's yearly spending.
The government may adjust this to make the economy look good.
GDP = C + G + I + NX
C = Consumer Spending
G = Government Spending
I = Investments (Equipment, inventories, housing, etc.)
NX = Exports minus Imports
GDP is a country's annual spending.
The government can print money to boost GDP. The government has a motive to increase and manage GDP.
Because government expenditure is part of GDP, printing money and spending it on anything will raise GDP.
They've done this. Since 1950, US government spending has grown 8% annually, faster than GDP.
In 2022, government spending accounted for 44% of GDP. It's the highest since WWII. In 1790-1910, it was 3% of GDP.
Who cares?
The economy isn't only spending. Focus on citizens' purchasing power or quality of life.
Since GDP just measures spending, the government can print money to boost GDP.
Even if Americans are poorer than last year, economists can say GDP is up and everything is fine.
How many people are unemployed is not counted in the unemployment rate.
The unemployment rate measures a country's labor market. If unemployment is high, people aren't doing well economically.
The BLS estimates the (self-reported) unemployment rate as 3-4%.
Why is the unemployment rate so high?
The US government surveys 100k persons to measure unemployment. They extrapolate this data for the country.
They come into 3 categories:
Employed
People with jobs are employed … duh.
Unemployed
People who are “jobless, looking for a job, and available for work” are unemployed
Not in the labor force
The “labor force” is the employed + the unemployed.
The unemployment rate is the percentage of unemployed workers.
Problem is unemployed definition. You must actively seek work to be considered unemployed.
You're no longer unemployed if you haven't interviewed in 4 weeks.
This shit makes no goddamn sense.
Why does this matter?
You can't interview if there are no positions available. You're no longer unemployed after 4 weeks.
In 1994, the BLS redefined "unemployed" to exclude discouraged workers.
If you haven't interviewed in 4 weeks, you're no longer counted in the unemployment rate.
If unemployment were measured by total unemployed, it would be 25%.
Because the government wants to keep the unemployment rate low, they modify the definition.
If every US resident was unemployed and had no job interviews, economists would declare 0% unemployment. Excellent!
Inflation is not measured by the CPI.
The BLS measures CPI. This month was the highest since 1981.
CPI measures the cost of a basket of products across time. Food, energy, shelter, and clothes are included.
A 9.1% CPI means the basket of items is 9.1% more expensive.
What is the CPI problem?
Here's a more detailed explanation of CPI's flaws.
In summary, CPI is manipulated to be understated.
Housing costs are understated to manipulate CPI. Housing accounts for 33% of the CPI because it's the biggest expense for most people.
This signifies it's the biggest CPI weight.
Rather than using actual house prices, the Bureau of Labor Statistics essentially makes shit up. You can read more about the process here.
Surprise! It’s bullshit
The BLS stated Shelter's price rose 5.5% this month.
House prices are up 11-21%. (Source 1, Source 2, Source 3)
Rents are up 14-26%. (Source 1, Source 2)
Why is this important?
If CPI included housing prices, it would be 12-15 percent this month, not 9.1 percent.
9% inflation is nuts. Your money's value halves every 7 years at 9% inflation.
Worse is 15% inflation. Your money halves every 4 years at 15% inflation.
If everyone realized they needed to double their wage every 4-5 years to stay wealthy, there would be riots.
Inflation drains our money's value so the government can keep printing it.
The Solution
Most individuals know the existing system doesn't work, but can't explain why.
People work hard yet lag behind. The government lies about the economy's data.
In reality:
GDP has been down since 2008
25% of Americans are unemployed
Inflation is actually 15%
People might join together to vote out kleptocratic politicians if they knew the reality.
Having reliable economic data is the first step.
People can't understand the situation without sufficient information. Instead of immigrants or billionaires, people would blame liar politicians.
Here’s the vision:
A decentralized, transparent, and global dashboard that tracks economic data like GDP, unemployment, and inflation for every country on Earth.
Government incentives influence economic statistics.
ShadowStats has already started this effort, but the calculations must be transparent, decentralized, and global to be effective.
If interested, email me at trevorstark02@gmail.com.
Here are some links to further your research:
You might also like

Pat Vieljeux
3 years ago
In 5 minutes, you can tell if a startup will succeed.
Or the “lie to me” method.

I can predict a startup's success in minutes.
Just interview its founder.
Ask "why?"
I question "why" till I sense him.
I need to feel the person I have in front of me. I need to know if he or she can deliver. Startups aren't easy. Without abilities, a brilliant idea will fail.
Good entrepreneurs have these qualities: He's a leader, determined, and resilient.
For me, they can be split in two categories.
The first entrepreneur aspires to live meaningfully. The second wants to get rich. The second is communicative. He wants to wow the crowd. He's motivated by the thought of one day sailing a boat past palm trees and sunny beaches.
What drives the first entrepreneur is evident in his speech, face, and voice. He will not speak about his product. He's (nearly) uninterested. He's not selling anything. He's not a salesman. He wants to succeed. The product is his fuel.
He'll explain his decision. He'll share his motivations. His desire. And he'll use meaningful words.
Paul Ekman has shown that face expressions aren't cultural. His study influenced the American TV series "lie to me" about body language and speech.
Passionate entrepreneurs are obvious. It's palpable. Faking passion is tough. Someone who wants your favor and money will expose his actual motives through his expressions and language.
The good liar will be able to fool you for a while, but not for long if you pay attention to his body language and how he expresses himself.
And also, if you look at his business plan.
His business plan reveals his goals. Read between the lines.
Entrepreneur 1 will focus on his "why", whereas Entrepreneur 2 will focus on the "how".
Entrepreneur 1 will develop a vision-driven culture.
The second, on the other hand, will focus on his EBITDA.
Why is the culture so critical? Because it will allow entrepreneur 1 to develop a solid team that can tackle his problems and trials. His team's "why" will keep them together in tough times.
"Give me a terrific start-up team with a mediocre idea over a weak one any day." Because a great team knows when to pivot and trusts each other. Weak teams fail.” — Bernhard Schroeder
Closings thoughts
Every VC must ask Why. Entrepreneur's motivations. This "why" will create the team's culture. This culture will help the team adjust to any setback.

Nick
3 years ago
This Is How Much Quora Paid Me For 23 Million Content Views
You’ll be surprised; I sure was
Blogging and writing online as a side income has now been around for a significant amount of time. Nowadays, it is a continuously rising moneymaker for prospective writers, with several writing platforms existing online. At the top of the list are Medium, Vocal Media, Newsbreak, and the biggest one of them, Quora, with 300 million active users.
Quora, unlike Medium, is a question-and-answer format platform. On Medium you are permitted to write what you want, while on Quora, you answer questions on topics that you have expertise about. Quora, like Medium, now compensates its authors for the answers they provide in comparison to the previous, in which you had to be admitted to the partner program and were paid to ask questions.
Quora just recently went live with this new partner program, Quora Plus, and the way it works is that it is a subscription for $5 a month which provides you access to metered/monetized stories, in turn compensating the writers for part of that subscription for their answers.
I too on Quora have found a lot of success on the platform, gaining 23 Million Content Views, and 300,000 followers for my space, which is kind of the Quora equivalent of a Medium article. The way in which I was able to do this was entirely thanks to a hack that I uncovered to the Quora algorithm.
In this article, I plan on discussing how much money I received from 23 million content views on Quora, and I bet you’ll be shocked; I know I was.
A Brief Explanation of How I Got 23 Million Views and How You Can Do It Too
On Quora, everything in terms of obtaining views is about finding the proper question, which I only understood quite late into the game. I published my first response in 2019 but never actually wrote on Quora until the summer of 2020, and about a month into posting consistently I found out how to find the perfect question. Here’s how:
The Process
Go to your Home Page and start scrolling… While browsing, check for the following things…
Answers from people you follow or your followers.
Advertisements
These two things are the two things you want to ignore, you don’t want to answer those questions or look at the ads. You should now be left with a couple of recommended answers. To discover which recommended answer is the best to answer as well, look at these three important aspects.
Date of the answer: Was it in the past few days, preferably 2–3 days, even better, past 24 hours?
Views: Are they in the ten thousands or hundred thousands?
Upvotes: Are they in the hundreds or thousands?
Now, choose an answer to a question which you think you could answer as well that satisfies the requirements above. Once you click on it, as all answers on Quora works, it will redirect you to the page for that question, in which you will have to select once again if you should answer the question.
Amount of answers: How many responses are there to the given question? This tells you how much competition you have. My rule is beyond 25 answers, you shouldn’t answer, but you can change it anyway you’d like.
Answerers: Who did the answering for the question? If the question includes a bunch of renowned, extremely well-known people on Quora, there’s a good possibility your essay is going to get drowned out.
Views: Check for a constant quantity of high views on each answer for the question; this is what will guarantee that your answer gets a lot of views!
The Income Reveal! How Much I Made From 23 Million Content Views
DRUM ROLL, PLEASE!
8.97 USD. Yes, not even ten dollars, not even nine. Just eight dollars and ninety-seven cents.
Possible Reasons for My Low Earnings
Quora Plus and the answering partner program are newer than my Quora views.
Few people use Quora+, therefore revenues are low.
I haven't been writing much on Quora, so I'm only making money from old answers and a handful since Quora Plus launched.
Quora + pays poorly...
Should You Try Quora and Quora For Money?
My answer depends on your needs. I never got invited to Quora's question partner program due to my late start, but other writers have made hundreds. Due to Quora's new and competitive answering partner program, you may not make much money.
If you want a fun writing community, try Quora. Quora was fun when I only made money from my space. Quora +'s paywalls and new contributors eager to make money have made the platform less fun for me.
This article is a summary to save you time. You can read my full, more detailed article, here.

Jared Heyman
2 years ago
The survival and demise of Y Combinator startups
I've written a lot about Y Combinator's success, but as any startup founder or investor knows, many startups fail.
Rebel Fund invests in the top 5-10% of new Y Combinator startups each year, so we focus on identifying and supporting the most promising technology startups in our ecosystem. Given the power law dynamic and asymmetric risk/return profile of venture capital, we worry more about our successes than our failures. Since the latter still counts, this essay will focus on the proportion of YC startups that fail.
Since YC's launch in 2005, the figure below shows the percentage of active, inactive, and public/acquired YC startups by batch.
As more startups finish, the blue bars (active) decrease significantly. By 12 years, 88% of startups have closed or exited. Only 7% of startups reach resolution each year.
YC startups by status after 12 years:
Half the startups have failed, over one-third have exited, and the rest are still operating.
In venture investing, it's said that failed investments show up before successful ones. This is true for YC startups, but only in their early years.
Below, we only present resolved companies from the first chart. Some companies fail soon after establishment, but after a few years, the inactive vs. public/acquired ratio stabilizes around 55:45. After a few years, a YC firm is roughly as likely to quit as fail, which is better than I imagined.
I prepared this post because Rebel investors regularly question me about YC startup failure rates and how long it takes for them to exit or shut down.
Early-stage venture investors can overlook it because 100x investments matter more than 0x investments.
YC founders can ignore it because it shouldn't matter if many of their peers succeed or fail ;)