Patrick Boyle

These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0
Check out our website http://www.onfinance.org/

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The option sensitivity measures familiar to most option traders are often referred to as the Greeks: delta, gamma, vega, lambda, rho, and theta. Delta is the price sensitivity of an option with respect to changes in the price of the underlying asset. It represents a first-order sensitivity measure analogous to duration in fixed income markets. Gamma is the sensitivity of an option's delta to changes in the price of the underlying asset, and represents a second-order price sensitivity analogous to convexity in fixed income markets. Vega is the price sensitivity of an option with respect to changes in the volatility of the underlying asset. See Pricing and Analyzing Equity Derivatives or the Glossary for other definitions.

The Greeks of a particular option are a function of the model used to price the option. However, given enough different options to work with, a trader can construct a portfolio with any desired values for its greeks. For example, to insulate the value of an option portfolio from small changes in the price of the underlying asset, one trader might construct an option portfolio whose delta is zero. Such a portfolio is then said to be “delta neutral.” Another trader may want to protect an option portfolio from larger changes in the price of the underlying asset, and so might construct a portfolio whose delta and gamma are both zero. Such a portfolio is both delta and gamma neutral. A third trader may want to construct a portfolio insulated from small changes in the volatility of the underlying asset in addition to delta and gamma neutrality. Such a portfolio is then delta, gamma, and vega neutral.

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In todays video we learn about variance swaps

These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0
Check out our website http://www.onfinance.org/

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What is a Variance Swap?

A variance swap is a financial derivative used to hedge or speculate on the magnitude of a price movement of an underlying asset.

A variance swap is a forward contract with a payoff based on the realized variance of the underlying asset. Variance swaps settle in cash based on the difference between the realized variance and the variance strike

Similar to a regular swap, one of the two parties involved in the transaction will pay an amount based upon the actual variance of price changes of the underlying asset. The other party will pay a fixed amount, called the strike, specified at the start of the contract. The strike is typically set at the start to make the net present value of the payoff zero.

At the end of the contract, the net payoff to the counterparties will be the notional amount multiplied by the difference between the variance and the strike variance, settled in cash. Due to any margin requirements specified in the contract, some payments may occur during the life of the contract should the contract's value move beyond the agreed limits.

The variance swap, in mathematical terms, is the arithmetic average of the squared differences from the mean value. The square root of the variance is the standard deviation.

A variance swap is a pure-play on an underlying asset's volatility. Options also give an investor the possibility to speculate on an asset's volatility. But, options carry directional risk, and their prices depend on many factors.

There are two main classes of users for variance swaps.

Speculators use these swaps to speculate on the future level of volatility for an asset.

Hedgers use variance swaps to cover short volatility positions.

They are similar to volatility swaps, watch my video on those here. https://www.youtube.com/watch?v=qclLj3E5zyk

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A revision slideshow on Futures and Forwards.

These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0
Check out our website http://www.onfinance.org/

Follow Patrick on twitter here: https://twitter.com/PatrickEBoyle

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In this deep dive, we unpack Donald Trump’s controversial deal with Nvidia and AMD — a 15% revenue-sharing arrangement that allows U.S. AI chips to be exported to China. Is this a clever geopolitical strategy or a dangerous precedent that monetizes national security?
We explore:
How the deal was brokered and what it means for U.S. trade policy
Legal and constitutional concerns surrounding export controls
Strategic risks of enabling China’s AI development
Comparisons to China’s rare earth leverage and Xi Jinping’s CEO control
The broader pattern of Trump’s executive interference in private enterprise
Featuring analysis on the H20 chip, inference bottlenecks, golden shares, and the future of American capitalism.

Patrick's Books:
Statistics For The Trading Floor: https://amzn.to/3eerLA0
Derivatives For The Trading Floor: https://amzn.to/3cjsyPF
Corporate Finance: https://amzn.to/3fn3rvC

Ways To Support The Channel
Patreon: https://www.patreon.com/PatrickBoyleOnFinance
Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

Visit our website: https://www.onfinance.org
Follow Patrick on Twitter Here: https://bsky.app/profile/pboyle.bsky.social

Business Inquiries ➡️ [email protected]

Patrick Boyle On Finance Podcast:
Spotify: https://open.spotify.com/show/7uhrWlDvxzy9hLoW0EYf0b
Apple: https://podcasts.apple.com/us/podcast/patrick-boyle-on-finance/id1547740313
Google Podcasts: https://tinyurl.com/62862nve

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These classes are all based on the book Trading and Pricing Financial Derivatives, available on Amazon at this link. https://amzn.to/2WIoAL0
Check out our website http://www.onfinance.org/

Follow Patrick on twitter here: https://twitter.com/PatrickEBoyle

In Todays video let's learn about time varying volatility and GARCH in risk management

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What Is Time-Varying Volatility?

Time-varying volatility refers to the changes in market volatility over different time periods. Investors may choose to study or consider volatility of an underlying security during various time periods. The use of time-varied volatility measures can influence the expectations of investments.

How Time-Varying Volatility Works
Time-varying volatility can be studied in any time-frame. Generally, volatility analysis requires mathematical modeling to generate volatility levels as one measure of the risk of an underlying security. This type of modeling generates historical volatility statistics.

What is the GARCH Process?

The generalized autoregressive conditional heteroskedasticity (GARCH) process is an econometric term developed in 1982 by Robert F. Engle, an economist and 2003 winner of the Nobel Memorial Prize for Economics, to describe an approach to estimate volatility in financial markets. There are several forms of GARCH modeling. The GARCH process is often preferred by financial modeling professionals because it provides a more real-world context than other forms when trying to predict the prices and rates of financial instruments.

Heteroskedasticity describes the irregular pattern of variation of an error term, or variable, in a statistical model. Essentially, where there is heteroskedasticity, observations do not conform to a linear pattern. Instead, they tend to cluster. The result is that the conclusions and predictive value one can draw from the model will not be reliable. GARCH is a statistical model that can be used to analyze a number of different types of financial data, for instance, macroeconomic data. Financial institutions often use this model to estimate the volatility of returns for stocks, bonds and market indices. They use the resulting information to help determine pricing and judge which assets will potentially provide higher returns, as well as to forecast the returns of current investments to help in their asset allocation, hedging, risk management and portfolio optimization decisions.

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Three years ago, the global auto industry was gripped by a collective hallucination. CEOs promised us that the internal combustion engine would be dead by 2035 and that legacy automakers were just one battery factory away from a trillion-dollar valuation.

That narrative has now collided with economic reality.

In this video, we analyze the collapse of the "inevitability" narrative. We look at why Ford has been forced to take a staggering $19.5 billion write-down, why the European Union is quietly dismantling its own petrol ban, and why—despite billions in subsidies—automakers are still losing $6,000 on every electric vehicle they sell.

We examine how the industry confused a political project with consumer demand, leading to a market where the cars are too expensive for the middle class and too unprofitable for the manufacturers.

Patrick's Books:
Statistics For The Trading Floor: https://amzn.to/3eerLA0
Derivatives For The Trading Floor: https://amzn.to/3cjsyPF
Corporate Finance: https://amzn.to/3fn3rvC

Ways To Support The Channel
Patreon: https://www.patreon.com/PatrickBoyleOnFinance
Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

Visit our website: https://www.onfinance.org
Follow Patrick on Twitter Here: https://bsky.app/profile/pboyle.bsky.social

Business Inquiries ➡️ [email protected]

Patrick Boyle On Finance Podcast:
Spotify: https://open.spotify.com/show/7uhrWlDvxzy9hLoW0EYf0b
Apple: https://podcasts.apple.com/us/podcast/patrick-boyle-on-finance/id1547740313
Google Podcasts: https://tinyurl.com/62862nve

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In todays video we will discuss the Credit Crunch, and the role played by credit derivatives and securitization.

Buy My Book Here: https://amzn.to/2wDMInh
The Big Short https://amzn.to/2JcyAnx
Soros Book https://amzn.to/2JdEqFf
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Credit Derivatives and the Financial Crisis of 2007 -2008

What Caused the Financial Crisis of 2008?
Easy availability of credit in the United States, fueled by low interest rates and reduced credit monitoring by financial institutions, led to a housing boom which facilitated debt-financed consumer spending. The existence of credit derivatives and securitization allowed financial institutions to make larger volumes of riskier loans than had been made in the past and consumers assumed an unprecedented debt load.
Between 1998 and 2006, the price of the typical American house increased by 124%. Between 1981 and 2001, the national median home price ranged from 2.9 to 3.1 times median household income. This rose to 4.6 times median household income in 2006.

When home prices declined in the latter half of 2007 and the secondary mortgage market collapsed, a global financial crisis was triggered. Credit derivatives were blamed by many for bringing about this crisis, or for intensifying it.

Credit ratings agencies are widely believed to have failed the markets in their calculations of credit risks on credit derivative products in the lead up to the financial crisis of 2007-2008. They relied on models that were given to them by the credit derivative issuers. The fact that they are paid by the security issuer, rather than the buyer, brought their impartiality into question. There is a structural conflict in this market whereby investors are the beneficiaries or ultimate end users of credit ratings calculations, yet the party paying for the ratings themselves is the issuer.

On the back of the financial crisis, politicians and regulators globally are pressuring originators to resume the former practice of maintaining at least some of the credit risks on the instruments they originate on their own balance sheets. Politicians face a trade-off of hoping to incentivize high consumer spending and home-ownership rates to boost GDP and achieve social goals associated with home-ownership while seeking to avoid the negative outcomes from widespread over-indebtedness from lax credit standards and real estate bubbles. Stronger credit controls stabilize an economy but reduce home values, decrease homeownership levels, and reduce an economy’s GDP growth.

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FlexiSpot’s Fall Sale is here, up to 50% OFF! Don’t miss your last chance to save big this season! Use my exclusive code "YTE7P50” to get an extra $50 off on E7 pro, E7 plus, and E7L. FlexiSpot also have ""100% Free Orders"" on Sep 29th, 9:00 PM PST!!!

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In a recent CNBC interview Tony Robbins extolled the virtues of investing in private equity, arguing that private equity provided high returns – with low risk. Is he right? Should everyone invest in Private Equity?

Here is a link to the full CNBC video: https://www.youtube.com/watch?v=DWZ67Cx1zm8

Patrick's Books:
Statistics For The Trading Floor: https://amzn.to/3eerLA0
Derivatives For The Trading Floor: https://amzn.to/3cjsyPF
Corporate Finance: https://amzn.to/3fn3rvC

Ways To Support The Channel
Patreon: https://www.patreon.com/PatrickBoyleOnFinance
Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

Further Reading:
An Inconvenient Fact: Private Equity Returns & The Billionaire Factory: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3623820
A Bottom-Up Approach to the Risk-Adjusted Performance of the Buyout Fund Market: https://www.tandfonline.com/doi/pdf/10.2469/faj.v72.n4.1#:
Cliff Asness – Volatility Laundering: https://www.institutionalinvestor.com/article/2bstqfcskz9o72ospzlds/opinion/why-does-private-equity-get-to-play-make-believe-with-prices
Mark Anson Paper: https://www.jstor.org/stable/43503783
Aswath Damodaran Slides: https://pages.stern.nyu.edu/~adamodar/pdfiles/eqnotes/privateequity.pdf
MSCI Leverage in Private Equity: https://www.msci.com/www/blog-posts/leverage-in-private-equity-what/04942552461#:~:text=Leverage%20can%20be%20a%20key,improvements%20rather%20than%20financial%20engineering.

Visit our website: https://www.onfinance.org
Follow Patrick on Twitter Here: https://twitter.com/PatrickEBoyle

Business Inquiries ➡️ [email protected]

Patrick Boyle On Finance Podcast:
Spotify: https://open.spotify.com/show/7uhrWlDvxzy9hLoW0EYf0b
Apple: https://podcasts.apple.com/us/podcast/patrick-boyle-on-finance/id1547740313
Google Podcasts: https://tinyurl.com/62862nve

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*For the FlexiSpot free orders promotion. Customers need to pay upfront for the products - and the first 10 orders after 9PM PST on September 29th will receive a reimbursement of up to $1000 (sorted by order time). If the customer spends more than $1000, the portion of the order amount exceeding $1000 will be excluded from the free order refund.

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All slides are available on my Patreon page: https://www.patreon.com/PatrickBoyleOnFinance

Todays Class is an introduction to Behavioral Finance.

Books Mentioned
Thinking Fast & Slow by Daniel Kahneman https://amzn.to/2UFfz2s
Market Sense & Nonsense by Jack Schwager https://amzn.to/3bwKKDR

Victor Haghani Coin Flipping Paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2856963
Ewan Kirk Paper: https://www.cantabcapital.com/we-think/you-probably-can-t-lose?m=true


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👉 To try everything Brilliant has to offer for free for a full 30 days, visit https://brilliant.org/patrick/. You’ll also get 20% off an annual premium subscription.

Jeffrey Epstein was a college dropout with no formal financial training who amassed a fortune worth hundreds of millions of dollars and mingled with presidents and billionaires. Drawing on court records and media investigations we trace where Epstein's money came from and what happened to it? From his first job as a high school teacher to involvement in a Ponzi scheme, secretive offshore firms, and powerful clients like Les Wexner and Leon Black. As conspiracy theories swirl and official narratives shift, one question remains unanswered: where did Epstein's money actually come from?

Patrick's Books:
Statistics For The Trading Floor: https://amzn.to/3eerLA0
Derivatives For The Trading Floor: https://amzn.to/3cjsyPF
Corporate Finance: https://amzn.to/3fn3rvC

Ways To Support The Channel
Patreon: https://www.patreon.com/PatrickBoyleOnFinance
Buy Me a Coffee: https://www.buymeacoffee.com/patrickboyle

Visit our website: https://www.onfinance.org
Follow Patrick on Twitter Here: https://bsky.app/profile/pboyle.bsky.social

Business Inquiries ➡️ [email protected]

Patrick Boyle On Finance Podcast:
Spotify: https://open.spotify.com/show/7uhrWlDvxzy9hLoW0EYf0b
Apple: https://podcasts.apple.com/us/podcast/patrick-boyle-on-finance/id1547740313
Google Podcasts: https://tinyurl.com/62862nve

Join this channel to support making this content:
https://www.youtube.com/channel/UCASM0cgfkJxQ1ICmRilfHLw/join

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