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Celebrate the power of compound interest and see how your money 💰 could grow over time 🕑 with the Compound Interest Calculator:   #investoreducation#
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How i trade with the Black-Scholes Model: i built Black-Scholes from SCRATCH six months into my quant journey the formula everyone learns in school, the one that won Merton and Scholes a Nobel, i figured if it was famous enough to have a Nobel, it was famous enough to trust that was my first MISTAKE here's what i actually learned from building it, using it, and losing money with it --------------- the build: Black-Scholes takes 5 inputs and outputs an option price, that's stock price, strike price, time to expiry, risk-free rate and volatility tech stack i used: > Python 3.11 as the base language > scipy(dot)stats for the normal cumulative distribution function > numpy for the vectorized math when i extended it across multiple strikes > yfinance to pull SPY option chain data for backtesting > matplotlib for the initial visualization the entire pricing engine was around 40 lines of Python, i wrote it in a jupyter notebook first, then moved it into a proper module once i started using it for real trades when i first ran it and compared to real SPY option prices, the model was within 2-3% on liquid at-the-money options with 30-90 days to expiry i thought i had cracked the CODE --------------- what actually worked: pricing accuracy on at-the-money SPY options was solid enough that i could use the model as a reference, not as gospel, but as a check against what the market was showing me the GREEKS were the real win tho i extended the code to output all 4 first-order Greeks from the same closed-form formula: > delta = how much the option moves for a $1 stock move > gamma = how fast delta itself changes as the stock moves > theta = the daily cost of holding the position from time decay > vega = sensitivity to a 1% change in implied volatility i built a simple streamlit dashboard on top of the pricing engine that showed all 4 Greeks on my open positions in real time, refreshed every 30 seconds against live yfinance data for the first time i actually understood WHY my positions were moving the way they were --------------- what broke, expensively: my first real trade was SPY puts before a Fed meeting i used 14% historical vol as my sigma, model priced the puts at $2.85, live market at $3.40 implied vol had already jumped to 22% ahead of the print market dropped 2% like i expected, my model P&L said i should be up 60%, i closed up 28% IV CRASHED from 22% to 13% the moment the Fed resolved, my puts lost the vega premium even though the direction was right lesson: Black-Scholes assumes constant vol, real markets don't work like that the other assumptions broke too: > log-normal returns fail on tail events, this is why the vol smile exists > no-dividends assumption cost me on ex-dividend dates, my code didn't adjust for it > frictionless markets are a joke, my real fills were 5-10% worse than mid-price --------------- how i actually trade with it now: i stopped using Black-Scholes to price options, i use it to read the market the gap between my model price and the market price is implied vol vs my assumption, that's INFORMATION, not a mispricing to fade example: model says $2.85 using 14% vol, market says $3.40, market is implying 22% on that strike then i decide with vega: > if 22% looks too high going into an event, i short vega through a spread > if 22% still looks cheap, i buy vega > i never trade the gap as a pure mispricing the Greeks are what i actually check before every trade: > delta: my directional exposure across the book > gamma: how fast delta changes on big moves, i size smaller when gamma is high > theta: daily cost or income from time decay > vega: my volatility exposure, i cut this before earnings and Fed meetings --------------- the honest breakdown: Black-Scholes is not a trading model, it's a FRAMEWORK for understanding options the formula prices options for a market that doesn't exist, no jumps, no vol changes, no dividends, no slippage but the intuition it gives you about Greeks is priceless build it once from SCRATCH in Python, price a few real options against the market, then watch it break on your first real trade that's how you actually learn options for serious pricing you eventually move to Heston, but that's a rabbit hole for another post use Black-Scholes for the Greeks, read the price gap as implied vol, trade with vega instead of against the model
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MONEY PRINTER ALERT🚨 NVIDIA vLLM B200 CAN GENERATE UP TO💰️$15 BILLION💰️OF ANNUAL PROFITS PER GIGAWATT serving the open DeepSeekv4.1 Flash model at the official interactivity & official selling prices. Using Engram DRAM offloading on NVIDIA results in a 50% increase in revenue per GigaWatt.
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MONEY MARKETS ARE NOW FULLY PRICING THREE ADDITIONAL FED RATE HIKES OVER THE NEXT YEAR AS INVESTORS DEMAND HIGHER RETURNS ON LONG-TERM BONDS, WHILE TRUMP AND XI DISCUSSED AI COMPETITION AFTER THE U.S.-CHINA TRADE TRUCE WAS EXTENDED BY ABOUT TWO MONTHS TO JAN. 10.
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MONEY MARKETS NOW PRICE THREE FED HIKES OVER THE NEXT YEAR AS PERSISTENT INFLATION, GOVERNMENT SPENDING AND AI-RELATED CORPORATE BORROWING DRIVE BOND VOLATILITY; THE S&P 500 WAS LITTLE CHANGED, DOW FELL 0.3%, WTI ROSE 2.9% TO $94.83 AND GOLD FELL 0.4% TO $4,269.50.
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Money is becoming software. HIFI is the infrastructure it runs on. We've raised a $37 million Series A led by @leftlanecap. Thank you to the customers who run on HIFI, the team that builds it, and the investors who back it. Demand is accelerating. We now process more than $7 billion a year, and existing customers have grown their usage more than 400% in the past six months. Together, they've onboarded more than 10,000 businesses and 200,000 individuals through HIFI. Our technology runs from Wall Street to everyday payments. In July, HIFI's platform was part of DTCC's pilot for tokenized repo. And through our partnership with Visa, developers can pair HIFI's stablecoin settlement with Visa Direct to move money globally. With this round, we're building toward the full stack of tokenized money, from payments and stablecoin cards to tokenized capital markets. We're growing our teams in New York and key international markets, acquiring strategic regulatory licenses, and reimagining new products for the partners building on HIFI. We're just getting started. → Read our blog: → Read the exclusive in Axios:
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Money reveals priorities because every yes to one thing is quietly a no to something else.
Money can’t buy happiness… but it can buy a lot of things that help. 💸 Same girl. Different tax bracket. 😂💸 #SWTwitter# #Richmen# #LuxuryLifestyle# #MoneyTalk# #ViralTweet#
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Moneybagg Yo and Ari Fletcher are now married after holding a traditional Muslim wedding ceremony at a mosque.
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Money feels different when nobody can fire you from making it.