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➡️ Quantitative Finance from Scratch, part 47: What does a market maker actually do? A market maker is a trading firm that always provides two prices for a stock: the ask (higher, what you pay when you buy) and the bid (lower, what you get when you sell). When...

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QuantFinanceToGo

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➡️ Quantitative Finance from Scratch, part 35: how market makers make money. The first source is the spread. Like an exchange booth, a market maker buys a little below the fair price at the bid and sells a little above it at the ask, so every trade earns half the gap whatever the stock does next. After selling a call, it buys delta shares, so small moves no longer matter. The second source comes from the other Greeks: theta is the income, because the call it owes loses value every day, and gamma is the cost, because after every big move it must buy shares high and sell them low to keep the hedge. If the stock moves exactly as much as the implied volatility in the price, income and cost cancel. If it stays calmer, the market maker earns, and if it moves more, it loses. Vega is the risk to this income, because a jump in implied volatility makes the call it owes more expensive. If a customer sells it the call instead, everything flips. The code (marketmaker.py, 16 lines) sells our call from part 33 at the ask (fair $10.45, ask $10.55, bid $10.35) and hedges it every day on 2,000 simulated years with an implied volatility of 20 %. With a real volatility of 16 % it earns $1.59 per call on average and every path ends in profit; at 20 % it earns $0.10, about the spread; at 24 % it loses $1.41 and only 0.3 % of paths end in profit. Honest notes: a simplified model with one option, daily hedging, Black Scholes prices, constant volatility, no trading costs, no dividends and no other customers. Real market makers manage many options at once and also face fees, inventory limits and jumps. #quantfinance #options #marketmaking #greeks #finance
2:35

➡️ Quantitative Finance from Scratch, part 35: how market makers make money. The first source is the spread. Like an exchange booth, a market maker buys a little below the fair price at the bid and sells a little above it at the ask, so every trade earns half the gap whatever the stock does next. After selling a call, it buys delta shares, so small moves no longer matter. The second source comes from the other Greeks: theta is the income, because the call it owes loses value every day, and gamma is the cost, because after every big move it must buy shares high and sell them low to keep the hedge. If the stock moves exactly as much as the implied volatility in the price, income and cost cancel. If it stays calmer, the market maker earns, and if it moves more, it loses. Vega is the risk to this income, because a jump in implied volatility makes the call it owes more expensive. If a customer sells it the call instead, everything flips. The code (marketmaker.py, 16 lines) sells our call from part 33 at the ask (fair $10.45, ask $10.55, bid $10.35) and hedges it every day on 2,000 simulated years with an implied volatility of 20 %. With a real volatility of 16 % it earns $1.59 per call on average and every path ends in profit; at 20 % it earns $0.10, about the spread; at 24 % it loses $1.41 and only 0.3 % of paths end in profit. Honest notes: a simplified model with one option, daily hedging, Black Scholes prices, constant volatility, no trading costs, no dividends and no other customers. Real market makers manage many options at once and also face fees, inventory limits and jumps. #quantfinance #options #marketmaking #greeks #finance

QuantFinanceToGo

93,300 Aufrufe • vor 13 Tagen

➡️ Quantitative Finance from Scratch, part 45: Statistical Arbitrage. The arbitrage from the last part was a profit without any risk. Statistical arbitrage is the practical version: many small bets that can each lose, but win on average. One of the best known and simplest forms is pairs trading: two stocks in the same business that move together. The gap between them, the spread = P_A − β · P_B (P_A price of stock A, P_B price of stock B, β the hedge ratio), keeps coming back to its average. That is the edge: the trade treats this return almost like a law, so the further the spread moves away, the more it should come back, and that way back is the profit. The rule: z = (spread − average) / standard deviation. When z reaches +2 or −2, you sell the expensive stock, buy the cheap one, and close both when the gap is back at its average. Because one stock is long and the other short, a move of the whole market mostly cancels out. News about one company can still hit a single pair, so funds make many such trades at once, and the surprises average out. The big risks: the link between two stocks can break for good, for example after a merger, and when many funds hold the same trades, they can all lose at once. The code (statarb_reel.py, 16 lines of plain Python without packages) is general on purpose: the spread from two prices and the hedge ratio, the z score, and the signal that sells the expensive stock and buys the cheap one at two standard deviations and closes at the average. If you want to go deeper, the link to my website is in my bio. #quantfinance #statisticalarbitrage #pairstrading #meanreversion #python Education only, not financial advice.
1:29

➡️ Quantitative Finance from Scratch, part 45: Statistical Arbitrage. The arbitrage from the last part was a profit without any risk. Statistical arbitrage is the practical version: many small bets that can each lose, but win on average. One of the best known and simplest forms is pairs trading: two stocks in the same business that move together. The gap between them, the spread = P_A − β · P_B (P_A price of stock A, P_B price of stock B, β the hedge ratio), keeps coming back to its average. That is the edge: the trade treats this return almost like a law, so the further the spread moves away, the more it should come back, and that way back is the profit. The rule: z = (spread − average) / standard deviation. When z reaches +2 or −2, you sell the expensive stock, buy the cheap one, and close both when the gap is back at its average. Because one stock is long and the other short, a move of the whole market mostly cancels out. News about one company can still hit a single pair, so funds make many such trades at once, and the surprises average out. The big risks: the link between two stocks can break for good, for example after a merger, and when many funds hold the same trades, they can all lose at once. The code (statarb_reel.py, 16 lines of plain Python without packages) is general on purpose: the spread from two prices and the hedge ratio, the z score, and the signal that sells the expensive stock and buys the cheap one at two standard deviations and closes at the average. If you want to go deeper, the link to my website is in my bio. #quantfinance #statisticalarbitrage #pairstrading #meanreversion #python Education only, not financial advice.

QuantFinanceToGo

37,000 Aufrufe • vor 2 Tagen

➡️ Part 32 of Quantitative Finance From Scratch: put call parity. A call gives you the right to buy a stock at the strike on a fixed date, and a put gives you the right to sell it at that price. If you buy a call and sell a put with the same strike and the same date, you end up buying the stock at the strike whatever happens, because above the strike you use your call, and below it the buyer of your put sells you the stock. That sure deal is worth the stock price today minus the present value of the strike, so the call minus the put equals the stock minus the present value of the strike. Our test run (putcall.py, 16 lines of plain Python) prices both options with Black Scholes for a stock and a strike of 100 dollars, a rate of 5 %, one year and a volatility of 20 %. The call costs 10.45 dollars and the put 5.57 dollars, and their difference of 4.88 dollars equals 100 minus 95.12, the present value of the strike. Six end prices drawn with seed 32 show that the call minus the put always pays the end price minus the strike. The rule needs no model for the stock price (Merton 1973), so traders use it to check quotes and to turn a call price into a put price. It holds exactly for European options, which can only be used at expiry, on stocks without dividends. #quantfinance #putcallparity #options #blackscholes #python
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➡️ Part 32 of Quantitative Finance From Scratch: put call parity. A call gives you the right to buy a stock at the strike on a fixed date, and a put gives you the right to sell it at that price. If you buy a call and sell a put with the same strike and the same date, you end up buying the stock at the strike whatever happens, because above the strike you use your call, and below it the buyer of your put sells you the stock. That sure deal is worth the stock price today minus the present value of the strike, so the call minus the put equals the stock minus the present value of the strike. Our test run (putcall.py, 16 lines of plain Python) prices both options with Black Scholes for a stock and a strike of 100 dollars, a rate of 5 %, one year and a volatility of 20 %. The call costs 10.45 dollars and the put 5.57 dollars, and their difference of 4.88 dollars equals 100 minus 95.12, the present value of the strike. Six end prices drawn with seed 32 show that the call minus the put always pays the end price minus the strike. The rule needs no model for the stock price (Merton 1973), so traders use it to check quotes and to turn a call price into a put price. It holds exactly for European options, which can only be used at expiry, on stocks without dividends. #quantfinance #putcallparity #options #blackscholes #python

QuantFinanceToGo

22,900 Aufrufe • vor 17 Tagen

every time you hit buy, the market maker on the other side already solved for two numbers not on the asset - on you specifically the first: their internal fair value. not the midpoint you see on screen their number is adjusted for the last 30 seconds of order flow, their current inventory imbalance and which volatility regime the model thinks the market is in it's different from the displayed price, and they never show it to you the second: your adverse selection probability. a live estimate of whether you're informed or just emotional if the model flags you as a potential informed trader, the spread widens before your fill - automatically, invisibly, before you notice anything changed that bad fill you blamed on "low liquidity"? sometimes it's a market maker's algorithm deciding you look too dangerous to fill at the quoted price this is Glosten-Milgrom - published 1985, sits in every market microstructure textbook on earth, runs inside every serious market making operation that's ever quoted you a price Bookmark this feature before it lost when you click buy, you're answering a question you didn't know was being asked retail spends all its time thinking about where price is going the desk filling your order is spending that same time thinking about you
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every time you hit buy, the market maker on the other side already solved for two numbers not on the asset - on you specifically the first: their internal fair value. not the midpoint you see on screen their number is adjusted for the last 30 seconds of order flow, their current inventory imbalance and which volatility regime the model thinks the market is in it's different from the displayed price, and they never show it to you the second: your adverse selection probability. a live estimate of whether you're informed or just emotional if the model flags you as a potential informed trader, the spread widens before your fill - automatically, invisibly, before you notice anything changed that bad fill you blamed on "low liquidity"? sometimes it's a market maker's algorithm deciding you look too dangerous to fill at the quoted price this is Glosten-Milgrom - published 1985, sits in every market microstructure textbook on earth, runs inside every serious market making operation that's ever quoted you a price Bookmark this feature before it lost when you click buy, you're answering a question you didn't know was being asked retail spends all its time thinking about where price is going the desk filling your order is spending that same time thinking about you

Livsun

18,906 Aufrufe • vor 4 Monaten

Qullamaggie on Feeling Like a Genius, It's The Market Not You “A melt-up market is when everything is going straight up. And it becomes too easy to make money. You start feeling like a genius — that’s a melt-up market. Trust me, you are not a genius. None of you. It’s the market, not you. No, it’s true. It’s true. Most of my money has come from periods when the market is really good. You just have to line your trading with a period where the market is really good. You know, you gotta be aggressive when the market is really good. Your job is to identify good setups in a good market — and then let the market take care of the rest. Too many people think they are the shit just because they’re making a lot of money. But that’s not really true. It’s the market, not you.”
0:56

Qullamaggie on Feeling Like a Genius, It's The Market Not You “A melt-up market is when everything is going straight up. And it becomes too easy to make money. You start feeling like a genius — that’s a melt-up market. Trust me, you are not a genius. None of you. It’s the market, not you. No, it’s true. It’s true. Most of my money has come from periods when the market is really good. You just have to line your trading with a period where the market is really good. You know, you gotta be aggressive when the market is really good. Your job is to identify good setups in a good market — and then let the market take care of the rest. Too many people think they are the shit just because they’re making a lot of money. But that’s not really true. It’s the market, not you.”

Lone

14,021 Aufrufe • vor 5 Monaten

I activated a bot that market makes on Polymarket and earns passive income from the spread Main function: Market Making In simple terms: The bot automatically places buy orders LOWER and sell orders HIGHER, earning from the difference (spread) > What the bot does: 1. Analyzes the market: - Checks current prices - Calculates optimal spread - Determines order size 2. Places orders 3. Waits for execution 4. Earns from the spread > Repeats the cycle: - Constantly updates orders - Monitors price - Manages position This two markets which I used to market-making:
0:48

I activated a bot that market makes on Polymarket and earns passive income from the spread Main function: Market Making In simple terms: The bot automatically places buy orders LOWER and sell orders HIGHER, earning from the difference (spread) > What the bot does: 1. Analyzes the market: - Checks current prices - Calculates optimal spread - Determines order size 2. Places orders 3. Waits for execution 4. Earns from the spread > Repeats the cycle: - Constantly updates orders - Monitors price - Manages position This two markets which I used to market-making:

cryptovcdegen

12,569 Aufrufe • vor 9 Monaten

Don’t get fooled by that big number on your chart, it’s not the price just waiting for you. I want to be clear about that up front. That bold price you see is just where two traders shook hands on a deal. That’s history. Honestly, I used to look at it like it was some live pulse on the market. I’d plan my whole trade around it, hoping to get filled close to that number. More than once, I watched my fill slip further away, and yeah, I used to blame the exchange before I admitted I just misunderstood the book. So let’s get real about what’s actually moving. A buyer can say this is the highest price I'm willing to pay( $100 that's the bid) Right now, the top bid might be $100, while the the seller can say best offer sits at $101. That $1 gap? That’s your spread. The bid and ask is the conversation still happening right in front of you. When you fire off a market order, it doesn’t chase down that last print. It grabs the best available price, and if there’s not enough there, it keeps reaching for the next one in line. The number flashing on your screen and the price you actually get can end up pretty far apart. I used to think that meant something was wrong with my broker, but it’s almost always the market talking. Thin order books, volatile moments, or simply dropping an order bigger than what’s sitting there, any of those will throw your fill off the mark. Usually, a tight spread means buyers and sellers are pushing hard against each other. If the spread’s wide, it’s just more expensive to jump in or out. But here’s something that took me a while to learn. A close bid and ask doesn’t mean there’s real weight behind those numbers. Sometimes, there’s just a tiny sliver of size sitting there, and it can disappear in a blink, leaving you chasing worse prices. The spread doesn’t judge your asset or hand out prizes. It’s just a snapshot of what’s happening right now. Every time I size up for a trade, I check four things: Where’s the best bid? Where’s the best ask? How wide is the spread? And how much size is actually parked at those prices? That’s the difference between being a spectator and actually reading the market. That’s what Opportunity Compass was all about. The gold, stocks, Blbitcoin, doesn’t matter. It’s all just auctions in action. But the feel changes with every market because rules, hours, and liquidity change the look of the book. MEXC rolled out Opportunity Compass to help people read those conditions, not just add another trading pair to their list. Anyone can pull up an order book. Understanding what it’s telling you is how you hear the market speak before your trade becomes the next deal. Last price is just your receipt. Bid and ask is the live discussion. The spread tells you how far apart buyers and sellers really are. Depth shows you how much weight a price can hold before it budges. So tell me, when you hover over that buy button, what grabs your eye first? The last price? The spread? Or the stack behind those numbers? Check Out Full Opportunity Compass path: Not financial advice. DYOR. #MEXC
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Don’t get fooled by that big number on your chart, it’s not the price just waiting for you. I want to be clear about that up front. That bold price you see is just where two traders shook hands on a deal. That’s history. Honestly, I used to look at it like it was some live pulse on the market. I’d plan my whole trade around it, hoping to get filled close to that number. More than once, I watched my fill slip further away, and yeah, I used to blame the exchange before I admitted I just misunderstood the book. So let’s get real about what’s actually moving. A buyer can say this is the highest price I'm willing to pay( $100 that's the bid) Right now, the top bid might be $100, while the the seller can say best offer sits at $101. That $1 gap? That’s your spread. The bid and ask is the conversation still happening right in front of you. When you fire off a market order, it doesn’t chase down that last print. It grabs the best available price, and if there’s not enough there, it keeps reaching for the next one in line. The number flashing on your screen and the price you actually get can end up pretty far apart. I used to think that meant something was wrong with my broker, but it’s almost always the market talking. Thin order books, volatile moments, or simply dropping an order bigger than what’s sitting there, any of those will throw your fill off the mark. Usually, a tight spread means buyers and sellers are pushing hard against each other. If the spread’s wide, it’s just more expensive to jump in or out. But here’s something that took me a while to learn. A close bid and ask doesn’t mean there’s real weight behind those numbers. Sometimes, there’s just a tiny sliver of size sitting there, and it can disappear in a blink, leaving you chasing worse prices. The spread doesn’t judge your asset or hand out prizes. It’s just a snapshot of what’s happening right now. Every time I size up for a trade, I check four things: Where’s the best bid? Where’s the best ask? How wide is the spread? And how much size is actually parked at those prices? That’s the difference between being a spectator and actually reading the market. That’s what Opportunity Compass was all about. The gold, stocks, Blbitcoin, doesn’t matter. It’s all just auctions in action. But the feel changes with every market because rules, hours, and liquidity change the look of the book. MEXC rolled out Opportunity Compass to help people read those conditions, not just add another trading pair to their list. Anyone can pull up an order book. Understanding what it’s telling you is how you hear the market speak before your trade becomes the next deal. Last price is just your receipt. Bid and ask is the live discussion. The spread tells you how far apart buyers and sellers really are. Depth shows you how much weight a price can hold before it budges. So tell me, when you hover over that buy button, what grabs your eye first? The last price? The spread? Or the stack behind those numbers? Check Out Full Opportunity Compass path: Not financial advice. DYOR. #MEXC

Andy Lui

22,294 Aufrufe • vor 1 Monat

Ex-Tower Research HFT trader Annanay Kapila (ak0) on adverse selection, the hidden cost of market making: "The problem with market making is there is a concept called adverse selection." "It basically says you're way more likely to trade when your estimate of the fair value is wrong." "Those people are more likely to trade against you than the so-called random trader, or just an investor who wants to buy and sell in the market, who is kind of equally likely to trade at all times." "If I think the fair price is $100.5 and it's actually $99.9, there's still no free money in this market. But as soon as I put a bid over here, I am on average losing $0.10 for every share that I do." "I'm way more likely to trade when I have that bid at $100, just because arbitrageurs are generally smart, and they'll trade very quickly if they think your pricing is wrong."
0:54

Ex-Tower Research HFT trader Annanay Kapila (ak0) on adverse selection, the hidden cost of market making: "The problem with market making is there is a concept called adverse selection." "It basically says you're way more likely to trade when your estimate of the fair value is wrong." "Those people are more likely to trade against you than the so-called random trader, or just an investor who wants to buy and sell in the market, who is kind of equally likely to trade at all times." "If I think the fair price is $100.5 and it's actually $99.9, there's still no free money in this market. But as soon as I put a bid over here, I am on average losing $0.10 for every share that I do." "I'm way more likely to trade when I have that bid at $100, just because arbitrageurs are generally smart, and they'll trade very quickly if they think your pricing is wrong."

Ethan Kho

17,168 Aufrufe • vor 11 Tagen

If you invest $1,000 in a stock, you can lose $1,000. But if you’re right, you can make $5,000, $10,000, or $20,000. In the stock market, you don’t need to be right all the time to win. What matters is this: when you find a solid company, don’t panic sell when the stock crashes. If possible, buy more — and most importantly, don’t sell. Selling great companies too early is a terrible mistake. 90% of success in the stock market is patience and the ability to not panic. Most of the time, you don’t need to do anything. Just wait
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If you invest $1,000 in a stock, you can lose $1,000. But if you’re right, you can make $5,000, $10,000, or $20,000. In the stock market, you don’t need to be right all the time to win. What matters is this: when you find a solid company, don’t panic sell when the stock crashes. If possible, buy more — and most importantly, don’t sell. Selling great companies too early is a terrible mistake. 90% of success in the stock market is patience and the ability to not panic. Most of the time, you don’t need to do anything. Just wait

Daniel

365,417 Aufrufe • vor 8 Monaten

One Of The Most Eye-Opening Videos On The Internet: “Market Maker This… Market Maker That…” “I Am The Market Maker…” Everyone Claims To Be A Market Maker. But ICT Finally REVEALS Who The REAL Market Makers Actually Are 😳. MUST-WATCH!
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One Of The Most Eye-Opening Videos On The Internet: “Market Maker This… Market Maker That…” “I Am The Market Maker…” Everyone Claims To Be A Market Maker. But ICT Finally REVEALS Who The REAL Market Makers Actually Are 😳. MUST-WATCH!

JeRRy MMXM

21,846 Aufrufe • vor 3 Monaten

➡️ Part 25 of Quantitative Finance From Scratch: the value factor. A value stock has a low price to book ratio; researchers flip it to book to market and compare the cheapest stocks with the most expensive ones. In our simulation (500 simulated stocks, 30 years, assumed numbers) the value portfolio earns 4.7 % a year with a t statistic of 4.29. It is a model with a small built-in premium, so it shows how the method works, not what real markets will pay. The chart in the hook is a schematic, not real data. Value and momentum have tended to move in opposite directions in real markets. In our simulation they are almost unrelated (correlation 0.04), and the 50/50 mix is still smoother than either alone. Education only, not financial advice. #quantfinance #valueinvesting #factorinvesting #python #finance
1:45

➡️ Part 25 of Quantitative Finance From Scratch: the value factor. A value stock has a low price to book ratio; researchers flip it to book to market and compare the cheapest stocks with the most expensive ones. In our simulation (500 simulated stocks, 30 years, assumed numbers) the value portfolio earns 4.7 % a year with a t statistic of 4.29. It is a model with a small built-in premium, so it shows how the method works, not what real markets will pay. The chart in the hook is a schematic, not real data. Value and momentum have tended to move in opposite directions in real markets. In our simulation they are almost unrelated (correlation 0.04), and the 50/50 mix is still smoother than either alone. Education only, not financial advice. #quantfinance #valueinvesting #factorinvesting #python #finance

QuantFinanceToGo

13,100 Aufrufe • vor 26 Tagen

Trading Both Sides Of The Curve In A Market Maker Sell Model. Nasdaq Market Maker Sell Model. 16 April 2025.
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Trading Both Sides Of The Curve In A Market Maker Sell Model. Nasdaq Market Maker Sell Model. 16 April 2025.

Frank369

23,461 Aufrufe • vor 1 Jahr

Daily Packs: You rip a pack. You get a market position. Starting with prediction markets. The packs experience you already love and now with way to get exposure to financial markets. You can sell back to the market, or hold as the market moves. Suddenly it's two experiences in one. The protocol's inventory is not physical. No added costs for warehouses or shipping.
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Daily Packs: You rip a pack. You get a market position. Starting with prediction markets. The packs experience you already love and now with way to get exposure to financial markets. You can sell back to the market, or hold as the market moves. Suddenly it's two experiences in one. The protocol's inventory is not physical. No added costs for warehouses or shipping.

armand type beat

133,893 Aufrufe • vor 20 Tagen

When Price Reaches The Draw On Liquidity, And The Signs Are There Of A Smart Money Reversal, Anticipate Spooling Towards The Opposing Side Of Liquidity. $NQ Market Maker Buy Model. 28 July 2026.
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When Price Reaches The Draw On Liquidity, And The Signs Are There Of A Smart Money Reversal, Anticipate Spooling Towards The Opposing Side Of Liquidity. $NQ Market Maker Buy Model. 28 July 2026.

Frank369

29,491 Aufrufe • vor 3 Monaten

Jack Duval reveals how market makers pump coins overnight before farming buyers “Most launchpad volume and opportunity is pre-bond on Pumpfun, PONS and other bonding-curve platforms. But it isn’t as simple as buying at a $3K market cap and selling at $6K you’ll lose everything trading like that.” “If you know what you’re doing, pre-bond volume can be scaled. But I’m focused on perfecting how I trade around market makers because that’s everything in this market, and it isn’t discussed enough.” “Almost every coin valued at high eight figures or multiple nine figures has market makers involved to some extent.” “Market makers paint charts to attract maximum volume. They manufacture a breakout, swing the chart down, push it back toward new highs and then farm everyone who buys into the move.” “When volume is low in the middle of the night, they can push the chart back to all-time highs with much less sell pressure. That’s basic market-maker 101.”
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Jack Duval reveals how market makers pump coins overnight before farming buyers “Most launchpad volume and opportunity is pre-bond on Pumpfun, PONS and other bonding-curve platforms. But it isn’t as simple as buying at a $3K market cap and selling at $6K you’ll lose everything trading like that.” “If you know what you’re doing, pre-bond volume can be scaled. But I’m focused on perfecting how I trade around market makers because that’s everything in this market, and it isn’t discussed enough.” “Almost every coin valued at high eight figures or multiple nine figures has market makers involved to some extent.” “Market makers paint charts to attract maximum volume. They manufacture a breakout, swing the chart down, push it back toward new highs and then farm everyone who buys into the move.” “When volume is low in the middle of the night, they can push the chart back to all-time highs with much less sell pressure. That’s basic market-maker 101.”

Umar

49,208 Aufrufe • vor 1 Monat

As assets go onchain, liquidity should follow. Done right, tokenized stocks tap into the deep liquidity already available in traditional markets. “In an ideal world, when you buy tokenized Tesla onchain, you are getting the same price as you would get in a brokerage account.” Instead of creating a parallel market, Ondo Stocks taps into liquidity where it already exists. “There is just a user buying it at the liquidity that is available on Nasdaq or the New York Stock Exchange.” The right tokenization model pairs traditional market depth and pricing with the access, transferability, and utility of onchain finance.
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As assets go onchain, liquidity should follow. Done right, tokenized stocks tap into the deep liquidity already available in traditional markets. “In an ideal world, when you buy tokenized Tesla onchain, you are getting the same price as you would get in a brokerage account.” Instead of creating a parallel market, Ondo Stocks taps into liquidity where it already exists. “There is just a user buying it at the liquidity that is available on Nasdaq or the New York Stock Exchange.” The right tokenization model pairs traditional market depth and pricing with the access, transferability, and utility of onchain finance.

Ondo Finance

31,557 Aufrufe • vor 3 Monaten

Introducing Trailing Stoploss on Kite web. A regular stop loss stays fixed at the price you set. This works when you enter a trade, but it can become a problem if the trade moves in your favour. Say you buy a stock at ₹100 and set a stop loss at ₹90. The stock then moves to ₹140, but your stop loss remains at ₹90. If the price reverses, you could give back a large part of the move. The obvious solution is to keep moving the stop loss higher manually. But once the trade is live, it is easy to delay the decision, second-guess the move, or miss the price action altogether. With trailing stoploss, this adjustment happens automatically. The stop-loss trigger moves as the trade moves in your direction and stays unchanged when the price moves against you. Here's all you need to know👇
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Introducing Trailing Stoploss on Kite web. A regular stop loss stays fixed at the price you set. This works when you enter a trade, but it can become a problem if the trade moves in your favour. Say you buy a stock at ₹100 and set a stop loss at ₹90. The stock then moves to ₹140, but your stop loss remains at ₹90. If the price reverses, you could give back a large part of the move. The obvious solution is to keep moving the stop loss higher manually. But once the trade is live, it is easy to delay the decision, second-guess the move, or miss the price action altogether. With trailing stoploss, this adjustment happens automatically. The stop-loss trigger moves as the trade moves in your direction and stays unchanged when the price moves against you. Here's all you need to know👇

Zerodha

48,768 Aufrufe • vor 4 Monaten

Marc Andreessen on the 3 things he looks for when investing in a startup The first thing Marc Andreesen looks for is a big market: “Is there a big existing market that you think you can go after and displace incumbents? Or do you believe there will be a new market that will be big?” The second thing he looks for is a 10x better product: “Is there a fundamental technology or economic change that justifies a new company? And the way I always think about that is: Is there a 10x change happening in the technology landscape? Is something 10x faster, 10x cheaper, or 10x better? If it’s not 10x, we as both VCs and entrepreneurs have to ask ourselves if it’s really worth doing because it’s really hard to start new companies . . . Existing companies are usually pretty good at what they do. So for a new company to exist, it has to bring a product to market that’s so much better than what exists that it punches through the status quo.” The third is the team: “Is the team outstanding? . . . You want to have a founding team of complementary skillsets. You want to have at least one super strong technologist — quite possibly more than one. Some of the best startups are actually more than one founding technologist. And then it often helps to have someone who is a marketing or salesperson who has a really good understanding of business.” Marc believes that you need all three of these, but if you’re going to compromise on one of those as an investor, it should be the product: “A great market is a lot easier to make up for with iterative product execution. The problem with a poor or small market is that even if you do a good job on the product, there just aren’t that many customers so it’s hard to ever get big and people get demoralized . . . And then we evaluate the team of a startup by its ability to get into a big market with a good product.”
2:43

Marc Andreessen on the 3 things he looks for when investing in a startup The first thing Marc Andreesen looks for is a big market: “Is there a big existing market that you think you can go after and displace incumbents? Or do you believe there will be a new market that will be big?” The second thing he looks for is a 10x better product: “Is there a fundamental technology or economic change that justifies a new company? And the way I always think about that is: Is there a 10x change happening in the technology landscape? Is something 10x faster, 10x cheaper, or 10x better? If it’s not 10x, we as both VCs and entrepreneurs have to ask ourselves if it’s really worth doing because it’s really hard to start new companies . . . Existing companies are usually pretty good at what they do. So for a new company to exist, it has to bring a product to market that’s so much better than what exists that it punches through the status quo.” The third is the team: “Is the team outstanding? . . . You want to have a founding team of complementary skillsets. You want to have at least one super strong technologist — quite possibly more than one. Some of the best startups are actually more than one founding technologist. And then it often helps to have someone who is a marketing or salesperson who has a really good understanding of business.” Marc believes that you need all three of these, but if you’re going to compromise on one of those as an investor, it should be the product: “A great market is a lot easier to make up for with iterative product execution. The problem with a poor or small market is that even if you do a good job on the product, there just aren’t that many customers so it’s hard to ever get big and people get demoralized . . . And then we evaluate the team of a startup by its ability to get into a big market with a good product.”

Startup Archive

17,333 Aufrufe • vor 9 Monaten

This will change how you see the stock market. Serial investor JL Collins explains stock market investment using the beer analogy: "When most people look at investment news, it's all this churning and trading; what stocks are hot right now, what stocks are falling. That's not the simple path to wealth; that's the foam." "The value of a stock is a combination of two things: the beer and the foam." "The beer is the fundamental operating value of the company; the sales, expenses, and profits while the foam is what the market determines the stock is worth based on emotions and speculation."
1:29

This will change how you see the stock market. Serial investor JL Collins explains stock market investment using the beer analogy: "When most people look at investment news, it's all this churning and trading; what stocks are hot right now, what stocks are falling. That's not the simple path to wealth; that's the foam." "The value of a stock is a combination of two things: the beer and the foam." "The beer is the fundamental operating value of the company; the sales, expenses, and profits while the foam is what the market determines the stock is worth based on emotions and speculation."

Fibonacci 🥷

43,392 Aufrufe • vor 6 Monaten

Stop whatever you’re doing and pay attention: IF the US is being serious and decides to literally print $15T to “sell” to the open market in order to buy Bitcoin… and it starts “buying” Bitcoin -A FINITE CURRENCY- at the open market price You can cheat You can be smart Or You can be the first If the US does try to be the first… …to sell trillions of dollars… …with the openly stated mission of getting away from worthless paper and debt based currency… …to get a FINITE money that can only become more valuable over time… … …so, I’ll ask the question: why are so many in the markets still holding USD? Or, holding assets beholden to the USD? —If you know ***in advance*** the biggest player in the world is about to sell and needs Bitcoin ONLY… (Send this to all your Bitcoin friends and all your noncoiners. The clip is from the movie Margin Call, and the principal is the same)
2:29

Stop whatever you’re doing and pay attention: IF the US is being serious and decides to literally print $15T to “sell” to the open market in order to buy Bitcoin… and it starts “buying” Bitcoin -A FINITE CURRENCY- at the open market price You can cheat You can be smart Or You can be the first If the US does try to be the first… …to sell trillions of dollars… …with the openly stated mission of getting away from worthless paper and debt based currency… …to get a FINITE money that can only become more valuable over time… … …so, I’ll ask the question: why are so many in the markets still holding USD? Or, holding assets beholden to the USD? —If you know ***in advance*** the biggest player in the world is about to sell and needs Bitcoin ONLY… (Send this to all your Bitcoin friends and all your noncoiners. The clip is from the movie Margin Call, and the principal is the same)

Financial Physics

127,791 Aufrufe • vor 1 Jahr