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Why the Sharpe ratio is not as useful as everyone thinks? It only looks at mean return and standard deviation. That can miss tail risk when returns are skewed. Strategies with small steady gains and
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Why is order flow predictable but prices are not? Institutions split large orders into hundreds of small ones over hours or days. All same direction. So the order flow has a long memory, the sign aut
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Can neural networks improve Black-Scholes hedging? A recent paper from LSE trains 5 identical LSTMs on the same hedging problem under stochastic volatility and transaction costs. Same architecture, d
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Why volatility is a surface, not a number? Most models assume a single volatility per stock. Real option prices don’t agree. Deep out-of-the-money puts have much higher implied vol than at-the-money
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How to build a simple time-series momentum model? The idea is to compare an asset to its own past. If the price is higher than 12 months ago, the trend is up and you stay invested. If not, you step o
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888
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How do quants eliminate risk? Options move with the stock, which makes their P&L noisy. Delta hedging reduces this by offsetting the option with a position in the underlying: β€’ Delta (Ξ”) measures ho
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Why quants never use the normal distribution raw? The normal distribution fits the center of returns well. But real markets have fat tails and skew. Crashes happen far more often than the bell curve
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How quants size every bet they make? Most people hunt for an edge. Quants focus on sizing it. The Kelly Criterion gives the optimal fraction f* to risk to maximize long-run geometric growth. For a si
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743
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Why quants penalize their own models? Ridge regression (Hoerl & Kennard, 1970) adds a penalty on coefficient size. You trade a bit of training accuracy for much more stable out-of-sample predictions
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Why quants never trust their covariance matrix ? Most portfolio optimization models rely on the covariance matrix. 500 stocks = 125,000 parameters to estimate from only 252 trading days. More relat
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Most people think quants predict market direction. We usually don’t Here’s what they do predict: volatility, how much prices move. Key points: Volatility clusters: big moves follow big moves, small
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Can machine learning predict NVIDIA’s stock price? I trained an LSTM on 5 years of NVDA data. RΒ² = 0.99, looks perfect. But zoom in: the prediction is just yesterday’s price copied forward. Directio
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949
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About @vince.quant

Vincent is a Instagram micro influencer. With 14.9K followers and 17 posts, vince.quant's account shows a follower-to-following ratio of N/A:1. This profile demonstrates strong community engagement within its niche. View all content anonymously on Pictame - no login required.

vince.quant's engagement rate sits at 14.64%. That's 486% above what you'd typically see for accounts with 10K-100K followers (average 2.5%) β€” a sign of a genuinely connected audience.

Out of the last 12 posts, 100% are videos and 0% are photos. New posts appear roughly every 2 days β€” a steady, reliable rhythm. Captions lean detailed, averaging 855 characters.

14.64% engagement rate β€” 486% above average for 10K-100K follower accounts.
New content every 2 days β€” a steady rhythm.

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@vince.quant

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