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@a_____a9388: #CapCut 🥺🫴A

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Monday 13 July 2026 06:52:41 GMT
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ansafkhan738
[email protected] :
🥰🥰🥰
2026-07-19 04:46:26
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danish.jutt7572
꧁༒☬𝓓𝓐𝓝𝓘𝓢𝓗 𝓙𝓤𝓣𝓣☬༒꧂ :
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2026-07-15 18:47:17
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itx.heer80
MASN❤️❤️ :
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2026-07-14 08:48:34
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danish.jutt7572
꧁༒☬𝓓𝓐𝓝𝓘𝓢𝓗 𝓙𝓤𝓣𝓣☬༒꧂ :
❤️❤️❤️
2026-07-15 18:47:15
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faizanofficial165
Faizan official 😍 :
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2026-07-15 17:23:15
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ahsanqirashi249
Ahsan Qurashi,🦅👀 :
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2026-07-14 08:29:53
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ali_zain468456
ALI ZAIN SIAL 786 :
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2026-07-13 19:47:40
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rai.faisal4573
Rai Faisal :
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2026-07-13 15:27:52
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m.amjad.rajput
❣️Rahman Rana rajputt ❣️ :
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2026-07-13 07:02:01
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deedaralibrohi
Deedar Ali Brohi :
♥️💖💖🌹💝💗
2026-07-15 15:33:36
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What a wonderful thing it is to live in a country where you can go to the hospital without having to weigh if it is enough of an emergency or if you will be able to afford the bill. #germany #deutschland #healthcare
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Explore this green oasis in the heart of London 🍃 Step into a tropical paradise right in the heart of London at the Barbican Conservatory. With over 2,000 plants, it's like a secret garden waiting to be explored. 🌿✨ The Barbican Estate itself is an iconic example of Brutalist architecture, designed in the 1970s by Chamberlin, Powell and Bon. Known for its bold concrete structures and integrated urban spaces, it was a pioneering vision for modern living. The building is also home to a wonderful theatre, exhibition spaces and regularly hosts cultural events. Ready to escape the hustle and bustle? 📆 Sat & Sun from 12pm-5pm 🎟️ Entry is FREE, but be sure to book your spot in advance. 📍 EC2Y 8DS #barbicanconservatory #barbican #londongardens #explorelondon #londonattractions #spring #visitlondon #londonthingstodo #thingstodoinlondon
Explore this green oasis in the heart of London 🍃 Step into a tropical paradise right in the heart of London at the Barbican Conservatory. With over 2,000 plants, it's like a secret garden waiting to be explored. 🌿✨ The Barbican Estate itself is an iconic example of Brutalist architecture, designed in the 1970s by Chamberlin, Powell and Bon. Known for its bold concrete structures and integrated urban spaces, it was a pioneering vision for modern living. The building is also home to a wonderful theatre, exhibition spaces and regularly hosts cultural events. Ready to escape the hustle and bustle? 📆 Sat & Sun from 12pm-5pm 🎟️ Entry is FREE, but be sure to book your spot in advance. 📍 EC2Y 8DS #barbicanconservatory #barbican #londongardens #explorelondon #londonattractions #spring #visitlondon #londonthingstodo #thingstodoinlondon
How do quants detect a market regime change in real time? The textbook approach fits a hidden Markov model on daily returns, but the raw online signal flips roughly nine times a year in the tests below. The statistical jump model (Bemporad, Breschi, Piga and Boyd, 2018, Automatica) reframes regime detection as clustering with memory: k-means on exponentially weighted downside deviation and Sortino features, plus a fixed penalty for every state transition, fitted by coordinate descent with a dynamic programming step. Shu, Yu and Mulvey (2024, Journal of Asset Management) tune the penalty through walk-forward cross-validation on the strategy's Sharpe ratio and test out-of-sample on the S&P 500, DAX and Nikkei 225 from 1990 to 2023, with 10 bps transaction costs and a one-day trading delay: on the S&P 500 the signal switched about once a year, and in their backtest the strategy reduced volatility and maximum drawdown versus buy-and-hold, with a higher Sharpe ratio than the HMM version, and held up better under longer trading delays. Limitations: backtests on three equity indices, two-state model, one small feature set; results depend on the jump penalty, tuned by cross-validation in the paper; detection latency was around half a month in their COVID-19 example, so the model confirms regime shifts, it does not predict them. Not investment advice. Papers: Shu, Y., Yu, C., Mulvey, J.M. (2024).
How do quants detect a market regime change in real time? The textbook approach fits a hidden Markov model on daily returns, but the raw online signal flips roughly nine times a year in the tests below. The statistical jump model (Bemporad, Breschi, Piga and Boyd, 2018, Automatica) reframes regime detection as clustering with memory: k-means on exponentially weighted downside deviation and Sortino features, plus a fixed penalty for every state transition, fitted by coordinate descent with a dynamic programming step. Shu, Yu and Mulvey (2024, Journal of Asset Management) tune the penalty through walk-forward cross-validation on the strategy's Sharpe ratio and test out-of-sample on the S&P 500, DAX and Nikkei 225 from 1990 to 2023, with 10 bps transaction costs and a one-day trading delay: on the S&P 500 the signal switched about once a year, and in their backtest the strategy reduced volatility and maximum drawdown versus buy-and-hold, with a higher Sharpe ratio than the HMM version, and held up better under longer trading delays. Limitations: backtests on three equity indices, two-state model, one small feature set; results depend on the jump penalty, tuned by cross-validation in the paper; detection latency was around half a month in their COVID-19 example, so the model confirms regime shifts, it does not predict them. Not investment advice. Papers: Shu, Y., Yu, C., Mulvey, J.M. (2024). "Downside Risk Reduction Using Regime-Switching Signals: A Statistical Jump Model Approach." Journal of Asset Management, 25(5), 493-507. DOI: 10.1057/s41260-024-00376-x. Open access: arXiv:2402.05272. Bemporad, A., Breschi, V., Piga, D., Boyd, S.P. (2018). "Fitting Jump Models." Automatica, 96, 11-21. Preprint: arXiv:1711.09220. Hamilton, J.D. (1989). "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle." Econometrica, 57(2), 357-384. DOI: 10.2307/1912559. #finance #quant #trading #algotrading #stocks

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