Florian Ielpo

Rates against the machine, no more! So the FED decided to go big, cutting the policy rate by 50 bps, above consensus expectations of 25 bps but in line with odds embedded in the futures and OIS curves. By doing so, the financial institution wants to solidify the soft landing scenario. This dovish cut has been accompanied with some pull back in the comments that this move is not necessarily the playbook looking forward. The 'dot plot' has been adjusted downwards due to more front-loading rate cuts this year but gradualism is maintained thereafter and the direction of travel as well. What matters for financial markets? Bonds are back in Q3. Good! Still not all is crystal clear. The future pace of cuts could change again as the 'dot plot' range remains wide and the average path is less consensual than before. Moreover, current market pricing remains very and probably too aggressive. So, bond market volatility could resurface to some extent, albeit not as much as at the beginning of the year as the monetary easing cycle has now started. And the carry/yield will protect performance. Equities have generally performed well in the past after an initial rate cut in a soft landing scenario. Not necessarily in the very short term, but more over time, as a cyclical rebound takes hold. But for that to happen, leading indicators of the manufacturing sector must improve significantly. It remains to be seen to what extent monetary policy easing will actually contribute positively to economic activity. Hopefully, it will. AG Insurance Insurance #markets #economy #finance #financenews #investments #investmentnews #investmentinsights Thanks to Trends Canal Z and Marion Boxho

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Monitor: US BSL CLO New Issue Arb Trend Since 2017 The median arbitrage metric YTD at 195 bps is actually lower than in both 2022 and 2023, but this year’s new issue volume has already far exceeded the past two years’ volume on an annualized basis. Similarly, 2018-vintage deals had the lowest median arbitrage metric at 191 bps, but 2018 was a record-breaking year for new issue #CLO volume at the time. On the other hand, 2020-vintage deals had the best median arbitrage metric at 243 bps, but their new issue volume was the lowest. If you’re interested in learning more about the premium content or would like a walkthrough of the website via Zoom, please don’t hesitate to email me at [email protected]. https://lnkd.in/e6sUTfjw

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Regional heterogeneity and the aggregate transmission of monetary policy. A very interesting and relevant topic! "The Regional Keynesian Cross" by Marco Bellifemine, Adrien Couturier, and Rustam Jamilov https://lnkd.in/e-hT3XU4

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Relative importance of market volatility and oil shocks for green bonds https://lnkd.in/eDYVPMuU

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As one would expect, SPX Skew (1m 25d) should be elevated with the upcoming US elections. Below we are looking at HS<go> and the SPX vs the SX5E Skew (1m 25d). The upper chart shows that overall Skew was coming off for both after Covid. (blue box) But it also shows, that Skew has been rising since end of 23 for the SPX, and end of Feb 24 for the SX5E. The chart in the middle shows that SPX Skew used to be over the SX5E up to the end of 21, and only since about July this year turned more expensive relative to the SX5E again. Correlation between the two is at its highest since end of 21 too. You can create your own Skew indices using CIX<go>

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[High View Paper] #callforreading 📃The paper “A State-of-the-Art Review of #Probabilistic Portfolio Management for Future Stock Markets” 🔍 has been viewed by 4952. ✨ Keywords: #portfolio_optimization; Shanghai stock market; #time_series prediction; #Monte_Carlo #simulation; return and #risk 📌 Please click the link to learn more: https://buff.ly/3YbCzrK #Portfolio_theory; #Monte_Carlo_methods #MDPIOpenAccess #ComSciMath_Mdpi

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"Gaussian Processes for Implied Volatility Estimation": "A Bayesian nonparametric method generates posterior distributions of implied volatility functions, producing confidence intervals and quantifiable measures of model uncertainty." https://lnkd.in/eNiK5VAv

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Algorithmic trading transforms finance, enhancing trade efficiency and precision. Utilizing math and tech, strategies seize opportunities and manage risks, from high-frequency to trend-following approaches, in dynamic markets. Let's delve into the world of algorithmic trading strategies and uncover key insights into this dynamic field: ✅ 𝐐𝐮𝐚𝐧𝐭𝐢𝐭𝐚𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Algorithmic trading relies on quantitative analysis of market data, utilizing mathematical models and statistical techniques to identify profitable trading opportunities. ✅ 𝐇𝐢𝐠𝐡-𝐅𝐫𝐞𝐪𝐮𝐞𝐧𝐜𝐲 𝐓𝐫𝐚𝐝𝐢𝐧𝐠 (𝐇𝐅𝐓): HFT strategies involve executing large volumes of trades at ultra-fast speeds, capitalizing on small price discrepancies and market inefficiencies. ✅ 𝐓𝐫𝐞𝐧𝐝 𝐅𝐨𝐥𝐥𝐨𝐰𝐢𝐧𝐠: Trend-following algorithms aim to capitalize on market trends by buying assets that are rising in value and selling those that are declining, based on historical price data. ✅ 𝐌𝐞𝐚𝐧 𝐑𝐞𝐯𝐞𝐫𝐬𝐢𝐨𝐧: Mean reversion strategies seek to profit from the tendency of assets to revert to their historical mean prices after experiencing temporary deviations, employing statistical measures like moving averages or standard deviations. ✅ 𝐀𝐫𝐛𝐢𝐭𝐫𝐚𝐠𝐞: Arbitrage strategies exploit price differentials between different markets or assets, executing simultaneous buy and sell orders to profit from the price gap. ✅ 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐀𝐈: Advanced algorithms powered by machine learning and artificial intelligence analyze vast datasets to identify patterns and optimize trading decisions in real-time. Algorithmic trading empowers traders with sophisticated tools, enhancing decision-making and performance in fast-paced markets. As technology evolves, it will shape finance, driving innovation and efficiency globally. #businessdevelopment #softwaredevelopment #fintech #BFSI #siteclick

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'Common risk factors in cross-sectional FX options returns' by Xuanchen Zhang, Raymond H Y So and Tarik Driouchi is now available in Review of Finance, Volume 28, Issue 3. Abstract: We identify a comprehensive list of thirty-eight characteristics for predicting cross-sectional FX options returns. We find that three factors—long-term straddle momentum, implied volatility, and illiquidity—can generate economically and statistically significant risk premia not explained by other return predictors. Meanwhile, the predictability of the other characteristics becomes insignificant after accounting for the FX option three-factor model. The significance of the three factors is confirmed through a series of robustness tests covering different data sources, alternative options strategies, diversification effects, bootstrapping, and omitting crisis years. Read the article: https://lnkd.in/ethzW-HF #reviewoffinance #finance

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Since vol is back again - one chart and quite a bit of data visualized if this helped. First chart shows the SX5E. Second one are its 3m atm implied vols. Third chart is 3m 25d Skew. Fourth one is a 3m vs. 12m atm termstructure comparison. The bottom chart shows 10d, 30d and 60d realized vol. Additionally all indices with Bollinger Bands for context.

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Is ETH About to Plummet Below $3K or Will the Bulls Step In? (Ethereum Price Analysis) ➡️ Read All : https://lnkd.in/ePAD6xbm Following a period of consolidation near critical support marks defined by the 0.5 and 0.618 Fibonacci retracement levels, alongside the 100-day MA, Ethereum witnessed a... [...] #CryptoTrading, #BullishRebound, #ResistanceLevel, #FuturesMarket, #Liquidity, #Crypto, #Ethereum, #NBTC

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