Systematic Investment Planning

Why Alternatives, and Why Now? Markets shift, cycles turn, and investors ask the same question: How will alternatives hold up when the tide changes? We’ve run the numbers, mapped out the scenarios, and here’s the takeaway: Alternatives remain relevant across bull, bear, and base cases—but how you allocate matters. 🔴 Bear Case: Market Disruption Recession, geopolitical risk, and tighter liquidity? Equity markets struggle, defaults rise, and risk tolerance fades. • Private Equity: Distressed buyouts gain traction as secondary markets pick up bargains. • Macro Hedge Funds: A bright spot—volatility creates opportunities in FX and rates. • Private Credit: Defaults climb, but high-quality credit holds steady. • Infrastructure: Defensive assets like utilities and essential services remain resilient. ⚪ Base Case: Stabilization & Modest Growth Rates stabilize, inflation stays in check, and markets tread water. • Private Equity: Mid-market buyouts and secondaries thrive, while defensive sectors like healthcare attract capital. • Macro Hedge Funds: Systematic strategies benefit from macro trends. • Private Credit: Direct lending remains a steady performer. • Infrastructure: ESG and sustainability-linked projects attract capital. 🔵 Bull Case: Accelerated Growth Global expansion, rate cuts, and rising optimism fuel risk-taking. • Private Equity: Tech, AI, and healthcare see surging valuations. • Macro Hedge Funds: Trend-following strategies ride the market wave. • Private Credit: Yield-seeking investors move into structured financing. • Infrastructure: Capital floods into renewable energy and transport projects. My Take? The case for alternatives isn’t binary—it’s about resilience, flexibility, and knowing where to lean in. When equity beta wobbles, alternatives offer a playbook for every market regime. As Howard Marks put it: “You can’t predict. You can prepare.” Are you positioned for what’s next? #Investing #Alternatives #Markets #PrivateEquity #MacroHedgeFunds #PrivateCredit #Infrastructure

🤔 Will alternative investments including hedge funds and real estate really DISAPPEAR from the portfolios of pension funds and endowments over the next 10-20 years? That's what investment consultant Richard Ennis thinks. Already in 2020 he wrote "Alternatives a ‘loser’s game’" (https://lnkd.in/eafShkdx). Ennis says that since the Global Financial Crisis, hedge funds have failed to add value for institutional investors, and referenced to the HFR Fund-Weighted Composite Index's annualized return. However, this comparison misses several critical points: 1. The index itself is flawed as a measurement tool as the HFR Fund-Weighted Composite isn't investable. It suffers from selection bias, survivorship bias, and backfill bias. Many of the best-performing funds aren't even included as they're closed to new investment. 2. Risk-adjusted returns tell a different story. The cited period includes unprecedented market conditions, including ultra-low interest rates and massive central bank intervention that artificially supported traditional assets. Yet hedge funds delivered these returns with significantly lower volatility and drawdowns—precisely what institutional investors seek. 3. Top-quartile managers consistently outperform. The dispersion of returns in alternative investments is much wider than in traditional asset classes. Sophisticated institutions with access to premier managers have achieved returns substantially above the index. 4. Diversification benefits remain compelling. Hedge funds' true value proposition isn't just absolute returns but rather portfolio efficiency through low correlation to traditional assets. During the COVID market crash, many hedge fund strategies provided critical downside protection. 5. The landscape has evolved. Fee structures have become more investor-friendly since the GFC, with reduced management fees, hurdle rates, and performance crystallization terms that better align manager and investor interests. 6. A working paper by Barth et al. (2023) indicates that a newly emergent subset of hedge funds—ones not included in vendor databases—has produced better returns than those that do participate in the databases. Indeed, while #multistrategy firms' dominance has made it harder for under-the-radar names to compete, investors still look for and invest in up-and-coming managers, e.g. Blackstone and the Teacher Retirement System of Texas seeded new funds and sought out emerging managers. Institutional allocators invest in hedge funds not to replace equities but to enhance overall portfolio construction through differentiated return streams. When properly selected and incorporated into a sophisticated investment program, #hedgefunds continue to serve an essential role in institutional portfolios. In private banking, appetite for alternative assets is growing: https://lnkd.in/emxTUd7D What's your view?

As financial markets grow more complex and data-rich, firms are turning to AI technologies like Machine Learning (ML) and Natural Language Processing (NLP) to sharpen decision-making, boost operational efficiency, and stay ahead of the curve. AI is reshaping #assetmanagement. 🔍 Machine Learning is powering smarter trading strategies, real-time risk modeling, and fraud detection—trained on vast datasets to identify patterns and generate above-market returns. In 2024 alone, the ML segment hit $2 billion and is projected to grow at a CAGR of 23.8% through 2034. 🗣️ Natural Language Processing is enhancing predictive insights and enabling real-time responses to market shifts, making it easier for firms to decode unstructured data and uncover actionable intelligence. 🛡️ Interestingly, despite the rise of cloud solutions, 60% of firms still prefer on-premises deployment—prioritizing control, compliance, and security for their proprietary AI models. 💡 This wave of innovation is fueling the rise of robo-advisory platforms, AI-driven trading tools, and highly tailored strategies designed to thrive in volatile, fast-moving markets. As we look ahead, one thing is clear: AI isn't replacing humans—it’s amplifying their potential. 📈 The U.S. market is leading the charge, but this is just the beginning. The question isn’t if AI will redefine asset management—it’s how fast your firm will adapt. #AI #MachineLearning #Fintech #InvestmentStrategies #NLP #FinancialInnovation #DigitalTransformation https://lnkd.in/gmzpq67M 

𝐓𝐡𝐞 𝐑𝐢𝐬𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐖𝐞𝐚𝐥𝐭𝐡 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: What can (affluent) investors expect? 💡 This week, we are diving into the so-called Wealth Channel - the attempts of alternative asset managers to raise capital from smaller investors through intermediaries such as wealth managers and family offices. Today, let's tackle the key question of what those smaller investors can expect from this trend. But let's start with another question - 𝐰𝐡𝐲 𝐬𝐡𝐨𝐮𝐥𝐝 𝐭𝐡𝐞𝐲 𝐜𝐚𝐫𝐞 𝐚𝐛𝐨𝐮𝐭 𝐬𝐮𝐜𝐡 (𝐚𝐥𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐯𝐞) 𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐩𝐥𝐚𝐜𝐞? They don't 𝘯𝘦𝘦𝘥 to - often, investors can easily achieve their target return with conventional investments. But we do see some structural advantages, such as the chance at a higher return (~2-4% over public benchmarks), access to differentiated sources of return (think niche lending or esoteric royalties), and some structural benefits (like fewer constraints). Attentive readers might wonder: Jan, you said yourself that most retail-oriented investments you saw were NOT worth their money. Why should that be different for this new wave of products? There's a few reasons that make me cautiously optimistic, such as: 🏦 Product Structure: Unlike prior retail-specific products with terrible risk-return, many Wealth Channel products invest pari passu with institutional investors, and often have the GPs as the biggest co-investors. 🌊 Liquidity Profile: Most existing retail products were EXTREMELY illiquid with no fair secondary markets. Many of the new products are semi-liquid, offering investors the chance to sell their stakes at regular intervals. 🪞 Transparency: Semi-liquid vehicles have an auditable track record - unlike dubious mezzanine bonds that are marketed based on expected (but never realized) returns. Of course, there's many easy ways to critize each of my points, including but not limited to recent criticism of evergreen secondary funds, or liquidity-limiting factors such as gating (as we saw with BREIT). And alternative products certainly offer many chances for advisors to charge more - the opposite of the general trend to cheaper products like ETFs. 𝐁𝐮𝐭 𝐧𝐞𝐯𝐞𝐫𝐭𝐡𝐞𝐥𝐞𝐬𝐬, 𝐢𝐟 𝐝𝐨𝐧𝐞 𝐫𝐢𝐠𝐡𝐭, 𝐭𝐡𝐞𝐲 𝐬𝐞𝐞𝐦 𝐥𝐢𝐤𝐞 𝐚 𝐦𝐮𝐜𝐡 𝐛𝐞𝐭𝐭𝐞𝐫 𝐨𝐩𝐭𝐢𝐨𝐧 𝐭𝐡𝐚𝐧 𝐦𝐚𝐧𝐲 𝐨𝐟 𝐭𝐡𝐞 𝐞𝐱𝐢𝐬𝐭𝐢𝐧𝐠 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬. One can only dream of a day where retail investors actually get an equal (or better…?) product than institutional investors at perhaps just a slightly higher price.

From Competition to Co-Opetition: How Partnerships Fuel Bank Success 💡 Automotive trailblazer Henry Ford said, “Coming together is a beginning, staying together is progress and working together is success.” He understood the importance of partnerships in elevating the art of the possible. Banks face a pivotal choice. They can either stand by as big banks, big brands, big tech and fintechs steal their customers, or they can invest in innovation partnerships to meet growing demands and expand revenue streams 💰 In isolation, banks cannot keep up with the rapid pace of tech innovation. However, partnerships can be a game-changer, quickly enhancing an institution’s capabilities. Savvy banks recognize the need to partner with a wider range of ecosystem players — including brands, tech firms and fintechs — to accelerate growth and enhance technology, branding and distribution. This shift in the innovation paradigm from “build, buy, partner” to “partner, build, buy” is redefining how banks innovate and operate, empowering them to reach new heights 🚀 Effective collaboration starts with a cohesive strategy between the bank and partner, building trust in the partnership. The relationship will have ups and downs, but maintaining a long-term partnership requires flexibility and adapting to unexpected challenges. Strategic partnerships work best when a bank has a future-state vision of its role in a distinct and defined ecosystem. This approach forces the bank to self-reflect and address gaps in resources, technology and processes 👨💻 With distinct partnership modules and archetypes to pursue, the bank must consider several factors, including resource availability, risk appetite, and technology and partnership orchestration capabilities. These archetypes span organizations that range from “traditionalists” that want to maintain the status quo and compete independently (low risk) to “ecosystem maestros,” where the bank aims to build and manage a network of partnerships (higher risk) to provide a broad and holistic set of services to customers 🙋♂️ Partnerships can progress from initial value chain integrations to full co-creation driven by success or customer needs. Source: L.E.K. Consulting - https://shorturl.at/GBOxZ #Innovation #Fintech #Banking #Bigtech #FinancialServices #Payments #Lending #Partnerships #Ecosystem 

Asset pricing models use various variables to forecast future returns of assets like stocks. These models help investors identify potentially high-performing assets. Assets are interconnected through factors like supply chains, industry sectors, and market conditions, influencing their relative prices. Graph networks are well-suited for modeling these complex relationships. Existing GNN-based asset price prediction models often focus on fixed asset groups and static relationships, neglecting the dynamic nature of asset pools and their interconnections. As financial markets are dynamic, models must adapt to changes like new market entries, asset maturation, and corporate events. This requires a flexible framework that can adapt to the dynamic nature of asset pools and their interconnections. To address the dynamic nature of the market for asset pricing, the authors of [1] propose DySTAGE (Dynamic-graph-representation-learning via Spatio-Temporal Attention and Graph Encodings), a framework with a universal formulation that transforms asset pricing time series into dynamic graphs, accommodating the addition, deletion, and changes in correlations of assets which includes a graph learning model specifically designed for this purpose. In the DySTAGE framework, assets at various historical time steps are structured as a sequence of dynamic graphs, where connections between assets reflect their long-term correlations. DySTAGE effectively captures both topological and temporal patterns. The Topological Module deploys Asset Influence Attention to learn global interrelationships among assets, further enhanced by Asset-wise Importance Encoding, Pair-wise Spatial Encoding, and Edge-wise Correlation Encoding. In the Temporal Module, DySTAGE encapsulates node representations across the temporal dimension through an attention mechanism. #QuantFinance They validate DySTAGE through extensive experiments on 3 real-world stock pricing datasets. The results show that DySTAGE outperforms popular benchmarks in return prediction and provides profitable investment strategies. The link to their paper [1] is shared in the comments.

The Biggest Mistake I See Accredited Investors Make With Alternative Investments After working closely with accredited investors, one mistake shows up again and again. They chase the investment instead of building a strategy. I see investors jump into private deals, real estate syndications, funds, or alternatives because the returns look attractive — without asking how that investment fits into their overall portfolio. High returns don’t mean much if: → Liquidity is ignored. → The risk is misunderstood. → Tax impact isn’t planned for. → Cash flow doesn’t match their goals. Alternative investments are powerful — but only when used with intention. They should: → Support income and tax planning. → Reduce portfolio risk, not increase it. → Align with time horizon and exit strategy. The most successful investors I work with don’t ask, “Is this a good deal?” They ask, “Is this the right deal for me?” That shift is what separates disciplined investors from deal collectors. Alternative investing isn’t about chasing returns. It’s about structure, control, and long-term positioning.

Strategic Partnerships in Luxury: A Game-Changer Strategic partnerships have become transformative alliances in the luxury industry, redefining brand value, market influence, and the consumer experience. When done right, these collaborations don’t just elevate a brand’s status—they also pave the way for long-term growth and innovation. Why Strategic Partnerships Matter in Luxury: 1) Market Expansion: Collaborations open doors to new demographics and markets, helping brands expand their global presence. 2) Shared Expertise: Combining strengths allows for unique innovations that truly resonate with discerning consumers. 3) Elevated Brand Prestige: Partnerships with complementary brands enhance credibility and amplify exclusivity. Real-Life Examples of Successful Luxury Partnerships: - Apple x Hermès: This iconic collaboration merges Apple’s cutting-edge technology with Hermès’ artisanal craftsmanship. The result? The Apple Hermès watch—a masterful blend of elegance and functionality. - Loro Piana & Mytheresa: Loro Piana brought its timeless sophistication to a wider audience through curated collections on the premium e-commerce platform Mytheresa. - The Row & Oliver Peoples: Their partnership produced understated yet luxurious eyewear collections that perfectly align with the values of “quiet luxury.” Of course, the road to a successful partnership isn’t always smooth. Misaligned values, unclear objectives, or cultural differences can derail even the most exciting ventures. That’s why thoughtful planning is key: - Align with partners who share your values and vision. - Define clear, mutually beneficial goals. - Be culturally attuned to ensure seamless collaboration. Luxury thrives on authenticity and exclusivity. Partnerships should enhance the story of both brands, creating a synergy that inspires and captivates audiences. If you’re thinking about elevating your brand strategy through impactful collaborations, let’s connect. Together, we can craft a strategy that unlocks new opportunities and drives sustainable growth. Ready to take the next step? #LuxuryStrategy #StrategicPartnerships #LuxuryMarketing #BusinessGrowth #BrandInnovation

“Payment first” At the IAA MOBILITY conference couple weeks ago I was asked about our partnership with NIO and whether strategic capital is the key to scaling brands like Lemmo. Honestly? I'm pretty skeptical of strategic investments that start with equity discussions. Here's how I think about it: if a corporate partner really believes in what you're doing, they should be willing to pay for it first. With NIO, we started with a real pilot, an actual commercial program with a clear timeline. My rule is simple: prove the partnership works commercially before you even think about equity. Consider opening the cap table only if a partner consistently moves core metrics. Like if they're doubling your reach, cutting your customer acquisition costs by 30%, for example or helping you hit operational targets faster. Look, I've seen too many startups give away equity upfront for "strategic value" that never materializes. The corporate gets cheap equity, the startup gets vague promises of synergies. My take? The best strategic investments start as purchase orders. Make them pay first, prove the value, then maybe discuss equity. What's been your experience with strategic partnerships? #StartupFunding #StrategicPartnerships #VentureCapital #Mobility #StartupStrategy #Futureofmobility

🚀 Just Released: ML-Enhanced Stock Prediction using Ito's Lemma! 📈 I'm excited to share my latest project that bridges the gap between traditional financial mathematics and cutting-edge machine learning! 🔬 What makes this special? ✅ Combines Ito's Lemma (stochastic calculus) with LSTM neural networks ✅ Multi-head attention mechanism for complex temporal pattern recognition ✅ Predicts volatility and drift parameters dynamically using ML ✅ 20+ technical indicators including RSI, MACD, Bollinger Bands ✅ Monte Carlo simulations with confidence intervals ✅ Real-time 6-month forecasting with uncertainty quantification 📊 Key Results: 68.3% profit probability (ML) vs 61.2% (traditional) 2.15% reduction in prediction uncertainty Dynamic parameter estimation that adapts to market conditions 🛠 Tech Stack: PyTorch for deep learning architecture LSTM + Attention for sequence modeling Geometric Brownian Motion enhanced with ML predictions yfinance for real-time market data This hybrid approach demonstrates how mathematical finance and AI can work together to create more robust prediction models. The model doesn't just predict prices—it learns market dynamics and adjusts volatility/drift parameters in real-time. 🔗 Open Source: Available on GitHub with comprehensive documentation and examples! Disclaimer: This is for educational/research purposes only. Always consult financial professionals for investment decisions. #MachineLearning #QuantitativeFinance #StochasticCalculus #DeepLearning #PyTorch #FinTech #DataScience #LSTM #StockPrediction #OpenSource What do you think about combining traditional financial mathematics with modern ML techniques? Would love to hear your thoughts! 💭