Scott Oeth, CFP®’s Post

Another extract from my forthcoming article in Perspective Magazine. So, what exactly is capitalism? Marx’s definition …the private ownership of the means of production…is attractive because of its simplicity. Unfortunately, Marx’s analysis is binary: the means of production can be privately owned (capitalism), or communally (in reality, state) owned. He doesn’t seem to have considered the possibility of some of the means of production being in private hands with the rest owned by the state. This public/private mixture is, of course, what we usually find in the modern world, and it’s a mixture that invites questions. Furthermore, ownership isn't the whole, or even the real story. The real issue is control. If you own (say) a factory but you can manufacture only what the state allows and sell at prices they dictate, ownership doesn't really count for very much. The important question is obviously this: Just how much of an economy can be controlled by the state before it ceases to be capitalist? There isn’t much agreement about the point (range?) at which state control of industry turns a capitalist economy into a socialist one. Later in the article, I attempt to identify some of the important considerations here, but first I want to go a little off-topic to look at something Ha-Joon Chang wrote about it. According to Ha-Joon Chang: "There's no scientifically defined boundary for the free market [via-a-viz the state]." Ok, I can agree with that. But then he goes on to say: "Recognising the boundaries of the market are ambiguous and cannot be determined in an objective way lets us realize that economics isn't a science like physics or chemistry, but a political exercise...If the boundaries of what you are studying cannot be scientifically determined, what you are doing is not a science." I've met Ha-Joon Chang and he's a charming and impressive guy, but regardless of the accuracy (or inaccuracy) of his claim (that economics is a political exercise rather than a science) his argument completely fails. Does physics set its own boundaries? If so, how? Using physics? What about Chemistry? Is there an experiment which will throw the boundaries of chemistry into sharp relief? No. Subjects do not and cannot set their own boundaries 'scientifically'. The boundaries are set by convention. But to infer from this that physics and chemistry are mere matters of convention is to radically miss the point.

It’s a narrative we often encounter. During our schooling years, we questioned the relevance of advanced mathematical concepts in our everyday lives. Algebra, Calculus, Probability – how often would these enter our daily adult existence? However, as we venture into the realm of adulthood and, more specifically, investing, the importance of these mathematical principles becomes resoundingly clear. #mathematics #investing #financialmaths https://lnkd.in/dbaSZuwe

Prediction: CFOs will soon want to upgrade their finance knowledge... with old fundamentals! Austrian economics (#mises #hayek) provide a first-principles framework to navigate the Coming Normal: #debt crisis, #automation (white collar AIs, blue collar robots), #decentralization (deglobalization / fragmentation / derisking), rather divergent from our keynesian school curriculums. Human: your time is scarce, but learning hard moneys is easy with good books. The hard feat will be how to reposition businesses. https://lnkd.in/e_9AtJvb by Dr. Saifedean Ammous

Course on Behavioural Finance by Duke: I recently completed a fascinating course on Coursera that talked about the newly and blossoming field of Behavioural Finance. The instructors of the course were Emma B. Raisel and John Forlines III, who are part of the Economics department at Duke University. It was a rather interesting course that talked about the irrational decisions humans make from day-to-day by violating the axioms of dominance, invariance and independence. The course further highlighted how we can avoid making these errors by understanding the biases which cause them. We went over numerous cognitive biases that cause us to make irrational decisions, and also explored how we can avoid making these small financial errors in our every day lives. Overall, it was truly a delight to spend 3 weeks getting an introduction to the prodigious field of behavioural finance through this captivating course.

Unlocking the secret of stock markets! SFI’s LMF Model, proposed by Doyne Farmer, Fabrizio Lillo, and Szabolc Mike, explains the “long memory” behavior in stock markets. A recent study using Japanese stock market data confirms the model’s predictions, showcasing quantifiable laws in #finance. Financial markets, akin to physics, follow precise models. Despite the influence of buy and sell orders on prices, the resulting deviation from market efficiency is relatively small on average. h Understanding the intricacies of long-memory in order arrival opens new avenues for exploring market dynamics.

Tips and Strategies to handle a GD A group discussion is based on variety of topics which can be broadly classified into- 1.      Factual 2.      Abstract. Given below is the strategy to tackle these two types of GD topics: 1. Factual: These topics are based on static or dynamic components of the environment (such as social, political, economical, etc.). In other words, these topics check your general knowledge as well as understanding of current happenings. The first step towards approaching a factual topic is to analyse the topic from multiple angles. Try to explore the history of the topic- find the people/events that triggered the issue. Discuss the pros and cons from various perspectives. Give examples to justify your viewpoint. Find the stake holders in the given issue- figure out the elements that are going to lose or benefit from the issue. Generally, the factual topics belong to the following areas- education, sports, social, political, economics, IT, environment, national & international events etc. Examples of factual topics- The Euro crisis: issues and challenges, Genesis of Caste System in India etc. 2. Abstract: These topics assess your perception and interpretation on wide-ranging subjects. The way you look at the topic decides your subsequent participation and performance in a GD. The challenge here is to put forth multiple implications of the topic and then evoke a discussion on some of them. Idea generation and ability to add a tangible angle to an otherwise abstract topic are essential to ace such kind of GDs. Think creatively on the topic and then translate that thinking into concrete ideas and words. A creative idea is best justified if it is supported with facts or linked to a current event. Pay attention to other candidates’ points so that they can be developed further. These topics have a wide scope. So, try to explore them from various aspects. 6 Use POPBEANS approach for idea generationPeople, Objects, Place, Behaviour, Event, Actions, Nature, Society. Examples of abstract topics: Smart work v/s Hard work, Modernization is not westernization, Red, Borderless world – a myth/reality? etc.

Recursive Methods in Economic Dynamics First Edition by Nancy L. Stokey (Author), Robert E. Lucas Jr. (Author), Edward C. Prescott October 10, 1989 "Recursive Methods in Economic Dynamics" is a subject primarily focused on advanced mathematical and computational techniques used in economic modeling and analysis. This field applies recursive functions and iterative processes to solve dynamic economic models involving intertemporal choices, optimization problems, and economic decision-making over time. Subjects covered within "Recursive Methods in Economic Dynamics" may include: 1. Dynamic Programming: Techniques for solving multi-period decision problems by breaking them down into smaller, more manageable parts. 2. Bellman Equations: Mathematical formulations used to solve dynamic optimization problems, particularly in sequential decision-making processes. 3. Euler Equations: Equations that express the intertemporal trade-offs between consumption and saving decisions over time. 4. State-Space Models: Representation of dynamic systems in terms of states, transitions, and controls, often used in economic forecasting and policy analysis. 5. Computational Techniques: Application of numerical methods and algorithms to solve complex economic models efficiently, such as value function iteration or simulation methods. 6. Applications in Macroeconomics and Microeconomics: Practical applications of recursive methods in various economic models, including growth theory, asset pricing, optimal taxation, and more. #Economics #RobertLucas #PlainfieldNJ https://a.co/d/eGclqHw

Diving into the world of economics through the prism of mathematical chaos theory opens up new perspectives for understanding and predicting market phenomena. In recent years, I have been actively studying how mathematical models based on the principles of chaos can be applied to analyze economic systems. One of the most intriguing examples is the use of fractal geometry to analyze financial markets. The works of Benoit Mandelbrot have shown how fractal models can describe the complex structure of financial data, revealing patterns in the seeming chaos of market fluctuations. These studies have formed the basis of my analysis, allowing a deeper understanding of market dynamics. Also, significant influence on my research came from works in the field of nonlinear dynamics. Experiments with logistic mapping, showing how simple nonlinear systems can exhibit complex behavior, help to understand how small changes in economic conditions can lead to drastically different outcomes. Applying these principles to economic data demonstrates that many market phenomena, previously considered random or unexplainable, actually follow internal regularities. An important aspect of my research is also the analysis of financial market time series. Using methods developed within the framework of chaos theory, I investigate how time series of stock prices and currency rates can demonstrate fractal properties and chaotic behavior. These studies confirm that traditional linear models often fail to adequately describe the complexity and dynamics of market processes. In conclusion, my research confirms that mathematical chaos theory offers a powerful tool for analyzing economic systems. The possibility of using these principles for more accurate prediction of market fluctuations and crises opens new horizons for economic analysis and strategic planning. This is an approach that can radically change our understanding of economic processes and provide new tools for effective financial risk management.

Stepping into History, Embracing Tomorrow of Finance: Insights from My Lecture 📖🚀 At the end of last semester, I had the incredible opportunity to step into the historic halls of our University of Zurich main building, perched atop the picturesque hills of Zurich. 🏰✨ It was a refreshing change from my usual lectures, which often took place in the modern quarters of the computer science department. 😄💻 Huge thanks to Smart Contracts Lab for making it happen. The turnout in July was inspiring—students eager to explore arbitrage and leverage strategies sparked insightful questions. 🙌🔍 As a new semester approaches, I encourage all students to delve into DeFi. Join the Internet Economics Seminar by the Computer Science Department for a deeper dive. 🌐📈 Excited to see you in class in two weeks! Attached: A snapshot of the lecture focusing on economics and finance aspects of DeFi. 📊🤝 Connect with me 👉 and tap the 🔔 icon on my LinkedIn to stay updated 👇 📲 Share within your network. ✍️ Drop your feedback in the comments. 📩 Feel free to DM me for further conversations!