CRYTOGEDON

15 January 2024

AI, Apps, Bez kategorii, Business, Open Source, Programming languages, Security, Sharing economy, Software

CRYTOGEDON

Reading Time: 5 minutes

INTRODUCTION

Crypto assets are no longer on the fringe of the financial system.

The market value of these novel assets rose to nearly $3 trillion in November from $620 billion in 2017, on soaring popularity among retail and institutional investors alike, despite high volatility. This week, the combined market capitalisation had retreated to about $2 trillion, representing an almost four-fold increase since 2017.

Amid greater adoption, the correlation of crypto assets with traditional holdings like stocks has increased significantly, which limits their perceived risk diversification benefits and raises the risk of contagion across financial markets.

The stronger association between crypto and equities is also apparent in emerging market economies, several of which have led the way in crypto-asset adoption between returns on the MSCI emerging markets index and Bitcoin was 0.34 in 2020–21, a 17-fold increase from the preceding years.

Stronger correlations suggest that Bitcoin has been acting as a risky asset. Its correlation with stocks has turned higher than that between stocks and other assets such as gold, investment grade bonds, and major currencies, pointing to limited risk diversification benefits in contrast to what was initially perceived.

Crypto assets have experienced tremendous growth over the past two decades, with the number of coins increasing from just Bitcoin in 2009 to over 5,000 currently, and reaching a total market capitalization of over USD 3 trillion towards the end of 2021^. However, this growth has been accompanied by significant volatility, with most crypto coins going through several cycles of rapid growth followed by dramatic collapses. This is reminiscent of other periods in financial history in which private forms of money have proliferated in the absence of adequate government regulation, leading to frequent financial crises (such as in the US during the “Free Banking Era” of 1837–1863).

The rapid ascent of crypto assets, coupled with their increasing mainstream adoption, has generated concerns among policymakers and regulators, who are mindful about the potential contagion risks to other financial markets as well as the broader macro-financial. Crypto asset markets can both act as a source of shocks or as amplifiers of overall market volatility, thereby having the potential to have significant implications for financial stability. Consequently, policymakers face an imperative to enhance their comprehension of the interconnections between crypto assets and financial markets, enabling them to devise regulatory frameworks that effectively counteract the potential adverse consequences of crypto assets on financial stability.

The complex and rapidly evolving nature of the crypto market pose challenges for regulators in effectively assessing and addressing associated risks. Crypto assets encompass a wide range of technological attributes and features, serving means of payment, to store of value, speculative asset, support for smart contracts, fundraising, asset transfer, decentralized finance, privacy, digital identity, governance, among others. However, their relationship with traditional financial assets, particularly in terms of diversification potential, remains a subject of debate. While substantial research has investigated the nature, direction and intensity of linkages between crypto assets and crypto assets and other financial assets, the findings are still relatively inconclusive and paint a complex picture of interdependencies.

The multifaceted interaction channels between crypto assets and financial markets may make it challenging to assess the relationship, while it may also have changed over time.

On the one hand, a “fight-to-safety channel” would suggest that investors may allocate their funds into crypto assets during periods of economic uncertainty or market stress if cryptos are perceived as safer and offering a good hedge to certain financial assets. Crypto assets can thus provide diversification benefits if their correlation with certain classes of traditional assets is low. However, their tendency for high volatility raises important concerns. Another potential channel is the “speculative demand channel”, which would suggest that demand for crypto assets may increase during times of high financial market risk appetite, as cryptos offer the potential for high returns due to their volatility. Further channels could be related to market liquidity and to information spillovers or investor sentiment, which can lead to additional comovement between various classes of financial assets and crypto markets.

This dataset consists of the daily closing price of the five largest crypto assets by market capitalization namely Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), Binance (BNB), and Tether (USDT) as of December 31st, 2021. The stock market is captured by the US S&P500 index, and we also include the Brent oil price, as well as the 10-year U.S. treasury bill as control variables to account for the possible impact of variations in commodity prices and financial condition on asset prices. The US S&P500 tracks the performance of 500 large companies in leading industries and represents a broad cross-section of the U.S. economy and is widely considered representative of the overall stock market . Tether (USDT) is a stable coin used in this study to provide insight into the inflow and outflow of funds in the market and as a tool for hedging against the volatility of the crypto market. For this reason, the USDT is likely to be more sensitive to the movement of price in the crypto market. presents a time series plot of the sampled variables. The daily datasets are in U.S. dollar currency and span from the period January 2018 to December 2021, excluding non-trading days for uniformity. Data on cryptocurrencies (Bitcoin, Ethereum, Ripple, Binance, and Tether) were retrieved from Yahoo Finance, whereas data on Brent oil, and U.S. 10-year treasury bills were retrieved from the U.S. Federal Reserve Bank of St. Louis. Additionally, the U.S. S&P500 was retrieved from Investing market indices. The baseline specification of this study considers the S&P500 index as an endogenous variable whereas cryptocurrencies and the control variables are used as dependent variables.

The increased and sizeable co-movement and spillovers between crypto and equity markets indicate a growing interconnectedness between the two asset classes that permits the transmission of shocks that can destabilise financial markets.

CONCLUSION

This analysis suggests that crypto assets are no longer on the fringe of the financial system, IMF said.

The market value of these novel assets rose to nearly $3 trillion in November from $620 billion in 2017, on soaring popularity among retail and institutional investors alike, despite high volatility. This week, the combined market capitalization had retreated to about $2 trillion, still representing an almost four-fold increase since 2017.

By- Shannul Mawlong 50401

AI Sources: chat gpt 4

Other sources: https://www.business-standard.com/article/markets/crypto-prices-moving-in-sync-with-stocks-posing-systemic-risks-122011200477_1.html

IMF says crypto prices correlation with stocks poses new risks to financial stability

https://www.sciencedirect.com/science/article/pii/S2405844023033868https://www.elibrary.imf.org/viewhttps://www.imf.org/en/Blogs/Articles/2022/01/11/crypto-prices-move-more-in-sync-with-stocks-posing-new-risksjournals/001/2023/213/article-A001-en.xml

6 January 2024

THE EU RENAISSANCE :

Reading Time: 4 minutes

European stocks and bonds have had a lot to deal with in recent years, not least war, an energy crisis and surging inflation. Now things are looking up. Germany’s DAX index of shares has added 14% since the start of November. Yields on French ten-year government bonds have dropped from 3.5% in October to 2.6%. Even Italian yields have fallen below 4%, from 5% in mid-October. Investors are upbeat in part because inflation is falling faster than expected. Yet their mood also reflects a grimmer reality: the economy is so weak that surely interest-rate cuts are not far away. As Russia’s war in Ukraine takes a rising toll on Europe’s economies, growth is flagging across the continent, while inflation shows little sign of abating.

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Europe’s advanced economies will grow by just 0.6 percent next year, while emerging economies (excluding Türkiye and conflict countries Belarus, Russia, Ukraine) will expand by 1.7 percent, according to projections in our latest World Economic Outlook. That’s down by 0.7 percentage point and 1.1 percentage points, respectively, from July’s projections.

This winter, more than half of the countries in the euro area will experience technical recessions, with at least two consecutive quarters of shrinking output; among these countries, output will fall, on an average, by about 1.5 percent from its peak. Croatia, Poland and Romania will experience technical recessions as well, with an average peak-to-trough output decline of more than 3 percent. Next year, Europe’s output and income will be nearly half a trillion euros lower as compared to the IMF’s pre-war forecasts—a stark illustration of the continent’s severe economic losses from the war.

And while inflation is projected to decline next year, it will stay significantly above central bank objectives, at about 6 percent and 12 percent, respectively, in advanced and emerging European economies.

Growth and inflation could both get worse than these already sobering forecasts. European policymakers have swiftly responded to the energy crisis and built adequate gas storage ahead of the heating season, but further disruptions to energy supplies could lead to more economic pain.

Our scenarios show that a complete shutoff of remaining Russian gas flows to Europe, combined with a cold winter, could result in shortages, rationing and gross domestic product losses of up to 3 percent in some central and eastern economies. On top of these, it could also result in yet another bout of inflation across the continent.

Even without any new energy supply disruptions, inflation could remain higher for longer. Most of the inflation surge so far is driven by high commodity prices—primarily energy, but also food, particularly in the Western Balkan countries. While these prices might remain elevated for some time, there is hope that they will stop increasing and thereby contribute to a steady decline in inflation throughout 2023.

Inflation risks

However, our latest Regional Economic Outlook shows that the pandemic and Russia’s war in Ukraine might have fundamentally altered the inflation process, with rising input and labor shortages contributing notably to the recent high-inflation episode. This suggests there may be less economic slack and, accordingly, more underlying inflationary pressures, than commonly thought across Europe.

These results highlight a risk to our forecasts and those by others that inflation will fall steadily next year. Other wild cards include a de-anchoring of medium-term inflation expectations, or a much sharper acceleration in wages that would trigger an adverse feedback loop between prices and wages.

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Tightening needed

In advanced economies, including in the euro area, tight monetary policy will likely be needed in 2023 unless activity and employment weaken more than expected, materially bringing down medium-term inflation prospects.

A tighter stance is generally warranted in most emerging European economies, where inflation expectations are not as well anchored, demand pressures are stronger and nominal wage growth is high—often in the double digits.

Finally, steady implementation of reforms that enhance productivity, relieve supply constraints in energy and labor markets, and expand economic capacity remain essential to raise growth and ease price pressures over the medium-term. This includes accelerating the implementation of the 800-billion-euro economic recovery package, the Next Generation EU programs.

Strength, coordination and solidarity pulled Europe out of the COVID-19 crisis. Once again, the task ahead is immense, but if European policymakers muster the spirit of the pandemic response, it can be accomplished.

BY SHANNUL MAWLONG

SOURCES:

https://www.imf.org/en/Blogs/Articles/2022/10/23/europe-must-address-a-toxic-mix-of-high-inflation-and-flagging-growth

https://www.economist.com/finance-and-economics/2023/12/12/europes-economy-is-in-a-bad-way-policymakers-need-to-react?utm_medium=cpc.adword.pd&utm_source=google&ppccampaignID=18151738051&ppcadID=&utm_campaign=a.22brand_pmax&utm_content=conversion.direct-response.anonymous&gad_source=1&gclid=Cj0KCQiAkeSsBhDUARIsAK3tiecATz5NVf8Qx52oZxN23a41RBXf5F50g4jSpncU8ka8Dk11PypgCMcaAjf-EALw_wcB&gclsrc=aw.ds

19 December 2023

2 Comments

Business, Open Source, Sharing economy

R(US-K)RAINE- DOOMSDAY OR MAYDAY FOR THE ECONOMY?

Reading Time: 4 minutes

Introduction:

The global economy’s gradual recovery from both the pandemic and Russia’s invasion of Ukraine remains on track. China’s reopened economy is rebounding strongly. Supply chain disruptions are unwinding, while dislocations to energy and food markets caused by the war are receding. Simultaneously, the massive and synchronized tightening of monetary policy by most central banks should start to bear fruit, with inflation moving back towards targets.

The global markets experienced immediate and significant impacts due to the Russia-Ukraine war. The surge in energy prices, triggered by the commencement of the conflict, directly affected both consumers and industries with energy-intensive operations. This impact was particularly pronounced for nations heavily reliant on energy imports from Russia. Furthermore, the escalation in energy prices exacerbated an already challenging inflation situation, partly stemming from the expansive fiscal and monetary measures implemented during the peak of the COVID-19 crisis.

Although markets have exhibited some recovery since the invasion of Ukraine on Feb. 24, 2022, considerable uncertainties persist. Looking ahead, we anticipate that inflation, economic growth, and the efficacy of monetary policy will play pivotal roles in shaping market dynamics. However, various fundamental factors will also come into play. A thorough understanding of the performance over the past year can equip investors with valuable insights to analyze potential risks and opportunities in 2023.

Equity markets displayed considerable volatility and delivered some unexpected outcomes in the aftermath of the Russian invasion, marking a turbulent year for global financial markets. The conflict triggered notable economic and investment consequences, including the departure of major multinational corporations from Russia and the removal of Russian companies from the MSCI Emerging Markets Index.

Contrary to initial concerns, European equity markets performed better than anticipated, concluding the one-year period with a 2% increase when measured in local currency. However, the strengthening of the U.S. dollar against major European currencies tempered the MSCI Europe Index’s USD returns to 3% for international investors. Despite this, there was considerable variability in returns among European countries. Nations with geographical proximity to the conflict zone and gas dependency on Russia, such as Hungary, Poland, and Germany, experienced significant negative returns. In contrast, the U.K. demonstrated resilience, finishing the year strongly despite grappling with challenges posed by energy-price inflation.

Concerns about the risk of an uncontrolled wage-price spiral do not seem justified at this juncture. Nominal wage gains are trailing behind price increases, indicating a decline in real wages. This is occurring despite robust labor demand, marked by numerous job vacancies, and a lingering labor supply shortage as some workers are yet to fully return to the workforce post-pandemic. While one might expect real wages to rise, the current scenario suggests otherwise. Paradoxically, corporate margins have expanded, driven by significantly higher prices but only modestly increased wages.

On a different note, the side effects of the sharp monetary policy tightening over the past year are starting to manifest in the financial sector, as previously cautioned. The prolonged period of subdued inflation and low interest rates had bred complacency in the financial sector regarding maturity and liquidity mismatches. The rapid tightening of monetary policy in the past year resulted in considerable losses on long-term fixed-income assets and elevated funding costs.

In a hypothetical scenario where banks, responding to rising funding costs, prudently reduce lending, there could be an additional 0.3 percent reduction in output this year. However, the financial system may face more significant tests, with nervous investors targeting institutions with excess leverage, credit risk, interest rate exposure, dependence on short-term funding, or located in jurisdictions with limited fiscal space. A sharp tightening of global financial conditions, a ‘risk-off’ event, could lead to substantial impacts on credit conditions and public finances, especially in emerging market and developing economies, causing large capital outflows, increased risk premia, a rush to safety in the U.S. dollar, and major declines in global activity.

In such a severe downside scenario, global growth could slow to 1 percent this year, with a 15 percent estimated probability of such an outcome. As we navigate this challenging phase with lackluster economic growth, heightened financial risks, and unresolved inflation concerns, policymakers need a steady hand and clear communication.

CONCLUSION

The repercussions of Russia’s war on Ukraine have reverberated not only within the affected nations but also across the region and the globe. This underscores the critical need for a robust global safety net and regional arrangements to cushion economies in the face of such shocks.

In a recent briefing in Washington, IMF Managing Director Kristalina Georgieva emphasized the reality of living in a more shock-prone world. She stressed the importance of collective strength in dealing with the shocks that may arise in the future, recognizing the interconnectedness of nations in addressing global challenges.

While the full extent of the consequences may take years to become clear, there are already evident signs that the war and the subsequent surge in costs for essential commodities will pose challenges for policymakers. Striking a delicate balance between containing inflation and supporting economic recovery from the pandemic will become more arduous for some countries. The increased costs of essential commodities can exacerbate inflationary pressures, complicating the task of policymakers navigating the post-pandemic economic landscape.

In this evolving scenario, the imperative for a global safety net and effective regional arrangements becomes even more pronounced. These mechanisms can provide crucial support to countries grappling with the economic fallout of unforeseen global shocks, emphasizing the interconnected and interdependent nature of today’s world.

BY-SHANNUL H MAWLONG

Source: chat gpt

https://www.imf.org/en/Blogs/Articles/2022/03/15/blog-how-war-in-ukraine-is-reverberating-across-worlds-regions-031522

https://www.imf.org/en/Blogs/Articles/2023/04/11/global-economic-recovery-endures-but-the-road-is-getting-rocky

https://www.imf.org/en/Blogs/Articles/2023/07/25/global-economy-on-track-but-not-yet-out-of-the-woods

https://www.msci.com/www/blog-posts/global-markets-one-year-after/03668219477

4 December 2023

THE DOLLAR-ECOMNOMY

19 November 2023

2 Comments

AI, Apps, Bez kategorii, Devices, Games, Open Source, Programming languages, Security, Sharing economy, Software

MACHINE LEARNING AND IT’S BLISS ON NETFLIX

Reading Time: 4 minutes

INTRODUCTION:

As the world’s leading Internet television network with over 160 million members in over 190 countries, our members enjoy hundreds of millions of hours of content per day, including original series, documentaries and feature films. Of course, all our all-time favourites are right on our hands, and that is where machine learning has taken it’s berth on the podium. This is where we will dive into Machine Learning.

Machine learning impacts many exciting areas throughout our company. Historically, personalization has been the most well-known area, where machine learning powers our recommendation algorithms. We’re also using machine learning to help shape our catalogue of movies and TV shows by learning characteristics that make content successful. Machine Learning also enables us by giving the freedom to optimize video and audio encoding, adaptive bitrate selection, and our in-house Content Delivery Network.

I believe that using machine learning as a whole can open up a lot of perspectives in our lives, where we need to push forward the state-of-the-art. This means coming up with new ideas and testing them out, be it new models and algorithms or improvements to existing ones.

Operating a large-scale recommendation system is a complex undertaking: it requires high availability and throughput, involves many services and teams, and the environment of the recommender system changes every second. In this we will introduce RecSysOps a set of best practices and lessons that we learned while operating large-scale recommendation systems at Netflix. These practices helped us to keep our system healthy:

1) reducing our firefighting time, 2) focusing on innovations and 3) building trust with our stakeholders.

RecSysOps has four key components: issue detection, issue prediction, issue diagnosis and issue resolution.

Within the four components of RecSysOps, issue detection is the most critical one because it triggers the rest of steps. Lacking a good issue detection setup is like driving a car with your eyes closed.

ALL YOUR FAVOURITE MOVIES AND TV SHOWS RIGHT HERE!

The very first step is to incorporate all the known best practices from related disciplines, as creating recommendation systems includes procedures like software engineering and machine learning, this includes all DevOps and MLOps practices such as unit testing, integration testing, continuous integration, checks on data volume and checks on model metrics.

The second step is to monitor the system end-to-end from your perspective. In a large-scale recommendation system there are many teams that often are involved and from the perspective of an ML team we have both upstream teams (who provide data) and downstream teams (who consume the model).

The third step for getting a comprehensive coverage is to understand your stakeholders’ concerns. The best way to increase the coverage of the issue detection component. In the context of our recommender systems, they have two major perspectives: our members and items.

Detecting production issues quickly is great but it is even better if we can predict those issues and fix them before they are in production. For example, proper cold-starting of an item (e.g. a new movie, show, or game) is important at Netflix because each item only launches once, just like Zara, after the demand is gone then a new product launches.

Once an issue is identified with either one of detection or prediction models, next phase is to find the root cause. The first step in this process is to reproduce the issue in isolation. The next step after reproducing the issue is to figure out if the issue is related to inputs of the ML model or the model itself. Once the root cause of an issue is identified, the next step is to fix the issue. This part is similar to typical software engineering: we can have a short-term hotfix or a long-term solution. Beyond fixing the issue another phase of issue resolution is improving RecSysOps itself. Finally, it is important to make RecSysOps as frictionless as possible. This makes the operations smooth and the system more reliable.

To conclude In this blog post I introduced RecSysOps with a set of best practices and lessons that we’ve learned at Netflix. I think these patterns are useful to consider for anyone operating a real-world recommendation system to keep it performing well and improve it over time. Overall, putting these aspects together has helped us significantly reduce issues, increased trust with our stakeholders, and allowed us to focus on innovation.

BY: SHANNUL H. MAWLONG

Sources: https://netflixtechblog.medium.com/recsysops-best-practices-for-operating-a-large-scale-recommender-system-95bbe195a841

https://research.netflix.com/research-area/machine-learning

References:

[1] Eric Breck, Shanqing Cai, Eric Nielsen, Michael Salib, and D. Sculley. 2017. The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction. In Proceedings of IEEE Big Data.Google Scholar

[2] Scott M Lundberg and Su-In Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett(Eds.). Curran Associates, Inc., 4765–4774.

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A blog on technology, run by Kozminski University students and supervised by NeRDS

Author Archives: 50401

THE EU RENAISSANCE :