Leveraging Machine Learning for Predicting Market movements using Historical Data

Abstract

Due to the complexity and volatility of financial markets, predicting stock market movements has always been a difficult endeavour. The purpose of this research study is to create a prediction model that uses the Random Forest Classifier algorithm to anticipate the upward trend of the Nifty50 index. As input characteristics, the model uses two prominent technical indicators, Simple Moving Average (SMA) and Exponential Moving Average (EMA) ratios. The study used historical data from the Nifty50 index, as well as SMA and EMA as inputs for training the Random Forest Classifier model. These indicators are carefully chosen to represent the underlying trends and patterns that may impact the Nifty50 index’s upward trajectory. The findings show that the suggested model predicts the Nifty50 index’s upward trend with a 66% accuracy rate. This shows that when paired with the SMA and EMA ratios, the Random Forest Classifier might give useful insights into market movements and prospective investment opportunities. Furthermore, the findings demonstrate the Random Forest Classifier algorithm’s potential as an excellent tool for anticipating stock market movements, notably the Nifty50 index’s upward march. Furthermore, the study shows the use of SMA and EMA ratios as input characteristics, demonstrating their capacity to capture key market movements. Investors, financial institutions, and market analysts can use the findings of this study to make educated judgments and maximize their investment strategy.

Keywords: Random Forest Classifier, Nifty50, upward trend, prediction, SMA, EMA, technical indicators, stock market.

Introduction

For investors, traders, and financial analysts looking to maximize returns on investments, the forecasting of stock market movements has been a topic of significant interest. Accurately predicting market fluctuations, especially the rising trend of stock indexes, can offer insightful information and business prospects. In this study, we offer a predictive model to forecast the increasing trend of the Nifty50 index, a well-known stock market indicator in India. This model makes use of the Random Forest Classifier algorithm.

The top 50 firms listed on the National Stock Exchange of India (NSE) are represented by the Nifty50 index, which acts as a barometer for the state of the market as a whole. However, because of the inherent complexity and uncertainties related to financial markets, forecasting the future direction of such an index is a difficult endeavour. (Antonacci, (April 2013). )

The technique used is the Random Forest Classifier, which can handle high-dimensional data and capture intricate correlations between variables. With the help of several decision trees combined, this ensemble learning technique produces reliable and precise forecasts. We can take use of the patterns and linkages available in the data to forecast future upward moves more accurately by training the model on past data from the Nifty50 index.

FIGURE1: NIFTY50 INDEX (SOURCE: GOOGLE FINANCE)

The main objectives of this study are to analyse a model’s capacity for properly forecasting the upward trend of the Nifty50 index and to evaluate the efficacy of the suggested strategy. Our goal is to demonstrate the great potential of applying machine learning as a trustworthy tool for market forecasting by obtaining a high level of accuracy. This easy model can also be strengthened by include other technical indicators that have been appropriately adjusted as input for greater accuracy. (Mehtab, December 1, 2019)

The results of this study may have significant implications for traders, financial institutions, and investors. Making educated investment decisions, optimizing portfolio management, and strengthening general market analysis tactics may all be facilitated by the ability to anticipate the rising trend of the Nifty50 index with some degree of reasonable accuracy. We detail the data collecting and preprocessing methods, talk about the experimental setting, and then give the findings and analysis in the following sections of the research. Finally, we conclude with a discussion of the implications of our findings and possible directions for more stock market forecasting research.

Methodology

We use a systematic approach and 25 years’ worth of historical data to construct and assess our prediction model, which is used to estimate the rising trend of the Nifty50 index. Daily OHLC prices are included in the dataset for study. To make the model’s training, testing, and validation easier, we separate the dataset into several subsets. To teach the model, the underlying patterns and correlations connected to the Nifty50 index, we initially trained it using the first 10 years of data (Coqueret). Then, we compare the forecasts with the actual observed values to assess the model’s success by forecasting the rising trend of the Nifty50 index over the ensuing 11 years. Google Finance provided the data necessary to train and test the prediction model. The necessary financial data needed for the investigation was accessed and retrieved using the Google Sheets API.

FIGURE2: Illustration of the concept of chronological generalization for machine learning

The model is then trained using data from the following 10 years, advancing the analysis, and allowing it to adjust to changing market conditions. The rising trend of the Nifty50 index is then forecasted using this trained model for the 12th year, and its accuracy is evaluated by contrasting the predicted values with the corresponding actual values. We use the Random Forest Classifier method throughout the training and testing phases because of its reliability in handling high-dimensional data and identifying complicated correlations between variables. Simple Moving Average (SMA) and Exponential Moving Average (EMA) ratios are two popular technical indicators that we include as components in our forecasting model. To help the model comprehend and recognize patterns and probable price reversals in stock prices, SMA and EMA are changed as ratios with respective to the close price. Here are the formulas for calculating SMA and EMA

1.Simple Moving Average (SMA):

    The SMA is a straightforward calculation that provides the average price of a security over a specific time period.

SMA = (Sum of closing prices over ‘n’ periods) / ‘n

Where,

• ‘n’ represents the number of periods (e.g., days, weeks, months) over which the average is calculated.
• The sum of closing prices is obtained by adding the closing prices of the security for ‘n’ periods.

    2.Exponential Moving Average (EMA):

    The EMA places more weight on recent prices compared to older prices, making it more responsive to recent market movements.

EMA = (Closing price – EMA(previous day)) * (2 / (n + 1)) + EMA(previous day)

Where: 

• ‘n’ represents the number of periods used in the EMA calculation.
• The initial EMA value is usually set to the first closing price available or the SMA for ‘n’ periods.

The chosen time periods, which reflect various intervals for analysing the historical data of the Nifty50 index, were 2, 5, 60, 250, and 1000. After investigation, we found that the SMA and EMA ratios’ time periods had a substantial impact on how well the model predicted the rising trend of the Nifty50 index. The model may catch more instantaneous price changes and react fast to short-term trends when using shorter time periods, such 2 and 5. These shorter-term indicators were more susceptible to noise and volatility, which could have resulted in forecasts that were less precise. While smoothing out short-term swings, larger time periods, such as 60, 250, and 1000, offered a wider view on the general trend. The Nifty50 index’s long-term patterns and probable reversals were better captured by these indicators. Combining various time periods for SMA and EMA ratios allowed for a thorough study of the market’s short- and long-term tendencies. By considering many viewpoints and reducing the influence of transient price movements, this helped to enhance the model’s predictions.

We used performance measures like accuracy, precision to measure how accurately our model predicts the future. These metrics offer numerical evaluations of how well the model recognized the increasing trend of the Nifty50 index. We aim to develop a robust prediction model using this technique to anticipate the increasing trend of the Nifty50 index. We can evaluate the model’s adaptability and determine its accuracy in forecasting future market movements thanks to the iterative process of training on historical data and assessing on succeeding years.

Random Forest Classifier

The Random Forest Classifier is an ensemble learning technique that blends many decision trees to provide predictions. A fraction of the training data and a random selection of features are used to build each decision tree in the random forest. The final forecast is then made by averaging the predictions of each individual tree (Mehtab, December 1, 2019).

Unlike the SMA or EMA, the Random Forest Classifier does not use a single mathematical formula, but rather combines several important ideas and methods. The Random Forest Classifier involves the following primary steps:

1. Building Decision Trees: A portion of the training data is used to build each decision tree in the random forest. Random sampling is used to choose the subset, often using bootstrapping methods. Individual trees are produced using the decision tree method, such as CART (Classification and Regression Trees), based on the chosen subset.
2. Random Feature Selection: Each decision tree is built with a random selection of features that are considered at each split. This procedure aids in introducing unpredictability and lessens association between trees, increasing the random forest’s variety and resilience.
3. Voting or Averaging Predictions: Following the construction of all the decision trees, they all offer predictions on unknown data points. The random forest employs majority voting for classification problems, where each tree’s forecast is considered and the class receiving the most votes becomes the final prediction. The random forest averages the expected values from all the trees while doing regression tasks.
4. Ensemble Learning: The predictions from each individual decision tree are combined to create the final prediction of the random forest classifier. The generalization skills of the model are enhanced, and overfitting is reduced thanks to the ensemble learning technique.

The Nifty50 index’s rising trend is predicted using the Random Forest Classifier algorithm as the main predictive model. To train the model and provide predictions, the algorithm is used to the dataset, which consists of historical data and other financial indicators.

The Random Forest Classifier was used in this study in the following ways, specifically:

1. Building the Model: A portion of the historical data from the Nifty50 index is used to train the Random Forest Classifier. Along with other pertinent financial indicators, this training data contains elements like SMA and EMA ratios. Multiple decision trees are built by the algorithm utilizing various subsets of the training data and randomly chosen characteristics.
2. Predicting the Upward Trend: After the model has been trained, it is utilized to forecast the Nifty50 index’s upward trend. The trained model is given unobserved data points, which represent times during which the true rising trend is unknown. The decision trees’ forecasts are combined by the random forest ensemble to get a final forecast for the rising trend.
3. Evaluating Accuracy: By contrasting the projected values with the actual observed values, the accuracy of the Random Forest Classifier in forecasting the rising trend of the Nifty50 index is assessed. The percentage of accurate forecasts for the rising trend is used to construct the accuracy measure.

The purpose of using the Random Forest Classifier algorithm in this research is to take advantage of its capacity to recognize complicated associations and manage large datasets. To provide more reliable and precise forecasts about the increasing trend of the Nifty50 index, the model makes use of the ensemble of decision trees.

The parameters used for this model are

• n_estimators: 200

This parameter specifies the number of decision trees to be created in the random forest. In this case, the random forest will consist of 200 decision trees.

• min_samples_split: 50

This parameter sets the minimum number of samples required to split an internal node during the construction of each decision tree in the forest. If the number of samples at a node is less than min_samples_split, the node will not be split further, and it will become a leaf node.

• random_state: 1

This parameter sets the random seed for reproducibility. By setting a specific value (in this case, 1), you ensure that the random forest classifier will produce the same results when trained and tested multiple times, given the same input data and settings.

Results and Discussion

Our predictive model began producing forecasts in October 2013 and trained itself to do so up to June 2023, in accordance with the adopted approach. The Nifty50 index had an upward trend throughout this ten-year period in around 53.96% of the trading sessions (2411). Our model correctly predicted 61.95% of the events that occurred on these positive days. A 66.1% accuracy rate was attained by the model for forecasts of the rising trend.

It is important to note that although though the model was only able to predict 61.95 percent of the days with an upward trend, the predictions it did make had a high accuracy rate of 66.1%.

Figure3: comparison of actual and prediction by the model

The results of this study are a compelling demonstration of the model’s enormous potential to provide extremely insightful and useful data, providing analysts and investors with important assistance in making solid and convincing decisions based on the indicated upward trajectories. It is important to keep in mind that although while this model achieves impressively high accuracy, its range is somewhat constrained by the rather little amount of data it presently uses. Therefore, it is necessary to improve and further develop this model.

One possible area for development to solve this constraint is to increase the number of technical indicators used by the model. It is possible to significantly improve the machine’s capacity for inference and meaningful conclusion-drawing by adding and adapting new technological indications. A news API must be used to integrate current market news for the model to reach its full potential. Real-time market data is added to the model’s knowledge base, enriching it while also ensuring that predictions and projections are based on the most recent data. The model’s forecasts can effectively enable market players to optimize their investment strategies through a thorough retraining process that incorporates these developments. Investors may be able to take advantage of opportunities, optimize profits, and move more quickly and confidently across the market’s changing terrain by relying on the forecasts made by the improved model.

In conclusion, the model’s shown skills provide a solid platform for further improvements in predictive analysis. It is anticipated that the model’s predictions would have a significant influence on market players when it has been improved, expanded the set of technical indicators, added real-time market data via a news API, and undergone extensive retraining. This improved approach has the potential to transform investment methods and pave the path for better success in the constantly changing financial landscape by opening previously undiscovered opportunities and facilitating strategic decision-making.

References

1. Coqueret, Guillaume, Persistence in Factor-Based Supervised Learning Models (November 1, 2021). Journal of Finance and Data Science
2. Antonacci, Gary, Absolute Momentum: A Simple Rule-Based Strategy and Universal Trend-Following Overlay (April 2013).
3. Burgess, Nicholas, Machine Earning – Algorithmic Trading Strategies for Superior Growth, Outperformance and Competitive Advantage (March 29, 2021). International Journal of Artificial Intelligence and Machine Learning.
4. Arnott, Robert D. and Harvey, Campbell R. and Markowitz, Harry, A Backtesting Protocol in the Era of Machine Learning (November 21, 2018)
5. A Mehtab, Sidra and Sen, Jaydip,,Robust Predictive Model for Stock Price Prediction Using Deep Learning and Natural Language Processing  Proceedings of the 2019 International Conference on Business Analytics and Intelligence (ICBAI 2)

Honorary Mention in Journal Volume 8 Issue 1,

Author – Sundhara Pandiyan R

TAPMI

INDIA’S BILATERAL ALLIANCES: A TRADING BOOM OR A CURRENCY DILEMMA

Well over the past few months, India has been seeding roots in various trades across the world. Be it strengthening old alliances or building new connections. From the UK-launched healthcare alliance to the enrichment of ties between Vietnam and the UAE, the list goes on. One thing is certain this time, is the backing of our beloved currency the Indian Rupee.

India’s policymakers have made significant changes in positioning the rupee across the global landscape. One most recent would be the memorandum of understanding signed between the UAE and India stating the usage of local currencies for cross-border transactions and another MoU was signed about the integration of the countries payment systems. India has also made notable progress in initiating trade in INR with its neighbors Nepal, Bhutan, Bangladesh and Sri Lanka and even the banks of Russia.

With the current turmoil in the global markets, the almighty US dollar certainly looks to still reign its supremacy in the global monetary system even though recent reports stating an upcoming recession could sweep in. With India’s strong financial prowess, it seems likely that the Indian Rupee can see new heights on the global pedestal, but will that prove to be a boom for the Indian economy? or are we digging our graves?

Historical perspective:

India’s involvement in bilateral alliances can be traced back to the period following its independence. In the early years, India’s foreign policy was focused on non-alignment and self-sufficiency, reflecting a desire to maintain a balanced stance in international affairs. However, with the advent of economic liberalization in the early 1990s, India began to shift its focus towards increased economic engagement and active participation in the global arena. This shift in policy led to a greater emphasis on bilateral alliances, as India sought to forge closer ties with key partners to promote its economic and strategic interests.

Since then, India has entered into a wide range of bilateral and regional trade agreements, including free trade agreements (FTAs), comprehensive economic cooperation agreements (CECAs), and preferential trade agreements (PTAs).

Comprehensive Economic Cooperation Agreement (CECA) with Singapore: This agreement was signed in 2005 and came into effect in 2009.

India-Japan Economic Partnership Agreement (JEEPA): This agreement was signed in 2007 and came into effect in 2011.

ASEAN-India Free Trade Area (AIFTA): This agreement was signed in 2003 and came into effect in 2009.

India has been working towards the internationalization of the rupee for several years. In 2013, the Reserve Bank of India (RBI) allowed foreign investors to hold rupee-denominated bonds, known as masala bonds. This made it easier for foreign investors to buy and sell such assets in India. In 2015, the RBI further liberalized the market by allowing foreign investors to trade in rupee-denominated derivatives. And in 2019, the Indian government began a process of liberalizing the exchange rate, making the rupee more attractive as a reserve currency.

The Internationalisation of the Indian Rupee:

For starters, the RBI has taken steps to allow for Special Vostro Rupee Accounts (SVRA’s) for settling payments in the Indian rupee. In simple terms, SVRAs are accounts that are held by a foreign bank in India. These allow for easier transactions to facilitate imports and exports, improve settlement time & enhanced transparency. Now since it has such a major influence on foreign trade. It also bears some weight in controlling currency fluctuations. Having established about 18 SVRA’s for Fiji, Germany, Guyana, Israel, Kenya, Malaysia, Mauritius, Myanmar, New Zealand, Oman, Russia, Seychelles, Singapore, Sri Lanka, Tanzania, Uganda, Russia and the United Kingdom.

Now some may ask, why does India want the rupee to go global, won’t that only strengthen the rupee which will be beneficial in the short run, however, can have adverse implications in the long run.

Why Internationalising is necessary?

The US is bound to speculation on recession, so much so that Michael Burry famous for “The Big Short” put up a bet of 1.6 Billion against the US market, taking a bearish stance. As the saying goes the US sneeze’s the globe catches a cold.  Well, internationalizing the rupee is creating a well-protective mask to withstand the flu. The US or to be more specific the USD makes up over 88% of the total volume traded in the world’s foreign currency markets, followed by the Euro, Japanese Yen, and British Pound. Only 1.7% of the total is in Indian rupees.

Such dependency on the USD will only hinder the growth of the rupee. Focusing on trade linkages can increase the bargaining power and reduce currency risk for a large portion of Indian businesses by keeping the volatility of currency in place. Such control can also muster a competitive advantage for local businesses.

Most recently, the Union Minister of Commerce and Industry, Consumer Affairs, Food and Public Distribution and Textiles launched the Foreign Trade Policy (FTP) 2023. As per the policy, the government aims to touch 2 Trillion in exports, Digitization and faster processing, Amnesty schemes and over 50% reduction in the threshold for recognition of star trade houses along with the restructuring of schemes. With all this in place, can the rupee even make a comeback? observing the trends, it’s quite surprising to see the state of the Indian rupee over the past few years.

Alarming Shifts in Currency:

To give a better idea of the currency shifts the below table depicts the trends over the past ten years. Although it may seem alarming that at such a sensitive stage when the global economy is set on the edge, tipping on either end of the spectrum.

In the past year, RBI Intervention will keep maximizing the efforts to keep the rupee in a tight range. Predictions for the upcoming three-month period spanned from 80.67/dollar to 83.80/dollar, a margin only slightly broader than the range of 80.88 to 82.95 observed thus far in the current year. The decline was also experienced by other Asian currencies, which also encountered difficulties due to a risk-averse sentiment triggered by the credit rating downgrade of the U.S. by the rating agency Fitch. Trade plays a crucial part in the global currency markets. Mentioned below are a few known trade partners, however, recent standings can pose a dilemma to the Indian Rupee.

India’s peculiar trading partners:

Now to understand where India stands on the global forefront,

India with the US:

Boosted by growing economic connections, the United States became India’s top trading partner in 2022-23. The trade between the two countries rose by 7.65% to $128.55 billion, up from $119.5 billion in 2021-22, while imports grew by about 16% to 50 billion. The major items of trade include petroleum, polished diamonds, pharmaceutical products, jewellery, light oils and petroleum, frozen shrimp etc.

However, Petroleum, raw diamonds, liquefied natural gas, gold, coal, garbage and scrap, almonds, etc. are major imports from the United States.

If India, wants to join the motion of de-dollarization, then this is a definitive factor that puts a hold on that fruitful vision.

Balance of trade refers to the difference between a country’s export value and import value for a given period. India although showing highly positive signs in growth and stability, still compares quite a slump to the likes of Giants like the US. One major observation is to understand the trade surplus, being a goods surplus or a service surplus. Both have different observations as a service surplus would boost the economy of the country using the services.

India with the UAE:

Over recent years, the middle east has instilled investments far and wide, and India stands tall in such matters. De-dollarization is particularly important because the UAE is India’s second-largest supplier of LPG and LNG and its fourth-largest supplier of crude oil. In the most recent news, a significant milestone was achieved as Adnoc and the Indian Oil Corporation conducted the inaugural crude oil transaction using the local currency settlement (LCS) system.

The Indian embassy in the UAE confirmed this pivotal moment, highlighting that the transaction involved the sale of approximately one million barrels of crude oil. Notably, Indian rupees and dirhams were utilized in this groundbreaking transaction. Its effect is still to be witnessed in the currency markets.

To put it into perspective, the above draw out a map of the year preceding. Stating the growth and influence UAE has grown over the years. Although the UAE may seem to be a strategic partner dealing in the local currency, its ties with China-based imports can also have a substantial effect based on the comparison of the rupee to the Chinese Yuan.

This can be observed with the trade that took place with Russia aligning the same site of potential events can take place depending on the reserves and trade efficiency which can be better understood by taking a look at Prof Vijay Victor’s article –“ Rupee must catch up with Yuan before replacing $- https://www.deccanherald.com/opinion/rupee-must-catch-up-with-yuan-before-replacing-2646279

Another observation is the country that ranks third in India’s exports mentioned – the Netherlands.

India with the Netherlands:

A known fact, the Netherlands emerged as India’s third-largest export destination. The trade surplus with the Dutch has also shown an uptrend to 13 billion from 8 billion. Due to its efficient port & hub connectivity due to which an increase in the shipping of goods like petroleum products, electronics, chemicals, and aluminium products. Everything sounds great until news broke out yesterday that

In the second quarter of 2023, the economy in the Netherlands shrank by -0.3%, showing a decline from the previous three months. This has led to what’s called a “technical recession,” which means the country’s economy is struggling due to two consecutive contractions in a row. The main reasons for this downturn were less spending within the country and reduced trade with other nations.

Now although, the Netherlands is a major export destination. The same cannot be said from the perspective of the Netherlands whose import composition does not share a major composition with India. So who is at a loss here, if the Dutch chose to shun down on imports or increase exports to recover?

India with China:

And lastly a crucial player, competitor and a friendly foe. Who has been India’s top trading partner but has also been the cause of the widening of the trade deficit? China has been a fierce competitor not only on the manufacturing and technology forefront from beating Tesla in EV sales to being the world’s factory.

China has not withheld its intentions to internationalize the Yuan as well. As it also seeks to de-throne the US dollar. One major entity that creates a mutual dependency is Russia after being sanctioned due to the War have been settling more trade in Yuan which has also become Russia’s reserve currency.

However, India is still behind in the race it holds a better chance with the prospect of a Global democratic image, where China’s democratic behaviour and ties in the global supply chain during the pandemic have raised eyebrows across the globe. The Chinese have continued the effort being a country that has a high level of resources and investments in a large number of countries including the US.

If we compare the currency trends, we can see that both nations still don’t show any substantial promise to be the dominant currency of the globe yet. The parallel phases don’t seem to coincide as higher volatility can be noticed in the INR changes that take place. For India, upcoming corrections are expected where measures will be taken up to control the rupee from further decline, but only time will tell how global inflation can pan out across the globe.

In Conclusion:

With recent events happening around the globe, all eyes stay on the US Fed’s next move. India stands in a strong position with the advent of UPI technology being recognised and utilized for which mass users can be reached. India should act quickly in seizing this opportunity to improve and expand more Vostro accounts, indulge in policy making that brings in foreign inflows and focus on reducing the current trade deficit. All this is easier said than done, as the government has implemented steps to venture into self-sufficient schemes and initiatives.

When it comes to the US, they should understand that India’s interests sometimes differ. On the economy, India disagrees with the U.S. on trade matters, like e-commerce and duties on electronic stuff. On security, India didn’t criticize Russia for Ukraine. While the U.S. likes working with similar countries, India’s changing democracy is a concern. If the U.S. and India don’t improve their economic and security ties, it’s risky. But, focusing on each separately has limits. India is open to trading more if it gets benefits. Connecting trade and technology can lead to better teamwork and a stronger bond between India and the U.S., based on rules and actions, not just talk.

India’s exports in July 2023 were around $59.43 billion, even though there were challenges from around the world. The difference between what we sell and buy globally got better by 45.22% in July 2023, going from $15.24 billion to $8.35 billion, which is positive news. Also, the difference in goods we trade (merchandise) improved by 18.74%, being $20.67 billion in July 2023 compared to $25.44 billion in July 2022.

I didn’t ponder upon the adverse effects of a strengthening Rupee as from the current standpoint it is highly unlikely to reduce to such an extent to have substantial effects on the economy. A more call for concern is the increase that is taking place even after such remedies, schemes and plans have been put into place. The RBI has kept a watchful eye to analyse the situation and act accordingly, but it requires high priority.

But the aspiration of establishing the Rupee as a global currency remains distant. Dealing with global consequences like recession, trade barriers, insufficient inflows and excess imports can hurt the economy. Many countries within the EU have also made efforts to take over the dollar, however poor policy and bickering between nations led to democratic instability which further kept the rise of the Euro to the lands of the European nations. Many lessons can be learnt, as India is slowly gaining access to the global stage one step at a time, for instance, receiving a seat in the “Economic and Social Council” of the UN for the term 2023-25. This puts the opinions of our nation on a global standpoint and can prove to be a pedestal for the future of the economy. As we mark our 77th year of independence, we seek to grow and embrace gradual progress and a determination to rise to build international partnerships and address each challenge head-on.

References:

https://www.deccanherald.com/opinion/rupee-must-catch-up-with-yuan-before-replacing-2646279

https://www.xe.com/currencycharts/?from=USD&to=CNY

https://www.businesstoday.in/latest/in-focus/story/us-emerges-as-indias-biggest-trading-partner-in-fy23-at-12855-billion-377549-2023-04-16

https://www.drishtiias.com/daily-updates/daily-news-editorials/rise-of-the-indian-rupee

https://www.npr.org/2023/07/24/1189268260/economy-recession-inflation-jobs-interest-rates

https://pib.gov.in/PressReleaseIframePage.aspx?PRID=1948550

~ Aaron Cardozo,

Editor, TJEF

Tesla’s India Entry: Navigating the Apple Model and Chinese Suppliers

The talks between Tesla and India have been ongoing for several weeks, with the objective of establishing a factory capable of producing a $24,000 electric car for the Indian market and potential exports. However, the delicate state of India-China relations adds a layer of complexity to Tesla’s plans, as it could impact the company’s efforts to collaborate with Chinese suppliers. As Tesla (TSLA.O) explores the possibility of establishing a manufacturing plant in India, government officials have proposed a strategic approach inspired by Apple’s success. The officials have advised Tesla to seek partnerships with local Indian firms while also considering the involvement of Chinese suppliers, according to reliable sources familiar with the ongoing discussions.

Elon Musk, the visionary founder of Tesla, is eager to expand the company’s presence beyond its largest foreign market, China, where the process of obtaining regulatory approvals for expansion has proven to be slow and challenging. Tesla’s potential entry into the Indian market holds immense importance, with the potential to bring about transformative changes in India’s automotive and clean energy sectors. As a pioneer in the electric vehicle industry, Tesla’s presence could accelerate the adoption of EVs in the country, spurring awareness and demand for sustainable mobility solutions.

One of the most significant impacts of Tesla’s entry could be the development of a robust charging infrastructure in India. Tesla’s commitment to building charging networks could address a key barrier to EV adoption, facilitating the transition toward cleaner transportation.

Tesla’s Entry in India

India’s burgeoning economy and expanding middle class have sparked a surge in demand for luxury goods, including electric vehicles, making it an attractive market for the forward-thinking company. According to the International Energy Agency, India is projected to become the world’s third-largest market for electric vehicles by 2030, a fact that has not gone unnoticed by Tesla’s keen eye for emerging opportunities.

Adding to the allure are India’s supportive government policies for electric vehicles. The Indian government has set ambitious goals for EV adoption and has gone the extra mile by offering incentives to buyers of electric cars. The availability of subsidies, such as up to $2,500 for an electric vehicle purchase, further sweetens the deal for Tesla and aligns with the company’s vision of sustainable mobility.

Tesla also sees the strength of India’s manufacturing sector as a strategic advantage. With a robust manufacturing base and an abundant pool of skilled workers, India provides a platform for the company to potentially reduce production costs. Additionally, the country houses numerous auto parts suppliers, creating a conducive ecosystem for Tesla to thrive in.

The Indian workforce itself is a significant asset, with a large number of highly skilled engineers and technicians readily available. This bodes well for Tesla’s plans to set up and operate a manufacturing plant within the country, further solidifying its commitment to the Indian market.

One of the most compelling reasons behind Tesla’s interest in India is its vast population. As the second most populous country in the world, India offers an immense potential market for Tesla’s electric cars. The company’s vision of widespread electric mobility aligns well with India’s growing need for sustainable transportation solutions.

The chart shows that Tesla has been expanding its global presence at a steady pace over the years. The company entered the Indian market in 2022, and it is now present in 13 countries.

Nevertheless, Tesla acknowledges the challenges that lie ahead. Doing business in India can be costly, and the country’s infrastructure for electric vehicles is still developing. Moreover, certain government policies may present obstacles to foreign companies. However, Tesla’s history of overcoming challenges and its substantial resources position the company well to navigate these hurdles successfully.

Tesla’s foray into the Indian market represents a significant step in the country’s transition towards cleaner and greener transportation. As India strives to address its environmental concerns and reduce its carbon footprint, Tesla’s electric vehicles hold great promise. With its cutting-edge technology and commitment to sustainability, Tesla has the potential to make a lasting impact on India’s automotive landscape.

The Apple Model: A Case Study

Indians who opt for iPhones are more likely to be “switchers” due to the dominant presence of Android in the Indian smartphone market, spearheaded by brands like Samsung and various Chinese manufacturers. With Android commanding over 95% of the market share, consumers in India have been accustomed to a wide range of affordable Android devices.

Price plays a crucial role in influencing consumer behavior. In India, the majority of smartphones are priced well below the least-expensive Apple iPhone. Industry analyst IDC reported that the average selling price of a smartphone in India is $224, a figure that increased by 18% in 2022. In contrast, Apple’s entry-level phone, the iPhone SE, retails for $429 in the U.S. The price-conscious Indian market leans towards more cost-effective Android options that offer competitive features and affordability.

To address the challenges posed by relying heavily on manufacturing in China, Apple is embarking on a massive project to build its products in India. This endeavor necessitates collaboration not only from Apple but also from its manufacturing partners and local and national governments in India.

Currently, most iPhones are assembled in China, which has led to issues over the past five years. These problems range from trade tensions and potential tariffs during the Trump administration to recent supply chain disruptions caused by Covid and China’s Covid-related policies, leading to sales shortfalls for Apple.

As part of its strategy to diversify production, Apple’s primary manufacturing partner, Foxconn, is also expanding its operations in India. The company is reportedly investing $700 million in building a plant for iPhone parts in Bangalore, signaling Apple’s commitment to strengthening its manufacturing base in the country. The Indian government, akin to its Chinese counterparts, is eager to embrace Apple as a symbol to attract other high-tech firms for manufacturing and development in India. Over the past two decades, China has successfully worked at various levels of government to establish massive factories, such as Foxconn’s renowned “iPhone City” in Zhengzhou. The Indian government’s efforts mirror this approach, striving to create a favorable environment for high-tech manufacturing investments, with Apple at the forefront.

Lessons Tesla can learn

Tesla’s potential plans to bring its cheaper Model 3 to India for around Rs 20 lakh has raised discussions about the feasibility of the company’s entry into the Indian market. The Indian government’s stance on not providing duty waivers or concessions for individual companies, including Tesla, echoes its approach with Apple in the past. However, drawing lessons from Apple’s experience in India, Tesla can adopt a proactive strategy to align its business with the government’s priorities and build a win-win model for both parties. India’s consistent policy has been to create an industry-level framework rather than offering specific concessions to individual companies. This approach ensures a level playing field and avoids preferential treatment to particular entities. Apple’s requests for import duty reductions were met with a refusal by the Indian government, which reiterated its focus on industry-wide policies in 2017.

Apple’s Success Story

Despite facing obstacles, Apple did not abandon its plans for the Indian market. Instead, the tech giant assembled an India team, comprising local experts to engage with the government and industry associations. The company embraced the government’s priorities, particularly enhancing manufacturing, supporting the ‘Make in India’ initiative and generating employment opportunities. Apple’s approach in India demonstrated a willingness to collaborate with the government and other stakeholders to build a mutually beneficial model. The company assured the government that it would not resort to predatory pricing that could adversely affect local retailers. It also accommodated the demands of competing players to foster a conducive environment for all participants.

Key Components of Apple’s Strategy

Promoting Local Manufacturing

By partnering with Taiwanese contract manufacturers, such as Foxconn, Wistron, and Pegatron, Apple leveraged the government’s Production-Linked Incentive (PLI) scheme for smartphones. This allowed the company to produce and even export phones from India, furthering its commitment to domestic manufacturing. India’s preliminary clearances to some of Apple’s Chinese suppliers to form joint ventures with Indian companies reflect the government’s cautious approach. The joint venture route ensures that Chinese component makers enter India only in partnership with Indian entities, offering greater control and regulatory oversight.

Regulations on Automobile Industry

In response to the ever-evolving regulatory landscape, automotive companies are reevaluating their business models to meet fuel efficiency and emissions standards. With a growing emphasis on reducing greenhouse gas emissions and curbing fossil fuel dependence, manufacturers are investing in research and development to create more efficient engines, lightweight materials, and aerodynamic designs. The transition to electric vehicles and hybrid technologies has been accelerated as regulations encourage the adoption of zero-emission vehicles, with companies like Tesla leading the charge in the electric mobility market.

The stringent emissions laws have also influenced automotive business models. Vehicle manufacturers must meet strict standards for tailpipe emissions, which have led to increased engineering and manufacturing costs due to the introduction of catalytic converters and other emissions control devices. Despite the additional costs, companies can leverage their focus on producing cleaner and more environmentally friendly vehicles to differentiate themselves and cater to the growing market of environmentally conscious consumers.

Moreover, regulations have affected the way cars are sold, with an increased focus on transparency and sustainability. Consumer protection laws and environmental standards have raised awareness among consumers about their environmental impact, leading to a demand for eco-friendly products. Automotive businesses have had to adapt their models to meet these changing customer expectations, emphasizing sustainability and providing transparent information about vehicle emissions and environmental practices.

Regulatory Challenges for Tesla

Specific regulations impacting Tesla’s operations in India, explore the company’s efforts to align with local policies and discuss the opportunities that lie ahead for Tesla in one of the world’s most dynamic economies.

Challenges

1. Import Duties and Tariffs: As a foreign automaker, Tesla faces the hurdle of import duties and tariffs on its vehicles and components if it chooses to import completely built units (CBUs). These costs could significantly impact the final price of Tesla’s vehicles for Indian consumers, potentially affecting their affordability and demand.
2. Local Sourcing Norms: To avail of government incentives and schemes, Tesla must meet certain local sourcing norms for components and manufacturing. Complying with these requirements poses a challenge for Tesla, as its supply chain and manufacturing operations are predominantly located outside India.
3. EV Policies and Emission Standards: India has implemented stringent emission standards for vehicles to combat pollution and improve air quality. Tesla must adhere to these standards while also aligning with India’s EV policies and incentives aimed at promoting clean energy adoption.

Tesla’s Strategic Approach

1. Establishment of Local Manufacturing: To address import duty challenges and local sourcing norms, Tesla has indicated its commitment to establishing local manufacturing operations in India. The company’s proposal to introduce its more affordable Model 3 in India reflects Tesla’s intent to align with the country’s EV policies and make its products accessible to a wider Indian consumer base.
2. Engaging with the Government: Recognizing the importance of collaboration, Tesla has actively engaged in discussions with the Indian government. By understanding and aligning with local regulations and policies, Tesla aims to foster a conducive environment for its operations while supporting India’s objectives of cleaner transportation and boosting domestic manufacturing.
3. Focus on Sustainability: Tesla’s core mission revolves around sustainable mobility and reducing global carbon emissions. This vision aligns seamlessly with India’s ambitious sustainability goals, making Tesla an attractive partner for the government’s green initiatives.

Opportunities

1. Growing EV Market: India’s EV market is poised for significant growth as the country prioritizes sustainability and renewable energy solutions. By entering the Indian market, Tesla can tap into the vast potential for electric vehicles, where demand is projected to surge in the coming years.
2. Fostering Economic Growth: Tesla’s local manufacturing plans can contribute to India’s economic growth by creating job opportunities, developing a skilled workforce, and attracting investments in the automotive sector.
3. Strengthening India’s EV Ecosystem: Tesla’s entry into India can serve as a catalyst for the development of a robust EV ecosystem. It can spur investments in charging infrastructure, battery manufacturing, and renewable energy projects, further propelling the country’s clean energy transition.

 Expanding Access To India’s Charging Infrastructure

In India, electric vehicles (EVs) are gaining popularity due to their cleaner and more sustainable nature. However, a fundamental challenge hindering their widespread adoption is the lack of charging infrastructure. A robust charging network is essential to promote the mass acceptance of EVs in the country.

Charging infrastructure plays a critical role in enabling the transition from internal combustion engine vehicles to EVs. It ensures that EV owners have convenient access to charging facilities, allowing them to travel longer distances without range anxiety. With the growth of EVs, the charging ecosystem has seen substantial efforts to expand, resulting in a fivefold increase in public and private charging stations.

The importance of charging stations goes beyond supporting EV growth. Installing and maintaining charging infrastructure creates job opportunities and contributes to economic growth. Furthermore, by reducing the use of fossil fuels and energy consumption, charging stations help decrease overall expenses and the carbon footprint, benefiting the environment.

Public charging stations are vital for encouraging consumers to adopt EVs as a practical transportation option. Having readily available charging options reduces the total ownership cost of EVs and eliminates the need for customers to invest in expensive charging stations for their homes.

Collaborations

Tesla has taken significant steps to address the charging infrastructure challenge in India through collaborations with prominent companies in the energy and electric vehicle charging sectors. These partnerships are aimed at establishing a comprehensive network of charging solutions across the country, making electric vehicle adoption more feasible and convenient for Indian consumers.

One of Tesla’s key collaborations is with Tata Power, one of India’s largest power companies. Together, they have embarked on an ambitious plan to set up fast-charging stations throughout India. The first of these charging stations was inaugurated in Mumbai in 2022, marking the beginning of a network that will enhance the accessibility of charging facilities for Tesla owners and other electric vehicle users across the nation.

In addition to Tata Power, Tesla has also teamed up with EEBL, a joint venture between Energy Efficiency Services Limited (EESL) and Convergence Energy Services Limited (CESL). Through this collaboration, Tesla is working towards the establishment of a network of slow-charging stations across India. The first of these stations was inaugurated in Delhi in 2022, extending the reach of charging infrastructure to various regions and ensuring convenience for EV owners in their daily charging needs.

Furthermore, Tesla has partnered with ChargeGrid, a prominent electric vehicle charging network in India, to provide Tesla owners with seamless access to ChargeGrid’s extensive charging network. With over 1,000 charging stations located strategically across the country, ChargeGrid’s network significantly contributes to the ease of charging for Tesla users and supports the overall growth of the electric vehicle ecosystem in India.

These collaborations underline Tesla’s commitment to overcoming the charging infrastructure hurdle in India and promoting electric vehicle adoption on a large scale.

Relying on Chinese Suppliers

Tesla’s dependence on Chinese suppliers has been a double-edged sword, offering advantages in terms of access to a skilled workforce, low labor costs, and government support, while also posing concerns about supply chain security, intellectual property theft, and potential political interference. Recognizing the importance of managing these risks, Tesla has been proactive in addressing the issues associated with its reliance on Chinese suppliers.

One of the primary benefits of working with established Chinese manufacturers has been access to a vast and skilled workforce. China’s reputation as a manufacturing powerhouse has allowed Tesla to tap into a pool of talented workers with expertise in automotive production. This, in turn, has facilitated efficient manufacturing processes and contributed to keeping costs down. Tesla’s ability to leverage China’s skilled labor force has been instrumental in delivering competitive pricing to its customers and maintaining a strong market presence.

Moreover, China’s low labor costs have played a significant role in Tesla’s cost management strategy. By manufacturing certain components in China, Tesla has been able to capitalize on the cost advantages and pass on savings to its customers through competitive pricing for its electric vehicles. Lower production costs have played a crucial role in making Tesla’s vehicles more accessible to a broader segment of consumers, fostering higher adoption rates and expanding its customer base.

Almost all parts are “MADE IN CHINA”

When dismantling a Tesla car, four core components stand out: the chassis, cockpit central control, body sheet metal interior, and charging system. Remarkably, many of these crucial components come from Chinese suppliers. The battery and charging system relies on companies like Ganfeng Lithium, Tianqi Lithium, and Shanshan. The electric drive system utilizes modules from Xuri and motors from Zhongke Sanhuan and Jingda, all Chinese companies. In the central control system, the large screen comes from BOE, Jingrui, and Tianhua Ultra Clean, predominantly Chinese suppliers. Even Tesla’s automatic driving features source the visual sensor from Lianchuang Electronics and the high-precision map from NavInfo, both Chinese companies. This significant involvement of Chinese suppliers highlights their crucial role in Tesla’s supply chain and reflects China’s dominance in the electric vehicle technology sector.

However, Tesla’s reliance on Chinese suppliers has not come without risks. The foremost concern lies in supply chain security and the potential for China to exert control over Tesla’s supply chain. Given the sensitive nature of electric vehicle technology and Tesla’s intellectual property, there is a valid fear of intellectual property theft or unauthorized access to proprietary information. To mitigate this risk, Tesla has taken significant steps, such as diversifying its supplier base and investing in battery production capacity. By reducing its dependence on specific Chinese suppliers, Tesla aims to safeguard its sensitive technology and maintain a level of autonomy over its supply chain.

Moreover, political interference remains a concern, as China has been known to impose regulatory and market access barriers on foreign companies for political reasons. Tesla’s efforts to work closely with the Chinese government and develop a cooperative framework demonstrate the company’s commitment to fostering a stable and mutually beneficial relationship. Establishing clear channels of communication and ensuring adherence to international trade norms can help safeguard Tesla’s operations from undue political influence.

Strategies for scaling Operations

Tesla’s roadmap for sustainable growth in India encompasses short-term and long-term goals to establish a strong presence in the country’s electric vehicle (EV) market. In the short term, Tesla aims to set up sales and service centers, build brand awareness, and target early adopters interested in premium electric vehicles. Simultaneously, the company will focus on scaling operations and expanding market reach in the long term. Strategies include partnering with local companies, investing in research and development for the Indian market, and expanding the sales and service network. Tesla’s entry into India could significantly impact the EV industry by raising awareness among consumers, driving competition, and accelerating the adoption of sustainable transportation solutions. By embracing local collaborations and innovating for the Indian market, Tesla can pave the way for a greener and more electrified future in India.

Conclusion

In my opinion, Tesla’s entry into the Indian market holds great potential due to the country’s growing interest in electric vehicles and Tesla’s reputation for high-quality and high-performance products. However, Tesla will face challenges such as the relatively small EV market and the lack of charging infrastructure. To achieve sustainable growth, Tesla should focus on targeting early adopters, partner with local companies, and invest in research and development tailored to the Indian market. Expanding the sales and service network and collaborating with the Indian government to develop supportive policies will further enhance Tesla’s success in India.

-Senior TJEF Editor

-Bhagavath

References

https://www.autocarpro.in/news/tesla-slated-to-meet-indian-officials-this-week-report-115104

https://www.linkedin.com/pulse/navigating-impact-regulations-automotive-sector-chaiz/

https://www.businesstoday.in/technology/news/story/govt-suggests-apple-like-model-for-teslas-india-factory-report-392359-2023-08-02

https://www.linkedin.com/pulse/navigating-impact-regulations-automotive-sector-chaiz/

Use of Blockchain and Crypto in BFSI

Blockchain technology and cryptocurrencies have become popular search terms over the last few years across a variety of industries. The new idea has received a mixed reception from governments and society, with many wealthy nations either outlawing it or attempting to stop its spread. But the question remains: Would the system that has been so meticulously designed over the past few centuries be destroyed by the decentralization that technology brings?

What exactly is blockchain, and how does it relate to cryptocurrencies?

A blockchain is a distributed database or ledger shared across the nodes of a computer network, according to the textbook description of the technology. Any industry can benefit from using blockchains to make data immutable, which is the technical phrase for not being able to be changed.

Let’s use an example to better grasp this. Consider an Excel spreadsheet. It is utilized by us to enter and modify info. In Excel, a cell is a block into which we may enter any amount of data. After entering the data, it is encrypted, resulting in a hash, which is a hexadecimal number. The block’s title is contained in this hash. Every time new information was desired to be added, a new block with its hash was generated and attached to the previous block.

One could completely secure data using this method because the timestamp of the data could not be altered. If such a negative outcome occurred, it would have to coincide with the earlier building pieces that revealed the deception. The Bitcoin blockchain operates in this manner. The blockchain of each cryptocurrency functions differently. For instance, a transaction is finished on the Bitcoin blockchain after a block is closed. The block is not regarded as confirmed until five other blocks have been verified. The network takes a little under 10 minutes per block on average to complete confirmation, which takes around an hour. As opposed to this, the Ethereum blockchain selects one validator at random from among all users who have staked ether to validate blocks, which are then confirmed by the network. In comparison to the Bitcoin process, this is far faster and less energy-intensive.

Furthermore, because the database’s data is dispersed among several devices, including PCs and cell phones, it is impossible to change the data through a single node because the database would reject the effort. Because anybody can observe the technology using their node or blockchain explorers, it is also transparent.

 So, in a nutshell, what is cryptocurrency? Cryptocurrency is essentially a virtual currency with no physical equivalent. It is produced by crypto mining, a process that calls for powerful processing hardware to solve challenging mathematical puzzles. The currency is transacted on a ledger called the blockchain.

Why is money so difficult for people to understand and troublesome with a concept like this? The currency is worthless at its core. Cryptocurrency does not have an underlying, such as gold or cash that is a promissory note. These cryptocurrencies’ prices are turbulent and stationary for extended periods because they only respond to irregular human behavior.

However, since the BFSI business is rife with instances, banks, and financial services use blockchain and cryptocurrency for a variety of reasons.

Quorum from JP Morgan.

In 2016, JPMC developed Quorum as an offshoot of the Ethereum blockchain. Quorum is similar to Ethereum but includes more features that make it appropriate for business use. The attributes are

Permission: Users of Quorum can design protected networks that are permission-based and comprise just the nodes that have been granted permission to join.

Data Privacy: While all transaction data on Ethereum is accessible to the public, Quorum enables you to control who can access and view data. The data can be made available to the general public, just the nodes involved in the private network, or only a certain subset of those nodes.

Higher average transaction speed: Depending on the consensus mechanism selected and the network’s complexity, most Quorum users typically experience higher average transaction speeds compared to Ethereum users. Quorum can handle a few hundred transactions per second, but Ethereum can only handle roughly 15 per second.

JPMC launched the JPM token before ConsenSys acquired Quorum to simplify value transfers between businesses. JPM was a stable currency because it was tied to the US Dollar. JPM was only accessible to businesses with USD deposits in JPMC and was only used for B2B transactions, not by the general public. Since ConsenSys acquired Quorum, it has drawn a lot of interest from investors, including Microsoft, HSBC, ING Group, LVMH, and Novartis, to mention a few.

R3 Corda

R3 Corda Corda was developed by R3, a corporation that David E. Rutter, Todd McDonald, and Jesse Edwards formed. A group of 200 banks, financial services providers, and technology firms created it as an open-source initiative. This Distributed Ledger Technology (DLT) was created with financial services in mind.

Because R3 Corda employs a “shared ledger” method to DLT, no single user is required to connect to a single database. The ledger is instead duplicated by each user, who updates it with the most recent transactions. Sensitive information is kept private and confidential by only sharing it with the people engaged in a transaction. It is then added to each user’s ledger after the transaction has been validated and approved by all parties involved.

This strategy provides several benefits over other DLT platforms, including the blockchain of Bitcoin:

The amount of data that needs to be processed and stored is greatly decreased.

It greatly increases the difficulty for hostile actors to alter or remove data.

It makes it possible to manage who has access to what data in a much more detailed manner.

R3 Additionally, “smart contracts” are used by Corda to automate some portions of transactions. A piece of code known as a “smart contract” specifies the terms of a contract between two parties. The code is automatically carried out once the contract’s conditions have been accepted by all parties. In other words, automated processes can take the place of manual ones such as paperwork and signatures.

From straightforward operations like moving money from one account to another to more complicated ones like issuing bonds or syndicated loans, smart contracts can be used for a wide range of transactions.

Corda did not previously have a platform-wide exclusive cryptocurrency coin of its own because it is a private blockchain. Companies building private networks using Corda have always had the option of establishing their transaction tokens or coins.

Developers can generate tokens or coins that adhere to certain criteria by using the Token SDK specification provided by Corda.

The Corda network’s owner R3, and the hybrid public-private blockchain platform XinFin, signed a partnership agreement in March 2021. According to the agreement, the cryptocurrency XDC from XinFin was designated as the main settlement coin on Corda. Naturally, businesses can continue to make and use their coinage if they wish.

The agreement has made it possible for Corda-based private networks to communicate with other blockchain platforms as XDC is an Ethereum-compatible coin.

The first bank in India to use Blockchain for foreign remittances was ICICI Bank. However, it immediately stopped using that arm as a result of RBI’s position on cryptocurrency. Meanwhile, Axis Bank employs Ripple technology for the same purpose through the use of XRP. This type of remittance is preferable because it does not incur the commission fees associated with overseas transfers.

As a result, even though the fundamental idea behind cryptography still needs to be developed further, it cannot be disregarded. When considered on a larger scale, the use cases for blockchain and cryptocurrencies are enormous.

Capital Market

Issuance

Trading and sales

Settlement and clearing

Post-trade infrastructure and services

Asset maintenance

Custody

Asset Management

Fundraising 

Asset management transfer agency

Administration of funds

Payments and Remittances

Locally made retail payments

Settlement of wholesale domestic and foreign securities

International payments

Stablecoins tokenized fiat and cryptocurrencies

Trade Finance

Bills of lading and letters of credit.

Financing arrangements

Insurance

Processing and payment of claims

Specified contracts

Markets for reinsurance

Hence just riding on the coattails of Reserve Banks and the opinions of other institutions would not be advisable in the case of this innovation. While cryptocurrency may not be a wise choice for trading and investment purposes it makes a great tool for various financial institutions for activities other than the aforementioned.

References:

Adam Hayes, “Blockchain Facts: What is it, How it works and how it can be used”, Investopedia, April 23, 2023, https://www.investopedia.com/terms/b/blockchain.asp

Kaspersky, “What is cryptocurrency and how does it work”, https://www.kaspersky.com/resource-center/definitions/what-is-cryptocurrency

Ripple, “Ripple-powered Instant Payment Services Now Live with Axis Bank, RAKBANK, and Standard Chartered”, Nov 22, 2017, https://ripple.com/insights/ripple-powered-instant-payment-services-now-live-axis-bank-rakbank-standard-chartered/

–Senior TJEF Editor

-Denver Roberts

What if the USA fails to pay its debts: The Global Outcome.

The United States is swiftly approaching a critical point known as the “X-date,” where the government may no longer be able to meet its financial obligations. Recent assessments by the Congressional Budget Office and the U.S. Department of the Treasury have emphasized the potential consequences of reaching the debt ceiling. Historical evidence indicates that even nearing this threshold could cause significant disruptions in financial markets, negatively impacting households and businesses. Present real-time data reveals that market participants are already factoring in the risk of political brinkmanship associated with a potential federal government default, leading to increased risk premiums.

A breach of the U.S. debt ceiling would have severe ramifications for the national economy. Analysis conducted by the Council of Economic Advisers (CEA) and independent researchers highlights the detrimental effects of a U.S. government default on its obligations, whether to creditors, contractors, or citizens. Such a default would rapidly reverse the current positive trajectory of the economy, and the extent of the losses incurred would depend on the duration of the breach. If the default persisted over an extended period, the economy would likely suffer severe damage, causing job growth to shift from its current robust pace to millions of job losses.

The consequences of a government debt default could undo the remarkable economic progress achieved since the current administration took office. This includes an impressively low unemployment rate nearing a 50-year low, the extraordinary creation of 12.6 million jobs, and robust consumer spending that has consistently propelled reliable and solid economic growth. These achievements have been fueled by strong job market conditions and healthy household financial situations.

In a breach-induced recession resulting from default, the government’s ability to implement counter-cyclical measures would be limited, leaving few policy options to mitigate the impact on households and businesses. Furthermore, the ability of individuals and businesses, particularly small enterprises, to borrow from the private sector to alleviate the economic strain would also be hindered. The risks associated with default would trigger a surge in interest rates, affecting various financial instruments used by households and businesses, such as Treasury bonds, mortgages, and credit cards, exacerbating the economic challenges individuals and enterprises face.

Impending Debt Ceiling: Potential Consequences and Impacts

Unprecedented Risk: Impending Debt Ceiling Breach and its Catastrophic Economic Ramifications

The looming threat of breaching the debt ceiling has no historical precedent of being surpassed without Congress raising or suspending the federal debt limit. Nonetheless, economists widely agree that such an event would lead to an entirely avoidable economic catastrophe.

Notably, analysts Wendy Edelberg and Louise Sheiner from the Brookings Institution have emphasized the escalating likelihood of significant disruptions in financial markets due to worsening expectations of a possible default. These disruptions would likely coincide with declines in equity prices, a loss of confidence among consumers and businesses, and restricted access to private credit markets.

The mounting market stress related to debt ceiling tensions has already begun to manifest. Yields on Treasury bills with maturity dates around the anticipated X-date have experienced substantial increases, directly raising borrowing costs for the government and consequently burdening taxpayers. Figure 1 illustrates this trend, depicting a nearly 1-percentage point rise, equivalent to approximately a 20% increase, in yields on short-duration Treasury bills since mid-April.

Unprecedented Concerns: Soaring Costs of Insuring U.S. Debt Amid Default Fears

The escalating apprehensions surrounding a potential U.S. default have resulted in a substantial surge in the cost of insuring U.S. debt, reaching an unprecedented all-time high. This surge is indicative of heightened worries within the market.

Credit default swap (CDS) spreads, which represent the insurance premiums required to safeguard U.S. debt, have experienced a rapid and dramatic increase since April. Figure 2 provides a visual representation of this trend, illustrating the significant rise in CDS spreads.

Mounting Pressure: Proximity to Debt Ceiling Amplifies Market Stress and Undermines Economic Expansion

As the United States approaches the debt ceiling, there is growing anticipation that market stress indicators will deteriorate further, resulting in heightened volatility in equity and corporate bond markets. These conditions will impede firms’ capacity to secure financing and hinder their ability to engage in productive investments, which are crucial for sustaining the ongoing economic expansion.

The increasing proximity to the debt ceiling amplifies the impact on financial markets, exacerbating the challenges faced by businesses seeking necessary funding for expansionary endeavors. The resulting market instability and constrained access to capital have the potential to hinder the growth trajectory of the economy, undermining the current period of expansion.

Implications of a Brief Debt Ceiling Breach: Immediate Economic Consequences

If a breach of the debt ceiling occurs, the adverse effects on the economy would likely be swiftly felt. According to Mark Zandi, Chief Economist of Moody’s Analytics, even a brief default would trigger a crisis characterized by soaring interest rates and plummeting equity prices. The shutdown of short-term funding markets, which are vital for the flow of credit supporting day-to-day economic activities, would also be anticipated.

In the event of a default, Fitch Ratings highlights that the U.S. rating would be downgraded to “RD” (Restricted Default), and affected Treasury securities would carry a “D” rating until the default is resolved.

Moody’s warns that even a short breach of the debt limit could result in a decline in real GDP, the loss of nearly 2 million jobs, and an increase in the unemployment rate to around 5 percent from the current level of 3.5 percent. Furthermore, the lasting consequences would include higher interest costs as Treasury securities may no longer be perceived as risk-free by global investors. This, in turn, would impose a significant economic burden on future generations of Americans. According to Brookings’s analysis, defaulting on the debt could lead to over $750 billion in increased federal borrowing costs over the next decade. Economists at the Peterson Institute caution that reduced demand for Treasuries would weaken the dollar’s role in the global economy, potentially increasing volatility in its value against other currencies and decreasing liquidity, prompting investors to decrease their holdings of dollars in any form.

Long-Term Default: Escalating Costs and Prolonged Economic Consequences

In the case of a protracted default, the costs to the economy would be even more significant. An analysis conducted by the Council of Economic Advisers (CEA) depicts the severe impact of a prolonged debt ceiling breach, comparable to the magnitude of the Great Recession (as shown in Figure 3).

According to the simulation, during the first full quarter of the simulated breach (2023 Q3), the stock market experiences a staggering 45 percent decline, resulting in substantial losses in retirement accounts. The confidence of both consumers and businesses takes a major blow, leading to reduced consumption and investment. Unemployment rises by 5 percentage points as consumers curtail their spending and businesses are compelled to lay off workers. In contrast to previous economic downturns like the Great Recession and the COVID recession, the government’s ability to assist consumers and businesses is severely limited.

As the debt ceiling breach persists, the economy slowly begins to recover, but the healing process is slow. By the end of 2023, unemployment remains elevated, with a 3-percentage point increase compared to pre-breach levels. The enduring consequences of the protracted default prolong the economic challenges and hinder the restoration of a robust and stable economic environment.

Moody’s recent analysis, employing an alternative macroeconomic model, reached a similar conclusion, further emphasizing the gravity of the situation. Their findings indicate that with a clean increase in the debt ceiling, job growth would persist, adding around 900,000 jobs in the coming quarters. However, in the event of a prolonged default, job losses would escalate to a staggering count of nearly 8 million. This significant disparity in outcomes underscores the severe consequences of different debt ceiling scenarios, aligning with our modeling results.

The absence of counter-cyclical measures, such as extended unemployment insurance, would greatly impede the ability of federal and state governments to respond to the resulting turmoil and protect households from the ensuing impacts. Moreover, households would face limited options to borrow from the private sector, as the interest rates on commonly used financial instruments—such as Treasury bonds, mortgages, and credit cards—would skyrocket due to the heightened uncertainties of an uncertain future.

Throughout the extensive history of our nation, policymakers have consistently strived to avoid inflicting such immense harm on both the American and global economies. Virtually all analyses concur that defaulting on the debt would precipitate a profound and immediate recessionary state. While economists may not always see eye-to-eye on various matters, the consensus regarding the magnitude of risks posed by approaching or breaching the debt ceiling is deeply concerning and widely shared.

Devastating Impacts on the Global Economy and Everyday Consumers

The United States is on the brink of a historic debt default, with experts warning of dire consequences for the global economy. Failure to raise the debt ceiling, attributed to partisan divisions, has sparked concerns about the economic fallout and the international ramifications due to the US dollar’s status as the global reserve currency.

Economic Recession:

Even a short breach of the debt ceiling is expected to plunge the US economy into a recession. Moody’s analysis predicts a decline of 4.6% in real GDP, akin to the global financial crisis, while the White House Council of Economic Advisers warns of a potential contraction exceeding 6%. The lack of counter-cyclical measures from the government exacerbates the negative impact on households and businesses, and global trade would suffer as well.

Financial Market Fallout:

The stock market is poised to experience a significant downturn, with a potential 45% drop in a protracted default scenario, adversely affecting retirement accounts and consumer confidence. A mass stock selloff could wipe out $10 trillion in US household wealth, leading to repercussions in international stock markets.

Rising Unemployment:

The economic downturn resulting from a debt default would lead to a sharp increase in unemployment. Moody’s estimates nearly 8 million job losses in a prolonged default, pushing the unemployment rate above 8%. Even a short debt ceiling breach could cost 1.5 million jobs and raise the unemployment rate to around 5%.

Higher Borrowing Costs:

A debt default would heighten the risk of holding US Treasury debt, leading to increased borrowing costs for the US. Interest rates across the economy would rise, impacting financial instruments such as Treasury bonds, mortgages, and credit cards. Fitch Rating suggests a downgrade to the “RD” (Restricted Default) classification, while the White House report warns of skyrocketing interest rates.

Impact on Borrowers:

Mortgage interest rates are expected to surge, with estimates of 8.4% for 30-year mortgages, leading to a 23% decline in home sales. Borrowing costs for households and businesses would be significantly impacted, affecting their financial stability and overall economic activity.

The impending US debt default poses severe risks to the global economy and everyday consumers. The potential consequences include economic recession, financial market volatility, rising unemployment, higher borrowing costs, and reduced consumer confidence. Policymakers must prioritize avoiding risky brinkmanship to mitigate the far-reaching impacts on the American economy and its global leadership position.

What in India?

The US debt ceiling crisis presents two potential scenarios that could greatly impact the Indian economy. In the base case scenario, where the debt ceiling is eventually raised, the volatility in stock markets and currencies would still have a substantial effect on India. As markets face uncertainty, investors tend to shift towards safer assets, such as bonds, gold, and dollars. This leads to a strengthening of the dollar index, putting pressure on the Indian rupee. A default by the US would result in a loss of its financial prominence and a downgrade in its creditworthiness, significantly reducing the value of US sovereign bonds held by the Indian government. This would have direct consequences for India’s foreign exchange reserves and could disrupt the country’s financial stability.

Furthermore, the impact of a US default would extend to development projects in India. Many companies rely on borrowing to fund their initiatives, but a default would create obstacles in accessing liquidity. This would limit the availability of funds and hinder the progress of development projects, potentially slowing down economic growth in the country. Additionally, the depreciation pressures triggered by a brief default scenario would adversely affect emerging market currencies, including the Indian rupee. This would further amplify the challenges faced by India, impacting investor sentiment and potentially leading to economic instability.

Given the central position of the US dollar in global trade and its significance as the world’s reserve currency, the repercussions of a US default would reverberate throughout the global economy. The US dollar’s dominance and the interconnectedness of global financial markets would amplify the impact on India, both through currency depreciation and reduced liquidity. The Reserve Bank of India has not specifically prepared for such a scenario, highlighting the uncertainty surrounding the potential consequences. However, it is clear that a US debt default, in any form, would have catastrophic consequences for the Indian economy, requiring policymakers and stakeholders to carefully monitor the situation and implement measures to mitigate the potential risks.

References

• https://www.wionews.com/india-news/us-is-nearing-its-debt-default-deadline-what-is-its-impact-on-indian-economy-597206
• https://www.outlookindia.com/business/explainer-what-is-the-us-debt-ceiling-crisis-and-can-it-affect-indian-economy-news-287030
• https://www.hindustantimes.com/world-news/what-happens-if-us-fails-to-resolve-its-debt-ceiling-crisis-all-possibilities-listed-101684761499736.html
• https://www.bqprime.com/business/how-us-debt-crisis-may-impact-india
• https://www.pbs.org/newshour/world/heres-what-would-happen-to-the-global-economy-if-the-u-s-defaults-on-its-debt
• https://www.cfr.org/backgrounder/what-happens-when-us-hits-its-debt-ceiling
• https://abcnews.go.com/Business/us-debt-limit-default-affect/story?id=99016545

Author: Prachi Shree

~ Editor, TJEF

Journal 7 Issue 2

The start of a new academic year has arrived and we have gained valuable experiences over the past few months, including internships, academic projects, and personal growth that has contributed to our development as managers. These experiences will be beneficial to our future careers and the organizations we work for.

Given the unpredictability of today’s world, there are a lot of topics to cover up .Therefore, to make things easier for everyone we have selected two themes for the research paper. They are:

–India’s Competitive position and implications on global trade

-Future of fintech in India

We are looking for the best submissions without restricting the creativity of the writers, as long as they relate to economics and finance of the themes mentioned.

The editorial team values the creativity of the writers and believes that giving them the freedom to express their own unique perspectives on a curated topic enhances the quality of their work. In India, where opportunities are abundant and potential is limitless, providing such an opportunity to talented individuals across the country can help them amplify their ability to create research articles that make a difference.

This journal aims to showcase exceptional research articles from students throughout the nation. The TJEF editorial board extends gratitude to the writers for their dedication to producing valuable content for this journal. We hope that the readers will find these articles thought-provoking and inspiring.

We hope you enjoy this issue!

Journal_TJEF_2023 V7 I2.pdf

~ Editorial Team, TJEF