Overconfidence bias is observed when investors exhibit unwarranted faith in their estimations for a future return of assets by underestimating potential variance which has implications for asset pricing. Recently, a group of investors have become overconfident about the prospective good outcome of electric vehicle (EV) makers' stocks and under confident toward the good prospect of fuel vehicle makers' stocks for several reasons.
To prevent climate change, more than 60 countries have said they will minimise the net emission of carbon to zero by 2050. The mass adoption of EVs has been proposed as a strategy to achieve this target in the transport sector, which accounts for the highest amount (28.9%) of carbon emission. A total of 14 countries have already planned to end the sale of new petrol and diesel cars. To capitalise on this movement, EV manufacturers have invested $300 billion globally. Energy and maintenance cost efficiencies, futuristic capabilities, superior performance features of EVs and government incentives have contributed to the rapid growth of the EV industry in recent years.
Contrary to the positive aspects, a list of challenges poses future uncertainty for the EV industry. Firstly, even with the purchase grants and recent improvement of battery technology, the price of EVs is still higher than fuel vehicles because of the high cost of battery and the lack of economies of scale in production.
Secondly, the time required for mass adoption of EV is uncertain. Despite recent exponential sales growth, EVs grabbed only 2.2% of the global vehicle market in 2019 and it is expected that 7% of the vehicles in the USA in 2030 will be EVs. Several technical constraints of EVs are also responsible for slow adoption. Thirdly, electrical infrastructure needs to be developed for facilitating the charging of EVs across the country which would be costly.
How this installation cost will be shared is a major concern. Finally, it takes at least 30 minutes for 80% charging of EV's battery and the storage capacity of the battery is not adequate for long driving which is a key concern in the industry.
The EV makers have drawn much attention from the investors by announcing their plan for manufacturing and expansion of their plants. EV companies have experienced increased sales volume in recent quarters and their stock prices reflected a positive reaction upon the announcement of their sales growth. However, in recent months, the price of stocks of leading EV manufacturers show that the investors are overlooking the future risks in estimating the returns for EV stock. Investors tend to feel very certain about the estimated exponential growth of the EV industry and they are not incorporating the industry challenges into their estimations appropriately. Leading EV manufacturers (i.e. Tesla) have consistently reported a net loss but their stocks are trading at a very high price while leading fuel automobile companies (i.e. GM, Ford) are trading at a low price despite having a good profit margin.
This anomaly can be attributed to the investors who are exhibiting overconfidence in their intuition about the worth of EV stocks which cannot be justified based on fundamental analysis and recent earnings disclosures. This kind of mispricing for overconfidence bias creates an arbitrage opportunity for the arbitrageur. We can test the prediction of overconfidence by examining the metrics suggested in the existing literature.
Although most of the empirical research works are based on proprietary trading records, it is worth investigating whether aggregate market-level data reflects the investors' overconfidence in the EV stocks.
Excess Trading: A small fraction of excessive trading volume can be attributed to hedging and liquidity purposes while a large fraction of excess trading can be attributed to the overconfidence of investors. We can observe the turnover of leading automobile stocks trading in the US financial market for 252 trading days in 2019. Trading volume is observed as the number of stocks traded in a day relative to the number of shares outstanding at the end of the day.
Although almost all automobile companies who have devoted resources to making EVs account for a significant fraction of their total sales by 2025, Tesla and NIO are the two leading companies in the global EV industry. Conversely, Ford and General Motors are giants in the vehicle industry compared to Tesla. It can be immediately observed that the trading volume for NIO and Tesla were significantly higher compared to other leading vehicle manufacturers (i.e. GM, and Ford etc.) throughout the year. The trading volume of these two firms was so high that they were listed as the most actively traded stocks for several trading days on the exchange in 2019.
Though EV companies achieved increased sales, sales were lower than expected by analysts. Notably, their reported loss in every quarter was much wider than expected by investors. The excessive trading volume of the stocks of EVs manufacturers can be firmly attributed to the overconfidence of investors in the form of underestimation of the variability of performance of these stocks. The overconfidence hypothesis asserts that when public information is much different from the perception of investors, it triggers the trading of overconfident investors.
Excess Volatility: Overconfident investors overreact to private information and underreact to publicly available information which causes an overreaction to stock prices. On the subsequent release of more public information, stock price moves closer to the fundamental value. This overreaction-correction pattern results in excess volatility and leads the stock price away from the fundamental value. Since the daily return is a white noise process, we use the squared daily return as a proxy of daily volatility.
From Squared daily return data, it can be noted that NIO and Tesla stock price exhibited higher volatility compared to the volatility of other stocks in 2019. It can be inferred that the overconfidence of investors in EV stocks generated this higher unconditional volatility. Conversely, the relatively insufficient unconditional volatility of fuel vehicle manufacturers reflects that investors are under confident about their good future.
Return Predictability: Overconfidence causes investors to overestimate the precision of their private information signal and overreact based on that. If overconfident investors dominate in the market, their trading swings the price of stocks away from the rational value. When fundamental information gets released, the price of stocks reverts to its fundamental value.
This pattern of overreaction and correction implies that return reversal can be observed for the stocks for which investors are overconfident. There is a significant negative long-lag autocorrelation for a weekly return of NIO share at 14 lags which is an indication that investors were overconfident, and they led the price away from its fundamental value and later the release of public information reverted the price to equilibrium. However, the weekly returns for other companies were not predictable during the same period which supports market efficiency.
From the points identified above, we can argue that overconfidence bias is particularly prevalent in the EV industry. Because of excessive trading, the holding of poorly diversified portfolios, and the underestimation of risks, we can expect the overconfident investors of EV stocks to experience lower returns compared to the market return. To avoid overconfidence bias, we should evaluate private information and public information rationally.
Mohd Anisul Islam is an Assistant Professor at the Department of Finance, University of Dhaka and a former Commonwealth Scholar at the University of Warwick, UK. He can be reached at [email protected]
Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the opinions and views of The Business Standard.