In recent years, the global automotive industry has undergone significant transformations, driven by technological advancements and increasing environmental concerns. The rise of new energy vehicles, particularly electric vehicles, has become a focal point for sustainable development. Among these, BYD EV has emerged as a leading player in the market, contributing to efforts in addressing energy crises and reducing pollution. However, like any enterprise, BYD car company faces inherent financial risks that can impact its operational stability and growth. This article employs the Z-score model to systematically analyze the financial risk of BYD, focusing on its performance from 2018 to 2022. By examining key financial indicators and comparing them with a peer company, GAC Group, we aim to provide insights into BYD’s financial health and propose recommendations for risk mitigation. The analysis incorporates multiple tables and mathematical formulations to enhance clarity and depth.
Financial risk is an inevitable aspect of corporate management, often arising from factors such as liquidity shortages, debt burdens, or market fluctuations. For companies in the EV sector, like BYD EV, rapid expansion and high research and development costs can exacerbate these risks. The Z-score model, developed by researchers in the late 1960s, serves as a robust tool for predicting bankruptcy and assessing financial distress. It utilizes a combination of financial ratios to generate a Z-value, which indicates the likelihood of short-term bankruptcy. Over time, this model has been refined to improve its accuracy across various industries, including manufacturing and retail. In this study, we apply the Z-score model to BYD car company, leveraging its annual financial statements to evaluate risk levels and compare them with industry benchmarks.
The Z-score model is defined by the formula: $$ Z = 1.2X_1 + 1.4X_2 + 3.3X_3 + 0.6X_4 + 0.999X_5 $$ where the variables represent key financial ratios: \( X_1 \) denotes working capital to total assets, \( X_2 \) retained earnings to total assets, \( X_3 \) earnings before interest and taxes to total assets, \( X_4 \) market value of equity to total liabilities, and \( X_5 \) sales to total assets. Based on empirical studies, a Z-value below 1.81 suggests a high probability of bankruptcy, between 1.81 and 2.675 indicates financial instability, and above 2.675 reflects a healthy financial state. This model’s widespread applicability makes it suitable for analyzing BYD EV, given its dynamic market environment and financial complexities.
BYD, established in 1995, has evolved from a battery manufacturer to a comprehensive high-tech enterprise, with BYD car models gaining prominence in the global EV market. The company’s diverse portfolio includes automobiles, rail transit, renewable energy, and electronics, positioning it as a key contributor to China’s green initiatives. Despite its successes, BYD has faced financial challenges, such as liquidity constraints and high debt levels. For instance, in 2019, BYD reported total assets of approximately 195.6 billion yuan, with liabilities reaching 133 billion yuan, indicating a leveraged position. This underscores the importance of continuous financial monitoring for BYD EV to sustain growth and competitiveness.
To assess BYD’s financial risk, we begin with an analysis of short-term solvency, which measures the company’s ability to meet immediate obligations. Key indicators include the current ratio and quick ratio. The current ratio is calculated as current assets divided by current liabilities, while the quick ratio excludes inventory from current assets. Ideal values are around 1.5 to 2.0 for the current ratio and 1.0 for the quick ratio. Table 1 presents these ratios for BYD and GAC Group from 2018 to 2022.
| Ratio | Company | 2022 | 2021 | 2020 | 2019 | 2018 |
|---|---|---|---|---|---|---|
| Current Ratio | BYD | 0.72 | 0.97 | 1.05 | 0.99 | 0.99 |
| GAC Group | 1.62 | 1.25 | 1.34 | 1.37 | 1.65 | |
| Quick Ratio | BYD | 0.49 | 0.72 | 0.75 | 0.75 | 0.76 |
| GAC Group | 1.40 | 1.09 | 1.18 | 1.20 | 1.48 |
As shown in Table 1, BYD’s current and quick ratios are consistently below the recommended levels, indicating potential liquidity issues. For example, in 2022, BYD’s current ratio dropped to 0.72, reflecting increased current liabilities relative to assets. In contrast, GAC Group maintains ratios closer to ideal values, suggesting better short-term financial stability. This disparity highlights BYD EV’s reliance on short-term debt, which could pose risks if market conditions deteriorate.
Next, we evaluate operational efficiency through activity ratios, which include inventory turnover, accounts receivable turnover, and total asset turnover. These ratios assess how effectively BYD car company utilizes its resources to generate sales. Higher values generally indicate better performance. The formulas are as follows: inventory turnover equals cost of goods sold divided by average inventory, accounts receivable turnover equals net credit sales divided by average accounts receivable, and total asset turnover equals net sales divided by average total assets. Table 2 summarizes these metrics.
| Ratio | Company | 2022 | 2021 | 2020 | 2019 | 2018 |
|---|---|---|---|---|---|---|
| Inventory Turnover | BYD | 5.75 | 5.03 | 4.43 | 4.12 | 4.71 |
| GAC Group | 9.93 | 9.39 | 8.66 | 8.08 | 11.56 | |
| Accounts Receivable Turnover | BYD | 11.3 | 5.58 | 3.68 | 2.74 | 2.57 |
| GAC Group | 13.99 | 13.02 | 16.12 | 21.06 | 40.49 | |
| Total Asset Turnover | BYD | 1.07 | 0.87 | 0.79 | 0.65 | 0.70 |
| GAC Group | 0.64 | 0.51 | 0.45 | 0.44 | 0.58 |
From Table 2, BYD’s inventory and accounts receivable turnover ratios have improved over the years, indicating enhanced operational efficiency. For instance, BYD EV’s inventory turnover rose from 4.71 in 2018 to 5.75 in 2022, suggesting better inventory management. However, GAC Group outperforms BYD in most categories, except for total asset turnover, where BYD shows higher values. This could be attributed to BYD car company’s aggressive sales strategies and product innovations, such as the blade battery technology, which boosted market demand.
Profitability analysis is crucial for understanding BYD’s ability to generate earnings relative to its expenses and investments. Key metrics include return on assets (ROA), return on sales (ROS), and return on equity (ROE). ROA is calculated as net income divided by total assets, ROS as operating income divided by net sales, and ROE as net income divided by shareholders’ equity. These ratios are expressed as percentages. Table 3 provides a comparative view.
| Ratio | Company | 2022 | 2021 | 2020 | 2019 | 2018 |
|---|---|---|---|---|---|---|
| ROA | BYD | 5.67 | 2.59 | 5.05 | 3.03 | 4.03 |
| GAC Group | 4.53 | 5.18 | 4.37 | 5.04 | 9.78 | |
| ROS | BYD | 5.08 | 2.14 | 4.52 | 1.81 | 3.26 |
| GAC Group | 6.78 | 9.44 | 8.93 | 9.52 | 16.09 | |
| ROE | BYD | 16.14 | 3.73 | 7.43 | 2.62 | 4.96 |
| GAC Group | 7.93 | 8.42 | 7.27 | 8.46 | 14.97 |
Table 3 reveals that BYD’s profitability ratios fluctuated significantly, with notable improvements in 2020 and 2022. For example, BYD EV’s ROE surged to 16.14% in 2022, reflecting efficient use of equity. This can be linked to BYD car company’s diversification into mask production during the pandemic and advancements in EV technology. Conversely, GAC Group maintains more stable but lower ROE values, indicating BYD’s potential for higher returns despite risks.
Growth ability analysis assesses BYD’s potential for expansion, using metrics like revenue growth rate and asset growth rate. The revenue growth rate is computed as the percentage change in sales year-over-year, while asset growth rate measures the change in total assets. Table 4 displays these figures.
| Ratio | Company | 2022 | 2021 | 2020 | 2019 | 2018 |
|---|---|---|---|---|---|---|
| Revenue Growth Rate | BYD | 96.2 | 38.02 | 22.59 | -1.78 | 22.79 |
| GAC Group | 45.37 | 19.82 | 5.78 | -17.51 | 1.13 | |
| Asset Growth Rate | BYD | 66.97 | 47.14 | 2.75 | 0.55 | 2.75 |
| GAC Group | 23.23 | 7.98 | 3.93 | 4.00 | 10.47 |
As illustrated in Table 4, BYD demonstrates strong growth, with revenue growth peaking at 96.2% in 2022. This outperforms GAC Group, highlighting BYD EV’s rapid market penetration and the benefits of government support for new energy vehicles. The asset growth rate also shows BYD car company’s aggressive investment in infrastructure and technology, positioning it for future scalability.
We now apply the Z-score model to quantify BYD’s financial risk. Using the formula $$ Z = 1.2X_1 + 1.4X_2 + 3.3X_3 + 0.6X_4 + 0.999X_5 $$, we compute the Z-values for BYD and GAC Group based on their financial data from 2018 to 2022. The variables are derived as follows: \( X_1 = \frac{\text{Current Assets} – \text{Current Liabilities}}{\text{Total Assets}} \), \( X_2 = \frac{\text{Retained Earnings}}{\text{Total Assets}} \), \( X_3 = \frac{\text{Earnings Before Interest and Taxes}}{\text{Total Assets}} \), \( X_4 = \frac{\text{Market Value of Equity}}{\text{Total Liabilities}} \), and \( X_5 = \frac{\text{Sales}}{\text{Total Assets}} \). Table 5 presents the calculated Z-values and component ratios.
| Component | Company | 2022 | 2021 | 2020 | 2019 | 2018 |
|---|---|---|---|---|---|---|
| \( X_1 \) | BYD | -0.260 | -0.018 | 0.026 | -0.005 | -0.007 |
| GAC Group | 0.185 | 0.080 | 0.099 | 0.111 | 0.197 | |
| \( X_2 \) | BYD | 0.097 | 0.107 | 0.144 | 0.129 | 0.125 |
| GAC Group | 0.322 | 0.361 | 0.353 | 0.337 | 0.326 | |
| \( X_3 \) | BYD | 0.045 | 0.022 | 0.050 | 0.030 | 0.039 |
| GAC Group | 0.041 | 0.050 | 0.043 | 0.049 | 0.093 | |
| \( X_4 \) | BYD | 1.758 | 3.788 | 3.725 | 0.889 | 0.988 |
| GAC Group | 1.413 | 2.109 | 2.118 | 2.007 | 1.745 | |
| \( X_5 \) | BYD | 0.859 | 0.731 | 0.779 | 0.653 | 0.669 |
| GAC Group | 0.575 | 0.487 | 0.439 | 0.431 | 0.541 | |
| Z-value | BYD | 1.885 | 3.203 | 3.410 | 1.460 | 1.555 |
| GAC Group | 2.231 | 2.519 | 2.465 | 2.404 | 2.588 |
From Table 5, BYD’s Z-values exhibit volatility, with figures below 1.81 in 2018, 2019, and 2022, indicating a high bankruptcy risk during those periods. For instance, in 2022, BYD’s Z-value dropped to 1.885, nearing the critical threshold, primarily due to a significant increase in liabilities. In contrast, GAC Group’s Z-values remain in the gray zone (1.81 to 2.675), suggesting relative stability but ongoing risks. Notably, BYD EV outperforms in \( X_4 \) and \( X_5 \), reflecting stronger market confidence and operational efficiency for BYD car company, but weaknesses in \( X_1 \) and \( X_2 \) highlight liquidity and retention issues.
To further illustrate the Z-score calculation, consider the formula in detail. For BYD in 2022, the computation is: $$ Z = 1.2 \times (-0.260) + 1.4 \times 0.097 + 3.3 \times 0.045 + 0.6 \times 1.758 + 0.999 \times 0.859 $$ which simplifies to $$ Z = -0.312 + 0.1358 + 0.1485 + 1.0548 + 0.857 = 1.885 $$. This demonstrates how each component contributes to the overall score, emphasizing areas for improvement.
In conclusion, the Z-score analysis reveals that BYD’s financial condition is unstable, with periods of high bankruptcy risk, particularly in 2018, 2019, and 2022. Compared to GAC Group, BYD EV shows stronger growth potential and operational turnover but suffers from lower liquidity and higher debt dependence. The fluctuations in Z-values underscore the need for proactive financial management. For BYD car company, we recommend optimizing capital structure by reducing short-term debt, enhancing liquidity reserves, and diversifying funding sources. Additionally, leveraging government policies supporting new energy vehicles can aid in stabilizing finances. BYD should focus on innovation in BYD EV models to maintain competitive advantage and explore international markets to mitigate domestic risks. By implementing a robust financial early-warning system and continuous monitoring, BYD can navigate uncertainties and achieve sustainable growth in the evolving automotive landscape.
The analysis presented here utilizes publicly available financial data and the Z-score model to provide a comprehensive risk assessment. Future research could incorporate additional variables or machine learning techniques to enhance predictive accuracy. Overall, BYD’s journey in the EV sector exemplifies both opportunities and challenges, requiring balanced strategies to ensure long-term viability.