volkswagen hedging strategy case study

Both derivatives closed with offsetting transactions and the offsetting transactions themselves are included in the respective notional amount. The offsetting transactions cancel out the effects of the original hedging transactions. If the offsetting transactions were not included, the respective notional amount would be lower. In addition to the derivatives used for hedging foreign currency, interest rate and price risk, the Group held options and other derivatives on equity instruments at the reporting date, mainly in connection with fund investments. The notional volume with a remaining maturity of less than one year was €16.8 billion (previous year: €10.4 billion), and the notional volume with a remaining maturity of more than one year amounted to €1.8 billion (previous year: €0.2 billion).

Also in connection with fund investments, the Group held credit default swaps with a notional amount of €21.4 billion (previous year: €36.6 billion).

Existing cash flow hedges in the notional amount of €0.6 billion (previous year: €2.1 billion) were discontinued because of a reduction in the projections. In addition, hedges were to be terminated due to internal risk regulations.

Items hedged under cash flow hedges are expected to be realized in accordance with the maturity buckets of the hedges reported in the table. For cash flow hedges, the Volkswagen Group achieved an average hedging interest rate of 0.62% for hedging interest rate risk. In addition, currency risk was hedged at the following hedging exchange rates for the major currency pairs: EUR/USD at 1.20; EUR/GBP at 0.88; EUR/CNY at 7.83.

The fair values of the derivatives are estimated using market data at the balance sheet date as well as by appropriate valuation techniques. The following term structures were used for the calculation:

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These modules are namely Best Governance, Best Performance, Best Brand Equity, Software-enabled Car Company and Excellent Leadership. We continuously review the status and progress of these initiatives in order to analyze the target achievement, importance and suitability of the measures defined. This enables us to tailor these modules to the transformation underway within our company. In the Best Governance module, we are working to create a focused, streamlined corporate structure to manage the brands, continually leverage synergies and accelerate decision-making processes. We want the Group to be perceived as efficiently managed, trustworthy, sustainable and transparent. To this end, we are intensifying the dialog with our key stakeholders and systematically reviewing whether we are still the best owner for our various brands and companies. We also want our CO 2 targets to be measurable and our progress toward CO 2 neutrality in 2050 to be transparent.

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Case study: Volkswagen's DieselGate: Corporate governance and sustainability

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As a capstone exercise, this chapter is a case study of Volkswagen AG (VW) that seeks to apply the concepts of this book in an actual company setting, linked to the now-infamous ‘DieselGate’ scandal that became public in 2015. Why VW? It is a well-established company and brand in a sector that is also highly visible. The huge impact of the scandal continues to this day and has been widely reported in the popular media. As we will see, the DieselGate case is very much an ESG story, building from the competitive challenges of the auto sector, VW's stakeholder relations and its distinctive corporate governance structure. The case study focuses on the years 2014 and 2015—before the scandal became public and in its immediate aftermath. Rather than jump immediately into ESG issues, the approach of this case study is to begin with traditional elements of business and financial analysis: looking at the economic and commercial pressures in the auto sector and linking this to VW's competitive profile, strategy and financial outcomes. We also explore VW's own approach to sustainability and how this linked with the specific ESG issues facing the company. There are no ‘right’ or ‘wrong’ answers. But the purpose of the case is to provoke thought in terms of how ESG issues affected VW and its performance—and how investors might approach VW in terms of stewardship.

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Banking on interest rates: A playbook for the new era of volatility

The recent accelerated rise in global interest rates, the fastest in decades, brought the curtain down on an extended period of cheap money but provided little clarity on the longer-term outlook. In 2024, competing forces of tepid growth, geopolitical tension, and regional conflict are creating nearly equal chances of higher-for-longer benchmark rates and rapid cuts. In the banking industry, this uncertainty presents both risks and opportunities. But in the absence of recent precedent, many institutions lack the necessary playbook to tackle the challenge.

As rates have risen from their record lows, banks have in general profited from rising net interest margins (NIMs). However, if policy makers switch swiftly into cutting mode, banks may see the opposite effect. For now, futures markets predict the start of that process toward the end of 2024. In that context, the question facing risk managers is how they can retain the benefit of higher rates while preparing for cuts and managing the potential for macroeconomic surprises.

The question facing risk managers is how they can retain the benefit of higher rates while preparing for cuts and managing the potential for macroeconomic surprises.

The volatility playing out in rates markets is reflected in bank deposit trends, with customers more actively managing their cash to make the most of shifting monetary conditions. In Europe, deposits reached 63 percent of available stable funding (ASF) in 2023, compared with 57 percent in 2021. 1 Monitoring of liquidity coverage ratio and net stable funding ratio implementation in the EU – third report, European Banking Authority, June 15, 2023. In the US, conversely, the share of deposits over total liabilities fell over a similar period as money migrated to investments such as money market funds.

In the face of accelerating deposit flows, McKinsey research shows that bank risk management and funding performance has been highly variable. Between 2021 and 2023, the best-performing US and EU banks saw interest rate expenses rise 70 percent less than at the worst-performing banks (Exhibit 1). Among the drivers were better deposit and interest rate management.

Alongside the impacts of deposit flows, funding has come under pressure from other factors, including the steady withdrawal of pandemic-related central bank liquidity facilities. Meanwhile, innovations such as instant payments have motivated customers to make faster and larger transfers. These withdrawals can happen quickly and be fueled by social media, creating a powerful new species of risk.

In the context of a more uncertain environment, regulatory authorities are doubling down on oversight of the potential impacts of rate volatility—for example, by asking banks to mitigate the potential effects of rate normalization, increasing overall scrutiny, and demanding evidence of methodology upgrades. Among European supervisory priorities for 2024–26, banks are advised to sharpen their governance and strategic frameworks to strengthen asset and liability management (ALM) and develop new funding plans and contingency measures for short-term liquidity shocks, including evaluating the adequacy of assumptions supporting some behavioral models. 2 “SSM Supervisory Priorities, 2024-2026,” in Supervisory priorities and assessment of risks and vulnerabilities , European Central Bank, 2023. In the same vein, the Basel Committee on Banking Supervision in 2023 proposed a recalibration of shocks for interest rate risk in the banking book. Banks can achieve this by extending the time series used in model calibration from the current December 2015 standard to December 2022, bringing more volatile rate distributions into the equation.

In a recent McKinsey roundtable, 40 percent of Europe, Middle East, and Africa bank treasurers said the topic that will attract most regulatory attention in the coming period is liquidity risk, followed by capital risk and interest rate risk in the banking book (IRRBB). With these risks in mind, 34 percent of treasurers said their top priorities with respect to rate risk were enhancing models and analytics, revising pricing strategies on loans and deposits, and beefing up ALM governance and monitoring capabilities.

Most participants also expected treasury teams to get more involved in strategic planning and board engagement and to engage business units more closely to define pricing strategies and product innovation (Exhibit 2).

In response to these dynamics, we expect to see many banks revisiting the role of the treasury function in the months ahead. For many, this will mean moving away from approaches designed for the low-rate era and toward those predicated on uncertainty. In this article, we discuss how forward-looking banks are redesigning their treasury functions to obtain deeper insights into probabilities around interest rates and their impacts on pricing, customer behavior, deposits, and liquidity.

Five steps to enhancing the treasury function

To manage volatile interest rates more effectively, leading banks are revisiting practices in the treasury function that evolved during the low-interest-rate period and may no longer be fit for purpose—or at least should be updated for the new environment. Pioneers have taken steps in five broad focus areas: steering and monitoring, risk measurement and capabilities, stress testing, bank funding, and hedging.

Build efficiency and sophistication

A precondition of effective oversight of interest rate business is to ensure decision makers have a clear view of the current state of play. Currently, the standard approach across the industry is somewhat passive, meaning it is based on static or seldom-reviewed pricing and risk management decisions, often taken by relationship managers. Models are fed with low-frequency data, and banks use static fund transfer pricing (FTP) to calculate net interest margins. Monitoring often reflects regulatory timelines rather than the desire to optimize decision making.

Forward-looking banks are tackling these challenges through a more hands-on approach to steering and monitoring, including the following measures:

• dynamic reviews of FTP, reflecting microsegment behaviors and pricing strategies tied to customer lifetime value and the opportunity cost of liquidity
• increased product innovation to boost funding from both corporate and retail clients
• ensuring access to high-quality, frequent, and granular data, with systems equipped to send early warning signals on potential changes in customer behaviors, especially to capture early signs of liquidity shifts
• use of risk limits and targets as active steering mechanisms, bolstered by links to incentives
• automation of reporting and monitoring, so liquidity and other events can be scaled internally much faster, backed by real-time data where possible

Upgrade IRRBB measurement and capabilities

Leading banks are getting a grip on IRRBB risk in areas such as balance sheet management, pricing, and collateral. Many have assembled dedicated teams to help them make more effective decisions. Given the threat to deposits, some are making greater use of scenario-based frameworks, bringing together liquidity and interest rate risk management. They are using real-time data to inform funding and pricing decisions.

To ensure they consider all aspects of rate risk, leading banks employ a cascade of models, feeding the outputs into steering and stress-testing frameworks, and capturing behavioral indicators that can inform balance sheet planning and hedging activities. Some banks are employing behavioral models to forecast loan acceptance rates and credit line drawings. Best practice involves using statistical grids differentiated by type of customer, product, and process phase.

When it comes to loans, some banks are leveraging AI to predict prepayments and their impacts on balance sheets and hedging requirements. Best practice in prepayments modeling is to move away from linear models and toward machine learning algorithms such as random forests to consider nonlinear relationships (for instance, between prepayments and interest rate variation) and loan features (for example, embedded options), as well as behavioral factors. We see five key steps:

• Customer segmentation . Banks can use AI to achieve granulated segmentation—for example, incorporating behavioral factors.
• Prepayment behavior . Banks can quantify constant prepayments and prepayments subject to criteria including interest rate levels, prepayment penalties, age of mortgage, and borrower characteristics. Leading banks establish a parent model and leverage customer segmentation to derive dedicated prepayment functions, taking into account customer protections such as statutory payment holidays.
• Interest rate scenarios . Banks can employ Monte Carlo simulations and other models to analyze a range of scenarios, including extreme and regulatory scenarios, and simulate potential prepayment behaviors for each scenario.
• Hedging ratios and strategy . Decision makers should evaluate the value of mortgages under different interest scenarios and derive sensitivities to economic value and P&L. They can then select hedging instruments with the aim of neutralizing scenario impacts.
• Pricing . Mortgage pricing can be adjusted based on maturity and potential prepayment behavior. Banks can use fund transfer pricing, with risks handled by a dedicated team in the treasury function.

Another important focus area is deposit decay. Many banks still prioritize moving-average approaches segmented by maturity and backed by expert judgment. A best practice would be to identify a core balance through a combined expert and statistical approach, looking at trends across customer segmentation, core balance modeling, deposit volume modeling, deposit beta and pass-through rates, and replicating portfolio/hedge strategies. This would mean leveraging AI and high-frequency data relating to transactions, to estimate each account’s non-operational liquidity, which customers may be more likely to move elsewhere (see sidebar “Case study: Deposit modeling to limit deposit erosion”). Some banks also use survival models to gauge non-linearities in deposit behaviors.

Case study: Deposit modeling to limit deposit erosion

One bank achieved an equivalent of €150 million to €200 million positive P&L impact on €30 billion of deposits by using AI techniques for repricing. The tool provided transparency on the following measures:

• the amount of liquidity at risk for each client—that is, the excess liquidity the client could potentially invest or move freely to other banks
• the churn probability for each client, or the probability the client would move the liquidity if the bank took no action, based on client sophistication, the quality and intensity of the client’s relationship with the bank, and the level of market competition
• the customer value at risk, an estimate of future revenues that would be at risk if the client moved the liquidity elsewhere (for example, including not only the opportunity cost of funding, but also revenues from related services)

Armed with this transparency, the bank was able to formulate client-specific strategies for repricing actions and product offerings (for example, investment products and transaction banking services), optimizing both its funding sources and profitability. New capabilities to support the effort included a deposits command center, producing a real-time dashboard for monitoring, including early warning triggers, sales team mobilization, and new product offering, especially for cash-rich corporate clients.

In the context of IRRBB strategy, leading banks are keeping a close eye on both deposit beta and pass-through rates (the portion of a change in the benchmark rate that is passed on to the deposit rate). They back their judgments with views on client stickiness, which they traditionally arrive at through expert judgment and market research. A more advanced approach is to derive regime-based elasticities, capturing data from historical economic cycles.

Better modeling enables more resilience: One bank’s story

A European global bank wanted to improve its forecasting in a rising-interest-rate context. Managers decided to focus more on customer behavior. They moved away from expert-judgment buffers to AI and stochastic modeling and a more focused approach to model calibration. They also updated scenario planning based on regulatory guidelines and best-in-class approaches, such as an interest rate risk in the banking book (IRRBB) dynamic balance sheet methodology. Through these changes, the bank was able to estimate its duration gap (between assets and liabilities) more accurately and thereby reduce delta economic value of equity (EVE). As a result, the bank recorded a 70-basis-point uplift in return on equity, resulting from capital savings on interest rate risk and a direct P&L impact from reduced hedging.

Finally, risks need to be optimally matched with hedges. The recent trend is to use stochastic models to support hedging decisions, enabling banks to gauge non-linearities. Forward-looking banks increasingly integrate deposit, prepayment, and pipeline modeling directly into their hedging strategies. They also ensure model risk is closely monitored, with models recalibrated frequently to reduce reliance on expert input (see sidebar “Better modeling enables more resilience: One bank’s story”).

Improve stress testing

Several players are integrating interest rate risk, credit spread risk, liquidity risk, and funding concentration risk in both regulatory and internal stress tests. Indeed, the IRRBB, liquidity risk, and market risk (credit spread risk in the banking book, or CSRBB) highlight the trade-off between capital and liquidity regulations. In short, higher capital requirements may reduce the need for excessive liquidity, and vice versa, for a bank with stable funding—a situation that remains a challenge to current regulatory frameworks.

Stress testing to measure interest rate risk is also evolving, with some banks adopting reverse stress testing (see sidebar “Enhancing Basel's interest rate risk measures: Exploring the efficacy of reverse stress testing and VAR”).

Enhancing Basel’s interest rate risk measures: Exploring the efficacy of reverse stress testing and VAR

Research conducted by a group of bank risk managers suggests that the current supervisory outlier tests for interest rate risk in the banking book (IRRBB) may not adequately address all significant risk scenarios. Specifically, the scenarios outlined in the BCBS 368 guidelines for stress-testing economic value of equity (EVE) and net interest income (NII) may fall short in identifying substantial IRRBB risks. This oversight could make it more difficult for banks to recognize material risks of loss, especially if they have complex or unconventional portfolios.

To identify more material risks, experts are recommending a shift in approach. Instead of focusing solely on extreme and plausible scenarios, they are advised to consider all possible scenarios and integrate reverse stress testing. This would involve simulating thousands of historical and hypothetical scenarios, covering almost the entire spectrum of possible yield curves. After computing NII and EVE, attention would be directed to the scenarios that could have the most adverse impact on the bank’s balance sheet.

In alignment with this proposed methodology, Australian banks will be mandated from 2025 to calculate IRRBB capital using measures of expected shortfall rather than value at risk (VAR). The change is intended to incorporate tail risk, with the new methodology utilizing data from the past seven years, coupled with a distinct one-year stress period.

In upgrading their stress-testing frameworks and interest rate strategies, banks need to balance net interest income (NII) and economic value of equity (EVE) risks that may materialize as a function of rate volatility. On NII, banks can productively apply scenario-based yield curve analysis across regulatory, market, and bank-specific variables and weigh these in the context of overall balance sheet exposures, hedges, and factors including deposits, prepayments, and committed credit lines. Additional economic risks include basis risk, option risk, and credit spread risk, which also should be measured.

Tailor planning

Bank funding plans are often generic, periodic, and spread across different frameworks and methodologies, including funding plans, capital plans, internal capital adequacy assessment processes (ICAAP), and internal liquidity adequacy assessment processes (ILAAP). They are often designed for a range of purposes and audiences and updated only when prompted by regulatory requirements. In future, banks will need dynamic, diversified, and granular funding plans—for example, tailored to products and regions. The plans should reflect flexible and contingent funding sources, central bank policies, and the trade-off between risks and costs.

Embrace dynamic hedging strategies

In the era of low rates, hedging of interest rate risk was a less prominent activity. Banks often employed simple, static, short-term, or isolated strategies, mostly aimed at protecting P&L. Few banks paid a great deal of attention to collateral management.

Now, in a more volatile rate environment, the potential for losses is much higher, suggesting banks need more sophisticated, agile, and frequent hedging to respond to shifts in interest rates, credit spreads, and customer deposit behaviors (Exhibit 3). Indeed, in 2023, the traded volume of euro-denominated interest rate derivatives increased by 3.4 times compared with 2020, according to the International Swaps and Derivatives Association. 3 “Interest rate derivatives US: Transaction data,” ISDA.

Hedging strategies are evolving to be dynamic, horizontally integrated across the organization, and wedded to risk appetite frameworks, so banks can balance P&L priorities and reductions in tail risk. On the ground, banks will likely need to recalibrate their strategies frequently, ideally leveraging a comprehensive scenario-based approach to reflect changes in the external environment. Many, for example, have already revisited hedging to reflect higher rates, but as rates fall, they will need to assess factors such as the impact of convexity on short positions. The objective of these exercises would ideally extend beyond risk mitigation to the optimization of NII (see sidebar “Replication and hedging: The upsides of NIM optimization”).

Replication and hedging: The upsides of NIM optimization

Broadly, banks may consider four approaches to replication and hedging, each of which offers benefits that will vary according to the bank’s unique asset base.

Static replication is a widely applied and robust approach that involves derivation and adjustment of cash flows from deposit volume models for deposit rate elasticity and pass-through rates. The remainder of cash flows are replicated with bonds, interest rate swaps, or loans. Future deposit growth can be incorporated if desired.

Dynamic hedging of present value of net interest margin (NIM) treats the deposit portfolio like a structured product. Banks calculate the present value of NIM arising from deposits, enabling derivation of present value sensitivity to changes in interest rates. The method supports dynamic hedging and can take into account negative convexity.

Static NIM optimization provides the recommended trade-off between granularity and sophistication on the one hand and usability on the other, and it is our preferred approach. It involves design of the fixed-income portfolio to replicate deposit balance dynamics over a sample period. The analyst then selects the portfolio yielding the most stable margin, represented by minimization of margin standard deviation of the spread between the portfolio return and deposit rate. The approach enables NIM maximization, with the caveat that shorter tenors tend to be preferred in periods of low benchmark rates.

Dynamic NIM optimization permits banks to model future interest rates with NIM and investment strategy optimized for a future horizon. Again, NIM can be maximized, but the approach requires assumptions on volume growth, and the optimization horizon may not extend to the full rate cycle.

A key principle of best-in-class hedging strategy is that a proactive, forward-looking approach tends to work best and will enable banks to hedge more points on the yield curve. And with forward-looking scenario analysis, they should be able to anticipate risks more effectively. Consider the case of a bank that was exposed to falling interest rates and did not meet the regulatory threshold for outliers under the new IRRBB rules for changes in NII. Through analysis of potential client migrations to other products and a push to help clients make those transfers, combined with a new multi-billion-dollar derivative hedging strategy, the bank brought itself within the threshold.

Banks should not view hedging as a stand-alone activity but rather as integrated with risk management, backed by investment in talent and education to ensure teams choose the right hedges for the right situation. These may be traditional interest rate derivatives but equally could be options or swaptions to bring more flexibility to the hedging strategy. AI will be table stakes to support decision making and identify risks before they materialize. A more automated approach to data analytics will likely be required. And collateral management should be a core element of hedging frameworks, with analytics employed to forecast collateral valuations and needs, optimize liquidity reserves, and mitigate margin call risk.

Next steps: Making change happen

To effectively implement change across the activities highlighted here, best practice would be to bring together modeling capabilities under a dedicated data strategy. The target state should be comprehensive capabilities, a unified and actionable scenario-based framework, and routine use of AI techniques and behavioral data for decisions around pricing and collateral. Most likely, a talent strategy also will be required to support capability building across analytics, trading, finance, pricing, and risk management.

Banks must marshal a broad range of market data to support effective modeling. The data will include all credit lines, including both on–balance sheet and off–balance sheet items, deposit lines, fixed-income assets and liabilities, capital items, and other items on the banking book. Ideally, banks would assemble 15 to 20 years of data, which would take in the previous period of rising interest rates from 2004 to 2007. Alongside these basic resources, banks need information on historical residual balances, amortization plans, optionality, currencies, indexing, counterparty information, behavioral insights, and a full set of macro data. Some cutting-edge models incorporate about 150 different features.

Armed with comprehensive data, banks can build behavioral models (for example, prepayments, deposits) to estimate parameters and infer behavioral effects in different scenarios. They can then integrate behavioral outputs into stress-testing simulations, alongside expert-based insights. Once macroeconomic data has been inputted, banks should be able to compute delta NII and EVE for three years. Visualization tools and hedging replica analysis can help teams clarify their insights and test their hedging strategies across risk factors.

Banks that have embraced the levers discussed here have set themselves on a course to more proactive and effective interest rate risk management. Through a sharper focus on high-quality data and the use of AI and scenario-based frameworks, banks have shown they can make better decisions, upgrade their hedging capabilities, optimize the cost of funding, and ensure they stay within regulatory thresholds. In short, they will be equipped to respond faster and more flexibly as interest rates enter a new era of volatility.

Andreas Bohn is a partner in McKinsey’s Frankfurt office, Sebastian Schneider is a senior partner in the Munich office, Enrique Briega is a knowledge expert in the Madrid office, and Mario Nargi is an associate partner in the Milan office.

The authors wish to thank Gonzalo Oliveira and Stefano Terra for their contributions to this article.

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Step 1 – Problem Identification of Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) - Harvard Business School Case Study

The first step to solve HBR Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) case study solution is to identify the problem present in the case. The problem statement of the case is provided in the beginning of the case where the protagonist is contemplating various options in the face of numerous challenges that Vgca Warehousing is facing right now. Even though the problem statement is essentially – “Strategy & Execution” challenge but it has impacted by others factors such as communication in the organization, uncertainty in the external environment, leadership in Vgca Warehousing, style of leadership and organization structure, marketing and sales, organizational behavior, strategy, internal politics, stakeholders priorities and more.

Step 2 – External Environment Analysis

Texas Business School approach of case study analysis – Conclusion, Reasons, Evidences - provides a framework to analyze every HBR case study. It requires conducting robust external environmental analysis to decipher evidences for the reasons presented in the Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA). The external environment analysis of Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) will ensure that we are keeping a tab on the macro-environment factors that are directly and indirectly impacting the business of the firm.

What is PESTEL Analysis? Briefly Explained

PESTEL stands for political, economic, social, technological, environmental and legal factors that impact the external environment of firm in Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) case study. PESTEL analysis of " Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA)" can help us understand why the organization is performing badly, what are the factors in the external environment that are impacting the performance of the organization, and how the organization can either manage or mitigate the impact of these external factors.

How to do PESTEL / PEST / STEP Analysis? What are the components of PESTEL Analysis?

As mentioned above PESTEL Analysis has six elements – political, economic, social, technological, environmental, and legal. All the six elements are explained in context with Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) macro-environment and how it impacts the businesses of the firm.

How to do PESTEL Analysis for Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA)

To do comprehensive PESTEL analysis of case study – Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) , we have researched numerous components under the six factors of PESTEL analysis.

Political Factors that Impact Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA)

Political factors impact seven key decision making areas – economic environment, socio-cultural environment, rate of innovation & investment in research & development, environmental laws, legal requirements, and acceptance of new technologies.

Government policies have significant impact on the business environment of any country. The firm in “ Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) ” needs to navigate these policy decisions to create either an edge for itself or reduce the negative impact of the policy as far as possible.

Data safety laws – The countries in which Vgca Warehousing is operating, firms are required to store customer data within the premises of the country. Vgca Warehousing needs to restructure its IT policies to accommodate these changes. In the EU countries, firms are required to make special provision for privacy issues and other laws.

Competition Regulations – Numerous countries have strong competition laws both regarding the monopoly conditions and day to day fair business practices. Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) has numerous instances where the competition regulations aspects can be scrutinized.

Import restrictions on products – Before entering the new market, Vgca Warehousing in case study Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA)" should look into the import restrictions that may be present in the prospective market.

Export restrictions on products – Apart from direct product export restrictions in field of technology and agriculture, a number of countries also have capital controls. Vgca Warehousing in case study “ Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) ” should look into these export restrictions policies.

Foreign Direct Investment Policies – Government policies favors local companies over international policies, Vgca Warehousing in case study “ Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) ” should understand in minute details regarding the Foreign Direct Investment policies of the prospective market.

Corporate Taxes – The rate of taxes is often used by governments to lure foreign direct investments or increase domestic investment in a certain sector. Corporate taxation can be divided into two categories – taxes on profits and taxes on operations. Taxes on profits number is important for companies that already have a sustainable business model, while taxes on operations is far more significant for companies that are looking to set up new plants or operations.

Tariffs – Chekout how much tariffs the firm needs to pay in the “ Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) ” case study. The level of tariffs will determine the viability of the business model that the firm is contemplating. If the tariffs are high then it will be extremely difficult to compete with the local competitors. But if the tariffs are between 5-10% then Vgca Warehousing can compete against other competitors.

Research and Development Subsidies and Policies – Governments often provide tax breaks and other incentives for companies to innovate in various sectors of priority. Managers at Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA) case study have to assess whether their business can benefit from such government assistance and subsidies.

Consumer protection – Different countries have different consumer protection laws. Managers need to clarify not only the consumer protection laws in advance but also legal implications if the firm fails to meet any of them.

Political System and Its Implications – Different political systems have different approach to free market and entrepreneurship. Managers need to assess these factors even before entering the market.

Freedom of Press is critical for fair trade and transparency. Countries where freedom of press is not prevalent there are high chances of both political and commercial corruption.

Corruption level – Vgca Warehousing needs to assess the level of corruptions both at the official level and at the market level, even before entering a new market. To tackle the menace of corruption – a firm should have a clear SOP that provides managers at each level what to do when they encounter instances of either systematic corruption or bureaucrats looking to take bribes from the firm.

Independence of judiciary – It is critical for fair business practices. If a country doesn’t have independent judiciary then there is no point entry into such a country for business.

Government attitude towards trade unions – Different political systems and government have different attitude towards trade unions and collective bargaining. The firm needs to assess – its comfort dealing with the unions and regulations regarding unions in a given market or industry. If both are on the same page then it makes sense to enter, otherwise it doesn’t.

Economic Factors that Impact Warehousing Strategy at Volkswagen Group Canada Inc. (VGCA)

Social factors that impact warehousing strategy at volkswagen group canada inc. (vgca), technological factors that impact warehousing strategy at volkswagen group canada inc. (vgca), environmental factors that impact warehousing strategy at volkswagen group canada inc. (vgca), legal factors that impact warehousing strategy at volkswagen group canada inc. (vgca), step 3 – industry specific analysis, what is porter five forces analysis, step 4 – swot analysis / internal environment analysis, step 5 – porter value chain / vrio / vrin analysis, step 6 – evaluating alternatives & recommendations, step 7 – basis for recommendations, references :: warehousing strategy at volkswagen group canada inc. (vgca) case study solution.

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Segmentation, targeting, positioning, marketing strategic planning, marketing 5 concepts analysis, swot analysis & matrix, porter five forces analysis, pestel / pest / step analysis, cage distance analysis international marketing analysis leadership, organizational resilience analysis, bcg matrix / growth share matrix analysis, block chain supply chain management, paei management roles, leadership with empathy & compassion, triple bottom line analysis, mckinsey 7s analysis, smart analysis, vuca analysis ai ethics analysis analytics, hedging at porsche case study solution & analysis / mba resources.

• Hedging at Porsche
• Finance & Accounting / MBA Resources

Introduction to case study solution

EMBA Pro case study solution for Hedging at Porsche case study

At EMBA PRO , we provide corporate level professional case study solution. Hedging at Porsche case study is a Harvard Business School (HBR) case study written by Stefan Nagel. The Hedging at Porsche (referred as “Porsche Volkswagen” from here on) case study provides evaluation & decision scenario in field of Finance & Accounting. It also touches upon business topics such as - Value proposition, Global strategy, Risk management. Our immersive learning methodology from – case study discussions to simulations tools help MBA and EMBA professionals to - gain new insight, deepen their knowledge of the Finance & Accounting field, and broaden their skill set.

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Case Description of Hedging at Porsche Case Study

Porsche is taking in more money from its options strategies than it is from the sale of cars. Some of the earnings are on foreign exchange options, but a significant chunk of the profits is coming from the company's huge stake in Volkswagen. Company executives argue they have built the stake in Volkswagen to fend off the takeover of its partner by another company, but others are crying foul, indicating that the company's speculation is too risky. They are questioning whether the company is still a car manufacturer or if it has become a hedge fund. Students are asked to recommend the best course of action.

Case Authors : Stefan Nagel

Topic : finance & accounting, related areas : global strategy, risk management, what is the case study method how can you use it to write case solution for hedging at porsche case study.

Almost all of the case studies contain well defined situations. MBA and EMBA professional can take advantage of these situations to - apply theoretical framework, recommend new processes, and use quantitative methods to suggest course of action. Awareness of the common situations can help MBA & EMBA professionals read the case study more efficiently, discuss it more effectively among the team members, narrow down the options, and write cogently.

Case Study Solution Approaches

Three Step Approach to Hedging at Porsche Case Study Solution

The three step case study solution approach comprises – Conclusions – MBA & EMBA professionals should state their conclusions at the very start. It helps in communicating the points directly and the direction one took. Reasons – At the second stage provide the reasons for the conclusions. Why you choose one course of action over the other. For example why the change effort failed in the case and what can be done to rectify it. Or how the marketing budget can be better spent using social media rather than traditional media. Evidences – Finally you should provide evidences to support your reasons. It has to come from the data provided within the case study rather than data from outside world. Evidences should be both compelling and consistent. In case study method there is ‘no right’ answer, just how effectively you analyzed the situation based on incomplete information and multiple scenarios.

Case Study Solution of Hedging at Porsche

We write Hedging at Porsche case study solution using Harvard Business Review case writing framework & HBR Finance & Accounting learning notes. We try to cover all the bases in the field of Finance & Accounting, Global strategy, Risk management and other related areas.

Objectives of using various frameworks in Hedging at Porsche case study solution

By using the above frameworks for Hedging at Porsche case study solutions, you can clearly draw conclusions on the following areas – What are the strength and weaknesses of Porsche Volkswagen (SWOT Analysis) What are external factors that are impacting the business environment (PESTEL Analysis) Should Porsche Volkswagen enter new market or launch new product (Opportunities & Threats from SWOT Analysis) What will be the expected profitability of the new products or services (Porter Five Forces Analysis) How it can improve the profitability in a given industry (Porter Value Chain Analysis) What are the resources needed to increase profitability (VRIO Analysis) Finally which business to continue, where to invest further and from which to get out (BCG Growth Share Analysis)

SWOT Analysis of Hedging at Porsche

SWOT analysis stands for – Strengths, Weaknesses, Opportunities and Threats. Strengths and Weaknesses are result of Porsche Volkswagen internal factors, while opportunities and threats arise from developments in external environment in which Porsche Volkswagen operates. SWOT analysis will help us in not only getting a better insight into Porsche Volkswagen present competitive advantage but also help us in how things have to evolve to maintain and consolidate the competitive advantage.

- Strong Balance Sheet – The financial statement of Porsche Volkswagen looks strong and will help the company going forward.

- Streamlined processes and efficient operation management – Porsche Volkswagen is one of the most efficient firms in its segment. The credit for the performance goes to successful execution and efficient operations management.

- Porsche Volkswagen business model can be easily replicated by competitors – According to Stefan Nagel , the business model of Porsche Volkswagen can be easily replicated by players in the industry.

- Low profitability which can hamper new project investment – Even though Porsche Volkswagen financial statement is stable, but going forward Porsche Volkswagen 5-7% profitability can lead to shortage of funds to invest into new projects.

Opportunities

- E-Commerce and Social Media Oriented Business Models – E-commerce business model can help Porsche Volkswagen to tie up with local suppliers and logistics provider in international market. Social media growth can help Porsche Volkswagen to reduce the cost of entering new market and reaching to customers at a significantly lower marketing budget.

- Developments in Artificial Intelligence – Porsche Volkswagen can use developments in artificial intelligence to better predict consumer demand, cater to niche segments, and make better recommendation engines.

- Growing dominance of digital players such as Amazon, Google, Microsoft etc can reduce the manoeuvring space for Porsche Volkswagen and put upward pressure on marketing budget.

- Age and life-cycle segmentation of Porsche Volkswagen shows that the company still hasn’t able to penetrate the millennial market.

Once all the factors mentioned in the Hedging at Porsche case study are organized based on SWOT analysis, just remove the non essential factors. This will help you in building a weighted SWOT analysis which reflects the real importance of factors rather than just tabulation of all the factors mentioned in the case.

What is PESTEL Analysis

PESTEL /PEST / STEP Analysis of Hedging at Porsche Case Study

PESTEL stands for – Political, Economic, Social, Technological, Environmental, and Legal factors that impact the macro environment in which Porsche Volkswagen operates in. Stefan Nagel provides extensive information about PESTEL factors in Hedging at Porsche case study.

Political Factors

- Little dangers of armed conflict – Based on the research done by international foreign policy institutions, it is safe to conclude that there is very little probability of country entering into an armed conflict with another state.

- Political consensus among various parties regarding taxation rate and investment policies. Over the years the country has progressively worked to lower the entry of barrier and streamline the tax structure.

Economic Factors

- Inflation rate is one of the key criteria to consider for Porsche Volkswagen before entering into a new market.

- Foreign Exchange movement is also an indicator of economic stability. Porsche Volkswagen should closely consider the forex inflow and outflow. A number of Porsche Volkswagen competitors have lost money in countries such as Brazil, Argentina, and Venezuela due to volatile forex market.

Social Factors

- Demographic shifts in the economy are also a good social indicator for Porsche Volkswagen to predict not only overall trend in market but also demand for Porsche Volkswagen product among its core customer segments.

- Consumer buying behavior and consumer buying process – Porsche Volkswagen should closely follow the dynamics of why and how the consumers are buying the products both in existing categories and in segments that Porsche Volkswagen wants to enter.

Technological Factors

- 5G has potential to transform the business environment especially in terms of marketing and promotion for Porsche Volkswagen.

- Artificial intelligence and machine learning will give rise to importance of speed over planning. Porsche Volkswagen needs to build strategies to operate in such an environment.

Environmental Factors

- Environmental regulations can impact the cost structure of Porsche Volkswagen. It can further impact the cost of doing business in certain markets.

- Consumer activism is significantly impacting Porsche Volkswagen branding, marketing and corporate social responsibility (CSR) initiatives.

Legal Factors

- Property rights are also an area of concern for Porsche Volkswagen as it needs to make significant Global strategy, Risk management infrastructure investment just to enter new market.

- Intellectual property rights are one area where Porsche Volkswagen can face legal threats in some of the markets it is operating in.

What are Porter Five Forces

Porter Five Forces Analysis of Hedging at Porsche

Competition among existing players, bargaining power of suppliers, bargaining power of buyers, threat of new entrants, and threat of substitutes.

What is VRIO Analysis

VRIO Analysis of Hedging at Porsche

VRIO stands for – Value of the resource that Porsche Volkswagen possess, Rareness of those resource, Imitation Risk that competitors pose, and Organizational Competence of Porsche Volkswagen. VRIO and VRIN analysis can help the firm.

What is Porter Value Chain

Porter Value Chain Analysis of Hedging at Porsche

As the name suggests Value Chain framework is developed by Michael Porter in 1980’s and it is primarily used for analyzing Porsche Volkswagen relative cost and value structure. Managers can use Porter Value Chain framework to disaggregate various processes and their relative costs in the Porsche Volkswagen. This will help in answering – the related costs and various sources of competitive advantages of Porsche Volkswagen in the markets it operates in. The process can also be done to competitors to understand their competitive advantages and competitive strategies. According to Michael Porter – Competitive Advantage is a relative term and has to be understood in the context of rivalry within an industry. So Value Chain competitive benchmarking should be done based on industry structure and bottlenecks.

What is BCG Growth Share Matrix

BCG Growth Share Matrix of Hedging at Porsche

BCG Growth Share Matrix is very valuable tool to analyze Porsche Volkswagen strategic positioning in various sectors that it operates in and strategic options that are available to it. Product Market segmentation in BCG Growth Share matrix should be done with great care as there can be a scenario where Porsche Volkswagen can be market leader in the industry without being a dominant player or segment leader in any of the segment. BCG analysis should comprise not only growth share of industry & Porsche Volkswagen business unit but also Porsche Volkswagen - overall profitability, level of debt, debt paying capacity, growth potential, expansion expertise, dividend requirements from shareholders, and overall competitive strength. Two key considerations while using BCG Growth Share Matrix for Hedging at Porsche case study solution - How to calculate Weighted Average Market Share using BCG Growth Share Matrix Relative Weighted Average Market Share Vs Largest Competitor

5C Marketing Analysis of Hedging at Porsche

4p marketing analysis of hedging at porsche, porter five forces analysis and solution of hedging at porsche, porter value chain analysis and solution of hedging at porsche, case memo & recommendation memo of hedging at porsche, blue ocean analysis and solution of hedging at porsche, marketing strategy and analysis hedging at porsche, vrio /vrin analysis & solution of hedging at porsche, pestel / step / pest analysis of hedging at porsche, swot analysis and solution of hedging at porsche, references & further readings.

Stefan Nagel (2018) , "Hedging at Porsche Harvard Business Review Case Study. Published by HBR Publications.

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California State University Long Beach Volkswagen Hedging Strategy Paper

User Generated

California State University Long Beach

Description

• Volkswagen's Hedging Strategy
• Embraer and the Wild Ride of the Brazilian Real
• Subaru's Sales Boom Thanks to the Weaker Yen
• What did you learn from these stories about hedging foreign exchange rate risk?
• Why did Volkswagen suffer a 95% drop in its 4 th quarter, 2003 profits?
• Do you think the Volkswagen’s decision to hedge only 30% of its anticipated U.S. sales was a good? Why or why not?
• Do you think the Volkswagen’s decision to revert back to hedging 70% of its foreign currency exposure was a good decision? Why or why not?

YOUR ANSWER

• Is a decline in value of the real against the U.S. dollar good or bad for Embraer? Why?
• How can Embraer reduce these risks?
• Do you think Embraer's decision to hedge against further appreciation of the real in the early 2000s was a good decision? Why or why not?
• Since 2008 Embraer has significantly reduced its dollar hedging operations. Is this wise? Why or why not?
• Why has Subaru concentrated its manufacturing in Japan?
• What was the impact of the depreciation of the yen on Subaru’s profits since 2012?
• Why is Subaru increasing its US production? Do you think it is a good decision? Why or why not
• NO CREDIT will be given if you do not follow the directions below
• Font size=12, line space=1.5, margins=1 inch on all sides
• Submit at BeachBoard. Plagiarism will be checked.
• Only complete answers to ALL questions will receive credit (No partial credit)
• Provide separate answers for each question. Do not delete the questions

Unformatted Attachment Preview

Explanation & Answer

Hello, I'm done, I answered all the questions that we agreed to answer as per the outline. Running head: VOLKSWAGEN HEDGING STRATEGY Volkswagen Hedging Strategy Name Institution Affiliation 1 VOLKSWAGEN HEDGING STRATEGY 2 95% drop in the profits of Volkswagen from $1.05 billion to approximately $50 million was reported by Volkswagen, a large carmaker company in Europe. It was as a result of the notice of too much concentration and the appreciation of the worth of the Euro in 2003. The company’s profits fell up to 5% from the previous year. The profit slump was associated with several causes. The Euro in relation to the U.S. dollar, surprised many individuals with its rise related to the foreign trade deficits in the United States regarding the future of the dollar. The depreciation of the Euro in 2003 against the dollar was very devastating. Volkswagen needed to ensure its movements against the exchange rates in 2002 when getting into the foreign exchange market (Medium, 2019). Volkswagen's to hedging 30% of the foreign currency about the average 70% of the traditional hedge led to a loss of advantaging the dollar. The appreciation of the dollar resulted in Volkswagen profit reducing by about $1.2billion. The decision would be of benefit to Volkswagen, but hedging always accompanies a cost. The Euro declining its value to the dollar resulted to result in the company making more profit without the use of hedging. Hedging proves to be very expensive as the foreign exchange investors charge the high commission for purchasing the currency. Volkswagen's alternative to hedge 30% of its expected U.S. sales is historical. The decision coasted the company varies greatly with it going back to its regular 70% foreign currency exposure (Medium, 2019). VOLKSWAGEN HEDGING STRATEGY 3 Yes, as it did not cost the company compared to the 30% hedging. Volkswagen's alternative to hedge 30% of the foreign sales in 2003 coasted the company around $1.3 billion, which made it revert of the standard 70% hedge. Japanese decision to put much attention on a large number of the manufacturers in the country was to reach the economies of scale to its industries and then exporting the vehicles to the United States. Subaru produces 80% of its motor vehicles in Japan regarding Honda, which produces 21% of them. It resulted in liability. The strongest Yen resulted in Subaru cars being priced outsid...

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