Value in the shadow of conflict: IP rights in dispute

Much of the value of IP assets relies on their performance in dispute. Targeted analysis can help rights holders to determine how best to maximise that value when faced with litigation

High-value IP rights inherently tend to attract legal disputes – in part because there is more to fight over and in part because the territorial nature of property rights encourages conflict. Once IP rights are ensnared in dispute, the associated value and risk become distorted and often compromised by the economics of litigation and the divergent outcomes of trial and settlement. In the presence of such distortion, how should we value these intangible assets? And how does the presence of legal conflict change the amount and character of IP risk? This article examines these issues and explores how game theory models of legal dispute can shed light on the problem.

Various methods are available for valuing IP rights in the normal course. These include the cost method, the market method, the income (discounted cash-flow) method, citation and renewal models. These are essential valuation tools for modern corporations invested in intellectual property. Understanding value serves to better allocate resources and aid in the efficient management, sale and acquisition of intellectual property.

None of these methods is perfect, but they all have in common the assumption of an ongoing absolute right and title to the property right and its validity - that is, the integrity of the economic value is taken for granted even if there may be substantial uncertainty as to its scale.

But what happens in a legal dispute when this assumption is invalid or called into question? From the moment that a demand letter is received or a notice of action is filed (and sometimes even before), the economic merit of a property right may be substantially impaired by conflict. Now the normal course value and risk characteristics are subsumed or at least qualified by the economic complexities and consequences of litigation. These can often be extreme and polarising, and include the following:

  • In entitlement disputes, ownership of the right becomes uncertain;
  • In infringement cases, the security and scale of future cash flows attached to a right can be jeopardised;
  • In licensing disputes, royalty payments may be significantly altered; and
  • In patent invalidity cases, the very existence of the IP right may be cast into doubt.

Ignoring the conflict

In a limited number of situations, it may be sufficient simply to ignore the presence of conflict. If the claim is certain to be dismissed or abandoned, or if a particular settlement is both obvious and certain, then ignoring the economic effect of the dispute may be good enough. However, this will rarely be the case. Litigants seldom provoke a legal conflict unless there is some measure of credibility to the threat – even if the claimant is a troll. In general, then, litigation will cast a large economic shadow. It will also add a substantial element of risk, because as Rhee (2006) notes: “[T]he governing condition of a meritorious civil action is the uncertainty of outcome.”

In addition to the sheer economic significance of litigation and the importance of understanding how it affects the IP portfolio value, there are several transactional situations in which the presence and the effect of a dispute cannot be ignored, such as patent acquisitions, M&A transactions, IP litigation funding decisions, IP rights lending/financing decisions, dispute settlement considerations and the pricing of IP insurance.

Without some form of indemnification against legal risk, both parties must appreciate how a dispute may impair, erode or undermine the value of an IP right. How then should we understand value in the shadow of conflict?

Figure 1. Whole claim value

Value in the shadow of conflict

In many ways, IP disputes are just like any other commercial litigation. There is nothing inherently different in economic terms between a contract dispute and a patent dispute. Fundamentally, both confer rights to future goods or cash flows, the certainty of which is made to turn on the outcome of adjudication or settlement bargaining.

In matters of litigation, it is tempting to look at the value of the legal claim as equal to the value of trial. Indeed, in the lingua franca of litigation, estimating the financial economic worth of trial is often referred to as ‘valuing the claim’. This is unfortunate terminology, because the real value of the claim is not the value of trial, but the value that someone would pay to own it – that is, the price at which the claim, as an asset or liability, would trade.

And just as geopolitical conflicts are more than the value of their potential military solution, so legal disputes are more than the sum of the rulings, verdicts and judgment awards that comprise their trial outcomes. The price value of a legal claim against an IP right – in fact, the value of any legal claim – must reckon with all the ways that a case might be terminated, including the potential for settlement. Let us call this broader measure the ‘whole claim value’ to differentiate it from the common use of ‘claim value’.

As we cannot know for sure whether a particular case will settle, at any point in time there is usually some non-zero probability of trial and some non-zero probability of settlement. As such, the real value of a claim is the expected value or probability-weighted sum of these possible outcomes. Thus, we have the simplified expression for the whole claim value relating to a property right in dispute as shown in Figure 1.

This expression gives us the value impact of the dispute as a whole and in this sense represents the economic shadow of conflict. Of course, this shadow can be accretive or decremental to value, depending on the nature of the dispute and which side of it we are looking at. In certain cases it may affect only one aspect of the property right, leaving the remainder intact. For purposes of discussion, we focus on a company as patent holder involved in an entitlement or invalidity claim. In this case, the shadow of conflict is a measure of the impairment caused to the IP rights valuation by a legal claim. Ignoring counterclaims for a moment, its value is likely negative, if only because of the cost of defence.

The value of a property right in dispute is thus equal to the value of the property right itself plus the whole claim value. We call this the ‘conflict-adjusted value’ (see Figure 2). This is what a company might now pay for the IP right where a legal claim is attached and in the absence of indemnification against legal risk.

However, our expression for the whole claim value is not entirely clear just yet. We need to consider the bilateral context in which it is derived and the bargaining considerations which influence its terms. There is more to this story than meets the eye.

Figure 2. Conflict-adjusted value

Problems with convention

Disputants know the importance of considering the possibility of settlement, especially when pricing disputed IP transactions. The due diligence requirements surrounding the acquisition of a conflicted property right or an M&A deal involving intellectual property compel a thorough examination of all potential outcomes of dispute. However, in practice, the approaches used to derive the different components of the whole claim value often reflect a methodology that is not altogether consistent with the nature of legal conflict.

Generally, litigants will make a unilateral estimate of where the case will settle, a unilateral estimate of the settlement probability and a unilateral estimate of the trial expected value. But when we consider the bilateral context of this calculus, something seems oddly amiss: where is the opponent in this analysis?

Deriving the whole claim value based on a set of unilateral expectations is an example of a decision-theory approach to analysis. However, this is the analytic discipline of one-person games. It acts as if settlement and trial are unilateral purchase or investment decisions that need only satisfy an individual litigant’s value or rate of return threshold in order to be rational. Further, it assumes that a litigant can choose settlement or trial independent of a bargaining process. Of course, nothing could be further from the truth.

A decision-theory framework can leave litigants overly focused on trial valuation, when this is only one element of conflict value. Attention may turn to mining historical verdict data in order to price the trial outcome, but then neglect the bargaining process that determines whether a trial will happen in the first place. Decision trees may be used to express unilateral trial expectations. However, these ignore a crucial point: litigants do not face trial expectations generically, but only after a specific settlement offer has been rejected.

 Parties to a legal conflict do not litigate data; they litigate what they believe. Instead of data mining, we need ‘belief mining’ 

Real nature of conflict

In short, decision theory fails to reflect the real nature of conflict. In reality, all elements of the whole claim value are critically dependent on the expectations of both disputants and a settlement bargaining process – even when that process fails.

For example, the settlement, if one occurs, will be influenced by actual offers and demands, all of which turn on the expectations of both parties. The probability that any settlement offer will be accepted will depend on the receiver’s beliefs about trial.

Even trial outcomes can be selectively filtered by the bargaining process. Litigants in receipt of a settlement offer respond strategically, typically accepting offers that are superior and passing to trial for adjudication only the most extreme subset of possibility. The rejection of a settlement offer contains information about the subsequent trial. In game theory terms, this is called ‘screening’ and it can have the effect of truncating the economic distribution of trial expectations. In this sense, trial can be seen as the residue of settlement bargaining. Litigants understand this filtering mechanism intuitively, but nowhere is this idea explicitly reflected in conventional approaches to trial valuation.

In conflict, value is no longer determined by individual opinion. Conflict makes value something that will be largely governed by a settlement transaction or a settlement decision, and those decisions will be driven by what the parties believe and how they interact. Therefore, to correctly price dispute and understand the shadow of conflict, we need a mathematical framework that can grapple with this reality.

We are used to the idea of litigants mining analogous case verdict data to illuminate the value of trial. However, when we are trying to understand the value of the whole conflict, we need a mathematics that can mine what the disputants are thinking. The parties to a legal conflict do not litigate data; they litigate what they believe. Instead of data mining, we need ‘belief mining’.

High settlement rate

Factoring the potential for settlement is especially important when we consider that settlement is by far the most common way in which IP disputes are terminated. Research by Kesan and Ball (2006), for example, shows that when it comes to patent disputes, over 65% of cases are resolved through settlement or probable settlement, while judgments based on jury verdicts and bench trials typically account for fewer than 7% of all cases.

Looking through the wrong lens

In truth, legal conflict is a bilateral game in which disputants compete against each other for a share of the combined cost savings which can be achieved through settlement (the ‘cooperative surplus’). The game involves litigants which are usually self-interested and wealth-maximising. It is characterised by sequential bargaining moves of offer, response and counter-offer. The parties consider and optimise their bargaining decisions in the presence of uncertainty about each other, and respond strategically to settlement offers.

Games with these characteristics fall more naturally into the province of game theory rather than decision theory. Simply put, to look at valuing IP rights in conflict using decision theory is to look at the problem through the wrong lens. Discounted cash-flow models and other decision theory tools simply cannot capture the real-world complexity of dispute. We need a better microscope.

Conflict as bargaining situation

Game theory and models of the settlement bargaining process, then, are better suited to capturing the value of IP rights in dispute or expressing the impairment of property rights in the context of a legal claim.

In the cut and thrust of legal conflict, some litigants may be tempted to view the consideration of settlement as tantamount to weakness. However, the analytic application of a settlement bargaining framework should not be confused with any particular tendency to concede.

A settlement bargaining price framework is not a nod to win-win negotiation or fair division theory; nor is it a concession to the ideas of integrative bargaining. Rather, it is wholly consistent with rational self-interest. An optimum settlement decision, after all, can include no settlement at all.

Game theory models that accommodate the potential for settlement and express the role of an opponent merely recognise a simple fact of any lawsuit: trial rarely occurs unless a bargaining process has first failed. Renowned game theorist and Nobel laureate Thomas C Schelling put it this way: “To study the strategy of conflict is to take the view that most conflict situations are essentially bargaining situations.”

High frequency of settlement errors

The need for better valuation tools for legal dispute finds support in empirical research. Four different studies have shown a high and consistent percentage of settlement errors in legal cases. The research shows that claimants make errors in about 60% of disputes, while defendants make errors in about 25%. And where there are settlement errors, there must be valuation errors.

We provide a list of this research on our website at We believe that the computational complexity of conflict and the misapplication of decision theory methods are significant contributors to the economic errors in settlement decision making and dispute management in general.

Economic DNA of dispute

The game theory of dispute refers to mathematical models that take into consideration not only the expectations of both parties, but also their strategic interaction. In the analysis of a claim, a litigant will encode not only its own expectations, but also what it believes its opponent may be thinking. As game theory can optimise on this bilateral set of expectations, it can better capture what is going on in a conflict and offer incremental insights.

Depending on the particular model and dispute in question, some of the more useful quantitative outputs of game theory analysis can include the following:

  • probability of settlement in response to an offer;
  • optimum settlement offer;
  • rejection-implied trial-expected value;
  • claim valuation; and
  • effective cost of a bargaining concession.

Combined, we refer to these quantitative insights as the ‘economic DNA of dispute’, because they are the building blocks of conflict and are formative to rational decision making.

It is beyond the scope of this article to survey the many game theory models of litigation or recommend a particular model of legal dispute. Along with the related field of information economics, game theory of litigation has been a fertile area of academic research for over 40 years. Needless to say, there are many different models to consider. Some are highly specific and will be appropriate to the particular characteristics of individual disputes. Others will have more general application.

Nevertheless, let us consider for a moment some of the core attributes of models that are beneficial in dispute pricing and litigation analysis in general. The most useful models for our purposes are those that can reflect the following real-world characteristics of litigation:

  • the bilateral nature of most commercial disputes;
  • the competitive aspects of settlement bargaining;
  • the sequential nature of settlement offer and response;
  • the strategic behaviour of the disputants;
  • the wealth-maximising objectives of the parties; and
  • the uncertainty of expectations.

Various game structures reflect some or all of these characteristics. However, models achieve a particular relevance to litigants when they offer the prospect of unique solutions and provide guidance as to the division of the cooperative surplus. The first of these is referred to as an ‘equilibrium’; the second as the ‘distribution problem’. Let us examine the benefits of each in turn.

Equilibrium solutions

An equilibrium is an extremely useful concept in game theory. It is a pair of strategies which are at once maximising for both players and from which neither has an incentive to deviate. Essentially, it is the solution to games involving two or more players.

Not all game theory models have a unique equilibrium solution, but those that do are said to have greater cutting power, insofar as they eliminate sub-optimal strategies from rational consideration and suggest strategies that are superior.

Notice that the concept of an equilibrium is more powerful than the idea of a mere optimum as in financial analysis or decision theory, because it represents a strategy and a potential outcome that both players have an incentive to bring about. As such, there is a sort of rational gravitational attraction to an equilibrium and empirical research seems to confirm some predictive value in certain game constructions.

It does not follow that, just because an equilibrium solution may exist in a particular dispute, both litigants will necessarily pursue it. However, to the extent that such a strategy pair is rational, mutually advantageous and superior to all other strategies, it should be of interest to litigants as potentially pointing the way.

Figure 3. Dispute wealth components (defendant)

Distribution problem

As discussed, the prospect of settlement brings with it the opportunity for both litigants to save the collective costs of further litigation. When bargaining over the distribution of this surplus, each litigant is uncertain as to how much its opponent will concede. How litigants seek to divide this surplus and how much risk they take in the process are the central considerations in settlement bargaining and the valuation of any conflict.

If we can understand how litigants attempt to solve the distribution problem, we can anticipate behaviour and gain insight into the elements of conflict value. Cooter and Rubinfeld (1989) provide succinct guidance as to where the solution lies: “A rational player will gauge his demands such that the gain from settling on slightly more favourable terms is offset by the increased risk of negotiations breaking down. The optimal strategy in settlement bargaining thus balances a larger share of the stakes against a higher probability of trial.”

We can illustrate what these authors allude to using a dispute wealth components chart (see Figure 3). This describes the wealth from a dispute as comprising the probability-weighted contributions from a potential settlement and potential trial, all as a function of the settlement offer. (We illustrate this with the case of a defendant where trial value is negative.)

As the defendant’s settlement offer moves from a conciliatory extreme to an aggressive extreme, the source of the wealth response shifts from primarily the cost of settlement to primarily the cost of trial. Crucially, the sum of these components changes across the contract zone – clearly, the value of any conflict is forged by the solution to this problem.

At some point between these two extremes, the probability-weighted combination of trial and settlement will pass through a maximum wealth (or minimum negative). It is at this margin that the advantage of a more favourable settlement is just offset by the incremental risk of a bargaining impasse and the attendant costs of trial. This resonates with what we know intuitively about optimising conflict resolution: it is about finding that bargaining stance which takes just the right amount of risk.

In a world constrained by the limitations of decision theory, litigants have sought to discover this optimum through the price discovery mechanism of trial and error negotiation (no pun intended). However, using a game theory approach, we now have a means to approach this problem quantitatively. Game theory models that offer the prospect of a unique bargaining equilibrium and provide insight into solving the distribution problem can help to optimise settlement policy, price the shadow of conflict and value litigation in general.

Game theory limitations

Like all analytic frameworks and pricing methodologies, game theory models of dispute are not without their limitations. Companies involved in IP disputes and other forms of litigation should consider these carefully and make informed decisions. There are three main areas to consider.


The most obvious drawback of game theory is its complexity. Game theory models are inherently more complex than their decision theory counterparts and complex models do not always yield to immediate and intuitive understanding. However, the complexity of analytic innovation should not be an obstacle to its application. The advent of financial option pricing models provides an encouraging analogue.

Before the development of the Black Scholes options pricing model in 1979, derivatives had been traded and priced using intuition and estimation for several hundred years. When mathematical pricing models came along, there was some initial resistance and notes of caution (indeed, this is still the case), but few would argue that the use of such quantitative methods has not enabled a better understanding of derivative instruments and portfolio risks. Today, trading operations and corporate treasury have come to rely heavily on quantitative pricing models, despite their complexity and known limitations.

We are in some ways at a similar juncture in dispute pricing and claim valuation. While decision theory, intuition and expert opinion will, and should, continue to play a role in the analysis of legal conflict, there is room for the application of more appropriate quantitative methods. That many of the ideas discussed in this article have been academic orthodoxy for over 25 years only serves to underscore this point. Legal claims are ripe for their own Black Scholes moment.


All theoretical models involve a level of abstraction from reality. However, because game theory attempts to describe more of the dynamics of litigation, it is hardly surprising that there is more abstraction at play.

Models of the bargaining process are often highly stylised. For example, the number of bargaining rounds may be arbitrarily limited. In addition, litigants themselves are often assumed to have idealised attributes. Models usually assume the parties to be strictly rational, wealth maximising and risk neutral.

Nevertheless, as simplifying as these assumptions may be, there can be no greater degree of abstraction than to pretend, as with decision theory, that trial value is a good proxy for claim value or imagine that decision theory reflects the real nature of a lawsuit. For all of its abstraction, game theory gets much closer to reflecting the essence of dispute.

Moreover, the assumptions of game theory may not be all that unreasonable when fully considered. Is it that unreasonable to assume that litigants are, by and large, wealth maximisers? In most cases, this is probably a fair approximation. And is it really so unreasonable to assume that litigants are rational? As Schelling (1960) points out: “The premise of ‘rational behaviour’ is a potent one for the production of theory.” Despite some of the valid questions raised by behavioural economics, surely rationality is not a bad place to start when trying to anticipate the actions of our legal adversaries.

Financial incompleteness

Part of the abstraction referred to above is that many good game theory models of legal dispute are not financially complete or production ready. While they may capture the essential elements of legal conflict, they often lack practical financial considerations, such as time value, costs of capital, hybrid fee structures, cost shifting and risk aversion.

Still, most of these deficiencies can be remedied. With care, suitable game theory models can be adapted to accommodate the most important financial economic considerations and real-world complications. Although this work is complex and detailed, these model refinements are quite feasible.

Visualising dispute risk

Risk measurement and management in the area of intellectual property often focuses on preserving IP value while it is in development or before it is infringed, attacked or misappropriated. Even patent strategy usually has a pre-emptive, defensive risk management quality about it. In general, the emphasis tends to be on strategic initiatives to monitor and secure the perimeter of property rights.

These are important steps; but once specific rights have been caught in the web of a particular conflict, a more immediate and tangible expression of risk exists in the probabilistic dispersion of value created by the potential outcomes of dispute. Conflict has its own risk and understanding it can make for better risk-adjusted dispute management decisions.

Here again, a game theory approach can help. A key benefit of certain models of conflict is that they provide a framework in which to examine the value dispersion created by a legal claim. If a particular claim will not be dismissed or abandoned, then financial outcomes are compelled to land in one of the three categories of settlement, trial win and trial loss – each of which has its own potential for dispersion.

Game theory models contain much of this risk information, but it is usually averaged or rolled up inside expected value measures of various model inputs and outputs. Although these provide useful shorthand for solving game theory equations, they can obscure a valuable source of risk information: financial variance.

However, Monte Carlo sampling can be used to interrogate or numerically mine game theory models of litigation to reveal the dispersion implied in model solutions. Using this approach, we can build up a visual picture of the probabilistic wealth response to individual settlement offers in the form of a wealth outcomes histogram. An example is shown in Figure 4.

Figure 4. Dispute wealth simulation (defendant)

These numerical analyses describe the outcomes allowed by the game structure, the expectations of the disputants and the settlement offer as input. In the example provided, the model calculates the probability of settlement, deduces the model-implied liability or award expectation and computes the shape of the residue of trial expectations that have survived the bargaining process. In essence, this wealth histogram is the solution to the game laid bare.

Using this numerical approach, companies can obtain a quantitative and visual expression of the risk associated with a particular settlement offer. This technique can be used to bench-test settlement strategies before going into live-fire negotiations. Litigants can compare the risk profile of alternative settlement offers and fine-tune their bargaining strategies to better match corporate risk tolerance.

And as models can also be prescriptive as to settlement, such an analysis can represent a risk picture for the dispute as a whole. Thus, by repeating dispersion analyses across the entire claim portfolio and then aggregating the results using another sampling process, a quantitative picture of total claim portfolio risk can be created. This process is schematically illustrated in Figure 5.

Figure 5. The sum of all conflict

In sum, as IP rights increasingly fall into the grip of legal dispute, it is imperative to understand how value is impaired – especially when IP transactions are at stake.

However, the economic shadow of conflict is complex. It is not well represented by the expected values of trials and it is not measured by solving decision trees. The shadow is cast by a competitive bilateral game of settlement bargaining and is shaped largely by the expectations of the disputants. To fully understand the conflict-adjusted value of IP rights, we need an analytic framework that can correctly account for expectations, bargaining, uncertainty, probabilistic outcomes and the contingent nature of trial. This is the stuff of game theory.

New objective function

In addition to a more realistic representation of conflict value, a game theory perspective enables management to rethink and refine the economic objectives of dispute management. By looking at conflict through a game theory lens, the objective function can shift from maximising trial outcomes to maximising whole claim values. This is an important refinement for repeat players in the world of IP disputes because trial is a poor measure of the corporate value added or subtracted. To put it more bluntly, shareholders do not eat trial values. On average, they benefit most when the whole claim value is maximised. With the right mathematical tools, litigants can ask the right question: what legal and managerial action would maximise the value of the whole claim?

Redefining the mandate

This perspective raises important questions about mandate and dispute management in general. If we think of legal claims as intangible assets or liabilities, the ability to make a more complete and quantitative statement of their value invites management to augment the legal mandate with a broader, perhaps more economically relevant perspective: that of investment management.

Potentially, all decisions regarding the management of IP disputes (not just settlement policy) could be evaluated in terms of how they affect the conflict-adjusted value. Based on their expert opinion, counsel can say, for example, whether a motion for change of jurisdiction will add or subtract from the net trial outcome, which is doubtless helpful. However, if we can examine those same decisions in terms of their impact on the value of the claim as a whole, should we not do that too?

This all begs a rather important question: what happens when optimising the trial value in a manner consistent with legal prudence conflicts with optimising the investment value of the claim in a manner consistent with investment prudence? When making the best legal decision conflicts with making the best investment decision? We believe that it is important to ask this question. As to answering it, well, that is another story. 

Action plan

Rights holders should consider the following when making decisions regarding how they should proceed when faced with a legal dispute:

  • Recognise that IP legal claims are valued and optimised in a settlement-bargaining context.
  • In the sale or acquisition of conflicted IP rights, include an examination of the conflict-adjusted value as part of the due diligence process.
  • Rethink the objective function for the management of IP conflicts. Where appropriate, focus on maximising whole claim values and the conflict-adjusted value of intellectual property.
  • At an organisational level, begin to supplement decision theory approaches to litigation analysis and settlement decision making with game theory methods.
  • Look at IP rights in conflict as having an asset/liability value and consider augmenting legal mandates with investment management considerations.
  • Establish quantitative settlement bargaining analysis as an additional analytic step in dispute management and position this function between litigation analysis and those responsible for settlement decision making.
  • Work with consultants and financial engineers to adapt useful game theory models of dispute to make them production ready.
  • Explore the integration of simulation techniques with game theory models in order to examine the financial variance of conflict.
  • Complement data-driven legal analytics of trial with model-driven litigation analytics of dispute.

Robert Parnell is founder and CEO of SettlementAnalytics, Hong Kong, China

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