My dissertation consists of three essays. In Chapter 1, I investigate a firm's lease-or-purchase decision when it deploys durable assets. Firms acquiring durable assets face a lease-or-purchase decision. The collateral channel narrative argues that durability can facilitate (hinder) purchases by enhancing pledgeability (requiring a large down payment). However, this prior research has not recognized that some durable assets (e.g. property) can appreciate at a rate that exceeds operational income growth. It also does not endogenize a firm's decision to lease assets. I show that when these considerations are explicitly incorporated into a firm’s optimal financing/investment decision-making calculus, financially constrained firms are incentivized to purchase durable assets. If leasing is feasible, firms revert to renting given the downpayment outlay. In Chapter 2, I examine the valuation of a co-tenancy clause in shopping centers. Shopping centers represent a rare example wherein prices reflect the internalization of externalities. The relatively lower rent anchors pay which other tenants subsidize proxies for externalities anchors create. A related proxy we theoretically model and empirically analyze are co-tenancy lease provisions triggered when an anchor leaves. This real option provides temporary rent relief and early lease termination. I show this option price increases (decreases) with base rent (rent abatement, lease term, bond price, and default time). Using 236 centers, I find co-tenancy increases a center's expected sales price and the odds of selling it for more than its offering price. In Chapter 3, I test the existence of price bubbles in a set of popular cryptocurrencies by applying the local martingale theory. Since cryptocurrencies do not have cash flows, it provides a natural laboratory environment to test the theory. Using a robust statistical algorithm, I test for price bubbles in eight cryptocurrencies: Bitcoin, Litecoin, Ethereum, Ripple, Bitcoin Cash, EOS, Monero, and Zcash from 1 January 2019 to 17 July 2019. The algorithm first estimates the cryptocurrencies' volatilities as a function of the price level. These estimates are extrapolated over the positive real line using a power function for testing a price bubble's existence. Controlling for Type I and II errors, I find that five of the eight currencies (Bitcoin, Bitcoin Cash, EOS, Monero, and Zcash) exhibit price bubbles, Litecoin does not, and the evidence for Ethereum and Ripple is inconclusive. I conclude that the results provide strong evidence for the prevalence of bubbles in cryptocurrencies.